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A General Authentication and key Agreement Framework for Industrial Control System

Chinese Journal of Electronics 2024年第4期33卷 1046-1062页

作者： Shan GAO Junjie CHEN Bingsheng ZHANG Kui rEN Xiaohua YE Yongsheng SHEN School of Cyber Science and Technology Zhejiang University Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Zhejiang Provincial Key Laboratory of Blockchain and Cyberspace Governance Hangzhou City Brain Co. Ltd

In modern industrial control systems(ICSs), when user retrieving the data stored in field device like smart sensor, there exists two main problems: one is lack of the verification for identification of user and field device;the other is that user and field device need exchange a key to encrypt sensitive data transmitted over the *** propose a comprehensive authentication and key agreement framework that enables all connected devices in an ICS to mutually authenticate each other and establish a peer-to-peer session key. The framework combines two types of protocols for authentication and session key agreement: The first one is an asymmetric cryptographic key agreement protocol based on transport layer security handshake protocol used for Internet access, while the second one is a newly designed lightweight symmetric cryptographic key agreement protocol specifically for field devices. This proposed lightweight protocol imposes very light computational load and merely employs simple operations like one-way hash function and exclusive-or(XOr) operation. In comparison to other lightweight protocols, our protocol requires the field device to perform fewer computational operations during the authentication phase. The simulation results obtained using Open SSL demonstrates that each authentication and key agreement process in the lightweight protocol requires only 0.005 ms. Our lightweight key agreement protocol satisfies several essential security features, including session key secrecy, identity anonymity, untraceability, integrity, forward secrecy, and mutual authentication. It is capable of resisting impersonation, man-in-the-middle, and replay attacks. We have employed the Gong-NeedhamYahalom(GNY) logic and automated validation of Internet security protocols and application tool to verify the security of our symmetric cryptographic key agreement protocol.

关键词： Performance evaluation Protocols Costs Industrial control Internet security Authentication Time measurement

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Microlensing bias on the detection of strong lensing gravitational wave

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 156-165页

作者： Xikai Shan Xuechun Chen Bin Hu Guoliang Li Institute for Frontier in Astronomy and Astrophysics Beijing Normal UniversityBeijing 102206China Department of Astronomy Beijing Normal UniversityBeijing 100875China Purple Mountain Observatory Chinese Academy of SciencesNanjing 210023China

Identifying strong lensing gravitational wave(SLGW)events is of utmost importance in astrophysics as we approach the historic first detection of SLGW amidst the growing number of gravitational wave(GW)***,one crucial method for identifying SLGW signals involves assessing the overlap of parameters between two ***,the distribution of discrete matter,such as stars and sub-halos,within the strong lensing galaxy can imprint a wave optical(WO)effect on the SLGW *** frequency dependent imprints introduce biases in parameter estimation and impact SLGW *** this study,we assess the influence of the stellar microlensing field embedded in a strong lensing *** findings demonstrate that the WO effect reduces the detection efficiency of SLGW by 5%-50%for various false alarm probabilities per pair(FAPper pair).Specifically,at an FAPper pairof 10^(-5),the detection efficiency decreases from~10%to~5%.Consequently,the presence of the microlensing field can result in missing half of the strong lensing ***,the microlensing WO effect introduces a noticeable bias in intrinsic parameters,particularly for chirp mass and mass ***,it has tiny influence on extrinsic *** all parameters,~30%of events exhibit a 1σparameter bias,~12%exhibit a 2σparameter bias,and~5%exhibit a 3σparameter bias.

关键词： gravitational wave gravitational strong lensing gravitational micro lensing wave optical effect

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An artificial interphase enables stable PVdF-based solid-state Li metal batteries

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Nano research 2024年第3期17卷 1482-1490页

作者： Mengjun Wu Jiangping Song Jiaheng Lei Haolin Tang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Department of Chemistry School of ChemistryChemical Engineering and Life SciencesWuhan University of TechnologyWuhan 430070China Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory Foshan 528200China

Composite polymer electrolytes(CPEs)have attracted much attention for high energy density solid-state lithium-metal batteries owing to their flexibility,low cost,and easy ***,the unstable Li/CPE interface is always challengeable for the practical utilization of ***,a polymer interlayer containing K+prepared by ultraviolet(UV)-curing precursor solution is coated on Li surface to stabilize the interface between poly(vinylidene difluoride)(PVdF)composite electrolytes and Li *** from the physical barrier of the interlayer,the continuous decomposition of PVdF is restrained and the intimate contact between electrode and electrolyte is also achieved to reduce the interface ***,the added K+is utilized to further regulate smooth Li *** a consequence,the symmetric Li|Li cell with coated Li demonstrates steady cycling at 0.4 mAh·cm^(-2) and a high critical current density of 1 mA·cm^(-2).The assembled Li|LiFePO_(4) cell presents outstanding cycling stability(capacity retention of 90%after 400 cycles at 1 C)and good rate *** associated pouch cell performs impressive flexibility and *** work provides a convenient strategy to achieve stable Li/PVdF interface for high-performance PVdF-based solid state Li metal batteries.

关键词： interfacial modification solid-state batteries composite polymer electrolytes interfacial compatibility lithium dendrite

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A rigorous real-time acoustic positioning method for ocean bottom seismic exploration

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Satellite Navigation 2024年第1期5卷 168-190页

作者： Jinye Ma Shouchuan Fang Jianhu Zhao School of Geodesy and Geomatics Wuhan University129 Luoyu RoadWuhan430079China Institute of Marine Science and Technology Wuhan UniversityWuhan430079China Surveying Service Center BGP Inc.CNPCZhuozhou072751HebeiChina

The conventional technique for positioning seafloor geophones in ocean bottom seismic exploration encounters several challenges,including the significant impact of outliers on positioning results,underutilization of high-precision observations,and low efficiency in real-time data *** issues inevitably affect the quality of seismic exploration *** address these challenges and enhance the accuracy of geophone positioning,this paper proposes a rigorous real-time acoustic positioning method for geophones based on sequential adjustment and Baarda's outlier detection *** proposed method comprises three key steps:grouping the original acoustic observations,constructing the intra-group acoustic positioning model,and synthesizing the positioning results across the different *** validity and practicality of this approach are confirmed through a simulation experiment as well as the field experiment conducted in the Bohai Sea,*** results demonstrate that the proposed method effectively eliminates outliers in the original observations and maximizes the utilization of high-quality *** to traditional acoustic positioning methods,it significantly reduces positioning errors from meters to decimeters,and in some cases can achieve centimeter-level *** the sound velocity profile in the operating sea area is measured,the method can attain the posterior standard deviation at the millimeter level and positioning errors within 10 *** the sound velocity profile is unknown,the method can achieve the posterior standard deviation at centimeter-level and positioning errors of approximately 20 cm.

关键词： Ocean bottom seismic exploration Geophone positioning Acoustic positioning method Sequential adjustment Outlier detection

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Monitoring bloom-forming Aphanizomenon using environmental dNA metabarcoding:Method development,validation,and field application

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Journal of Environmental Sciences 2025年第4期150卷 477-489页

作者： dexiang Sun Shiguo Li Wei Xiong Xun du Kun Qiao Aibin Zhan Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China College of Horticulture and Landscape Architecture Northeast Agricultural UniversityHarbin 150030China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China Yunnan Collaborative Innovation Center for Plateau Lake Ecology and Environmental Health Kunming 650214China

Harmful algal blooms(HABs)have emerged as a critical global environmental and ecological *** and accurate monitoring of the prevalent bloom-forming genera is crucial for *** microscope-based methods are time-consuming,laborintensive,and specialized expertise-dependent,often making them impractical for largescale *** methods,such as metabarcoding,provide efficient technical solutions;however,the lack of competent PCr primers and further field validation present obstacles to their wide ***,we successfully developed Aphanizomenon-specific primers and validated the application of environmental dNA(edNA)metabarcoding for field-based monitoring of Aphanizomenon in 37 sites across lentic and lotic freshwater ecosystems in *** sensitivity and specificity tests of newly developed primers demonstrated high performance-comprehensive recovery of biodiversity in Aphanizomenon communities and high ratios(>95%)of Aphanizomenon sequences in *** observed significant correlations between the sequence abundance derived fromedNAmetabarcoding and the total cell density determined through microscopic identification across all the sampling sites,both in the spring(r=0.8086,p<0.0001)and summer(r=0.7902,p<0.0001),thus validating the utility of edNA metabarcoding based on the newly developed primers for monitoring in the ***,we identified key environmental variables that were primary drivers responsible for the spatiotemporal distribution of Aphanizomenon *** variables included temperature,total nitrogen,and dissolved oxygen in lentic ecosystems,and total phosphorus in lotic *** method developed and validated here offers an accurate,efficient,and high-throughput tool for the monitoring of Aphanizomenon blooms in freshwater ecosystems.

关键词： edNA metabarcoding Aphanizomenon Algal bloom Environmental variable Algal bloom management

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Machine learning-guided optimization of coarse aggregate mix proportion based on CO2 intensity index

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JOUrNAL OF CO2 UTILIZATION 2024年 85卷

作者： Liu, Yi Zhang, Jiaoling Zhang, Suhui Zhang, Allen A. Peng, Jianwei Yuan, Qiang Cent South Univ Sch Civil Engn Changsha 410075 Hunan Peoples R China Natl Engn Res Ctr High Speed Railway Construct Changsha 410075 Hunan Peoples R China Southwest Jiaotong Univ Sch Civil Engn Chengdu 610031 Sichuan Peoples R China Highway Engn Key Lab Sichuan Prov Chengdu 610031 Sichuan Peoples R China CTCE Grp Anhui Engineer Mat Technol Co Ltd Hefei 230041 Peoples R China

Aggregate accounts for 60-80% volume fraction of concrete, which has a great influence on the CO2 emission and performance of concrete. Apart from natural coarse aggregate (NCA), recycled coarse aggregate (rCA) and carbonation recycled coarse aggregate (CrCA) are becoming an important component. This study established a database containing 925 experimental samples of compressive strength (CS) and CO2 emission, which including NCA, rCA, and CrCA concrete respectively. Additionally, the CO2 intensity index was introduced to evaluate the CS and CO2 emission. Machine learning (ML) methods were utilized to establish prediction models for CS, CO2 emissions, and CO2 intensity. The significance of features was analyzed through SHAP and PdP. For the optimization of coarse aggregate mix proportion, the GA and MOPSO algorithms were employed for single and biobjective optimization designs, respectively. The results indicated that the optimization of coarse aggregate mix proportion can effectively reduce CO2 emission and CO2 intensity of concrete. A CrCA content of 30% is optimal for achieving both enhanced CS and reduced CO2 emissions. The carbonation treatment of rCA presents a viable approach for mitigating CO2 footprint and enhancing the mechanical properties of rCA concrete. The proposed optimization frame can facilitate appropriate decision making for low-carbon concrete design.

关键词： Carbonation CO 2 utilization recycled coarse aggregate Machine learning Computational design optimization

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Evaluation of neutron cross sections of^(48)Ti based on the Unified-Monte-Carlo-B method

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Chinese Physics C 2024年第7期48卷 118-130页

作者：夏候琼续瑞瑞刘萍 roberto Capote 田源陶曦吴小飞张玥葛智刚舒能川冯松 China Nuclear Data Center China Institute of Atomic EnergyBeijing 102413China NAPC–Nuclear Data Section P.O.Box 100Vienna International CentreA-1400ViennaAustria School of Nuclear Science and Technology University of South ChinaHengyang 421001China

A cross section evaluation of neutron induced reactions on^(48)Ti is undertaken using the Unified Monte Carlo-B(UMC-B)*** evaluation concentrates on estimating the covariance and the use of the UMC-B allows avoiding the deficiencies of linear regression brought by the traditional least squares *** main neutron and charged particle emission reactions from n+^(48)Ti in the fast neutron energy region below 20 MeV are studied in this *** posterior probability density function(PdF)of each neutron cross section is obtained in a UMC-B Bayesian approach by convoluting the model PdFs sampled based on model parameters and the likelihood functions for the experimental *** model parameters including level density,pair corrections,optical model and Kalbach matrix element parameter are stochastically sampled with the assumption of normal distributions to estimate the model *** Cholesky factorization approach is applied to consider potential parameter ***,the posterior covariance matrices are generated using the UMC-B generated *** new evaluated results are compared with the CENdL-3.2,ENdF/B-VIII.0,JEFF-3.3,TENdL-2021 and JENdL-5 evaluations and differences are discussed.

关键词： covariance Unified Monte Carlo B(UMC-B) ^(48)Ti neutron cross sections Cholesky factor-ization approach

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Integrated spatial generalized additive modeling for forest fire prediction:a case study in Fujian Province,China

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Journal of Forestry research 2025年第3期36卷 208-223页

作者： Chunhui Li Zhangwen Su rongyu Ni Guangyu Wang Yiyun Ouyang Aicong Zeng Futao Guo College of Forestry Fujian Agriculture and Forestry UniversityFuzhou 350002People’s Republic of China S Technology and Resource Optimization Utilization Key Laboratory of Fujian Universities Fuzhou 350002People’s Republic of China Zhangzhou Institute of Technology Zhangzhou 363000People’s Republic of China Department of Forest Resources Management Faculty of ForestryUniversity of British ColumbiaVancouverBC V6T 1Z4Canada

The increasing frequency of extreme weather events raises the likelihood of forest ***,establishing an effective fire prediction model is vital for protecting human life and property,and the *** study aims to build a prediction model to understand the spatial characteristics and piecewise effects of forest fire *** monthly grid data from 2006 to 2020,a modeling study analyzed fire occurrences during the September to April fire season in Fujian Province,*** compared the fitting performance of the logistic regression model(LrM),the generalized additive logistic model(GALM),and the spatial generalized additive logistic model(SGALM).The results indicate that SGALMs had the best fitting results and the highest prediction *** factors significantly impacted forest fires in Fujian *** with high fire incidence were mainly concentrated in the northwest and *** improved the fitting effect of fire prediction models by considering spatial effects and the flexible fitting ability of nonlinear *** model provides piecewise interpretations of forest wildfire occurrences,which can be valuable for relevant departments and will assist forest managers in refining prevention measures based on temporal and spatial differences.

关键词： Forest fire prediction Logistic regression Spatial generalized additive model Spline functions Piecewise effects

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Multi-agent mobile networking observation experiment at the air-sea interface of ocean eddy

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Science China Earth Sciences 2024年第10期67卷 3083-3097页

作者： Yi ZHANG dongxiao WANG Li ZHOU Chunhua QIU Yunfei ZHANG Zhiliang dENG Biao ZHANG Yunping LIU Yeqiang SHU Fenghua ZHOU danian LIU Zhengqiu ZHANG School of Marine Sciences Sun Yat-Sen UniversityZhuhai 519082China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China School of Marine Technology and Geomatics Jiangsu Ocean UniversityLianyungang 222005China Zhuhai Yunzhou Intelligent Technology Co. Ltd.Research and Design CenterZhuhai 519000China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China School of Marine Sciences Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China

Current climate forecasting has advanced to the stage of investigating mesoscale air-sea interactions. recent studies have identified significant structural differences between the cores and edges of mesoscale eddies;however, the effects of these structural variations on air-sea fluxes and the Marine Atmospheric Boundary Layer(MABL) remain underexplored. Traditional observations often fail to capture the detailed structures of eddies, necessitating enhanced observations at high spatiotemporal resolution for mesoscale eddies. To address this, efforts have been made to develop multi-agent platforms and expendable air-sea interface observation technologies. A task-oriented observation scheme was developed to monitor the spatial characteristics of mesoscale eddies. The South China Sea(SCS) is rich in mesoscale eddies with rapid motion changes, requiring enhanced observations of the air-sea interface using multi-agent mobile networking. An anticyclonic eddy was observed in the eastern region of the Xisha Islands in the SCS, and we examined variations in air-sea fluxes across different regions within the eddy.

关键词： Multi-agent Mobile networking Mesoscale eddy Air-sea interface Collaborative observation

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Multi-agent deep reinforcement learning based multi-task partial computation offloading in mobile edge computing☆

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FUTUrE GENErATION COMPUTEr SYSTEMS-THE INTErnational JOUrNAL OF ESCIENCE 2025年 172卷

作者： Li, Han Meng, Shunmei Sun, Jin Cai, Zhicheng Li, Qianmu Zhang, Xuyun Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Peoples R China Macquarie Univ Sch Comp Sydney 2109 Australia

Mobile edge computing (MEC) can enhance the computation performance of end-devices by providing computation offloading service at the network edge. However, given that both end-devices and edge servers have finite computation resources, inefficient offloading policies may lead to overload, thereby increasing the computation delays of tasks. In this paper, we investigate a multi-task partial computation offloading problem combined with a queue model. Based on achieving load-balancing across the MEC system, our objective is to minimize the long-standing average task-processing cost of the end-devices while ensuring the delay thresholds of tasks. For this purpose, a distributed offloading algorithm utilizing the multi-agent deep reinforcement learning (MAdrL) method is proposed. Specifically, through interacting with the MEC environment and accumulating experience data, the device agents can collaborate to optimize their local offloading decisions over continuous time-slots, which includes adjusting the transmission power and determining the tasks' offloading ratios under the dynamic wireless channel conditions. Exhaustive experimental results demonstrate that in contrast with the baseline algorithms, the proposed offloading algorithm can not only better balance the computation loads between the end-devices and the MEC server, but also more effectively reduce the task-processing cost of the end-devices, as well as the percentage of timeout tasks.

关键词： Mobile edge computing Partial computation offloading Load-balancing Multi-agent reinforcement learning

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