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Neural Networks and Neurotechnologies (NeuroNT), II International Conference on

作者： Abdul Sttar Ismail Wdaa Shokhan M. Al-Barzinji Hiba A. Tarish College of Education for pure Science University of Anbar Ramadi Iraq Department of Computer Networks Systems College of Computer Science and Information Technology University of Anbar Ramadi Iraq Civil Engineering Departments University of Technology Baghdad Iraq

ISBN: (数字)9798350363739

ISBN: (纸本)9798350363746

An Evolutionary algorithm is a subset of evolutionary computations. Cloning, mutation, recombination, and selection are some of the methods used by the evolutionary algorithm that were inspired by biological evolution. The problem that was addressed in this study is how to find the coefficient values of the variables in linear equations that contain a set of variables, it must equal the right side. After reviewing previous research looking for optimization, genetic algorithm, which will use in this paper, so how are going to use this strategy to solve our problems? Select the best chromosomes from this population. Perform random chromosomal hybridization. Then, within the genes of our chromosomes, produce random mutations. Will send these chromosomes for selection again. The best chromosomes among them are selected again. It crosses and turns again, and the process is repeated until a certain number of generations have passed or find the best option. After applying the genetic algorithm through the Matlab program to the linear equation, which contains six variables, for example, the results were very excellent, as the parameter values were found in a very short time and with high accuracy, completely matching the right side of the equation.

关键词： Sensitivity analysis Evolution (biology) Sociology Evolutionary computation Statistics Biological cells Optimization

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Towards Near Real-time Digital Twins of Construction Sites: Developing High LOD 4D Simulation Based on computer Vision and RTLS 38

Towards Near Real-time Digital Twins of Construction Sites: ...

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38th International Symposium on Automation and Robotics in Construction, ISARC 2021

作者： Huang, Yusheng Hammad, Amin Torabi, Ghazaleh Ghelmani, Ali Guevremont, Michel Department of Building Civil and Environmental Engineering Concordia University Canada Concordia Institute of Information Systems Engineering Concordia University Canada Department of Electrical and Computer Engineering Concordia University Canada

ISBN: (纸本)9789526952413

4D simulation can be used in the planning phase of a project for constructability analysis, which aims to optimize construction processes and improve safety management. The same 4D simulation can be used as a digital twin in the construction phase for progress monitoring and identifying potential safety issues based on micro-schedules. A micro-schedule is a schedule listing tasks of short durations (i.e., days or hours) with the information of the resources assigned to each task (i.e., workers, equipment and materials). The site data can be collected using computer Vision (CV) or Real-Time Location systems (RTLS) to identify and recognize the activities of construction resources, as well as to capture the progress of the project. This paper aims to explore the possibility of developing near real-time digital twins of construction sites. The digital twin is developed as a high Level of Development (LOD) 4D Simulation based on CV and RTLS data. A case study is performed to investigate the proposed method. © 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.

关键词： computer vision

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Guest Editorial Special Issue on Near-Field Communications (NFCs) in Internet of Everything

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IEEE Internet of Things Journal 2025年第12期12卷 18459-18460页

作者： Pin-Han Ho Miaowen Wen Zhiguo Ding Marco Di Renzo Wei Duan Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada School of Electronic and Information Engineering South China University of Technology Guangzhou China Department of Computer Communication Engineering Khalifa University Abu Dhabi UAE Intelligent Physical Communications group in the Laboratory of Signals and Systems (L2S) Paris-Saclay University Gif-sur-Yvette France School of Information Science and Technology Nantong University Nantong China

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Leveraging Generalizability of Image-to-Image Translation for Enhanced Adversarial Defense

arXiv

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arXiv 2025年

作者： Zhang, Haibo Yao, Zhihua Sakurai, Kouichi Saitoh, Takeshi Department of Artificial Intelligence Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Japan Faculty of Economics and Business Administration The University of Kitakyushu Japan Department of Informatics Faculty of Information Science and Electrical Engineering Kyushu University Japan

In the rapidly evolving field of artificial intelligence, machine learning emerges as a key technology characterized by its vast potential and inherent risks. The stability and reliability of these models are important, as they are frequent targets of security threats. Adversarial attacks, first rigorously defined by Ian Goodfellow et al. in 2013, highlight a critical vulnerability: they can trick machine learning models into making incorrect predictions by applying nearly invisible perturbations to images. Although many studies have focused on constructing sophisticated defensive mechanisms to mitigate such attacks, they often overlook the substantial time and computational costs of training and maintaining these models. Ideally, a defense method should be able to generalize across various, even unseen, adversarial attacks with minimal overhead. Building on our previous work on image-to-image translation-based defenses, this study introduces an improved model that incorporates residual blocks to enhance generalizability. The proposed method requires training only a single model, effectively defends against diverse attack types, and is well-transferable between different target models. Experiments show that our model can restore the classification accuracy from near zero to an average of 72% while maintaining competitive performance compared to state-of-the-art methods. Significantly, our model operates more efficiently, reducing the time needed to process individual images and speeding up the training process to achieve faster convergence. Robustness tests further confirm stable performance under varying attack strengths, demonstrating the model’s practical value in real-world adversarial settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Generative adversarial networks

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What limits limits?

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National Science Review 2021年第1期8卷 11-14页

作者： Yong-Chun Liu Kun Huang Yun-Feng Xiao Lan Yang Cheng-Wei Qiu State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Frontier Science Center for Quantum Information Tsinghua University Department of Optics and Optical Engineering University of Science and Technology of China State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics School of Physics Peking University Department of Electrical and Systems Engineering Washington University Department of Electrical and Computer Engineering National University of Singapore

There are fundamental rules and principles setting the limits of physical systems. It triggers an interesting thought—can we break the limits under specific circumstances? A realistic system can only provide limited functionalities because its performance is physically constrained by some fundamental principles.‘Breaking the limit’, which usually implies that the capability of a system could be enhanced significantly,

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Learning Media Advancement Using Virtual Reality Technology for Heavy Equipment Safety in Indonesian Vocational Schools

Learning Media Advancement Using Virtual Reality Technology ...

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IEEE Region 10 International Conference TENCON

作者： Shofiyul Anam Al Mubarok Supeno Mardi Susiki Nugroho Feby Artwodini Muqtadiroh Surya Sumpeno Mauridhi Hery Purnomo Department of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Computer Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350350821

ISBN: (纸本)9798350350838

Mining Geology is one of the study programs provided by Indonesian Vocational Schools that explores surface mining. Mining is a work in hazardous environments that poses numerous risks. The use of heavy equipment is a frequent cause of mining accidents. Therefore, enhancing vocational students' understanding of heavy equipment safety is essential. However, having heavy equipment for learning its safety is costly and complex maintenance, demanding substantial financial investment from schools. Moreover, many vocational schools still use traditional learning media that cannot provide an immersive experience in learning. Thus, this study developed an immersive and engaging virtual reality (VR)-based learning media for vocational students learning heavy equipment safety. The validity and feasibility of the learning media contents were evaluated by experts. The result concluded that the contents presented are valid and have good feasibility. Moreover, the learning media was tested in the learning process and the usability was assessed by vocational students. The result concluded that the learning media demonstrates significant potential to improve the educational experience in vocational schools, leading to better learning outcomes and increased student engagement.

关键词： Atmospheric measurements Geology Immersive experience Media Particle measurements Safety Maintenance Usability Investment IEEE Regions

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QUANTIFYING SEASONAL WEATHER RISK IN INDIAN MARKETS: STOCHASTIC MODEL FOR RISK-AVERSE STATE-SPECIFIC TEMPERATURE DERIVATIVE PRICING

arXiv

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arXiv 2024年

作者： Hooda, Soumil Sharma, Shubham Bansal, Kunal Department of Electronics and Electrical Engineering BITS Pilani Hyderabad Campus India Department of Mechanical Engineering BITS Pilani Hyderabad Campus India Department of Computer Science and Information Systems BITS Pilani Hyderabad Campus India

This technical report presents a stochastic framework for pricing temperature derivatives in Indian markets, accounting for both monsoon and winter seasons. Utilizing historical temperature and electricity consumption data from 12 Indian states, we develop a model based on a modified mean-reverting Ornstein-Uhlenbeck process and employ Monte Carlo simulations for pricing. Our analysis reveals significant variations in option pricing across states, with monsoon call options ranging from 10.78 USD to 182.82 USD, and winter put options from 48.65 USD to 194.99 USD. The introduction of a risk aversion parameter shows substantial impacts on pricing, leading to an increase of up to 416% in option prices for certain states. Sensitivity analyses indicate that option prices are more responsive to changes in volatility than to mean reversion rates. Additionally, extreme weather scenarios can shift option prices by up to 409% during heatwaves and decrease by 60% during cold waves. These findings emphasize the importance of state-specific and season-specific approaches in temperature derivative pricing, highlighting the need for tailored risk management strategies in India’s diverse climate. © 2024, CC BY-NC-SA.

关键词： Sensitivity analysis

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Iterative AHA-Driven Microgrid Reconfiguration for Interconnection Performance Enhancement

Iterative AHA-Driven Microgrid Reconfiguration for Interconn...

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Global Power, Energy and Communication Conference (GPECOM)

作者： Wiam Ayrir Ahmed. M. Helmi Haitham S. Ramadan Electrical Engineering Networks and Telecommunication Systems Department National School of Applied Sciences Ibn Tofail University Kenitra Morocco Computer Engineering Department College of Engineering and Information Technology Buraydah Private Colleges Buraydah KSA Computer and Systems Engineering Faculty of Engineering Zagazig University Zagazig Egypt Electrical Power & Machines Department Zagazig University Zagazig Egypt Institut International Sur Le Stockage De l’Hydrogene (ISTHY) Belfort Territory France

ISBN: (数字)9798350351088

ISBN: (纸本)9798350351095

This paper presents an in-depth study on the reconfiguration of power distribution networks (PDN) in two interconnected microgrids using a recent bio-based optimization algorithm, the Artificial Hummingbird Algorithm, to minimize power losses and improve voltage profile within interconnected microgrids while keeping the radial topology in each microgrid and within the two. The proposed approach is validated by simulation on two interconnected 20-bus systems, demonstrating its effectiveness in achieving a balance between minimizing losses and improving voltage profile while reducing the cost function. Additionally, the results provide valuable insights into the field of PDN reconfiguration, providing a practical framework to optimize network performance and promote sustainable energy management.

关键词： Measurement Network topology Metaheuristics Microgrids Voltage Linear programming Topology

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Visualization System Using Virtual Reality for Work Improvement in Small and Medium Manufacturing Industries

Visualization System Using Virtual Reality for Work Improvem...

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IEEE International Conference on Embedded and Real-Time Computing systems and Applications (RTCSA)

作者： Shogo Ogihara Tetsuro Kato Takafumi Kawasaki Yuki Okura Takeshi Iwamoto Electrical and Computer Engineering Graduate School of Engineering Toyama Prefectural University Toyama Japan IoTry Inc. Toyama Japan Department of Information Systems Engineering Toyama Prefectural University Toyama Japan

The advancement of digitalization in the manufacturing industry has visualization that enables managers to comprehend the status and operation time of machines, thereby allowing them to identify and address bottlenecks in production lines. Although Gantt charts are commonly used for visualization in the manufacturing industry, there is an increasing need to adopt methods that more effectively visualize past events to facilitate understanding. Consequently, we have developed a Virtual Reality (VR) system aimed at improving the operations of small and medium-sized manufacturing enterprises through visualization. By utilizing sensors installed within the factory, we demonstrated that the VR space facilitates comprehensible work analysis instruction and simulation of optimal work processes.

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Data-driven Optimal Cooperative Output Regulation of Unknown Linear Discrete-time Multi-agent systems

Data-driven Optimal Cooperative Output Regulation of Unknown...

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第35届中国控制与决策会议

作者： Dong Liang Yi Dong Chaoli Wang Engang Tian Department of Control Science and Engineering School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University

The cooperative output regulation problem has been extensively studied on the basis of the distributed observer ***,the majority of the existing research assumes that the dynamics is known *** remove this condition,the cooperative output regulation problem is further solved via the data-driven framework where the dynamics of the plant is ***,a data-driven distributed observer is established to estimate the state of the leader with unknown dynamics subject to external ***,the unknown regulator equations are solved using the iterative recurrent neural network ***,the state-based data-driven distributed control law is synthesized to solve the *** optimal gains are derived by solving convex optimization problems using input and state ***,a numerical example is presented to verify the feasibility of the proposed framework.

关键词： Linear systems multi-agent systems cooperative output regulation data-driven control optimal control

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