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Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling

Computers, Materials & Continua 2023年第11期77卷 1967-1983页

作者： Seungwoo Kang Seyha Ros inseok song Prohim Tam Sa Math Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Telecommunication and Electronic Engineering Royal University of Phnom PenhPhnom Penh12156Cambodia Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Intelligent healthcare networks represent a significant component in digital applications,where the requirements hold within quality-of-service(QoS)reliability and safeguarding *** paper addresses these requirements through the integration of enabler paradigms,including federated learning(FL),cloud/edge computing,softwaredefined/virtualized networking infrastructure,and converged prediction *** study focuses on achieving reliability and efficiency in real-time prediction models,which depend on the interaction flows and network *** response to these challenges,we introduce a modified version of federated logistic regression(FLR)that takes into account convergence latencies and the accuracy of the final FL model within healthcare *** establish the FLR framework for mission-critical healthcare applications,we provide a comprehensive workflow in this paper,introducing framework setup,iterative round communications,and model evaluation/*** optimization process delves into the formulation of loss functions and gradients within the domain of federated optimization,which concludes with the generation of service experience batches for model *** assess the practicality of our approach,we conducted experiments using a hypertension prediction model with data sourced from the 2019 annual dataset(Version 2.0.1)of the Korea Medical Panel *** metrics,including end-to-end execution delays,model drop/delivery ratios,and final model accuracies,are captured and compared between the proposed FLR framework and other baseline *** study offers an FLR framework setup for the enhancement of real-time prediction modeling within intelligent healthcare networks,addressing the critical demands of QoS reliability and privacy preservation.

关键词： Edge computing federated logistic regression intelligent healthcare networks prediction modeling privacy-aware and real-time learning

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Three-dimensionalization via control of laser-structuring parameters for high energy and high power lithium-ion battery under various operating con ditions

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Journal of Energy Chemistry 2022年第1期31卷 93-102,I0004页

作者： Junsu Park Hyeongi song inseok Jang Jaepil Lee Jeongwook Um Seong-guk Bae Jihun Kim Sungho Jeong Hyeong-Jin Kim Ground Technology Research Insutitute Agency for Defense Development.P.O.Box 35Yuseong-guDaejeon 34186Republic of Korea Graduate School of Energy Convergence Gwangju Institute of Science and Technology123 Cheomdangwagi-ro.Buk-guGwangju 61005Republic of Korea School of Mechanical Engineering Gwangju Institute of Science and Technology123 Cheomdangwagi-ro.Buk-gu.Gwangju 61005Republic of Korea

Laser-structuring is an effective method to promote ion diffusion and improve the performance of lithium-ion battery(LIB)*** this work,the effects of laser structuring parameters(groove pitch and depth)on the fundamental characteristics of LIB electrode,such as interfacial area,internal resistances,material loss and electrochemical performance,are investigated,LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) cathodes were structured by a femtosecond laser by varying groove depth and pitch,which resulted in a material loss of 5%-14%and an increase of 140%-260%in the in terfacial area between electrode surface and *** is shown that the importance of groove depth and pitch on the electrochemical performance(specific capacity and areal discharge capacity)of laser-structured electrode varies with current *** pitch is more im porta nt at low current rate but groove depth is at high curre nt *** the mapping of lithium concentration within the electrodes of varying groove depth and pitch by laser-induced breakdown spectroscopy,it is verified that the groove functions as a diffusion path for lithium *** ionic,electronic,and charge transfer resistances measured with symmetric and half cells showed that these internal resistances are differently affected by laser structuring parameters and the changes in porosity,ionic diffusion and electronic *** is demonstrated that the laser structuring parameters for maximum electrode performance and minimum capacity loss should be determined in consideration of the main operating conditions of LIBs.

关键词： Lithium-ion battery Laser structuring Energy density Power density Laser induced breakdown spectroscopy Lithium-ion diffusion

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