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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Wang, Baosheng School of Computer and Software Nanyang Institute of Technology Nanyang China

ISBN: (纸本)9798350305463

this article proposes a new deep video hashing algorithm to improve video retrieval speed. this method utilizes the powerful feature extraction ability of neural networks (CNNs) to extract representative video and temporal features using the spatiotemporal information after stacking convolutional pooling layers, and then calculates compact binary codes. In the loss function, a dual objective loss function is used, which aims to maximize the inter class distance of video feature pairs and minimize the intra class distance, as well as minimize the loss between real valued codes and binary codes. this training process uses the Siamese network. Finally, calculations were conducted on databases CCB and JHMDB, and compared with other hash methods. the experimental results showed the effectiveness of the method. © 2024 IEEE.

关键词： Binary codes

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Sentiment Analysis Methods Based on Multi-Modal Fusion and Deep Learning 13

Sentiment Analysis Methods Based on Multi-Modal Fusion and D...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Wang, Jingdong Zhao, Wenyan Meng, Fanqi Qu, Guangqiang School of Computer Science Northeast Electric Power University Jilin China

ISBN: (纸本)9798350305463

Sentiment analysis is an important research topic in the field of artificial intelligence and occupies an important position in product evaluation, public opinion analysis, mental health analysis, risk assessment and other fields. However, traditional unimodal sentiment analysis is affected by factors such as missing data or noise, and suffers from shortcomings such as incomplete information, inconsistent information, lack of contextual information, and loss of multimodal features. Multimodal sentiment analysis can improve the accuracy, robustness and expressiveness of unimodal sentiment analysis by fusing data from multiple perceptual modalities, thus providing more comprehensive and accurate sentiment analysis results. therefore, this paper addresses the shortcomings of unimodal sentiment analysis, describes in detail multiple feature fusion methods, and introduces two techniques in the field of deep learning, points out the current problems and future development direction of multimodal sentiment analysis, and provides a new theoretical approach for sentiment analysis. © 2024 IEEE.

关键词： Risk assessment

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Numerical Calculation and Optimization Algorithm Based on Unity Physics Engine 13

Numerical Calculation and Optimization Algorithm Based on Un...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Ding, Lei Liu, Mengyao Miao, Lei Yang, Tingting Hu, Yan Zhou, Xiaocheng Computer Engineering College Anhui Wenda University of Information Engineering Anhui Hefei230201 China

ISBN: (纸本)9798350305463

In this paper, the physics engine of Unity is used to simulate the construction of physical models in the real world. Based on numerical calculation and optimization algorithms, the fast multipole algorithmm and hierarchical collision detection algorithm are used to improve the calculation methods and algorithms. In combination with the API of related physics engines, the real physical system is quickly realized, thus improving the development efficiency. Optimize the operation logic of model data to make the operation effect more stable and smooth. © 2024 IEEE.

关键词： Numerical methods

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Dual-Stage Deep Learning Framework for Effective Public Physical Violence Detection 13

Dual-Stage Deep Learning Framework for Effective Public Phys...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Divya, Adusumilli Lakshmi, D. Sree Niveditha, Paramatmuni Lakshmi Sri, Pabolu Siva Naganjana Sreya Rohith, Venigalla Tati, Venkat Bhavan Pvpsit Computer Science Department India

ISBN: (纸本)9798350305463

Violent acts endanger both personal safety and social peace. Various solutions have been considered to minimise such behaviours, including the establishment of surveillance systems. the development of surveillance equipment that can detect aggressive behaviour autonomously is critical. the suggested system requires two stages to be executed. It must first detect the presence of persons inside video frames, followed by the extraction of frames containing potential violence. Unnecessary frames are then removed, leaving only pertinent instances of aggressive behaviour that are preserved as separate pictures. Whenever feasible, the technology recognises the faces of persons taking part in the activities.. Two pre-trained models are combined for higher accuracy and faster processing, addressing limitations of relying solely on Convolutional Neural Networks. this innovative system holds promise for enhancing safety and security. this two-staged approach comprises Faster RCNN Inception V2 COCO and MobileNet V2 pre-trained models that offers improved accuracy and serves as a foundation for constructing the full model. © 2024 IEEE.

关键词： Deep learning

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Multimedia Teaching Mode in Colleges and Universities Based on Psychology-Based Human-computer Interaction Interface Design

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international JOURNAL OF HUMAN-computer INTERACTION 2024年第13期40卷 3507-3515页

作者： Wang, Xiujun Heilongjiang Univ Acad Art Harbin Peoples R China

In order to adapt to the development of teaching informatization and meet the needs of students, teachers and parents, it is necessary to strengthen the active participation of students and integrate various curriculum resources, and improve teaching quality and the modes. Comprehensive multimedia software should be produced, including audiovisual and other sensory experiences. this is a concentrated expression of media diversity and networking, which not only breaks the traditional single-source education model, but also improves students' interest and enthusiasm for learning. As a new teaching tool, multimedia teaching uses the latest computer, multimedia and network technologies to make the presentation of teaching materials more dynamic. this is because it can break through the constraints of time and space and show a high degree of flexibility and interactivity. However, most multimedia teaching and learning in China are faced with problems such as poor interactivity, insufficient programming, product personalization, intellectual property rights and insufficient knowledge of software automation. therefore, this paper designed the multimedia teaching system from the perspective of psychology through human-computer interaction, so as to improve the teaching quality and promote the diversified development of teaching. the results showed that the multimedia teaching improved by about 9% compared with the traditional model, and the students' learning effect also improved by about 11% compared with the traditional model.

关键词： Multimedia teaching human-computer interaction interface design psychological perspective teaching evaluation

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Research on Intelligent Dispatching Optimization of New Energy Grid Considering the Impact of Wind Power 13

Research on Intelligent Dispatching Optimization of New Ener...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Wang, Jingdong Ding, Xu Meng, Fanqi Qu, Guangqiang School of Computer Science Northeast Electric Power University Jilin China

ISBN: (纸本)9798350305463

Wind power has strong instability and stochasticity, which bring great challenges to the grid dispatch operation system. In order to make up for the shortcomings of existing studies that neglect the uncertain out-of-set risks and fail to fully consider the demand flexibility, there is an urgent need to establish a new grid intelligent scheduling system. therefore, this paper firstly analyses the characteristics of wind energy, describes the impact of wind energy on the new energy grid, and summarises and introduces the planning method of the grid accessed by wind power. then, it fully utilises the advantages of artificial intelligence algorithms and classical mathematical algorithms and proposes an optimisation model for new energy grid dispatch containing wind power with an improved particle swarm algorithm. It effectively reduces the risk of distribution grid scheduling and can provide guidance for realising more efficient and stable new energy grid scheduling containing wind power. © 2024 IEEE.

关键词： Wind power

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14th international conference on Emerging Ubiquitous Systems and Pervasive Networks / 13th international conference on Current and Future Trends of Information and Communication technologies in Healthcare, EUSPN/ICth 2023

14th International Conference on Emerging Ubiquitous Systems...

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14th international conference on Emerging Ubiquitous Systems and Pervasive Networks / 13th international conference on Current and Future Trends of Information and Communication technologies in Healthcare, EUSPN/ICth 2023

the proceedings contain 119 papers. the topics discussed include: automatic accident detection system using IoT compared to the systems that a traffic center uses for accident detection;usability evaluation of handheld and wearable AR devices: exploring collaboration and the role of physical props;an improved hybrid metaheuristic for active job-shop scheduling problems;machine learning for predicting energy efficiency of buildings: a small data approach;digital citizenship and sustainable governance: a design thinking approach;time pressure's impact on taxi drivers' driving speed: a driving simulator study;exploring driver behaviors during tailgating situations: a driving simulator study;information system for remediation and cleanup of contaminated soil with machine learning;and from raw data to informed decisions: the development of an online data repository and visualization dashboard for transportation data.

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Lithium-Ion Battery State of Health Estimation Based on LSTM-Transformer 13

Lithium-Ion Battery State of Health Estimation Based on LSTM...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Meng, Fanqi Wang, Pengyan Wang, Jingdong Computer Science School Northeast Electric Power University Jilin China

ISBN: (纸本)9798350305463

Deep learning methods have demonstrated potential in estimating the health state of lithium batteries, which is essential for safety management. Yet, they often struggle to capture long-term dependencies and global correlations within battery capacity sequences. To address this challenge, a fused LSTM-Transformer approach for lithium battery health state estimation is proposed. the excellent sequence modelling capability of LSTM enables it to effectively capture the long-term dependence of battery performance evolution over time and adapt to pattern changes in different time scales, while the Transformer model achieves excellent global correlation capture through the self-attention mechanism. to understand the charging and discharging behaviour of batteries in a more global perspective. this integration allows the models to surpass the limitations inherent in using a single model and improves the ability to model the dynamic complexity of battery systems. Additionally, experimental results using a public dataset confirm that the method introduced in this paper offers a more thorough and precise evaluation of battery health compared to alternative deep learning artifacts. © 2024 IEEE.

关键词： Lithium-ion batteries

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Advancing Assistive Robotics Design: A Critical Narrative Review and Call for a Systems and User-Centered Approaches to Enhance Quality of Life of Individuals with Disabilities 13

Advancing Assistive Robotics Design: A Critical Narrative Re...

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13th Nordic conference on Human-computer Interaction (NordiCHI)

作者： Frennert, Susanne Persson, Johanna Skavron, Sarah Lund Univ Design Sci Lund Sweden Lund Univ Dept Design Sci Lund Sweden

ISBN: (纸本)9798400709654

Background: Despite the rapid pace of assistive robotics development, adoption of these has been limited. this raises questions such as: What contributes to this low uptake? What strategies could be employed to increase uptake? What guidance can be found in the literature to inform alternative approaches or directions for development? Objective: this critical narrative review sheds light on the development of assistive robotics technology for individuals with disabilities. We explore factors contributing to the low uptake of assistive robotics technology and propose alternative approaches for increased adoption. Methods: We identified and reviewed 73 relevant publications. Results: the findings of the review indicate that to increase uptake of assistive robotics technology, a systems approach that consider factors at different levels-micro, meso, and macro-might be necessary. While user involvement has been highlighted as crucial, it does not automatically translate into higher uptake. the impact of user feedback on the design process is often unclear or not portrayed. Conclusion: this critical narrative review identified a growing recognition of the importance of involving users in the design process, however there is still a long way to go to ensure that designs are truly user-centered. the review identifies several gaps and shortcomings in current approaches in the evaluation and development of assistive robotics technologies, including a narrow focus on usability and safety, and the absence of detailed information on how and if the users feedback impacts the design.

关键词： assistive robotics technologies critical narrative review user needs key acceptance factors gender perspective ethics

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Transforming Modern Medicine with the Role of the Healthcare Internet of things in Enhancing Patient Care and Monitoring 13

Transforming Modern Medicine with the Role of the Healthcare...

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13th IEEE international conference on Communication Systems and Network technologies, CSNT 2024

作者： Inzimam Bhuvana, J. Desai, Karishma Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India Atlas SkillTech University Department of UGDX Maharashtra Mumbai India

ISBN: (纸本)9798350305463

the present healthcare sector is experiencing a fundamental upheaval with the emergence of the Healthcare Internet of things (HIoT). this article delves into the transformational potential of HIoT by examining its use in bettering patient care and monitoring. the paper dives into the introduction of HIoT, the methodologies adopted for research and development, the compelling findings gained, and the farreaching consequences in conclusion the opening part sets the scene by describing the fundamental transformation in healthcare facilitated by HIoT. It emphasizes the catalyst for rethinking patient care and monitoring as the combination of internet-connected devices, smart sensors, and data analytics. HIoT equips doctors with up-to-the-minute information, allowing for more precise diagnoses and more individualized plans of care. Furthermore, deep learning and artificial intelligence were incorporated to exploit the richness of HIoTgenerated data, allowing sophisticated analytics and informed decision-making. the compelling findings of this study are clear, with the suggested technique regularly beating existing methods across numerous criteria. A remarkable accuracy score of 0.94 was reached, demonstrating the reliability of the suggested strategy in supporting informed healthcare decisions. Furthermore, in terms of cost efficiency, the suggested approach scored 0.95, suggesting its costeffectiveness and potential for economic viability. the development of HIoT promises a healthcare system that is more patient-centered, data-driven, and efficient in the future. To ensure healthcare continues to grow into an age of unmatched patient care and monitoring, researchers, healthcare providers, and governments must work together to harness this transformational potential while tackling the issues that come with it. © 2024 IEEE.

关键词： Predictive analytics

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