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Experimental implementation of chaos-based video encryption using visible light communication technology

Applied Optics 2025年第9期64卷 C101-C118页

作者： Fotso, Sorel Bagio Nono Mbé, Jimmi Hervé Talla Takotue, Jean Ernest Takougang, Armand Cyrille Nzeukou Ndjiongue, Alain Richard Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang P.O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer Department of Electrical Engineering IUT-FV Bandjoun University of Dschang P.O. Box: 134 Bandjoun Cameroon Laboratory of Industrial Systems and Environmental Engineering Fotso Victor University Institute of Technology University of Dschang P.O. Box 134 Bandjoun Cameroon School of Electrical and Information Engineering Faculty of Engineering and the Built Environment University of the Witwatersrand Johannesburg South Africa

Simulations are commonly used to develop and evaluate video encryption algorithms. Although these approaches are useful for demonstrating theoretical feasibility and algorithm performance, they neglect practical challenges and real-world communication conditions. This oversight creates a critical gap in evaluating their effectiveness and security in practical applications. In this paper, we describe a novel, to the best of our knowledge, video encryption scheme that employs a modified chaotic Colpitts oscillator, a customized Josephus problem, and ribonucleic acid (RNA) operations, and is implemented in visible light communication (VLC) environment. The modified Colpitts oscillator reveals significant phenomena, the most prominent for this study being chaos. The encryption scheme involves block scrambling and pixel-level permutation employing a customized Josephus problem and a column and row shifting technique. Diffusion is then achieved through a custom Josephus problem-oriented RNA operation combined with basic RNA operations and cipher block chaining (CBC). Based on the results, we found that the customized Josephus problem-based permutation performed more efficiently than traditional methods, whereas the column and row shifting permutation was more robust. By eliminating key sequence coding and item-to-item operations, the proposed RNA operation reduces computational overhead. This video encryption scheme is proven to be effective and resilient at securing video data transmitted over the VLC channel, and it constitutes a significant advancement in areas such as surveillance, medical imaging, and military communication requiring robust secured video data. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Medical imaging

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Machine learning innovations in CPR: a comprehensive survey on enhanced resuscitation techniques

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Artificial Intelligence Review 2025年第8期58卷 1-41页

作者： Islam, Saidul Rjoub, Gaith Elmekki, Hanae Bentahar, Jamal Pedrycz, Witold Cohen, Robin Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Faculty of Information Technology Aqaba University of Technology Aqaba Jordan Department of Computer Science 6 G Research Center Khalifa University Abu Dhabi United Arab Emirates Gina Cody School of Engineering and Computer Science Concordia University Montreal Canada Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Research Center of Performance and Productivity Analysis Istinye University Sariyer/Istanbul Turkey David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada

This survey paper explores the transformative role of Machine Learning (ML) and Artificial Intelligence (AI) in Cardiopulmonary Resuscitation (CPR), marking a paradigm shift from conventional, manually driven resuscitation practices to intelligent, data-driven interventions. It examines the evolution of CPR through the lens of predictive modeling, AI-enhanced devices, and real-time decision-making tools that collectively aim to improve resuscitation outcomes and survival rates. Unlike prior surveys that either focus solely on traditional CPR methods or offer general insights into ML applications in healthcare, this work provides a novel interdisciplinary synthesis tailored specifically to the domain of CPR. It presents a comprehensive taxonomy that classifies ML techniques into four key CPR-related tasks: rhythm analysis, outcome prediction, non-invasive blood pressure and chest compression modeling, and real-time detection of pulse and Return of Spontaneous Circulation (ROSC). The paper critically evaluates emerging ML approaches-including Reinforcement Learning (RL) and transformer-based models-while also addressing real-world implementation barriers such as model interpretability, data limitations, and deployment in high-stakes clinical settings. Furthermore, it highlights the role of eXplainable AI (XAI) in fostering clinical trust and adoption. By bridging the gap between resuscitation science and advanced ML techniques, this survey establishes a structured foundation for future research and practical innovation in ML-enhanced CPR. It offers clear insights, identifies unexplored opportunities, and sets a forward-looking research agenda identifying emerging trends and practical implementation challenges aiming to improve both the reliability and effectiveness of CPR in real-world emergencies. © The Author(s) 2025.

关键词： Reinforcement learning

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Scalable Self-Tallying e-Voting using Homomorphic Time-Lock Puzzles and zk-SNARKs

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IEEE Transactions on Network Science and engineering 2025年

作者： Elsheikh, Muhammad Youssef, Amr M. Hasan, M. Anwar University of Waterloo Department of Electrical and Computer Engineering Canada Cairo Egypt Concordia University Concordia Institute for Information Systems Engineering QC Canada

Achieving fairness, verifiability, and abandon resistance poses challenges within e-voting protocols. This paper introduces a privacy-preserving self-tallying e-voting system leveraging blockchain technology. The system supports diverse e-voting models, including 'Yes/No', approval voting with multiple candidates, and score voting. By employing linearly homomorphic time-lock puzzles (LHTLPs) along with verifiable delay functions (VDFs) and zero-knowledge Succinct Non-interactive Argument of Knowledge schemes (zk-SNARKs), the proposed system ensures crucial security properties, including voter anonymity and eligibility, as well as ballot privacy and validity. It also provides efficient individual and universal verifiability (end-to-end verifiability), and dispute-freeness. More importantly, the system demonstrates fairness and abandon resistance. Furthermore, the evaluation of the proof-of-concept implementation on the Ethereum blockchain indicates that on-chain gas costs are either fixed or increasing slowly and logarithmically with the number of voters. © 2013 IEEE.

关键词： Blockchain

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Chatbot and its Impact on the Retail Industry 3

Chatbot and its Impact on the Retail Industry

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Tatikonda, Reshmi Kempanna, M. Thatikonda, Ramya Bhuvanesh, A. Thota, Ragupathi Keerthanadevi, R. Department of Computer Information Systems University of the Central Missouri Warrensburg United States Department of AI and ML Bangalore Institute of Technology Bengaluru India Department of Information Technology University of the Cumberlands Williamsburg United States Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli India Department of Information Technology Jawaharlal Technological University Hyderbad India Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli India

ISBN: (纸本)9798331527549

This study explores the transformative potential of chatbots in the retail industry, highlighting their role in enhancing customer engagement, optimizing business processes, and revolutionizing the nature of retail interactions. Through a comprehensive review of existing literature and case studies, the paper delves into the cognitive processes underlying human-chatbot interactions and examines their impact on customer experience, satisfaction, and loyalty. Chatbots serve a wide array of operational functions, including inventory management, automated order processing, data-driven analytics, and employee training. These functionalities streamline workflows, improve efficiency, and maximize resource utilization. The paper further explores the innovative applications of chatbots, including AI-driven personalization, conversational commerce, and seamless integration with emerging technologies. By analyzing both the current applications and challenges of chatbot technology in retail, the study uncovers the exciting opportunities they present for shaping the future of retail by fostering more personalized, efficient, and interactive customer experiences. © 2025 IEEE.

关键词： Inventory control

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Recyclable thin-film soft electronics for smart packaging and e-skins

arXiv

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arXiv 2025年

作者： Carneiro, Manuel Reis de Almeida, Aníbal T. Tavakoli, Mahmoud Majidi, Carmel Soft Machines Lab Department of Mechanical Engineering Carnegie Mellon University PittsburghPA15213 United States Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3030-290 Portugal

Despite advances in soft, sticker-like electronics, few efforts have dealt with the challenge of electronic waste. Here, we address this by introducing an eco-friendly conductive ink for thin-film circuitry composed of silver flakes (Ag) and a water-based polyurethane (WPU) dispersion. This ink uniquely combines high electrical conductivity (1.6x105 S/m), high resolution digital printability, robust adhesion for microchip integration, mechanical resilience, and recyclability. Recycling is achieved with an ecologically-friendly processing method to decompose the circuits into constituent elements and recover the conductive ink with a decrease of only 2.4% in conductivity. Moreover, adding liquid metal enables stretchability of up to 200% strain, although this introduces the need for more complex recycling steps. Lastly, we demonstrate on-skin electrophysiological monitoring biostickers along with a recyclable smart package with integrated sensors for monitoring safe storage of perishable foods. © 2025, CC BY-NC-ND.

关键词： Electronic Waste

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Design of a Rat Robotic Forelimb 13th

Design of a Rat Robotic Forelimb

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13th International Conference on Biomimetic and Biohybrid systems, Living Machines 2024

作者： Pham, Huy Jackson, Clayton B. Armstead, Benjamin Nourse, William R. P. Andrada, Emanuel Quinn, Roger D. Department of Mechanical and Aerospace Engineering Case Western Reserve University ClevelandOH44106 United States Institute of Zoology and Evolutionary Research Friedrich-Schiller University Jena Germany Department of Electrical Computer and Systems Engineering Case Western Reserve University ClevelandOH44106 United States

ISBN: (纸本)9783031725968

This paper presents the design of robotic rat forelimbs, scaled to 2.5 times the size of a female Sprague-Dawley rat. Based on a previous rat hindlimb model, significant enhancements were implemented to facilitate manufacturing, robustness, improve overall performance, and enhance biological accuracy. The two front legs are each equipped with five motors to enable sagittal rotations of the scapula, elbow, and wrist joints, along with scapula abduction and adduction. The leg segment dimensions are based on a scanned rat bones model, but the shapes are modified for 3D printing and assembly. Parts are printed using micro carbon fiber filled nylon, strengthened by various amounts of continuously inlaid carbon fiber. Revolute joints are driven by motors, and a pulley-belt transmission system is incorporated to move wrist and elbow motors higher up in order to reduce the inertia of the leg. Furthermore, the foot structure comprises two segments that are passively controlled by two torsion springs to enhance flexibility and facilitate a more naturalistic movement. Additionally, a new electrical board is integrated to enhance operational smoothness and align with the control scheme. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Machine design

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Hybrid Blockchain and IoT Driven Framework for Supply Chain Optimization by Enhancing Transparency, Efficiency and Cost Reduction 3

Hybrid Blockchain and IoT Driven Framework for Supply Chain ...

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

作者： Pradeep Kumar, S. Basha, C.H. Hussaian Prasath, C. Arun Amirthayogam, G. Lathif, Syed Ismail Abdul Leelavathi, R. Rajalakshmi Engineering College Computer Science Design Department Thandalam Chennai602105 India Sr University Department of Electrical and Electronics Engineering Warangal506371 India Mahendra Engineering College Department of Ece Namakkal637503 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai600062 India Srm Institute of Science and Technology Department of Data Science and Business Systems Chennai603203 India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode638012 India

ISBN: (纸本)9798331509675

Blockchain technology represents a modern supply chain management revolution which fixes operational challenges while providing enhanced transparency at reduced costs. The research develops HB-SCOF (Hybrid Blockchain-Enabled Supply Chain Optimization Framework) which combines blockchain self-verification databases with automatic smart contracts to maintain continuous supply chain observation and evaluate data credibility. The framework integrates tamper-proof transaction tracking mechanisms with unified supply chain network connectivity for securing data transmission as a trust delivery method through unbreakable shared databases. The retail-industry case study demonstrated a 25% decrease in expenses stemming from agency elimination alongside enhanced flow management and better stock distribution. The system demonstrates its effectiveness through assessments of key performance indicators including transaction speed and data accuracy together with business cost efficiency. This part looks at implementation methods through training stakeholders in addition to transforming organizational policies which produce successful outcomes. Blockchain technology labs verify its capability to enhance supply chain management efficiency while showing realistic deployment methods. © 2025 IEEE.

关键词： Smart contract

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Path Planning and Optimization for Cuspidal 6R Manipulators

arXiv

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arXiv 2025年

作者： Elias, Alexander J. Wen, John T. Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

A cuspidal robot can move from one inverse kinematics (IK) solution to another without crossing a singularity. Multiple industrial robots are cuspidal. They tend to have a beautiful mechanical design, but they pose path planning challenges. A task-space path may have a valid IK solution for each point along the path, but a continuous joint-space path may depend on the choice of the IK solution or even be infeasible. This paper presents new analysis, path planning, and optimization methods to enhance the utility of cuspidal robots. We first demonstrate an efficient method to identify cuspidal robots and show, for the first time, that the ABB GoFa and certain robots with three parallel joint axes are cuspidal. We then propose a new path planning method for cuspidal robots by finding all IK solutions for each point along a task-space path and constructing a graph to connect each vertex corresponding to an IK solution. Graph edges are weighted based on the optimization metric, such as minimizing joint velocity. The optimal feasible path is the shortest path in the graph. This method can find non-singular paths as well as smooth paths which pass through singularities. Finally, this path planning method is incorporated into a path optimization algorithm. Given a fixed workspace toolpath, we optimize the offset of the toolpath in the robot base frame while ensuring continuous joint motion. Code examples are available in a publicly accessible repository. © 2025, CC BY.

关键词： Inverse kinematics

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Semi-Autonomous Interaction Framework for Contact-Based Operations with Commercial UAVs IN GNSS-Denied Environments

Semi-Autonomous Interaction Framework for Contact-Based Oper...

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： A. González-Morgado Q. Zhang G. Damigos E. Cuniato T. Hui E. Sahin G. Nikolakopoulos R. Siegwart M. Fumagalli A. Ollero G. Heredia GRVC Robotics Labs University of Seville Spain 3D Media Group Tampere University Finland Department of Computer Electrical and Space Ericsson Research and the Robotics and AI Group Autonomous Systems Lab (ASL) at ETH Zurich Switzerland Department of Electrical and Photonics Engineering Technical University of Denmark Denmark Department of Computer Electrical and Space Robotics and AI Group

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Unmanned aerial vehicles (UAVs) are being increasingly established for autonomous contacted-based inspection of industrial assets, reducing the risk of errors by human operators. However, challenges remain in the navigation under unreliable Global Navigation Satellite System (GNSS) signals, or in the detection and interaction with the inspection surface, which limits the autonomy level of current UAV industrial technologies. This paper presents a semi-autonomous framework which combines automated target detection and interaction in GNSS-denied environments, with supervision commands by a human operator, to increase both safety and reliability. Our framework is composed of: (i) a camera-based onboard odometry solution for positioning the UAV in GNSSdenied conditions, (ii) a target-detection and filtering algorithm which estimates the orientation and position of the interaction target and (iii) a visual servoing strategy for approaching and contacting the target. The proposed framework is developed completely in ROS, and can be used with any commercial UAV. The framework is validated through outdoor flights, where a UAV detects and contacts a target on a vertical pipe.

关键词： Vibrations Global navigation satellite system Three-dimensional displays Switches Inspection Autonomous aerial vehicles Visual servoing Safety Odometry Reliability

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A Novel Approach to Smart Grid Energy Management Using the Osprey Optimization Algorithm 4

A Novel Approach to Smart Grid Energy Management Using the O...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Rudrapogu, Nissisolomon Hemalatha, N. Warkad, Sanjay B Jayanthi, A. Vinoth, K. Jayaram, B. Lecturer in Eee Nissisolomon Rudrapogu Mbts Government Polytechnic College Department of Electrical and Electronics Engineering Section Andhra Pradesh Guntur522005 India Bharath Institute of Higher Education and Research Department of Electrical and Electronics Engineering Tamil Nadu Chennai600073 India P. R. Pote Patil College of Engineering & Management Department of Electrical Engineering Maharashtra Amravati444602 India Jeppiaar Institute of Technology Department of Physics Tamil Nadu Sriperumbudur631502 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai600062 India Rmk Engineering College Department of Computer Science and Business Systems Tamil Nadu Thiruvallur601206 India

ISBN: (纸本)9798331523923

Smart Grid Energy Management (SGEM) denotes the function of optimizing energy flow in the grid while enhancing grid efficiency and stability. One major issue is that increased integration of Renewable Energy Sources (RESs) may add a layer of complexity to EM, which may, in turn, reduce the reliability and stability of the grid. Keeping such challenges in mind, this paper proposes the Osprey Optimization Algorithm (OOA) on its part to enhance SGEM through various facets of load balancing and energy distribution. The objective of this method is to minimize the Mean Absolute Percentage Error (MAPE), enhancing the precision of energy predictions and optimizing grid performance. The OOA optimizes energy distribution in micro grids, improving efficiency and reducing power losses. The performance of the suggested OOA method is assessed by contrasting it with other optimization approaches that are currently in use, including Particle Swarm Optimization (PSO), Multi Objective Genetic Algorithm (MOGA), Sparrow Search Algorithm (SSA), and Multi Objective Wind Driven Optimization (MOWDO). The OOA method is implemented on the MATLAB platform. The outcomes show that the proposed OOA method provides superior performance in minimizing MAPE, achieving the lowest MAPE value of 0.28%, indicating its enhanced accuracy in energy demand forecasting and optimization. © 2025 IEEE.

关键词： Clean energy

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