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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Alves, Cláudio Mendonça, Israel De Almeida Guimarães, Vanessa González, Pedro Henrique System Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan Coppead Graduate Business School Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

In the context of smart cities where green infras-tructure is incentived, besides important benefits like regulating temperatures and absorbing pollutants among others, tour by urban forests is a way to experience closer contact with nature near of big urban centers. Eventually, visitors get lost, and helping these people with velocity is important to avoid severe incidents. Normally, rescue operations mobilize firefighters, ex-pensive equipment like helicopters and public resources. Following that idea of reducing search time in rescue operations, this paper considers the Data Mule Routing Problem with Limited Autonomy (DMRP-wLA). To find high-quality solutions, this paper proposes an Ant Colony Optimization algorithm enhanced with Reinforcement Learning to create an adaptive decision-making algorithm. © 2024 IEEE.

关键词： Ant colony optimization

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A Novel Via-Based Magnetic Coupling Solution to Improving Illumination of Artificial Magnetic Conductor by Antenna-on-Chip

A Novel Via-Based Magnetic Coupling Solution to Improving Il...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Yiyang Yu Atif Shamim Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

Antenna-on-Chip (AoC) is one of the most promising solutions in upcoming 6G era. However, AoC suffers from low gain usually due to the highly conductive silicon substrate in mainstream complementary-metal-oxide-semiconductor (CMOS) processes. Artificial magnetic conductors (AMC) embedded within the stack-up of standard CMOS processes have been widely used to enhance the gain by isolating the AoC from the Si substrate and providing constructive reflection. Nonetheless, the ultra-thin stack-up of standard CMOS processes causes that only the AMC unit cells nearby the AoC can be illuminated well while the outermost part is illuminated poorly, which prevents the AMC from its optimal reflection performance. To mitigate the issue, this paper proposes a novel via-based magnetic coupling enhancement structures (H-CES- V) to improve the AMC illumination by coupling the energy from well-illuminated unit cells to outermost unit cells magnetically. Compared to conventional AMC, the gain can be improved by 1.5 dBi with the proposed structure. Finally, the proposed AMC-backed AoC with H-CES- V shows a boresight gain of 7 dBi (12 dBi better than a standalone AoC without AMC), and a radiation efficiency of 59 % at 94 GHz.

关键词： Couplings Lighting Conductors CMOS process Silicon Gain Antennas Substrates Magnetic circuits Standards

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Internet of Medical Things: A Bibliometric Analysis of Research Publications from 2018–2022 4th

Internet of Medical Things: A Bibliometric Analysis of Resea...

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4th International Conference on Electronics, Biomedical engineering, and Health Informatics, ICEBEHI 2023

作者： Maulana, Fairuz Iqbal Lestari, Dian Adi, Puput Dani Prasetyo Arifin, Mohammad Nazir Purnomo, Agung Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Faculty of Medicine Universitas Airlangga Surabaya60132 Indonesia Telecommunication Research Center National Research and Innovation Agency Jakarta11480 Indonesia Informatics Engineering Study Program University of Madura Pamekasan Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819714629

The field of the Internet of Medical Things (IoMT) is experiencing significant growth as it involves the integration of medical devices and systems with the internet and various digital technologies. This study provides a bibliometric analysis of scholarly articles pertaining to the Internet of Medical Things (IoMT) during the time frame of 2018 to 2022. The analysis is conducted using data sourced from the Scopus database. A total of 1165 documents were identified and analyzed to gain insights into the current state of research in this field. The analysis includes trends in publication output, top authors and institutions, and key research topics. The results of the analysis indicate a steady increase in publication output on IoMT over the past five years, with the highest number of publications in 2022. The top authors in this field were Mohanty, S.P., Kougianos, E., and Pirbhulal, S., while the top institutions were King Saud University, Chinese Academy of sciences, and University of North Texas. Co-citation analysis revealed that wearable devices, telemedicine, and data analytics were among the key research topics in IoMT. This bibliometric analysis offers useful insights into the present research landscape of the Internet of Medical Things (IoMT) spanning the years 2018 to 2022. The findings can be beneficial for researchers, practitioners, policymakers, and funding agencies in understanding the trends and priorities in this field. The top authors and institutions identified in this analysis can serve as valuable resources for collaboration and staying updated on the latest developments in IoMT. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital devices

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ChiBa—A Chirrup and Bark Detection System for Urban Environment 1

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10th International Conference on Mathematics and Computing, ICMC 2024

作者： Ganguly, Shuddhashil Mukherjee, Himadri Dhar, Ankita Marciano, Matteo Roy, Kaushik Department of Computer Science and Engineering Sister Nivedita University West Bengal Newtown India TISA Lab Department of Computer Science West Bengal State University West Bengal Berunanpukuria India Gazelien Records Lab Department of Arts and Humanities Music Program New York University Abu Dhabi Abu Dhabi United Arab Emirates

ISBN: (数字)9789819720699

ISBN: (纸本)9789819720682

The World is developing at a tremendous pace which has been catapulted by large-scale technological advancements. Building mega structures has never been easier and modes of commute have also developed thereby shortening travel-time. Such advancements have also brought along newer sources of pollution which are harming our planet at an even faster pace. Sound pollution is one such agent that has a long-term effect on not only humans but the entire biodiversity. Its effect on life is not immediately observed but the damage becomes visible over time. Birds are one of the most affected creatures due to sound pollution. This is one of the major reasons for declining bird population in the Urban areas. It is very important to preserve biodiversity for a sustainable future. Animals have calls that are melodious and rhythmic and these calls tend to change when they are in distress. An automated system can be very useful in this context which can monitor animal sounds and detect changes in their calls. Deployment of such a system in Urban areas is challenging due to the presence of ambient sounds which is extremely diverse. Thus it is essential to initially detect animal calls in the Urban environment prior to monitoring them. ChiBa is a system proposed to address this problem. Experiments were initially performed with the detection of birds and dogs (the most common and loudest creatures in cities) calls in the Urban environment. Tests were performed with over 7K clips comprising of the animal calls as well as Urban ambient sounds. The audios were modeled using a deep learning-based approach wherein the highest accuracy of 99.91% was obtained. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Birds

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Mitigating Misleading Chain-of-Thought Reasoning with Selective Filtering 30

Mitigating Misleading Chain-of-Thought Reasoning with Select...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wu, Yexin Zhang, Zhuosheng Zhao, Hai College of Zhiyuan Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9782493814104

Large language models have manifested remarkable capabilities by leveraging chain-of-thought (CoT) reasoning techniques to solve intricate questions through step-by-step reasoning chains. Despite its success, the efficacy of such reasoning is inherently contingent upon the quality of CoT. However, flawless CoT reasoning cannot be guaranteed due to the presence of indecomposable questions and the potential for erroneous reasoning chains, particularly in the case of small-scale language models. To tackle this challenge, we propose a novel approach called the selective filtering reasoner (SelF-Reasoner) that assesses the entailment relationship between the question and the candidate reasoning chain. Then, we proceed with CoT reasoning when the reasoning chain demonstrates confidence;otherwise, we opt to predict the answer directly. SelF-Reasoner improves the fine-tuned T5 baseline consistently over the scienceQA, ECQA, and LastLetter tasks. Code is available at https://***/LibroWu/SelF-Reasoner. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

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Privacy-Preserving Distributed Accelerated Resource Allocation in General Directed Networks

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IEEE Transactions on Consumer Electronics 2025年

作者： Zhang, Keke Lu, Qingguo Liao, Xiaofeng Li, Huaqing Huang, Tingwen Chongqing University College of Computer Science China Southwest University College of Electronic and Information Engineering China Texas A and M University Science Program Doha23874 Qatar

With the proliferation of consumer electronics applications, related devices usually entail allocating system resources to process large-scale distributed data in efficient ways. Effective allocation of system resources is crucial for improving device performance, optimizing energy efficiency, and safeguarding user experience. In this article, we study a distributed constraint-coupled resource allocation problem. Each node in directed networks maintains a private cost function and achieves a solution via only local communication. Problems of this nature considering efficiency and privacy usually emerge in consumer electronics (energy management, intelligent dispatch, energy conservation and utility optimization, etc.), which deserve to be addressed in depth. To tackle this problem, we propose an efficient privacy-preserving distributed accelerated resource allocation algorithm based on state decomposition with added noises. In one aspect, by applying the parametric distributed momentum method to the push-pull distributed resource allocation algorithm, we obtain accelerated allocation in directed networks. Given privacy concerns, our algorithm employs the differential privacy strategy along with a state decomposition scheme to avoid disclosing individual state information in communication. It is proven that our algorithm with a constant stepsize can linearly converge to a neighborhood of the optimal allocation while preserving privacy. The trade-off between convergence accuracy and privacy level is also shown. Extensive simulations further illustrate the efficacy of our algorithm and validate our theoretical discoveries. © 1975-2011 IEEE.

关键词： Cost functions

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Feasibility Analysis Study on Constructing a Grid Intrusion Detection System Using Semi-supervised Learning Models 2nd

Feasibility Analysis Study on Constructing a Grid Intrusion ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Tsai, Chia-Wei Lin, Jason Yang, Chun-Wei Loo, Fu-Nie Department of Computer Science and Information Engineering National Taichung University of Science and Technology No.129 Sec.3 Sanmin Rd North District Taichung404 Taiwan Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Rd. South District Taichung40227 Taiwan Master Program for Digital Health Innovation China Medical University No. 100 Sec. 1 Jingmao Rd. Beitun Dist. Taichung406040 Taiwan

ISBN: (纸本)9789819777853

In recent years, due to the proliferation of information and communication technology, as well as AI technology, industrial control systems, which were once in a closed network environment, have also integrated related technologies and gradually connected to external networks. Although this can enhance the efficiency of industrial production, it greatly increases the information security threats to industrial control systems. Among them, the information security issues of critical infrastructures are a key issue. If these critical infrastructures are attacked by cyber hackers, it could pose threats that jeopardize the safety of the general population. In light of this, this study focuses on the critical infrastructure of the power grid, proposing a semi-supervised intrusion detection system (IDS) technology by using the one-class classification. It analyzes data from the electricity distribution system to assess whether the system has been attacked. This research employs a power grid dataset to train the proposed model and execute the experiments. The experimental results demonstrate the feasibility of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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Multi-Normalization Residual Graph Convolutional Network for 3D Human Pose Estimation

Multi-Normalization Residual Graph Convolutional Network for...

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2025 International Workshop on Advanced Imaging Technology, IWAIT 2025

作者： Pramono, Andy Chang, I-Cheng Puspasari, Betty Dewi Animation Study Program Universitas Negeri Malang Jawa Timur Malang Indonesia Department of Computer Science and Information Engineering National Dong Hwa University Hualien Taiwan Department of Informatics Engineering Institut Teknologi Nasional Malang Jawa Timur Malang Indonesia

ISBN: (数字)9781510688131

ISBN: (纸本)9781510688124

3D human pose estimation (HPE) has improved significantly through Graph Convolutional Networks (GCNs), which effectively model body part ***, GCNs have limitations, including uniform feature transformations across nodes and reliance on skeleton-based graphs that may miss complex motion *** address these issues, we introduce a Multi-Normalization Residual Graph Convolutional Network that fine-tunes the graph structure through affinity multi-normalization and activation, allowing the representation of additional connections beyond the *** extensive ablation study shows that this approach enhances performance with minimal overhead while maintaining the same model size, consistently outperforming state-of-the-art techniques on two benchmark datasets. © 2024 SPIE.

关键词： Musculoskeletal system

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A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks 7

A Novel Hybrid Framework for Energy-Efficient Clustering and...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Gupta, Gopal Kumar Jain, Arpit Sharma, Khemraj Ashok Kumar, P.M. Gupta, Shubhi Agarwal, Sheenu Nagpur Campus Pune440008 India Koneru Lakshmaiah Education Foundation Department of Computer Science Engineering AP Vaddeswaram522502 India Nanhua University Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Amity University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Uttarakhand Technical University Department of Electronics and Communication Engineering U.K. Dehradun India

ISBN: (纸本)9798350350067

Smart computing has been particularly notable in the development of wireless sensor networks (WSNs), which have many applications. Battery-powered, self-configuring sensor nodes are the basis of these networks. Energy and resources are limited when it comes to sensors. Unbalanced nodes in the network consume more power, which adversely affects the network's lifespan. An improved energy-efficient cluster-based routing protocol for heterogeneous wireless sensor networks (WSNs) based on the Internet of Things is proposed in this study. Several performance metrics were used to evaluate the proposed model's effectiveness, including energy efficiency, alive nodes, dead nodes, network lifetime, and residual energy. The results of the comparison were compared with existing methodologies, such as LEACH, PSO, and hybrid PSO. The proposed approach outperforms the existing model by a substantial margin in networks with 50 and 100 nodes, according to the simulation results. © 2024 IEEE.

关键词： Sensor nodes

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Data Analytics and Visualization in Bimanual Rehabilitation Monitoring Systems: A User-Centered Design Approach to Healthcare Professionals Decision Support

Data Analytics and Visualization in Bimanual Rehabilitation ...

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2024 International Conference on Electrical engineering and Informatics, ICELTICs 2024

作者： Wisedsri, Parkpoom Anutariya, Chutiporn Sujarae, Aekavute Vachalathiti, Roongtiwa Bovonsunthonchai, Sunee School of Engineering and Technology Asian Institute of Technology Computer Science Program Pathum Thani Thailand Punsarn Asia Co. Ltd Thailand Mahidol University Faculty of Physical Therapy Nakhon Pathom Thailand

ISBN: (纸本)9798350366822

This study presents the design of a user-centered data visualization dashboard for stroke rehabilitation, which integrates the principles of visualization data analytics techniques in the field of healthcare. Addressing the complexities of visualizing for robotic bimanual rehabilitation, the design introduces novel methods to enhance data visualization, broadening monitoring capabilities, and improving the clarity of torque data. These enhancements lead to a clearer understanding of patient robot interactions. A prototype has been developed to visualize transparent torque data from a bimanual master slave robotic system, enabling healthcare professionals to monitor patient progress effectively. The dashboard features intuitive visual representations of master, slave, and assistive torques, simulating elbow joint movements through line and sunburst charts. Feedback from rehabilitation therapists during the design process ensures that the visualization approach is aligned with clinical needs. The findings suggest that the system can assist physiotherapists in devising personalized treatment strategies by providing actionable insights from the recorded data. However, additional research is needed to integrate real clinical data into the system for further enhancement and validation. This innovation has the potential to significantly improve stroke rehabilitation effectiveness and patient outcomes through a bimanual rehabilitation visualization and decision support system. © 2024 IEEE.

关键词： Clinical research

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