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Annual Conference on Wireless On Demand Network systems and Services (WONS)

作者： Maria Diamanti Aisha B Rahman Panagiotis Charatsaris Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9783903176713

ISBN: (纸本)9798331522025

6G networks envision a seamless integration of data and AI into their core operations, marking a new era where distributed client devices actively engage in intelligent processes, supported by a diverse ecosystem of AI service providers. This shift necessitates approaching traditional resource allocation problems from a market perspective, transparently reflecting the gains and losses of clients and providers within the ecosystem. In this paper, we use a multi-server, multi-model Federated Learning (FL) network as a case study to propose a market-based resource allocation framework. The framework models the joint problem of client resource allocation and pricing as a Fisher market, where servers compete to attract clients with private data and local computing resources for distributed model training. The joint problem is formulated as a convex program, aiming to maximize the total server utility related to their model’s accuracy, while incorporating clients’ total computing resource constraints and servers’ budget constraints. An analytical solution to the convex program is derived concluding the so-called Market Equilibrium (ME) point, where market clearance is achieved. The effectiveness of the proposed market-based resource allocation framework is validated through comparisons with established resource allocation and sharing schemes from the literature.

关键词： Federated learning Computational modeling Biological system modeling Ecosystems Distributed databases Pricing Data models Resource management Servers Artificial intelligence

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A Semantic Mapping Framework for Service Robots 25

A Semantic Mapping Framework for Service Robots

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Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing

作者： Lucyanno Frota Rui P. Rocha Dept. of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (纸本)9798400706295

Service robots are undergoing a massification process similar to what happened with personal computers and cell phones a few decades ago. Their ubiquitous coexistence and interaction with humans requires that their representation models of the workspace go beyond metric information used for safe navigation. They are also required to assign semantic meaning to objects and places, i.e. to build semantic maps, in order to understand scenes and engage in human-like interactions. This paper proposes the Semantic MAPping (SMAP) framework to provide a service robot operating in human populated environments with a semantic mapping layer on top of a metric SLAM layer. SMAP is modular, expandable, and efficient enough to run locally on the robot. It has been implemented in Robot Operating System 2 (ROS2) using modular Docker containers. Preliminary experiments with a Pioneer 3-DX mobile robot having a system on module Nvidia Jetson AGX Xavier demonstrated its potential for future service robotics applications.

关键词： semantic mapping

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Blockchain Integration for Robust Intellectual Property Protection in New Product Development (NPD) 3

Blockchain Integration for Robust Intellectual Property Prot...

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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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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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On-chip GaAs carrier lifetime investigation

arXiv

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arXiv 2025年

作者： Prayoonyong, Chawaphon Szydzik, Crispin Ren, Guanghui Corcoran, Bill Dubey, Aditya Murray, Caitlin E. Mitchell, Toby Mitchell, Arnan Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia MelbourneVIC Australia

We propose an alternative way to determine GaAs carrier lifetime using pump-probe measurement based on fibre optics and integrated waveguides. We find that our GaAs samples have the lifetime ranging from 30-80 ps, supporting the bandwidth ≥ 12.5 GHz. The platform utilised in this work could offer a cost-effective way to investigate photocarrier lifetime. Moreover, it may have the potential for high-speed switches and detectors, or could be exploited for possible all-optical modulation. © 2025, CC BY-NC-ND.

关键词： Gallium arsenide

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Securing Digital Media in the Age of AI and Deepfakes: A Hardware-Based Solution

Securing Digital Media in the Age of AI and Deepfakes: A Har...

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IEEE Southeastcon

作者： Eric Scott Sisson Steven C. Puckett Dept. of Electrical and Computer Engineering Mississippi State University Starkville AL USA Computer Science and Information Systems University of North Alabama Florence AL USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The current capabilities of deepfake and Artificial Intelligence (AI) technologies make it difficult to distinguish what is original from what is fabricated. Electronic documents can be digitally signed to verify and authenticate their information, making them admissible as evidence in court. In contrast, images and videos from Internet of Things (IoT) devices-such as police body cameras, security cameras, and smartphones are susceptible to deepfake manipulation, which can undermine their authenticity in legal proceedings. This research hypothesizes that digitally signing image and video data utilizing hardware cryptographic coprocessors could render them admissible in court. Utilizing our processes will also identify if any manipulation of the image data has occurred. Our approach addresses a critical need in the justice system to combat the challenges deepfakes pose and could pave the way for enhanced trust in digital evidence, bolstering the integrity of the judicial process.

关键词： Deepfakes Law enforcement Media Cameras Hardware Cryptography Internet of Things Artificial intelligence Digital signatures Coprocessors

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A Bi-LSTM Based Model for Social Media Extremism Detection in Context of Bangladesh

A Bi-LSTM Based Model for Social Media Extremism Detection i...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Sajib Saha Zahidul Islam Tanvirul Islam Md Monzur Morshed Tithee Chakma Mama Subhenur Latif Md Walid Bin Jashim Dept. of Computer Science & Engineering Daffodil Internation University Dhaka Bangladesh Department of Accounting & Information Systems University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

In today’s modern world, digital technology has advanced social networking with revolutionary changes. People use some most popular platforms like Facebook, YouTube and some other social media platforms to engage with each other for business, information sharing and so on. Attacking someone on social media platforms through comments, in response to their speech, has become a common occurrence in Bangladesh as well as worldwide. Very little research has been done in this related field for Bengali NLP. In this study we primarily focus on classifying these comments into two categories: extremist and non-extremist. Comments were collected from two of the most popular platforms, YouTube and Facebook, used in Bangladesh to build our "BEC (Bangla Extremist Comments)" dataset. To classify the comments, a CNN + Bi-LSTM hybrid model was employed considering extremist comments detection systems using deep learning-based sentiment analysis techniques. The proposed model achieved an accuracy rate of 85% in identifying the extremist comments. This research opens opportunities for future researchers to take advantage of contributing and collaboration in this field.

关键词： Deep learning Analytical models Sentiment analysis Video on demand Social networking (online) Computational modeling Information sharing Collaboration Web sites Context modeling

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Predicting Optimal Placement of Electric Vehicle Charge Stations Using Machine Learning: A Case Study in Glasgow, UK

Predicting Optimal Placement of Electric Vehicle Charge Stat...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Arash Mousaei Yahya Naderi dept. Computer and Electrical Engineering University of Tabriz Tabriz Iran Sustainable Energy Systems Department Ricardo AEA Glasgow U.K

ISBN: (数字)9798331525132

ISBN: (纸本)9798331525149

Given the reduced costs of establishing Electric Vehicle (EV) charging stations and the need to improve their accessibility, it is essential for EV developers and governments to identify optimized locations for new stations. This study presents a predictive modeling approach using Machine Learning to determine the optimal sites for EV charging stations in Glasgow. While various machine learning methods are available for this purpose, we focus on Linear Regression due to its simplicity and high accuracy. By analyzing a comprehensive dataset of 207 AC charging stations-including factors latitude, longitude, population density, number of kinds of plugs, total number of plugs, price per kWh, traffic conditions, distance to the nearest station, Air Quality Index (AQI), and land value - we aim to provide urban planners and policymakers with actionable insights. The study evaluates the performance of the Linear Regression model in predicting the most suitable locations for charging stations. The results indicate that the proposed model achieved impressive accuracy, with R 2 , Mean Absolute Error (MAE), and Mean Squared Error (MSE) values of 0.89, 0.05, and 0.08, respectively. This research contributes to the ongoing efforts in urban planning for sustainable mobility by offering a data-driven methodology for EV infrastructure development.

关键词： Accuracy Atmospheric modeling Linear regression Machine learning Predictive models Charging stations Electric vehicle charging Indexes Population density Plugs

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Reinforcement Learning for Unrelated Parallel Machine Scheduling with Release Dates, Setup Times, and Machine Eligibility 24

Reinforcement Learning for Unrelated Parallel Machine Schedu...

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Proceedings of the Winter Simulation Conference

作者： Sang-Hyun Cho Hyun-Jung Kim Lars Mönch Dept. of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Dept. of Mathematics and Computer Science University of Hagen Universitätsstraße 1 Hagen GERMANY

ISBN: (纸本)9798331534202

This paper presents a novel approach for solving unrelated parallel machine scheduling problems through reinforcement learning. Notably, we consider three main constraints: release date, machine eligibility, and sequence- and machine-dependent setup time to minimize total weighted tardiness. Our work presents a new graph representation for solving the problem and utilizes graph neural networks combined with reinforcement learning. Experimental results show that our proposed method outperforms traditional dispatching rules and an apparent tardiness cost-based algorithm. Furthermore, since we represent and solve the problem using graphs, our method can be used regardless of the number of jobs or machines once trained.

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Natural Language Processing for Conversational AI: Chatbots and Virtual Assistants

Natural Language Processing for Conversational AI: Chatbots ...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Neeraj Shrivastava Pushpa Tewari S. Sujatha Srinivasa Rao Bogireddy Neeraj Varshney Vinod Sharma Dept. of Engineering Medicaps University Indore India Dept. of Vocational Studies Guru Nanak College Dhanbad India Dept. of Civil Engineering K. Ramakrishnan College of Technology Trichy India Dept. of Software Engineer Horizon Systems Inc Phoenix Arizona Dept. of CSE GLA University Mathura India Dept. of Computer Science Jiwaji University Gwalior India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The frontline in developing the capabilities of chatbots and virtual assistants involves the use of NLP, enabling these machines to evolve into truly advanced, interactive machines that are able to comprehend and respond to human language with an almost unimaginable degree of accuracy. The paper will analyze some of the major NLP techniques and methodologies used for such systems: machine learning algorithms, neural networks, and semantic analysis. This would also mean that, with the help of big data and continuous learning, the work of chatbots and virtual assistants will range from answering queries to personalized recommendations. Language understanding, generation, and context management are discussed in detail, underlining how NLP improves user experience by making interactions more natural and intuitive. The challenges of ambiguous language processing, conversational context, and ensuring data privacy and security are discussed as well. Case studies and applications in real life show the impact of NLP on different sectors: customer service, healthcare, and e-commerce. The findings bring out the potential of NLP to change human-computer interaction and allow for more responsive and intelligent digital assistants.

关键词： Ethics Technological innovation Sentiment analysis Virtual assistants Semantics Speech recognition Chatbots Natural language processing User experience Text processing

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