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Protecting Intellectual Property Rights in the Digital Age: Implementing Cyber Security Measures and Strategies 1

7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Gadekar, Amit Goyal, S.B. Muqeem, Mohd Rajawat, Anand Singh Peiyu, Yao Chee, Weiming Sandip Institute of Technology and Research Centre Nashik India Faculty of Information Technology City University Petaling Jaya46100 Malaysia School of Computer Science & Engineering Sandip University Nashik422213 India City Graduate School City University Petaling Jaya46100 Malaysia

ISBN: (数字)9783031508875

ISBN: (纸本)9783031508868

The protection of intellectual property rights (IPR) has taken on increased importance in today’s interconnected world, but it also faces new obstacles. As patents, copyrights, trademarks, and trade secrets are increasingly represented digitally, they expose their owners to new risks in the form of cyberattacks. This paper explains why it’s crucial to use cutting-edge cybersecurity precautions and techniques when protecting intellectual property online. This book begins with a discussion of the current digital dangers to IPR, such as hacking, phishing, and unauthorized duplication and distribution, and then moves on to discuss the most effective modern cybersecurity strategies for mitigating these risks. Encryption, multi-factor authentication, IP management via blockchain, and AI-driven threat detection are just some of the methods investigated. The article also highlights the importance of cross-border cooperation, legal frameworks, and policies in bolstering IPR protection in the digital sphere. A comprehensive paradigm for protecting intellectual property rights in the digital age can be reached through the integration of technical cybersecurity measures with strong legislative and policy-driven tactics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Phishing

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A Survey on Applications of Large Language Model-Driven Digital Twins for Intelligent Network Optimization

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IEEE Communications Surveys and Tutorials 2025年

作者： Guo, Zhiqi Tang, Fengxiao Luo, Linfeng Zhao, Ming Kato, Nei Central South University School of Computer Science and Engineering Changsha410000 China Tohoku University Graduate School of Information Sciences Japan

With the widespread application of digital twin (DT) technology in network optimization and intelligent management, its integration with large language models (LLMs) presents immense potential. LLMs excel in natural language processing, multimodal analysis, and real-time optimization, enabling innovative solutions for intelligent monitoring, resource allocation, and decision-making in complex network environments. This paper systematically reviews the development of DTs and LLMs, elaborates on their core principles and application scenarios, and examines the capabilities of LLM-driven DTs in key network optimization tasks, including traffic prediction, fault diagnosis, resource allocation, and multi-objective optimization. By leveraging real-time data from DTs, LLMs can dynamically generate optimization strategies, enabling precise monitoring and intelligent tuning. Furthermore, this paper explores the potential of integrating LLMs and DTs to address complex challenges such as data quality, latency sensitivity, and energy consumption demands, while summarizing existing technical bottlenecks. Finally, the paper proposes several potential research directions to address these challenges, offering a comprehensive perspective for advancing the efficiency and automation of next-generation intelligent networks. © 1998-2012 IEEE.

关键词： Decision making

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Ubi-Care: An Elderly Life Support Healthcare Framework Based on Ubiquitous Personal Online Data Stores

Ubi-Care: An Elderly Life Support Healthcare Framework Based...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Chen, Hong Zhou, Tao Wu, Bo Graduate School of Human Sciences Waseda University Saitama359-1192 Japan Daiichi Institute of Technology Department of Information and Electronics System Engineering Taito Tokyo110-0005 Japan School of Computer Science Tokyo University of Technology Hachioji Tokyo192-0982 Japan

ISBN: (纸本)9781665410205

In recent years, the global aging population has intensified, leading to a sharp increase in social security benefits and caregiving costs. The elderly face greater health risks, and their behaviors often indicate signs of crises and illnesses. The rapid development of IoT technology offers new solutions for detecting abnormal signs, thereby promoting healthy aging, independent living, and social participation for the elderly. However, the diversity of IoT devices has led to the phenomenon of personal data silos. When the elderly leave their usual IoT environment, the issue of continuity in healthcare services becomes more pronounced. To address this issue, this study proposes a decentralized Ubi-Care framework. The framework aims to achieve complete separation of data and applications. It is based on the ActivityPub protocol and integrates various data from wearable devices, smart home sensors, and social networks, storing this data in a ubiquitous personal online data store (UPOD) and assigning different roles based on data type. UPOD applications support bidirectional following, allowing users to access data associated with relevant roles, addressing issues related to data categorization, sharing, privacy, and security. Additionally, this study proposes a method for utilizing complete UPOD data to perform anomaly detection based on the hidden Markov model (HMM). By effectively integrating IoT data into UPOD and enhancing data interoperability. The data-sharing model proposed in this study also facilitates elderly individuals and their family members in sharing relevant data as needed, while ensuring privacy protection. The methods proposed in this study will help prevent accidental injuries and enable early diagnosis of diseases, providing strong technical support for elderly healthcare. © 2024 IEEE.

关键词： Electronic health record

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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Data-Driven Incentive Mechanisms for Federated Learning in Vehicular Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Fathi, Faeze Montazeri, Mina N.araabi, Babak Du, Hongyang Niyato, Dusit Kebriaei, Hamed University of Tehran School of Ece College of Engineering Tehran Iran Urban Energy Systems Laboratory Dübendorf8600 Switzerland Nanyang Technological University School of Computer Science and Engineering The Energy Research Institute @ Ntu Interdisciplinary Graduate Program Singapore Nanyang Technological University School of Computer Science and Engineering Singapore School of Computer Science Tehran Iran

Centralized machine learning algorithms in vehicular networks face privacy and resource constraints. Federated Learning (FL) addresses these by enabling collaborative model training without sharing raw data. To incentivize vehicle participation despite resource constraints, we propose a contract between Roadside Units (RSUs) and vehicles, specifying required computation resources and rewards based on local data quality. The contract is designed to maximize the utility of the RSU, subject to constraints that ensure the participation of the vehicles in the task and truthful reporting of their data quality parameter. However, designing an optimal contract with classical methods is limited to specific utility functions. To extend the design methodology of optimal contracts to a broader range of utility functions, our study proposes a deep learning-based solution. Specifically, we present a novel application of Deep Neural Networks (DNNs), marking the first instance of applying DNNs in contract theory-based incentive mechanisms to achieve nearoptimal contracts. We design the DNN's structure to inherently satisfy specific constraints of the optimization problem, enhancing its efficiency and accuracy in determining the optimal contract. We utilize an augmented Lagrangian method to approximate the optimal contract in federated learning tasks. A case study on traffic sign recognition demonstrates the applicability and effectiveness of our method. Comparing our approach with the well-known generative diffusion model shows that in the FL scenarios, the DNN results are closer to the optimal contract compared to those of the generative diffusion model. © 1967-2012 IEEE.

关键词： Traffic signs

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An Interactive Sign Language Based Mobile Application for Deaf People 7

An Interactive Sign Language Based Mobile Application for De...

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7th International Conference on Trends in Electronics and Informatics, ICOEI 2023

作者： Setiawan, Vionna Thendyliputra, Raynaldo Santami, Sherly Angelina Hansen, Daniel Warnars, Harco Leslie Hendric Spits Ramdhan, Arief Doucet, Antoine School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Telkom University Bandung40257 Indonesia Universite de la Rochelle Laboratoire L3i France

ISBN: (纸本)9798350397284

Disability is a complex problem affecting many lives in Indonesia, especially people with hearing impairments. Disability is also a complex phenomenon, starting from the type of disability, degree of disability, and age of persons with disabilities to interactions and environmental impacts on disability. Moreover, there are many testimonies from around the world that people with disabilities are more likely to be weak and less likely to get an education. This paper aims to present a mobile application that offers sign language images and videos of any text in a learning environment that is shaped like a dictionary module to increase their vocabulary, learn a new sign language, and pronounce a word. This mobile application is specially designed for deaf people who have limitations in learning and educational training. This mobile application is equipped with several features such as user registration for the deaf and normal people who like to learn sign language, discussing through forums, using a sign language dictionary containing sign language text and pictures, using interactive learning videos, registering for an event activity, including giving input, and also make a donation. © 2023 IEEE.

关键词： Environmental impact

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Mobile Apps for Healthy Life Education for Young People 2

Mobile Apps for Healthy Life Education for Young People

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Suwandi, Benedictus Evan Warnars, Diana Teresia Spits Warnars, Harco Leslie Hendric Spits Utomo, Wiranto Herry Ramadhan, Arief Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Computing President University Department of Magister Science of Information Technology Bekasi17550 Indonesia

ISBN: (纸本)9781665400527

Health education is crucial for the community, especially the younger generation, because adolescent behavior/lifestyle will carry over into adulthood, and it is difficult to change it. This paper proposes designing and implementing a mobile application for young people for healthy lifestyle education. This mobile application implemented with the android studio is designed using use case diagrams to describe the business processes of this mobile application. In addition, activity diagrams describe the process details of each activity use case, and class diagrams describe the design of the database model, which is implemented using a MySQL database. © 2022 IEEE.

关键词： Mobile computing

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Consistency of determinism detection in sparse photoplethysmogram recordings 6

Consistency of determinism detection in sparse photoplethysm...

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6th International Conference on Biological information and Biomedical engineering, BIBE 2022

作者： Sviridova, Nina Sawada, Kazuya Ikeguchi, Tohru Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science Tokyo Japan International Research Center for Neurointelligence The University of Tokyo Tokyo Japan Department of Information and Computer Technology Graduate School of Engineering Tokyo University of Science Tokyo Japan

ISBN: (纸本)9783800759651

A human photoplethysmogram is a biological signal widely used for heart rate estimation, and it has a great potential for a variety of physiological and mental health monitoring applications. Photoplethysmogram is a highly complex, chaotic signal, and health monitoring applications beyond the heart rate estimation, such as mental health monitoring, may possibly require the extraction of photoplethysmogram dynamical properties that can be achieved by the application of nonlinear time series analysis. However, the applicability of nonlinear time series analysis imposes various requirements on the time series such as a sufficiently high sampling rate. This study aimed to investigate the effect of the sampling rate on the determinism of photoplethysmogram signals taken in reference conditions. The determinism, which is one of the fundamental properties of the dynamical system, was quantified by the recurrence quantification analysis, and the robustness of the determinism identification was verified by the surrogate data method. Results demonstrated that for the sampling frequency range 409.6~24.09 Hz only a minor decrease of determinism quantity is observed, thus confirming the consistency of the determinism detection in the photoplethysmogram time series of investigated sampling rates. © VDE VERLAG GMBH.

关键词： Harmonic analysis

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Rotational Regrasping For a Stick-type Object Using Inertial Force Based on High-speed Swing-up Motion

Rotational Regrasping For a Stick-type Object Using Inertial...

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2023 IEEE International Conference on Robotics and Biomimetics, ROBIO 2023

作者： Senoo, Taku Konno, Atsushi Otsubo, Hayato Ishii, Idaku Hokkaido University Course of Systems Science and Informatic Graduate School of Information Science and Technology Kita 14 Nishi 9 Kita-ku Hokkaido Sapporo060-0814 Japan Hiroshima University Smart Innovation Program Graduate School of Advanced Science and Engineering 1-4-1 Kagamiyama Hiroshima Higashi-Hiroshima739-8527 Japan

ISBN: (纸本)9798350325706

In this paper, robotic regrasping is considered with the goal of achieving dexterous manipulation. The strategy using quick wrist snap is based on human regrasping, and involves rotating the grasped object due to the inertial force while maintaining the contact state. The posture of the grasped object is measured by high-speed vision in real time and is used for posture control. Experimental results are shown where regrasping of a stick-type object in the direction contrary to gravity can be achieved by a high-speed robot hand. © 2023 IEEE.

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ACO with Reinforcement Learning Applied to Rescues Operations on Urban Forests 13

ACO with Reinforcement Learning Applied to Rescues Operation...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Alves, Cláudio Mendonça, Israel De Almeida Guimarães, Vanessa González, Pedro Henrique System Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan Coppead Graduate Business School Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

In the context of smart cities where green infras-tructure is incentived, besides important benefits like regulating temperatures and absorbing pollutants among others, tour by urban forests is a way to experience closer contact with nature near of big urban centers. Eventually, visitors get lost, and helping these people with velocity is important to avoid severe incidents. Normally, rescue operations mobilize firefighters, ex-pensive equipment like helicopters and public resources. Following that idea of reducing search time in rescue operations, this paper considers the Data Mule Routing Problem with Limited Autonomy (DMRP-wLA). To find high-quality solutions, this paper proposes an Ant Colony Optimization algorithm enhanced with Reinforcement Learning to create an adaptive decision-making algorithm. © 2024 IEEE.

关键词： Ant colony optimization

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