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3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Chinnasamy, P. Subashini, B. Nijanthan, Nijanthan Madasamy Raja, G. Swetha, Devulapally Sreenivasulu Reddy, L. School of Computing Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu India School of Computing Srmist Department of Data Science and Business Systems Kattankulathur India Paavai Engineering College Tamilnadu Namakkal India Paavai Engineering College Tamilnadu Namakkal India Vaagdevi Engineering College Dept. of Computer Science and Engineering Warangal Dist. Telangana Bolli Kunta506005 India School of Advanced Sciences Kalasalingam Academy of Research and Education Department of Mathematics Tamilnadu Krishnankoil India

ISBN: (纸本)9798331509675

The rapid advancement of Blockchain technology has led to its widespread application in several domains of digital activities, such as e-government concerns and monetary security. This article presents a smart contract-based Blockchain solution for protecting intellectual property rights in new product development. The proposed solution effectively tackles the challenges associated with the confidentiality of personally identifiable information, efficiency in storing transaction-related information, as well as cooperation and monitoring in IPR. Initially, we create a mathematical model based on smart contract enabled Blockchain and intelligent contracts. Subsequently, we develop algorithms for Blockchain generation, and intelligent contracts. The system is suitable for protecting IPR in a blockchain network, by implementation of distributed identity authentication and real-time extensible storage. These features enhance the security and expandability of circuit copyright protection based on blockchain technology. The experimental results demonstrate that the suggested algorithm has decreased the cost for communication and enhanced the effectiveness of storing information and administration. Furthermore, it demonstrates resilience against many common attacks such as double-spending assaults, while maintaining low cost and overhead. Additionally, it exhibits a superior level of security in comparison to three other competing algorithms. © 2025 IEEE.

关键词： Smart contract

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FedStar Caching: Decision Center Assisted Federated Cooperative Edge Caching

FedStar Caching: Decision Center Assisted Federated Cooperat...

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IEEE International Conference on Human-Machine systems

作者： Sirvan Gharib Mohammad Mansour Kesargheh S. Jamal Seyedmohammadi Zohreh Hajiakhondi Jamshid Abouei Konstantinos N. Plataniotis Dept. of Electrical Engineering Yazd University Yazd Iran Inst. of Information Systems Engineering Concordia University Montreal Canada Dept. of Electrical Engineering Concordia University Montreal Canada Dept. of Electrical and Computer Engineering University of Toronto Toronto Canada

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

With the explosion of data, Wireless Edge Caching (WEC) has become a promising approach for locally accessing cached contents. Due to the limited storage capacity of local caching devices and the varying preferences of humans for content, it is necessary to predict popular contents. In this article, we will address two distinct objectives: 1) Popularity prediction of the content that should be cached at the edge to effectively utilize edge device memory. 2) Edge devices collaboration for efficient content delivery. Accordingly, we propose an FL-based Star Cooperative Caching (FedStar Caching), utilizing a Star network topology for realizing an efficient cooperation among Femto-cell Access Points (FAPs) using a Decision Center (DC) to enhance power efficiency and delay performance. Considering human sensitivity to privacy, collecting users’ data on a central server is not desirable, therefore, we leverage Federated Learning (FL) to alleviate this challenge. Simulation results demonstrate that the proposed method outperforms alternatives in terms of cache efficiency, as well as delay and power consumption.

关键词： Wireless communication Wireless sensor networks Power demand Network topology Cooperative caching Simulation Stars

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Development of a visual programming tool called SmrAI for function testing to mitigate the shortage of programming personnel in the manufacturing

Computer Software

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computer Software 2022年第4期39卷 61-74页

作者： Sugiyama, Ko-Ichiro Okuda, Satsuki Tanabe, Tsubasa Takao, Kouji Higashi, Hirohito Tanaka, Kazuaki Dept. of Information Engineering National Institute of Technology Matsue College Japan NIPPO Co. Ltd. Japan Ruby Programming Shounendan Japan Shimane IT Open-innovation Center Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Japan

We have developed a visual programming tool called SmrAI for function testing, and investigated whether wrapping existing source code with Scratch Blocks is an effective means of mitigating the shortage of programming personnel in the manufacturing. SmrAI is based on Smalruby, which can convert Scratch Blocks into Ruby code. In addition, SmrAI introduces two new sets of Blocks that wrap existing Ruby libraries for function testing. Since existing tools and libraries were utilized, the cost of developing SmrAI was low, and there were no changes in the function testing procedure. We conducted a verification test using staff members who were familiar with the function testing process but had little or no programming experience, and confirmed that they were able to program using SmrAI and that they had confidence in its business applications. These results are expected to contribute to the diversification and increase of programming personnel responsible for function test programming. © 2022 Japan Society for Software Science and Technology. All rights reserved.

关键词： Application programs

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Multi-Topic Belief Formation Through Bifurcations Over Signed Social Networks

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IEEE Transactions on Automatic Control 2025年

作者： Bizyaeva, Anastasia Franci, Alessio Leonard, Naomi E. University of Washington NSF AI Institute in Dynamic Systems Dept. of Mechanical Engineering SeattleWA98195 United States University of Liège Dept. of Electrical Engineering and Computer Science Belgium WEL Research Institute Wavre Belgium Princeton University Dept. of Mechanical and Aerospace Engineering PrincetonNJ08544 United States

We propose and analyze a nonlinear dynamic model of continuous-time multi-dimensional belief formation over signed social networks. Our model accounts for the effects of a structured belief system, self-appraisal, internal biases, and various sources of cognitive dissonance posited by recent theories in social psychology. We prove that agents become opinionated as a consequence of a bifurcation. We analyze how the balance of social network effects in the model controls the nature of the bifurcation and, therefore, the belief-forming limit-set solutions. Our analysis provides constructive conditions on how multi-stable network belief equilibria and belief oscillations emerging at a belief-forming bifurcation depend on the communication network graph and belief system network graph. Our model and analysis provide new theoretical insights on the dynamics of social systems and a new principled framework for designing decentralized decision-making on engineered networks in the presence of structured relationships among alternatives. © 1963-2012 IEEE.

关键词： Continuous time systems

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Comparing Actual Measurement and PVsyst Simulation Results for Energy Generation of Microgrid-Connected PV systems

Comparing Actual Measurement and PVsyst Simulation Results f...

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Smart Grid Conference (SGC)

作者： Mohammad Nazififard Hamed Hashemi-Dezaki Kia Nazififard Dept. of Energy Systems Engineering School of Mechanical Engineering Kashan Iran Dept. of Electrical and Computer Engineering Kashan Iran Independent Researcher Tehran Iran

This paper evaluates the uncertainty in energy generation of a 12 kW p microgrid (MG)-connected solar photovoltaic (PV) system located at the University of Kashan campus. The study compares long-term recorded measurements and PVsyst simulations for energy generation of PV systems over the course of a year. It is focused on specific yield and the deviation between the measured net energy generated by the PV facility and the calculated useful produced energy by PVsyst software. The results indicate a significant difference between the output power and the simulation results from PVsyst during colder months. However, in warmer months, the disparity between recorded measurements and simulated results is less than 10%. The largest deviation occurs in November, where the difference exceeds 35%. Generally, PVsyst software estimates the energy output from the PV system with an uncertainty of less than 10%. These findings contribute to understanding the variability in PV power generation and developing effective energy management strategies. Such strategies are crucial for ensuring a reliable power supply within an MG.

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Mobile Gateways for LoRa End-Devices: Support Connectivity on the Move

Mobile Gateways for LoRa End-Devices: Support Connectivity o...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Vasileios Moysiadis Dimitrios N. Skoutas Charalabos Skianis Thomas Lagkas Vasileios Argyriou Panagiotis Sarigiannidis Dept. of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Dept. of Information and Communication Systems Engineering University of the Aegean Samos Greece Dept. of Computer Science International Hellenic University Greece Dept. of Networks and Digital Media Kingston University Kingston upon Thames United Kingdom

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

This paper proposes a method enabling mobile LoRa gateways to support mobile end devices. The approach utilizes trilateration and similar approaches based on RSSI to estimate the position of end devices and specify the movement of the gateways to maintain contact. The evaluation of the proposed method tests various parameters such as speed and number of end devices, and it shows that it is able to retain contact even with speeds up to 12 mps. Moreover, the evaluation shows that the ADR-MIN algorithm performs better in this scenario than the default ADR.

关键词： Performance evaluation Network servers Conferences Computational modeling LoRa Logic gates Low-power wide area networks

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Motion Profile Optimization in Industrial Robots using Reinforcement Learning

Motion Profile Optimization in Industrial Robots using Reinf...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Yunshi Wen Honglu He Agung Julius John T. Wen Electrical Computer and Systems Engineering Dept. Rensselaer Polytechnic Institute Troy NY USA

Path tracking problems are challenging with the absence of dynamic models and information about robot controllers. This paper presents a method of optimizing a motion profile constructed using a set of pre-defined motion primitives and a speed command to track a spatial trajectory with high accuracy, speed, and uniform motion using industrial robots. We use a bi-level optimization approach that optimizes execution accuracy using reinforcement learning and execution speed using bi-section search. We train and evaluate the reinforcement learning policy in simulation for an ABB robot. Experiment results demonstrate that the learned policy reduces the optimization cost to achieve the desired specifications. Additionally, the trained policy can generalize to trajectories not included in the training set.

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A Dementia Diagnosis Technique Based on AI and Hardware Acceleration

A Dementia Diagnosis Technique Based on AI and Hardware Acce...

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2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023

作者： Khalil, Kasem Khan Mamun, Mohammad M. R. Sherif, Ahmed Elsersy, Mohamed Imam, Ahmad Abdel-Aliem Abouzaid, Kamal University of Mississippi Electrical and Computer Engineering Department MS United States Tennessee Technological University Electrical and Computer Engineering Department TN United States University of Southern Mississippi School of Computing Sciences and Computer Engineering MS United States Higher Colleges of Technology Computer and Information Systems Dept. Al Ain United Arab Emirates William Carey University College of Osteopathic Medicine Mississippi MS United States

ISBN: (纸本)9798350322347

The effects of Alzheimer's disease (AD) are devastating, both personally and within the patient's family, as the disease progresses slowly over many years. It could significantly affect illness consequences and outcomes if detected early and accurately. Non-invasive medical testing often uses blood bio-samples because they are easy to collect and relatively cheap to analyze. This paper proposes a federated learning (FL)-based diagnostic model for AD using blood bio-samples. We have used blood bio-sample data sets downloaded from the ADNI website to test and compare the efficacy of our models. According to the enormous data collected for early AD detection, we used a hardware acceleration scheme to implement our FL model to fasten the training and testing operations. The hardware-Accelerator method is implemented using VHDL and Altera 10 GX FPGA. The simulation results show the proposed algorithms reach an accuracy and sensitivity of 89% and 87%, respectively, for early detection while taking less time to train than other state-of-The-Art algorithms. The proposed algorithms also consume 52-172 mW, which makes them suitable for constrained devices. © 2023 IEEE.

关键词： Diagnosis

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Assessment of Backup Generator Connection Barriers to Australian Medium Voltage Networks

Assessment of Backup Generator Connection Barriers to Austra...

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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Mingchen Gu Chathuranga Wanninayaka Moudud Ahmed Kazi N. Hasan Lasantha Meegahapola Mahdi Jalili Richardt Wilkinson Brendan McGrath Xinghuo Yu Reza Razzaghi School of Engineering RMIT University Australia Dept. of Electrical and Computer Systems Engineering Monash University Australia

Demand response (DR) programs can benefit electricity consumers, distribution network service providers (DNSPs), system operators and the energy market. However, the complexity and characteristics associated with loads connected to customer premises, utilisation of backup generators for DR and the baseline calculation process still require considerable research to optimise and further unlock the capabilities of DR programs. This paper analyses the barriers to using backup generators in medium voltage (MV) networks in DR programs. Two representative Australian MV networks (e.g., Urban-NSW1 network, Urban-VIC network) are analysed in DIgSILENT PowerFactory under different scenarios, such as variation in locations, power export limits, and dynamic export limits of backup generators. The study has found that a backup generator located at the end of the network can achieve better performance in supporting the network voltage. Moreover, the voltage limit and thermal limit of the power network mainly constrain the export limits of backup generators. Furthermore, a backup generator with a dynamic export limit can export 1 to 5 times more energy than the static export limit.

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Training Swinging Door Trending Compression Algorithm for IoT devices

Training Swinging Door Trending Compression Algorithm for Io...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Juan David Arias Correa Alex Sandro Roschildt Pinto Carlos Montez Post-graduate Program of Automation Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms.

关键词： Training Performance evaluation Communication systems Data compression Prediction algorithms Market research Internet of Things Computational complexity Compression algorithms

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