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Challenge of Evolution to Cloud-Based control systems with Aging Industrial Device Communication Protocols

Challenge of Evolution to Cloud-Based Control Systems with A...

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control, Automation, and Instrumentation (IC2AI), International conference on

作者： Michael J. Anthony Technology & Innovation Rockwell Automation - Capitol Technology University Milwaukee WI USA

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

This paper provides a future looking perspective on the evolution of cloud-native technologies in the design, operation, and maintenance of industrial control systems with aging device communication protocols. First a look at traditional control system design patterns and technologies before the Industry 4.0 shift. Then consider how advanced computing and networking power introduced with Industry 4.0 changed control systems in the past 10 years. Finally, a look at how the shift towards cloud-native technologies, big data processing, AI, and advanced computer-aided learning algorithms are challenged by the data modeling and transport norms of today's systems. This paper is a work in progress and draws no conclusions on the future. The purpose of this paper is to bring academic discussion into the needs for communication standardization in the evolving space of cloud-based control system design.

关键词： Cloud computing Technological innovation Protocols Industrial control Production Aerospace electronics control systems Data models Fourth Industrial Revolution Artificial intelligence

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Quantum-Driven Hybrid Network Architecture Leveraging 5G for High-Speed and Resilient Data Transmission 6

Quantum-Driven Hybrid Network Architecture Leveraging 5G for...

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6th International conference on Mobile Computing and Sustainable Informatics, ICMCSI 2025

作者： Kumar, Kusuma Ashok Mohandas, R. Suneel, Sajja Mahalakshmi, M.R. Kumar, Avinash Singh, Manmohan Department of Physics B V Raju Institute of Technology Medak District Telangana state Narsapur502313 India Chennai Institute of Technology Chennai India Institute of Aeronautical Engineering Dundigal Telangana Hyderabad500043 India Department of ECE Sri Muthukumaran Institute of Technology Tamil Nadu Chennai600 069 India Department of Computer Science and Engineering IES College of Technology Bhopal India

ISBN: (纸本)9798331522667

The integration of quantum communication principles with 5G technology presents a groundbreaking approach to addressing the growing demand for high-speed, secure, and resilient communication systems. This paper proposes a Quantum-Driven Hybrid Network Architecture that leverages Quantum Key Distribution (QKD) for unparalleled security and combines it with 5G's ultra-fast data transmission capabilities. The architecture integrates key components such as QKD modules, 5G infrastructure, and edge computing, organized into a layered framework comprising quantum, network control, and application layers. Simulation results demonstrate significant improvements in throughput (up to 23.5%), latency reduction (up to 25%), and error rate reduction in high-noise environments (from 0.25% to 0.05%). The proposed system also exhibits enhanced security, achieving a 100% success rate in mitigating eavesdropping and man-in-the-middle attacks. Using resource-efficient mechanisms, the hybrid network achieves an overall accuracy of 97.8% in secure and resilient data transmission. This work validates the potential of quantum-enhanced 5G systems to meet the challenges of future communication networks. © 2025 IEEE.

关键词： Quantum communication

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Empowering future Engineers: Unveiling Personalized Flipped Classrooms in Basic Programming Education

Empowering Future Engineers: Unveiling Personalized Flipped ...

引用

17th International conference on computer Supported Education, CSEDU 2025

作者： Aldalur, Iñigo Markiegi, Urtzi Sagarna, Xabier Electronics and Computing Department Mondragon Unibertsitatea Arrasate-Mondragon Spain San Sebastian Spain

ISBN: (纸本)9789897587467

In the evolving educational landscape of the 21st century, innovative pedagogical methods like the Flipped Classroom (FC) and Personalized Learning (PL) have increased renown. The FC methodology revolutionizes traditional teaching by moving initial concept exposure outside the classroom, allowing in-class time for interactive and practical activities. This approach increases a dynamic learning environment, enhancing critical thinking, problem-solving, and collaboration skills. Successful FC implementation involves comprehensive educational experiences utilizing digital resources and active classroom interactions. PL adapts teaching to individual student needs, recognizing diverse learning speeds and cognitive styles. By leveraging technology, PL provides customized educational experiences that increase learner autonomy and motivation, leading to deeper understanding and engagement. A case study on teaching C programming using a Personalized Flipped Classroom (PFC) approach illustrates the practical application of these methodologies. The course design includes structured planning, multimedia resources, and continuous evaluation, promoting effective learning. Students engage with instructional videos and practical exercises, promoting autonomy and active participation. The course covers fundamental programming concepts, with a thematic progression that balances foundational understanding and advanced topics. Despite challenges like increased workload and digital competency gaps, the PFC approach demonstrates significant potential in enhancing student performance and skill development. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Engineering education

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DLT-Based Approach for Secure and Cyber Resilient Resource Constrained IoT Devices: A Survey on Recent Advances

DLT-Based Approach for Secure and Cyber Resilient Resource C...

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10th International conference on Internet of Things, Big Data and Security, IoTBDS 2025

作者： Mthethwa, Sthembile Dlamini, Moses Jembere, Edgar School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Westville Durban South Africa Pretoria South Africa

ISBN: (纸本)9789897587504

Distributed Ledger Technologies (DLTs) are advancing various fields such as the financial sector, supply chain management, Internet of Things (IoTs), etc. Through its characteristics, DLTs have the potential to solve some of the challenges encountered by IoT devices as the number of connected devices continues to grow tremendously. These characteristics includes but not limited to decentralisation, traceability, security, transparency, immutability, non-repudiation, etc. There has been an increase in the body of knowledge in relation to the convergence of DLTs and IoTs. This paper examines how DLTs can enhance the security of resource-constrained IoT devices, which have limitations that prevent the implementation of traditional security measures like encryption due to size and computational power. This paper consolidates existing research by comparing techniques, technologies used, and results achieved over the years. Finally, the research identifies knowledge gaps for future exploration. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Supply chain management

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A Review of Grid-Connected Inverters and control Methods Under Unbalanced Grid Conditions

A Review of Grid-Connected Inverters and Control Methods Und...

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Power Electronic and Drive systems and Technologies conference (PEDSTC)

作者： Milad Ghavipanjeh Marangalu Fazal Ur Rehman Naser Vosoughi Kurkdjian Dep. Of Electrical and Computer Engineering Computer Queen’s University Kingston Ontario Canada Dep. Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Faculty of Electrical and Computer Engineering San Diego State University San Diego CA USA

ISBN: (数字)9798331533946

ISBN: (纸本)9798331533953

Grid-connected inverters play a pivotal role in integrating renewable energy sources into modern power systems. However, the presence of unbalanced grid conditions poses significant challenges to the stable operation of these inverters. This review paper provides a comprehensive overview of grid-connected inverters and control methods tailored to address unbalanced grid conditions. Beginning with an introduction to the fundamentals of grid-connected inverters, the paper elucidates the impact of unbalanced grid voltages on their performance. Various control strategies, including voltage and current control methods, are examined in detail, highlighting their strengths and limitations in mitigating the effects of grid imbalance. Lastly, the review identifies emerging trends and future research directions in the field, emphasizing the need for innovative solutions to address the evolving challenges posed by unbalanced grid conditions in the context of renewable energy integration.

关键词： Current control Photovoltaic systems Renewable energy sources Technological innovation Reviews Pressing Market research Inverters Power systems Voltage control

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Path Planning for Multi-agent systems Using Deep Q-Networks Reinforcement Learning 25th

Path Planning for Multi-agent Systems Using Deep Q-Networks...

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25th Annual conference on Towards Autonomous Robotic systems, TAROS 2024

作者： Alispahić, Ibrahim Tahirović, Adnan Faculty of Electrical Engineering Department of Automatic Control and Electronics Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9783031720611

This work presents a comprehensive study of the application of multi-agent reinforcement learning (MARL) based on deep Q-networks (DQN), aiming to enhance the cooperation and coordination of multiple agents in complex environments. The core problem addressed is the multi-agent traveling salesman problem, i.e. the effective collaboration and target-reaching by multiple agents. This challenge is inherently present in a variety of applications, including inspection and maintenance tasks based on autonomous aerial robotic systems. The research delves into the intricacies of multi-agent systems, emphasizing the dynamic interaction between agents and the environment. Although the proposed algorithm is developed and trained in a planar space, its principles and methodologies are easily extendable to any operational environment. The proposed approach is capable of training on a number of different scenarios, using various numbers of agents and targets, regardless of their initial positions, making it highly adaptable to scenarios like aerial inspections, where the number of agents, the number of inspection sites and their locations are unknown a priori. Furthermore, the work outlines how the enhanced DQN algorithm can be tailored for scenarios with numerous autonomous agents and targets, ensuring efficient path planning and target acquisition in constrained and unstructured spaces. This work also provides a solid foundation for future research in integrating advanced reinforcement learning techniques into the design and operational strategies for solving tasks, which can be described by the multi-agent traveling salesman problem, including inspection and maintenance with an autonomous multi-agent system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Traveling salesman problem

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Toward Consistency in Writing Proficiency Assessment: Mitigating Classification Variability in Developmental Education

Toward Consistency in Writing Proficiency Assessment: Mitiga...

引用

17th International conference on computer Supported Education, CSEDU 2025

作者： Da Corte, Miguel Baptista, Jorge University of Algarve Faro Portugal INESC-ID Lisboa Lisbon Portugal

ISBN: (纸本)9789897587467

This study investigates the adequacy of Machine Learning (ML)-based systems, specifically ACCUPLACER, compared to human rater classifications within U.S. Developmental Education. A corpus of 100 essays was assessed by human raters using 6 linguistic descriptors, with each essay receiving a skill-level classification. These classifications were compared to those automatically generated by ACCUPLACER. Disagreements among raters were analyzed and resolved, producing a gold standard used as a benchmark for modeling ACCUPLACER'S classification task. A comparison of skill levels assigned by ACCUPLACER and humans revealed a "weak" Pearson correlation (ρ = 0.22), indicating a significant misplacement rate and raising important pedagogical and institutional concerns. Several ML algorithms were tested to replicate ACCUPLACER'S classification approach. Using the Chi-square (χ2) method to rank the most predictive linguistic descriptors, Naïve Bayes achieved 81.1% accuracy with the top-four ranked features. These findings emphasize the importance of refining descriptors and incorporating human input into the training of automated ML systems. Additionally, the gold standard developed for the 6 linguistic descriptors and overall skill levels can be used to (i) assess and classify students' English (L1) writing proficiency more holistically and equitably;(ii) support future ML modeling tasks;and (iii) enhance both student outcomes and higher education efficiency. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Natural language processing systems

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The future of Traffic Management: Embracing AI for Sustainable Urban Mobility

The Future of Traffic Management: Embracing AI for Sustainab...

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IEEE Students' conference on Electrical, Electronics and computer Science (SCEECS)

作者： Prashant Sharma Siddharth Sharma Raj Pratap Rosey Chauhan Shikha Verma Computer Science And Engineering Sharda University Greater Noida India

ISBN: (数字)9798331529833

ISBN: (纸本)9798331529840

The management of traffic in urban environments has become increasingly complex due to rapid urbanization and the growing number of vehicles on the road. This literature review synthesizes research on various traffic management systems and technologies, focusing on solutions such as real-time image processing, IoT-based systems, wireless sensor networks, and deep learning models. The review highlights key advancements, including intelligent traffic controllers utilizing real-time video analytics, IoT for congestion control, and AI-enabled traffic monitoring systems.

关键词： YOLO Wireless sensor networks Smart cities Biological system modeling Visual analytics Traffic control Real-time systems Stability analysis Safety Systematic literature review

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Digital Touchpoints: Generating Synthetic Data for Elderly Smartphone Interactions

Digital Touchpoints: Generating Synthetic Data for Elderly S...

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11th International conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2025

作者： Maqbool, Bilal Herold, Sebastian Department of Mathematics and Computer Science Faculty of Health Science and Technology Karlstad University Karlstad Sweden

ISBN: (纸本)9789897587436

Context: Ensuring smartphone interfaces are usable and accessible is essential for elderly users, particularly those with motor impairments, who face challenges with touchscreen interactions. Problem: Hand tremors and limited motor control can hinder touchscreen accuracy and efficiency. Meanwhile, recruiting elderly participants for usability studies can be challenging, often resulting in limited interaction data. Objectives: This study aimed to investigate elderly users’ smartphone interaction patterns, identify key challenges, and generate synthetic data to address data scarcity for usability research. Method: A custom-designed mobile app collected interaction data from 51 elderly participants performing tapping, dragging, and tracing tasks. Hand steadiness was assessed using accelerometer data. Gaussian Process Regression (GPR) and Long Short-Term Memory (LSTM) models were used to generate synthetic datasets replicating user interaction patterns. Results: Users with shaky hands struggled with precision tasks, especially involving smaller GUI elements, while larger elements improved performance. Continuous control was also found to be challenging in tracing tasks. Synthetic datasets successfully replicated spatial, temporal, and distributional metrics, demonstrating potential utility in future usability evaluation research. Conclusions: Inclusive GUI designs and adaptive features can improve accessibility for the elderly with limited motor control. Synthetic data can offer a potential solution for further usability evaluation research in building AI-driven design evaluation tools, reducing reliance on resource-intensive participant recruitment in earlier prototypes. future work should examine diverse tasks and scenarios and involve people with severe motor impairments. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Usability engineering

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Optimization of Power in Power Converters Using Machine Learning: An Overview 1

Optimization of Power in Power Converters Using Machine Lear...

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1st International conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Nayak, Prashant Kumar Swain, Debabrata Panda, Kaibalya Prasad Pandit Deendayal Energy University Department of Computer Science and Engineering Gandhinagar India Pandit Deendayal Energy University School of Energy Technology Department of Electrical Engineering Gandhinagar India

ISBN: (纸本)9798331520540

The rapid evolution in power electronics have brought significant attention to the optimization of power converters, which are essential for efficient energy conversion and management. Traditional techniques for optimizing power converters often struggle with the increasing complexity of modern systems, including nonlinear dynamics, diverse operating conditions, and stringent efficiency requirements. Last few decades, it has been observed that machine learning has evolved as hopeful solution with data driven methodologies to address various challenges. This survey provides the integration of machine learning for optimizing power converter, reviewing new approaches, key procedures and application in different domain. This categorizes different types of machine learning techniques and evaluate their usage in multiple fields like real-time control, fault detection, thermal management and system design. The paper also discusses different datasets, evaluation metrics and implementation framework in field of power converters. Lastly, challenges like computational complexity, data security and real-world deployment are highlighted along with direction towards future research to enhance the integration between machine learning and power converters. The comprehensive review aims to provide insight of researchers carried out to develop an intelligent power system. © 2025 IEEE.

关键词： Adversarial machine learning

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