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Communication-Efficient Personalized Federated Learning for Green Communications in IoMT

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Communication-Efficient Personalized Federated Learning for ...

IEEE International Conference on Communications (ICC)

作者： Ziqi Chen Jun Du Chunxiao Jiang Yunlong Lu Zhu Han Department of Electronic Engineering Tsinghua University Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Houston Houston TX USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The rapid development of the Internet of Medical Things (IoMT) has brought about an enormous amount of healthcare data. Effectively and securely processing this sensitive data has become a significant challenge for green communication and privacy protection of the IoMT. As a decentralized learning framework, Federate learning (FL) enables model training without directly aggregating users' raw data, thus ensuring user privacy protection. Moreover, numerous studies have put forth various approaches to enhance the efficiency of FL by minimizing communication costs, yet they may not fully account for the unique characteristics of IoMT. Specifically, the efficiency and performance of model training are closely related to patient life and health. Meanwhile, existing research has indicated that reducing communication costs can result in a decline in training accuracy, which may be critical to patient health. Therefore, aimed at green communication and ensuring the model accuracy, we design a communication-efficient personalized federated learning framework, namely pFedCAS. Specifically, we introduce a control unit, which enables adaptive sparsity of local models, to reduce training costs. Furthermore, a selection unit based on communication quality is added into the global aggregation, which can select suitable clients for model updating. Simulation results validate that the proposed method can significantly reduce communication costs while ensuring the model accuracy. Additionally, The simulation results also validate the excellent robustness of our method to non-iid healthcare data.

关键词： Training Adaptation models Data privacy Costs Accuracy Federated learning Computational modeling

The Combined Effect of Konjac Glucomannan and Ultrasound Treatment on the Interaction of Surimi and Gluten Protein

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SSRN 2024年

作者： Cao, Geng Yang, Zuoqian Li, Xiangzheng He, Xiaoyang Song, Shuang Wen, Chengrong National Engineering Research Center for Seafood State Key Laboratory of Marine Food Processing and Safety Control Collaborative Innovation Center of Seafood Deep Processing National Engineering Research Center of Seafood National & Local Joint Engineering Laboratory for Marine Bioactive Polysaccharide Development and Application School of Food Science and Technology Dalian Polytechnic University Dalian116034 China School of Information Science and Engineering Dalian Polytechnic University Dalian116034 China

Gluten, surimi and mixted protein were analyzed for changes in protein structure after treatment with konjac glucomannan (KGM), ultrasound (U) and konjac glucomannan-ultrasound (UKGM). In this study, molecular weight, fluorescence intensity, intermolecular force, disulfide bond, microstructure, SDS-soluble protein and free amino acid content were investigated. All treatments increased, Imax, SH and free amino groups of gluten, while decreasing SS bonds. KGM and U treatment decreased the SDS-soluble protein, SH groups and Imax of surimi protein while increasing SS bonds. However, the effect of UKGM treatment was the opposite. For the mixed proteins, all treatments were found to decrease the Imax and SH groups, while increasing the SS group. KGM and UKGM treatments increased protein with ionic and hydrogen bond contents, while U treatment increased hydrophobic bonds. Consequently, UKGM treatment was able to improve the interaction of surimi and gluten and resulted in higher structural properties of the mixed protein. © 2024, The Authors. All rights reserved.

关键词： Proteins

Multi-Channel Graph Convolutional Network based End-Point Element Composition Prediction of Converter Steelmaking

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IFAC-PapersOnLine 2021年第3期54卷 152-157页

作者： Shuchao Chang Chunhui Zhao Yuanlong Li Min Zhou Chuan Fu Honglin Qiao State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou 310027 China Alibaba Group Hangzhou 310024 China

End-point composition is an important quality standard for the converter steelmaking process, which consists of multiple elements, including C, Si, Mn, etc. However, it is hard to measure the element composition online. Real-time and precise prediction for element composition is essential for the optimization of alloy addition so as to bring economic profits. Nevertheless, most conventional models neglect the correlations among element compositions and predict each element composition without the information from other elements. In this paper, a new multi-channel graph convolutional network is proposed to integrate these correlations with the process variables together for a more accurate prediction model. The proposed model uses graph structure to describe the correlations among element compositions. Specifically, through the multi-channel design, each element composition can be learned based on process variables in an independent channel. Element compositions and correlations among them are respectively described by nodes and edges in graph. With the constructed graph, the graph convolution across channels can fuse the features of correlated elements to explicitly exploit the correlation information for performance improvement. Besides, compared with conventional methods which learn relations among nodes based on distances, we take sparse representation learned by sparse coding as edges to describe the correlations among nodes. As strong correlations exist among element compositions, the consideration of correlation information can integrate the learning of correlated elements and bring performance improvement. Experiments based on the real converter steelmaking process demonstrate the superiority and effectiveness of the proposed model.

关键词： converter steelmaking end-point composition prediction graph convolutional network

Thermal Analysis of Stator Iron-Core-Less PMBLDC Motors Considering Both Winding Eddy and Circulating Current Losses

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Thermal Analysis of Stator Iron-Core-Less PMBLDC Motors Cons...

International Conference on Fluid Power and Mechatronics (FPM)

作者： Liu Yang Tianxiong Gao Wenqi Fu Rongren Wang Chao Ai Xiangdong Kong School of Mechanical Engineering Yanshan University Qinhuangdao China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Motor Power Division Beijing Institute of Aerospace Control Devices Beijing China

ISBN: (数字)9798350304947

ISBN: (纸本)9798350304954

Thermal analysis of three stator iron-core-less PMBLDC motors considering winding eddy and circulating current losses is investigated. First, the effects of strand diameter, permanent magnet (PM) magnetization and rotating speed on the above mentioned two winding losses and thermal characteristics are investigated by 3D finite element method (FEM). It is found that both strand diameter and rotating speed have great impacts on the temperature rise, Additionally, the temperature rise results for parallel and radial magnetizations are almost identical. Then, influence of eddy and circulating current losses on the thermal characteristics of the three PMBLDC motors are further studied separately. Furthermore, comprehensive study of the two winding losses on the thermal characteristics is carried out. Results show that thermal analysis considering both winding eddy and circulating current losses in parallel thin strands is vital during motor primary design process considering the limited insulation level of wires and PMs. Finally, three prototypes with different combinations of strand diameters and parallel numbers are selected for the temperature rise experiment. Experimental results demonstrate the effectiveness of the developed 3D FEM models and validate the obtained simulation results.

关键词： Insulation Temperature Three-dimensional displays Magnetization Windings Stator windings Motors

Design of a curled hyper-redundant manipulator and the motion control with tip-following algorithm

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Design of a curled hyper-redundant manipulator and the motio...

第35届中国控制与决策会议

作者： Aoshun Zhang En Li Feng Zhang Rui Guo Mingrui Luo Yuwei Zhang School of Artificial Intelligence University of Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Engineering Laboratory for Intelligent Industrial Vision CAS State Grid Intelligent Technology Co.Ltd. State Grid Shandong Electric Power Company Jinan Power Supply Company

In order to meet the operational needs in some narrow environments,the hyper-redundant snake-shaped manipulator has received extensive attention and has been widely studied due to its compact shape and multiple degrees of *** present,the research of hyper-redundant manipulator mainly focuses on the straight push *** the limitation of working space,this paper designed a hyper-redundant manipulator delivered by a curled *** to the characteristics of turntable delivery,a tip-following algorithm based on curve fitting and a tip-following strategy based on terminal posture record are ***,with the algorithm applied to the physical robot we made,we successfully realized the tipfollowing motion control of the hyper-redundant manipulator.

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A Novel Molecularly Imprinted Electrochemical Sensor Based on Nico 2 O 4 /Mwcnts 3d Microspheres for High-Sensitivity Analysis of Organophosphorus Pesticides in Foods

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SSRN 2024年

作者： Fa, Huanbao Zhang, Li Zhao, Tengda Yin, Wei Zhang, Yijiao Jin, SiWei Liu, Renlong Liu, Zuohua Chen, Shiqi Niu, Lidan Gong, Li School of Chemistry and Chemical Engineering Chongqing University Chongqing400044 China National-Municipal Joint Engineering Laboratory for Chemical Process Intensification and Reaction Chongqing University Chongqing400044 China Analytical and Testing Center Chongqing University Chongqing400044 China Key Laboratory of Condiment Supervision Technology State Administration for Market Regulation Chongqing Institute for Food and Drug Control China

Using molecularly imprinted polymer (MIP) covered spinel material NiCo2O4 as the sensing material, MWCNTs were introduced on the surface of NiCo2O4 microspheres through hydrothermal process to improve their electrical conductivity and specific surface area, and the quantitative determination of Dimethoate (DIM) was realized. Subsequently, the morphology and structure of the composites were characterised using scanning electron microscopy (SEM), X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The electrochemical sensor has the advantages of good selectivity, high stability, low detection limit (18.52 pM) and wide linear range (0.05~10000 nM). On the one hand，DIM is rebinding on specific MIP sites on the surface of NiCo2O4/MWCNTs. On the other hand, the synergistic effect of nickel and cobalt in mixed transition metal oxides is conducive to the improvement of sensing performance. This study demonstrates that the synthesised EMIP/NiCo2O4/MWCNTs composites have good prospects for practical application in the detection of DIM. © 2024, The Authors. All rights reserved.

关键词： Fourier transform infrared spectroscopy

High Emission of Black Carbon in Heavy-Duty Diesel Vehicles: Insights from Microscopic Operating Conditions

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SSRN 2024年

作者： Chen, Ting He, Xiao He, Liqiang Q. You, Yan Zeng, Lewei Gao, Mingqiu Cao, Yihuan Li, Zhenhua Zheng, Xuan Zhang, Shaojun Wu, Ye College of Chemistry and Environmental Engineering Shenzhen University Shenzhen518060 China State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation Chinese Research Academy of Environmental Sciences Beijing100012 China National Observation and Research Station of Coastal Ecological Environments in Macao Macao Environmental Research Institute Macau University of Science and Technology Macao999078 China Co. Ltd. Guangzhou511300 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China

The in-depth investigation of the high black carbon (BC) emission scenarios of heavy-duty diesel vehicles (HDDVs) is a crucial step toward developing effective control strategies. Chassis dynamometer tests were conducted for three in-use HDDVs, namely, vehicle #1, #2, and #3, focusing on the instantaneous BC characterizations during multiple driving conditions, i.e., speed phases and acceleration intervals. BC emission was found to increase with positive acceleration, and high acceleration could result in instantaneous BC spikes. The total BC emissions during velocity-acceleration interval 15-60 km h-1 and 0.1-0.9 m s-2 contributed to 43.4 ± 10.2% of the whole-cycle emissions, while the proportions of time spent in the velocity-acceleration interval to the whole cycle were 23.1 ± 7.6%. The cold-start microscopic operating condition was assessed by the cold-start extra emissions (CSEEs). Under various pre-defined cold-start durations, the proportions of CSEEs in the total cycle emissions were 9.4-21.0%, 0-9.1%, and 6.8-39.4% for vehicles #1, #2, and #3, respectively. The CSEEs exhibited an initial rise, followed by a plateau as the assumed cold-start durations extended. A uniform cold-start duration of 600 s was established based on the criterion that the relative standard deviation (RSD) of CSEEs during the plateau period was less than 10%. We proposed that the updated cold-start duration can enhance the accuracy and consistency of cold-start corrections in emission inventory models. © 2024, The Authors. All rights reserved.

关键词： Acceleration

Optimizing Photocatalytic Performance in an Electrostatic-Photocatalytic Air Purification System Through Integration of Triboelectric Nanogenerator and Tesla Valve

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SSRN 2024年

作者： Li, Xiaoliang Cao, Leo N.Y. Zhang, Ting Fang, Rongkun Ren, Yuqing Chen, Xiangyu Bian, Zhenfeng Li, Hexing MOE Key Laboratory of Resource Chemistry Shanghai Key Laboratory of Rare Earth Functional Materials Shanghai Normal University Shanghai China CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-nano Energy and Sensor Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing100083 China School of Nanoscience and Technology University of Chinese Academy of Sciences Beijing100049 China Sino-Dutch R&D Centre for Future Wastewater Treatment Technologies Key Laboratory of Urban Stormwater System and Water Environment Beijing University of Civil Engineering and Architecture Beijing100044 China State Key Laboratory of Pollution Control and Resource Reuse College of Environmental Science and Engineering Tongji University Shanghai200092 China Shanghai University of Electric Power Shanghai China

Increasing the collision frequency between gas molecules and photocatalysts can enhance the removal efficiency of volatile organic compounds (VOCs) and particulate matter (PM) in air. In this study, we propose an Electrostatic-Photocatalytic air purification system, containing Tesla valve, triboelectric nanogenerator (TENG), and photocatalysis parts. The incorporation of Ag@ZnO nanorod array (Ag@ZnO-NR) photocatalysts into the internal baffles of the Tesla valve pipeline effectively enhances the collision probability between air pollutant molecules and photocatalysts, and thus facilitating the removal efficiency of pollutants. Additionally, the high-voltage electricity (~9.0 kV) generated by the TENG facilitates the separation of electron-hole pairs in the photocatalyst, leading to increased production of superoxide radicals (O·-2), hydroxyl radicals (·OH), and holes (h+), thereby enhancing the photocatalytic efficiency. In a 1.8 L space system, we achieved an approximately 97% removal efficiency for toluene within 130 minutes and a similar efficiency for formaldehyde (~200 ppm) within 175 minutes. Additionally, the PM2.5 concentration rapidly decreased from 999 μg·m-3 to 42 μg·m-3 within 6 minutes, alongside with a significantly faster pollutant removal rate compared to conventional methods. By integrating Tesla valves, TENG, and photocatalysis, this combined system presents an efficient and promising approach for addressing indoor air pollution, with potential applications across various settings. © 2024, The Authors. All rights reserved.

关键词： Photocatalysis

Optimal Model and Dispatch Strategy of a Multi-Energy Microgrid Based on Hybrid Pumped Hydro-Battery Storage and Ground Source Heat Pump

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SSRN 2023年

作者： Li, Xinyue Wang, Honglei Li, Bin Tan, Zhukui Electrical Engineering College Guizhou University Guiyang550025 China Key Laboratory of "Internet+" Collaborative Intelligent Manufacturing in Guizhou Provence Guiyang Guizhou550025 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Electric Power Research Institute Guizhou Power Grid Co. Ltd Guiyang550002 China

The carbon neutrality target and the carbon emission problem caused by the ever-increasing energy demand necessitate the extensive use of renewable energy (RES) generation technologies. Multi-energy microgrid (MEMG) become effective vehicles for managing RES generation and storage. However, the uncertainty of RES and the randomness of load demand poses a challenge to the design and operation of MEMG. This study proposes a MEMG including combined cooling, heating, power system, pumped hydro storage, and ground source heat pump to solve the problem. Combined with demand-side management strategies, a system is designed considering complementary configuration and energy conversion management. A corresponding optimization model is established to minimize the total cost and maximize the island operation while satisfying the demand. The experimental results show that the established model and scheduling method improves the system’s ability to cope with the RES’ uncertainty and reduces the capacity of the energy storage system. In summer, the daily investment cost is saved by 1439RMB, and the utilization rate of clean energy reaches 96%. Compared with the uncombined system, the MEMG reduces 1620.02kg of carbon dioxide per day, realizing the full utilization of clean energy and having the role of demonstration and promotion. © 2023, The Authors. All rights reserved.

关键词： Battery storage