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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Inokuchi, Yuto González, Pedro Henrique Mendonça, Israel Aritsugi, Masayoshi Graduate School of Science and Technology Kumamoto University Kumamoto Japan Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350308365

While Spatio-Temporal Graph Convolutional Networks (STGCNs) are an effective method for traffic speed fore-casting, their training and inference tend to be time-consuming. In this paper, we aim to refine these networks by strategically reducing their number of nodes, thereby boosting computational efficiency. The nodes in these graphs represent data observed for road segments, and by analyzing the interconnections and layout of the graph, we can identify nodes with minimal contribution to overall performance. Removing these nodes can potentially decrease computation time while maintaining the prediction accuracy. We employ the Biased Random-Key Genetic Algorithm (BRKGA) to identify a good set of nodes for removal, based on a predefined percentage reduction of the original graph size (e.g., retaining 95 % of the original graph). We evaluate different graph size configurations, ranging from 95 % to 70 % node retention, to determine the least impactful node set performance. Our experiments on three real-world datasets reveal that reducing nodes can decrease computation time by up to 29%, and as a byproduct of removing noise, even improve the prediction accuracy. © 2024 IEEE.

关键词： Genetic algorithms

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Efficient Hyperparameter Optimization Using Deep Q-Network and BRKGA 13

Efficient Hyperparameter Optimization Using Deep Q-Network a...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Kobayashi, Kosei Aritsugi, Masayoshi González, Pedro Henrique Mendonça, Israel Graduate School of Science and Technology Kumamoto University Kumamoto Japan Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan System Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

Hyperparameter optimization (HPO) is paragon to maximize performance when designing machine learning models. Among different HPO methods, Genetic Algorithm (GA) based optimization is considered effective because it allows a wide and diverse range of solutions to be explored. However, GA's exploratory nature makes this type of algorithm to evaluate many solutions that do not improve the overall performance. This is specially costly when the objective function to be evaluated is time-consuming, like in the HPO field. In this paper, we propose an efficient hybrid algorithm that is able to reduce computational cost by combining deep reinforcement learning with the Biased Random Key Genetic Algorithm (BRKGA), a variant of genetic algorithms. Our reinforcement learning agent has a decision-making role during the population's fitness calculation, in which it filters out chromosomes that would not improve the overall fitness of the population. The agent uses small amounts of pre-trained data to identify trends in potentially good solutions, and carry out its decision process. We conduct experiments on eight different datasets to assess the effectiveness of the proposed method, and the results show that the proposed method can significantly reduce the computation time of hyperparameter search using BRKGA (up to 44% reduction in computational time) without compromising the quality of the solution (no statistically difference in results). © 2024 IEEE.

关键词： Genetic algorithms

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Efficient Node Reduction Heuristic for GNN-Based Traffic Speed Forecasting 11

Efficient Node Reduction Heuristic for GNN-Based Traffic Spe...

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11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Inokuchi, Yuto Gonzalez, Pedro Henrique Aritsugi, Masayoshi Mendonca, Israel Kumamoto University Graduate School of Science and Technology Kumamoto Japan Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350367300

In this paper, we aim to reduce the number of nodes from Graph Neural Networks (GNNs), thereby simplifying models and reducing computational costs. GNNs are highly effective for various tasks, such as prediction, classification, and clustering, due to their ability to learn node and edge attributes and relationships, and they have been utilized for intelligent transportation systems recently by converting sensor networks into graph structures. Deep spatio-temporal neural networks, including Spatio-Temporal Graph Convolutional Networks (STGCNs), capture spatial and temporal dependencies, making them suitable for traffic speed forecasting, traffic demand prediction, and travel time estimation. Despite their success, GNNs face challenges in industrial applications due to significant memory usage and time consumption. In this paper, we propose a new approach to node reduction that outperforms existing methods in computational efficiency. Our experiments on two real-world traffic datasets demonstrate that using the heuristic and edge information to reduce nodes can cut computation time of optimization up to 95% and, by eliminating noise, can even enhance prediction accuracy. © 2024 IEEE.

关键词： Graph neural networks

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Enabling Smart Home Energy Management through Gesture-Based Control and IoT technology

Enabling Smart Home Energy Management through Gesture-Based ...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Rambe, Khairul Hawani Ou, Chia-Ho International Master Program in Information Technology and Applications Sweden National Pingtung University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

The Internet of Things (IoTs) have become ubiquitous in all aspects of public needs today. The application of IoT technology is crucial for promoting energy-saving behavior. This paper presents a control system used for smart home devices based on hand gesture control and Android applications. The hardware design uses the ESP32 microcontroller, which has an in-chip Wi-Fi module, making it very suitable for creating IoT application systems. The software was designed using the Arduino IDE, and the application display design was developed using Kodular Creator, which is used to control the lamps and switches. The experiment results show that the electrical equipment can be activated using the Android application with gesture sensors by waving down, up, left, and right. © 2023 IEEE.

关键词： Internet of things

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3D Facial Reconstruction Applied to Medical Cosmetology 5

3D Facial Reconstruction Applied to Medical Cosmetology

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5th IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability, ECBIOS 2023

作者： Hsieh, Sheng-Hsien Lin, Ming-Yi Chen, Ching-Han National Pingtung University of Science and Technology Program of Artificial Intelligence and Mechatronics Pingtung Taiwan Yuan Ze University Department of Computer Science and Engineering Taoyuan Taiwan National Central University Department of Computer Science and Engineering Taoyuan Taiwan

ISBN: (纸本)9798350320978

We present a high-accuracy 3D facial reconstruction system with the following features: real-time 3D facial reconstruction using exposure synchronization multi-camera, feature alignment to quantify facial differences, a software system based on a naked eye 3D display, and medical records for a 3D face database. The proposed system is novel and practical, and the algorithm and the hardware/software architecture improve the current non-quantitative communication status in medical aesthetics. The system achieves preoperative expectations, real-time recording and feedback during surgery, and postoperative tracking analysis, thus making doctor-patient communication more efficient. The facial data database records personal and quantitative beauty data and its changes, providing accurate medical and aesthetic treatment analysis for individuals. In addition, the collected data of different genders, ages, injection sites, and dosages contribute to the development of more accurate medical materials. With artificial intelligence and cloud architecture, we provide reliable data for medical aesthetics customers, helping them understand their medical aesthetic needs. Doctors also provide stable medical care quality to consumers through cloud data, and medical aesthetic consultants do not need to exaggerate medical effects excessively. They can inform customers of specific differences before and after surgery through precise data and provide visual communication and customer expansion to improve consultation conversion rates. © 2023 IEEE.

关键词： Visual communication

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Performance Improvement of Joint Space Distance Measurement for PIP joints 7

Performance Improvement of Joint Space Distance Measurement ...

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7th International Conference on Imaging, Signal Processing and Communications, ICISPC 2023

作者： Suzuki, Moeko Goto, Tomio Nagoya Institute of Technology Dept. of Creative Engineering Program Nagoya Japan Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan

ISBN: (纸本)9798350325072

In order to analyze progresses of rheumatoid arthritis, we are developing an application to measure the distance between finger joints from X-ray images. In this paper, we focus on second joints, which are known to be prone to arthritis. We have proposed a method of filtering images and detecting edges, which has improved accuracy. Experimental results show that practical application of this system will reduce the burden on physicians and contribute to early detection of rheumatoid arthritis. © 2023 IEEE.

关键词： Diseases

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10-point connector formed by two snap buttons

10-point connector formed by two snap buttons

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2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Yang, Chang-Ming Wu, Shu-Cing Kao, Rally Liao, Kuo-Cheng Wu, Ze-We Chen, Shih-Hung Chen, Chi-Chun Ming Young Biomedical Corp Miaoli Taiwan National Chin-Yi University of Technology Program Prospective Technology of Electrical Engineering and Computer Science Taichung Taiwan Bonanza Biotechnology Co.Ltd National Chin-Yi University of Technology Dept. of Computer Science and Information Engineering Taichung Taiwan National Chin-Yi University of Technology Dept. of Electronic Engineering Taichung Taiwan

ISBN: (纸本)9798350324136

With the rapid advancement of electronic textiles, the design and integration of connectors have emerged as pivotal challenges. This study emphasizes the development of a connection solution that amalgamates miniaturization, efficiency, and reliability, specifically tailored for Flexible Conductive Silicone Circuits. A diversified connection scheme is proposed, incorporating elements such as snaps, Pogo pins, and conductive hook-and-loop fasteners, thereby achieving an innovative and pragmatic design. Through meticulous manufacturing processes, including the utilization of hot-melt adhesive, PET films, conductive fabric, and other multilayer materials, a connection system with low impedance and commendable conductivity was successfully engineered. Impedance test outcomes have indicated that the resistance at each connection point is less than 0.7 ohms, substantiating its superior electrical properties. In terms of assembly, this research demonstrates the precise interconnection of the controller and conductive fabric circuit, ensured by metal pin technology, leading to connection stability. This solution not only furnishes appropriate connection technology for specific application scenarios but also opens new avenues and directions for connection design within the domain of electronic textiles. © 2024 IEEE.

关键词： Connectors E-Textiles Flexible Conductive Silicone Circuit PET films

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Lightweight Authenticated Key Agreement Protocol for Smart Power Grid Systems Using PUF

IEEE Open Journal of the Communications Society

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IEEE Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power Grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 IEEE.

关键词： Hash functions

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Using Real-Time Integrated computer Vision and Deep Learning for Advanced Factory Safety 4

Using Real-Time Integrated Computer Vision and Deep Learning...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Tsai, Shang-Te Chang, Yu-Cheng Huang, Chao-Yi Yang, Fang-Yuan Chien, Wei Wu, Zong-Rong School Art and Design Sanming University Fujian China National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan National Yunlin University of Science and Technology Department of Information Management Yunlin Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan National Yunlin University of Science and Technology Department of Technical and Vocational Program in Artificial Intelligence Yunlin Taiwan

ISBN: (纸本)9798350360721

Innovative safety in the workplace is vital as the high safety risks associated with electrical engineering construction can lead to injuries or even fatalities. Using computer vision technology, we experimented with scenarios such as 'normal operations' and 'unexpected incidents' to enhance safety measures. We integrated an Internet of Things system into the setup, enabling the system to quickly detect and alert to unexpected events in real-time, thereby improving workplace safety. © 2024 IEEE.

关键词： computer vision

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Density Based Spatial Clustering of Applications with Noise and Sentence Bert Embedding for Indonesian Utterance Clustering

Density Based Spatial Clustering of Applications with Noise ...

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2023 International Conference on computer science, Information technology and engineering, ICCoSITE 2023

作者： Hasani, Muhammad Fikri Heryadi, Yaya Arifin, Yulyani Lukas Suparta, Wayan Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classification is a task of text classification. As in general text classification, the required dataset requires a label to carry out the classification process. To speed up and help the utterance analysis process, there is already a method, namely clustering, and Density-based clustering is a part of clustering that can determine cluster patterns based on arbitrary data, with DBScan as one of its algorithms. This research used 10000 client utterance data of awhatsapp based e-commerce conversation. SentenceBert also used as a state of art sentence embedding. This research yield silhouette score of 0.327 as the best result from eps of 0.1 and MinPts of 95. However, based on the cluster result, sentences labelled as noise can be further clustered. Text Preprocessing, text augmentation and sentence embedding techniques can be explored to increase the cluster performance. © 2023 IEEE.

关键词： Embeddings

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