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6th IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2024

作者： Choi, Wonseok Jeong, Euidong Woo, Jongsoo Hong, James Won-Ki Postech Department of Computer Science and Engineering Pohang Korea Republic of

ISBN: (纸本)9798350316742

Bitcoin proved the potential of blockchain technology through decentralized, transparent, and immutable transactions. However, there are still challenges for fast and stable transitions. Optimizing block propagation times within the network is one of them. Prolonged propagation times can restrict efficiency, scalability, and security. This paper presents a novel approach to reducing block propagation time through leveraging reinforce-ment learning (RL) for the node's neighbor selection strategies. We implemented a Deep Q-Network (DQN) model in minimizing block receive times at each node, thereby impacting overall block propagation time. We used a model that defines node states based on latencies of outbound connections, which present the node's region. By evaluating this model through simulations using SimBlock, a robust Bitcoin network simulator, we observed a significant reduction in block propagation time - approximately 30% for smaller networks and 20% for larger ones. Our analysis extended to node connections generated by our model and comparative evaluation against existing methodologies. © 2024 IEEE.

关键词： Deep reinforcement learning

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Platform for Helping Senior Citizens and Enhancing Employment for Specially- Abled 2

Platform for Helping Senior Citizens and Enhancing Employmen...

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2nd IEEE International Conference on Data science and Network Security, ICDSNS 2024

作者： Jhalani, Yash Kaur, Harman Tyagi, Vansh Thakur, Shweta Chandigarh University Department of Computer Science Engineering Mohali India

ISBN: (纸本)9798350373110

This study aims to track the difficulties faced by senior citizens in today's world and to make a platform titled 'Helping Senior Citizens' for Senior Citizens in several ways. 'Helping Senior Citizens' website would be a one-step solution to many things like companies posting job vacancies for the elderly or specially-abled people and a portal to apply for the same, recreational activities, easy food ordering, and deliveries. This would act as a catalyst in enhancing their quality of life and help them to do what they want to. Also, it would act as a stress buster platform for the users due to the people, they would be able to connect to through this website. Specially- abled people are the most ignored and less privileged. But special attention would be given to their employment opportunities so that the users could feel no less than any normal person out there. This paper articulates the making of this one-stop solution website 'Helping Senior Citizen' using MVC architecture framework and technologies like EJS, MongoDB, ***, HTML, and CSS and implementing middlewares for authorization and authentication. © 2024 IEEE.

关键词： Websites

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Decentralized Energy Grid System Using IoT and Blockchain: A Sustainable Future 2nd

Decentralized Energy Grid System Using IoT and Blockchain: A...

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2nd International Conference on Data science and Network engineering, ICDSNE 2024

作者： Debnath, Saswati Patil, Vedavati Agrawal, Dhruv Department of Computer Science and Engineering Alliance University Karnataka Bengaluru India

ISBN: (纸本)9789819783359

The global pursuit of sustainable energy solutions has led to the exploration of innovative technologies aimed at revolutionizing energy management and distribution. This paper presents integration of Blockchain and Internet of Things (IoT) technologies in decentralizing energy management with a focal point on transmitting power data from small-scale renewable power stations to a central power plant. IoT devices strategically monitor energy production from renewable energy sources, such as wind turbines, solar panels, and microgrids, enabling real-time data analysis to maximize efficiency. These transactions, which are automated by smart contracts, ensure trust. Interoperability, data security, and user interfaces are all covered as the technical architecture required for seamless integration in this paper. It is important that regulations need to be changed to make room for creative energy solutions. This framework highlights sustainability, encourages energy independence, and lessens dependency on centralized power by supporting renewable energy sources. By combining blockchain technology, IoT, and sustainable energy practices, the proposed system aims to transform the way of energy distributing, improving security, resilience, and sustainability while giving to communities more control over how much energy they use and produce. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Clean energy

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Generative Adversarial Networks (GANs) for Education: State-Of-Art and Applications

Generative Adversarial Networks (GANs) for Education: State-...

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International Conference on Power engineering and Intelligent Systems, PEIS 2024

作者： Kavyashree, K.N. Shidaganti, Ganeshayya Department of Computer Science and Engineering Ramaiah Institute of Technology Bangalore India

ISBN: (纸本)9789819767090

In the ever-changing educational landscape, technology integration has become essential to improving students’ understanding of basic topics. The COVID-19 pandemic hastened the transition to online education while posing new difficulties for teachers and students alike. The disruption of traditional classroom dynamics was exacerbated by the lack of digital innovation and interactive instructional tools, which made student participation less effective. Traditional teaching paradigms must make way for ones that encourage self-directed learning and fortify technical infrastructure in order to handle these difficulties. Generative Adversarial Networks (GANs), a cutting-edge use of deep learning, are starting to revolutionize educational technology. With the use of GANs, a range of features that are tailored to the individual learning preferences of each student may be created, thereby bridging knowledge gaps and providing a more dynamic and interesting learning environment for students. This research investigates several state-of-the-art features that leverage technology linked to GANs to enhance students’ virtual learning environments. The novel applications of generative adversarial networks are explored, with a focus on applications for student observation, academic performance, questioning and answering, and personalized learning. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Optimized Consensus for Blockchain in Internet of Things Networks via Reinforcement Learning

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Tsinghua science and Technology 2023年第6期28卷 1009-1022页

作者： Yifei Zou Zongjing Jin Yanwei Zheng Dongxiao Yu Tian Lan Institute of Intelligent Computing School of Computer Science and TechnologyShandong UniversityQingdao 266237China Department of Electrical and Computer Engineering George Washington UniversityWashingtonDC 20052USA

Most blockchain systems currently adopt resource-consuming protocols to achieve consensus between miners;for example,the Proof-of-Work(PoW)and Practical Byzantine Fault Tolerant(PBFT)schemes,which have a high consumption of computing/communication resources and usually require reliable communications with bounded ***,these protocols may be unsuitable for Internet of Things(IoT)networks because the IoT devices are usually lightweight,battery-operated,and deployed in an unreliable wireless ***,this paper studies an efficient consensus protocol for blockchain in IoT networks via reinforcement ***,the consensus protocol in this work is designed on the basis of the Proof-of-Communication(PoC)scheme directly in a single-hop wireless network with unreliable communications.A distributed MultiAgent Reinforcement Learning(MARL)algorithm is proposed to improve the efficiency and fairness of consensus for miners in the blockchain *** this algorithm,each agent uses a matrix to depict the efficiency and fairness of the recent consensus and tunes its actions and rewards carefully in an actor-critic framework to seek effective *** results from the simulation show that the fairness of consensus in the proposed algorithm is guaranteed,and the efficiency nearly reaches a centralized optimal solution.

关键词： consensus in blockchain Proof-of-Communication(PoC) MultiAgent Reinforcement Learning(MARL) Internet of Things(IoT)networks

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Adaptive 360-Degree Video Streaming with Super-Resolution and Interpolation 32

Adaptive 360-Degree Video Streaming with Super-Resolution an...

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32nd IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2025

作者： Hong, Siyuan Wang, Ruiqi Cao, Guohong The Pennsylvania State University Department of Computer Science and Engineering United States

ISBN: (纸本)9798331536459

360° video streaming requires considerable bandwidth, and many techniques have been proposed to address this problem. One such technique is super-resolution, where the video is compressed at the server, and the client runs a deep learning model to enhance the video quality. However, most of today's off-the-shelf mobile devices cannot support super-resolution for all tiles in real time. As a result, some tiles cannot be reconstructed to high resolution, significantly reducing users' Quality of Experience (QoE). To address this problem, we utilize linear interpolation, which requires much less computational overhead. Through experiments, we observe that interpolation can achieve comparable quality, and even outperform super-resolution for some tiles with low spatial complexity. Building on this, we develop a 360° video streaming system that adaptively selects the most suitable downloading strategy, whether interpolation, super-resolution, or ABR at the appropriate bitrate, for each tile to maximize user QoE while considering network bandwidth limitations and the computational constraints of mobile devices. We formalize the 360° video streaming problem as an optimization problem and propose an efficient algorithm to solve it. Extensive evaluations using real user viewing data and 5G network traces demonstrate that our solution significantly outperforms existing techniques in terms of QoE under various scenarios. © 2025 IEEE.

关键词： Interpolation

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Energy Consumption in Wireless Sensor Networks Using Fruit Fly and Ant Colony Optimization Algorithms in Homogenous and Heterogeneous Environments 7

Energy Consumption in Wireless Sensor Networks Using Fruit F...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Neetu Gunjan Kaur, Amandeep Nit Delhi Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350350067

Wireless sensor networks (WSNs) is crucial in sensing environmental conditions in far-flung areas. However, their energy consumption remains a critical issue, affecting the network's lifetime and coverage area. Clustering has emerged as an efficient strategy to prolong sensor network lifespan, and the Fruit Fly Algorithm (FFA) and Ant Colony Optimization (ACO) are promising techniques for cluster formation and efficient path establishment, respectively. In this study, we propose an innovative approach that combines FFA for cluster formation and ACO for path establishment. This novel algorithm is implemented in MATLAB and evaluated in both homogeneous and heterogeneous environments. We compare our proposed algorithm with the Butterfly Optimization Algorithm (BOA) based clustering and Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm. Our findings suggest that the algorithm we proposed significantly outperforms both BOA based clustering and LEACH. It takes lifetime of Network and area of coverage, particularly in heterogeneous environments. © 2024 IEEE.

关键词： Ant colony optimization

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GOSVM: Gannet optimization based support vector machine for malicious attack detection in cloud environment

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International Journal of Information Technology (Singapore) 2023年第3期15卷 1653-1660页

作者： Arunkumar, M. Kumar, K. Ashok Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

Cloud computing is the most useful computing technology for the new service progression. Due to the distributed nature of cloud computing, security threats and cyber attacks are major problems that penetrate the network and cause sudden harm to the financial and business accounts by affecting the servers. Commonly, the vigorous and stable growth of cloud computing is mainly affected due to the security issues in a cloud computing environment. Various malware variants generate cyberattacks. Thus, intrusion detection technology is employed for securing cloud computing from malicious attacks. Cloud Intrusion Detection System (CIDS) identifies malicious attack behavior and guarantees the security and reliability of cloud computing. But, virtual network flow is uncontrollable and unnoticeable among the virtual machines. This paper proposes a novel Gannet Optimization Algorithm-based hybrid Support vector Machine-Extreme Learning Machine (GOA-optimized hybrid SVM-ELM) technique to identify and prevent malicious attacks in a cloud computing atmosphere. Gannet Optimization Algorithm (GOA) optimizer is adopted for selecting optimal features and for minimizing the loss of information. The parameters of the hybrid SVM-ELM model are optimized by the GOA algorithm. The proposed architecture improves the overall security and performance of a cloud-based Intrusion Detection System (IDS). This proposed technique is used for classifying the different attacks like Normal, web attack, Brute Force, Infiltration, Portscan, DoS/DDoS, and Botnet ARES and is executed using Matlab through employing the CICIDS2017 dataset, and the evidence detection in cloud forensics dataset. The results revealed that high precision, F-Measure, and recall rate are obtained in this technique. Then the training time decreased to 389 ms on the evidence detection in the cloud forensics dataset and 399 ms on the CICIDS2017 dataset. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute

关键词： Attacks Cloud Detection accuracy Feature selection GOA GOA-optimized SVM-ELM technique Intrusion detection Intrusion detection system Security

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Unlocking the Potential of Virtual Pet Ownership - The Impact of Blockchain and Web3 3

Unlocking the Potential of Virtual Pet Ownership - The Impac...

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Godha, Rohan Singh, Kunal Devi, Priyanka Bhardwaz, Saumyamani Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350361186

Virtual pet ownership has witnessed significant advancements with the emergence of blockchain and Web3 technology. This research paper delves into the transformative impact of integrating blockchain in virtual pet platforms, focusing on the case study of Meta-Pet. Through a comprehensive literature review and critical analysis of 17 relevant papers, this study examines the potential of decentralized technology in redefining ownership, care, and trading mechanisms for digital pets. The methodology involves a detailed exploration of the implementation process, followed by a thorough analysis of the implications and challenges associated with the adoption of blockchain and Web3 in the Meta-Pet platform. The findings underscore the enhanced user engagement and the potential for fostering trust and transparency in virtual pet communities. The research highlights the significance of this integration and provides insights into the future-prospects of blockchain and Web3 in the virtual pet landscape. © 2024 IEEE.

关键词： Blockchain

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Traffic Rule Violation Detection System 15

Traffic Rule Violation Detection System

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kumar, Jitender Gulshan Department of computer science engineering Chandigarh University Punjab India

ISBN: (纸本)9798331300579

Traffic rules play an important role in regulating traffic flow, ensuring the safety of all road users and preventing the occurrence and frequency of accidents. Without the implementation of traffic rules, the roads will always be chaotic and the risk of accidents will be much higher, but traffic rule violations are now a big emerging problem for the majority of nations. In the developing countries there are many technologies which are solving the crisis, but still the accidents are happening in roadways. As both the number of vehicles and the number of traffic law offences are growing quickly, even the literate people fail to understand the importance of following traffic rules and they also break them. Increasing traffic on the roads make it difficult for the traffic controlling authorities to control it, despite the fact that the traffic management has automated but still there are many challenges which we need to overcome. The major purpose of this project is to control traffic rule violations correctly and efficiently. Automated traffic rule detection system locates vehicles that violate the traffic guidelines it includes jumping signal, driving in opposite direction, takes unethical turns, driving without helmets etc. Due to these scenarios, there are chances of occurrence of accidents which may cost someone life. These can be reduced by finding the vehicle which is violating the traffic rules with the help of machine learning and deep learning techniques. © Grenze Scientific Society, 2024.

关键词： Deep learning

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