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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

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A Novel Federated Learning Framework for Healthcare Applications Using Wearable Devices 4

A Novel Federated Learning Framework for Healthcare Applicat...

引用

4th IEEE international conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Natarajan, Rajesh Krishna, Sujatha Ranjith, Christodoss Prasanna University of Technology and Applied Sciences Al-Aqr 324 College of Computing and Information Sciences Information Technology Department Shinas Oman Messiah University Computer Science Department MechanicsburgPA United States

ISBN: (纸本)9798331518882

A key necessity in managing signals for processing and generating useful information in the healthcare domain is the use of many algorithms. Traditional computing methods have been successful but may not be effective in the future as secure privacy matters. This has led to the increasing popularity of machine learning technologies. However, we present a novel device for devices and sensors for federated learning (FL), which is aimed at establishing a new, safer framework. This pattern uses machine learning with a lot of emphasis on the availability of the devices. In such a case, models for the detection, monitoring, and management of diseases can be created. The FL approach is also believed to be applicable to several healthcare contexts. © 2025 IEEE.

关键词： Federated learning

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Loss Sensitivity Calculation and Analysis Based on Graph computing 9

Loss Sensitivity Calculation and Analysis Based on Graph Com...

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9th international conference on Power and Renewable Energy

作者： Wu, Yuezhou Yang, Tianlin Lu, Jiangang Guo, Wenxin Zhao, Ruifeng Tan, Huijuan Guangdong Power Grid Co Ltd Power Dispatching Control Ctr Kaiping City Guangdong Peoples R China

ISBN: (纸本)9798350377477;9798350377460

Loss sensitivity in electricity systems refers to the responsiveness of power losses in electrical transmission and distribution networks to various influencing factors. This concept is critical for optimizing the efficiency and reliability of power delivery from generation sources to end consumers. Especially in the electricity market trading process, network losses, although only a small part of the total cost, have a significant impact on each specific transaction and grid user. Therefore, in-depth understanding and analysis of the impact of generation transactions on the grid network loss can provide a basis for the power purchase plan for the grid to provide reference for the grid network loss management, which is of great significance. The current mainstream calculation and analysis method for network loss sensitivity is the marginal loss coefficient method, which determines the network loss share of each bus by analyzing the impact of bus injected power on the total network loss changes, but the nature of its serial calculation cannot properly solve the balance between real-time analysis of network loss optimization and accuracy, and with the increase in system size, this problem has gradually become a major obstacle to the realization of real-time analysis. This paper presents a novel parallel computing method based on graph computing for determining the sensitivity of system network loss and node-injected power. Graph computing is a parallel computing method that stores, computes, and analyzes the information in a system by constructing a topological graph model and based on it. The method alleviates the computational burden associated with calculating network loss sensitivity as the scale of the power system expands by leveraging the parallel computing capabilities of graph databases. Furthermore, it facilitates the graphical calculation and analysis of network loss sensitivity through the utilization of graph storage.

关键词： Loss Sensitivity Graph computing Generators Loss Sensitivity Loads Loss Sensitivity Flexible Load

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MACHINE-ATTENTION-BASED VIDEO coding FOR MACHINES 30

MACHINE-ATTENTION-BASED VIDEO CODING FOR MACHINES

引用

30th IEEE international conference on Image Processing (ICIP)

作者： Lee, Yegi Kim, Shin Yoon, Kyoungro Lim, Hanshin Kwak, Sangwoon Choo, Hyon-Gon Konkuk Univ Seoul South Korea Elect & Telecommun Res Inst ETRI Daejeon South Korea

ISBN: (纸本)9781728198354

Conventional video coding methods have been developed based on the human visual system (HVS). However, in recent years, video has occupied a huge portion of internet traffic, and the mount of video data for machine consumption has increased rapidly due to the progress of neural networks. This paper proposes a novel machine-attention-based video coding method for machines. Inspired by the saliency-driven research, we first extract attention regions, sensitively affecting the machine vision performance, from the object detection network. Subsequently, a maximum a posterior (MAP)-based bit allocation method is applied to assign more bits to the attention regions. Our proposed method helps to maintain high machine vision performance whereas reducing the bitrate. Experimental results show that our proposed method achieves up to 34.89% bjontegaard delta (BD)-rate reduction for the video dataset and up to 44.70% BD-rate reduction for the image dataset compared to state-of-the-art video coding technology.

关键词： Video coding for Machines Video Compression Image Compression Machine-Attention MPEG VCM

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Optimizing information Propagation for Blockchain-empowered Mobile AIGC: A Graph Attention Network Approach 20

Optimizing Information Propagation for Blockchain-empowered ...

引用

20th IEEE international Wireless Communications and Mobile computing (IEEE IWCMC) - Green and Intelligent Communications

作者： Liao, Jiana Went, Jinbo Kang, Jiawen Zhang, Yang Du, Jianbo Li, Qihao Zhane, Weiting Yang, Dong Guangdong Univ Technol Guangzhou Peoples R China Nanjing Univ Aeronaut & Astronaut Nanjing Peoples R China Beijing Jiaotong Univ Beijing Peoples R China Jilin Univ Changchun Peoples R China Xian Univ Posts & Telecommun Xian Peoples R China

ISBN: (纸本)9798350361261;9798350361278

Artificial Intelligence-Generated Content (AIGC) is a rapidly evolving field that utilizes advanced AI algorithms to generate content. Through integration with mobile edge networks, mobile AIGC networks have gained significant attention, which can provide real-time customized and personalized AIGC services and products. Since blockchains can facilitate decentralized and transparent data management, AIGC products can be securely managed by blockchain to avoid tampering and plagiarization. However, the evolution of blockchain-empowered mobile AIGC is still in its nascent phase, grappling with challenges such as improving information propagation efficiency to enable blockchain-empowered mobile AIGC. In this paper, we design a Graph Attention Network (GAT)-based information propagation optimization framework for blockchain-empowered mobile AIGC. We first innovatively apply age of information as a data-freshness metric to measure information propagation efficiency in public blockchains. Considering that GATs possess the excellent ability to process graph-structured data, we utilize the GAT to obtain the optimal information propagation trajectory. Numerical results demonstrate that the proposed scheme exhibits the most outstanding information propagation efficiency compared with traditional routing mechanisms.

关键词： Mobile AIGC information propagation age of information graph attention network

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Secure and privacy-preserving federated learning-based resource allocation for next generation networks

Secure and privacy-preserving federated learning-based resou...

引用

international conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Dandoush, Abdulhalim Gouissem, Ala Ciftler, Bekir Sait Division of Information Technology College of Computing and Information Technology University of Doha for Science and Technology Doha Qatar ESME Sduria/L2TI at Sorbonne University Paris Nord France Division of Data Science and Artificial Intelligence College of Computing and Information Technology University of Doha for Science and Technology Doha Qatar

ISBN: (纸本)9781032803722

This paper surveys recent research on federated learning-based resource allocation for next-generation networks in order to identify research gaps and potential future directions. We start by outlining the main challenges and requirements for secure and privacy-preserving resource allocation in these networks. The existing solutions and techniques proposed in the literature are then reviewed. The strengths and limitations of these solutions are analyzed, and trade-offs in terms of security, privacy, efficiency, and scalability are discussed. The research gaps and promising directions for future research are identified, such as integrating multiple solutions (e.g., game theory or optimization techniques with federated learning) and developing new models and algorithms for AI-based resource allocation that address specific challenges and requirements of next-generation networks. The goal is to inspire further research in this critical and rapidly evolving field. © 2025 The Author(s).

关键词： Federated learning

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Investigation and Modeling of Solar PV: A Simulation Method 21

Investigation and Modeling of Solar PV: A Simulation Method

引用

21st international conference on Electrical Engineering/Electronics, Computer, Telecommunications and information technology (ECTI-CON)

作者： Nishat, Mirza Muntasir Faisal, Fahim Islamic Univ Technol IUT Dept Elect & Elect Engn EEE Dhaka Bangladesh

ISBN: (纸本)9798350381566;9798350381559

Combining solar photovoltaic panels with preexisting buildings may be a workable way to reduce carbon emissions and address the present energy issue. The purpose of this project is to create an energy-harvesting system that can assist nations like Bangladesh in meeting their energy needs while lowering their carbon footprint and forgoing the need for extra resources. This will be accomplished by utilizing three software tools (PVSOL, PVsyst, and SAM) that are tailored for various installations. One of Bangladesh's longest bridges, the Bangabandhu Bridge, underwent computer-aided design, modeling, and simulation of a mono-facial solar panel-based energy model in a sustainable manner. To obtain a more comprehensive understanding of the system's effectiveness, a thorough energy analysis was conducted. Based on our findings, we conclude that there is a great deal of promise for this endeavor. The average energy yield, according to the statistics, is 2948512kWh year. In the event of an energy crisis, this dependable energy can be used to power the entire bridge and the national grid.

关键词： Sustainability Modeling and Simulations Ubiquitous computing PVSOL PVsyst PV

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Navigating the Cloud: Enhancing Healthcare through Opportunities and Challenges of Cloud computing 8

Navigating the Cloud: Enhancing Healthcare through Opportuni...

引用

8th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Saratkar, Saniya Langote, Meher Datta Meghe Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha India

ISBN: (纸本)9798350376425

The availability of computing resources and services through the Internet is a revolutionary approach to delivering computer resources. It is considered by many managers and experts as capable of making changes in the state and quality of health care services research, and health information technology. technology has been described as a revolution in the health sector in which cloud computing is a major development that offers hitherto opportunities for creativity, efficiency, and cooperation. In this article, the author exposes the possible changes brought by cloud computing in the context of healthcare services. It analyses the several ways cloud computing could potentially revolutionize the delivery of healthcare services concerning enhanced data storage and processing, modularity, and open access. Cloud computing is a modern approach to delivering resources and services that focus on computing. It is thought that many managers and experts have the potential to enhance healthcare services and research and change health information technology. Cloud computing is among the most revolutionary technical innovations applied in the healthcare sector, creating unprecedented creativity, value, and synergism. The following article aims to investigate the enabling role of cloud computing in the UK healthcare services industry. They look at the different approaches that cloud computing is likely to deliver for the provision of healthcare in terms of accessibility, scalability, data management, and even analysis. © 2024 IEEE.

关键词： Electronic health record

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Foreign Exchange Rate Forecast by a Large Language Model Integrated with Trend Description 11

Foreign Exchange Rate Forecast by a Large Language Model Int...

引用

11th international conference on Soft computing and Machine Intelligence, ISCMI 2024

作者： Peng, Kexin Iima, Hitoshi Kyoto Institute of Technology Kyoto Japan Kyoto Institute of Technology Kyoto Japan

ISBN: (纸本)9798331518127

In this paper, we propose a large language model to forecast the direction of change in a foreign exchange rate. The input of the proposed model is textual information as a prompt, whereas that of conventional forecast models is numerical information. A recent trend in the exchange rate is added to input textual information to enhance forecast accuracy. GPT-2 is adopted as our large language model and is fine-tuned using training data. The effectiveness of the proposed model is empirically examined using actual data. © 2024 IEEE.

关键词： Prediction models

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Improving Security and Performance of Databases Through Single Cache System 4

Improving Security and Performance of Databases Through Sing...

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4th international conference on Blockchain technology and information Security, ICBCTIS 2024

作者： Ul Haq, Ikram Khan, Salabat Khan, Mansoor Tamsal, Saher School of Computer Science and Technology Southwest University of Science and Technology Mianyang China School of Computer and Information Engineering Qilu Institute of Technology Jinan China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China University of Agriculture Department of Computer Science Faisalabad Pakistan

ISBN: (纸本)9798331528324

In today's world, connectivity and performance-driven technology are rapidly advancing each year, and new platforms and mechanisms are being utilized to enhance the security and performance of databases and cloud computing, which are trending in the global market. This examination focused on customer information security in cloud computing, i.e., information stockpiling security issues and how to control unapproved access to data by proposing access control;valuable measures were characterized subsequently, and an entrance control show was prescribed. Cloud computing can be described as an innovation that depends on the web and the sharing of resources. It has an adaptable foundation that customers can use with much of a stretch. With its wide event relationship, there are numerous obstacles to continuing with cloud computing because of security issues, mostly considering customer data security. The proposed study helped hesitant clients sensibly continue forward in the cloud while understanding the dangers of cloud computing. The research objective is to examine the security techniques employed in cloud technology to improve its performance by utilizing data mining within a unified cache system. We will apply the Apriori algorithm as a proposed solution to be used in a single cache while considering the security measures in the cloud. The study expects to apply this method to all cloud providers and vendors by entering data into a single cache mechanism that can be extended into different components and implemented using SPSS modelers to improve the security of the database. © 2024 IEEE.

关键词： Cloud security

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Image denoising algorithm based on self-attention residual network 3

Image denoising algorithm based on self-attention residual n...

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3rd international conference on Algorithms, Microchips, and Network Applications, AMNA 2024

作者： Wu, Wei Wu, Hao School of Economics and Trade Anhui Business and Technology College Anhui Hefei231311 China School of Computer and Artificial Intelligence Hefei Normal University Anhui Hefei230601 China

ISBN: (纸本)9781510680098

Image denoising algorithm based on depth learning generally uses convolution sparse self-coding network as the main framework of the denoising network. However, although convolution sparse self-coding network can effectively suppress the noise information in the image, it has the problem of loss of certain details in the image after denoising. Aiming at this defect, on the basis of convolutional sparse self-encoding network, the detail information of each layer feature map is extracted from the output of each encoder layer using self-attention mechanism, and the detail information is integrated into the input layer of the corresponding decoder using residual connection method. Experimental results show that compared with the traditional convolutional self-coding noise reduction network, the proposed convolutional self-coding network based on self-attention residuals can effectively improve the level of network noise reduction. At the same time, compared with the mainstream noise reduction network, the proposed algorithm can also achieve better noise reduction effect. © 2024 SPIE.

关键词： Image denoising

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