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Path signature-based XAI-enabled network time series classification

Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

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Ultrafast laser processing of camouflaged metals by topography inherited multistep removal for information encryption

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Nano Research 2024年第8期17卷 7242-7249页

作者： Guangzhi He Jianfeng Yan Jiawang Xie Ming Qiao Ma Luo Yuzhi Zhao Haoze Han State Key Laboratory of Tribology in Advanced equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

Surfaces with micro-nanoscale structures show different optical responses,including infrared reflection,thermal radiation,and protective *** realization of structure camouflage is important for material ***,external cloaks or coatings are necessary in structure camouflage,which limits the surface ***,we propose a novel strategy for the direct structure camouflage through topography inherited removal(TIR)with ultrafast laser,featuring pristine topography preservation and scattering surface *** multistep TIR,pristine topographies are partially and uniformly removed to preserve the original designed *** response changes show the suppression of specular reflection by uniformizing reflected light intensity to a low level on the inherited *** produce various structure camouflages on large scaled substrates,and demonstrate applications of information encryption in code extraction and word recognition through structure *** proposed strategy opens opportunities for infrared camouflage and other technologies,such as thermal management,device security,and information encryption.

关键词： topography inherited removal ultrafast laser structure camouflage optical response information encryption

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Deep neural network-enabled battery open-circuit voltage estimation based on partial charging data

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Journal of Energy Chemistry 2024年第3期90卷 120-132,I0005页

作者： Ziyou Zhou Yonggang Liu Chengming Zhang Weixiang Shen Rui Xiong State Key Laboratory of Mechanical Transmission for Advanced equipment&College of Mechanical and Vehicle Engineering Chongqing UniversityChongqing 400000China department of Vehicle Engineering School of Mechanical EngineeringBeijing Institute of TechnologyBeijing 100081China department of Electrical Engineering Harbin Institute of TechnologyHarbin 150000HeilongjiangChina School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthornVictoria 3122Australia

Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion *** main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation *** addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging *** incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV *** analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional *** validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 *** this level of precision for OCV estimation requires only around 50 s collection of partial charging *** validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed *** cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV *** method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.

关键词： Lithium-ion battery Open-circuit voltage Health diagnosis Deep learning

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Simulation of gas-solid flow characteristics of the circulating fluidized bed boiler under pure-oxygen combustion conditions

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Chinese Journal of Chemical Engineering 2024年第6期70卷 9-19页

作者： Kaixuan Gao Xiwei Ke Bingjun Du Zhenchuan Wang Yan Jin Zhong Huang Yanhong Li Xuemin Liu Key Laboratory of Special equipment Safety and Energy-Saving for State Market Regulation China Special Equipment Inspection&Research InstituteBeijing 100029China department of Energy and Power Engineering Tsinghua UniversityBeijing 100084China School of Electrical and Power Engineering Taiyuan University of TechnologyTaiyuan 030024China

Under the pressure of carbon neutrality,many carbon capture,utilization and storage technologies have witnessed rapid development in the recent years,including oxy-fuel combustion(OFC)***,the conventional OFC technology usually depends on the flue gas recirculation system,which faces significant investment,high energy consumption,and potential low-temperature corrosion *** these deficiencies,the direct utilization of pure oxygen to achieve particle fluidization and fuel combustion may reduce the overall energy consumption and CO_(2)-capture *** this paper,the fundamental structure of a self-designed 130 t·h^(-1) pure-oxygen combustion circulating fluidized bed(CFB)boiler was provided,and the computational particle fluid dynamics method was used to analyze the gas-solid flow characteristics of this new-concept boiler under different working *** results indicate that through the careful selection of design or operational parameters,such as average bed-material size and fluidization velocity,the pure-oxygen combustion CFB system can maintain the ideal fluidization state,namely significant internal and external particle ***,the contraction section of the boiler leads to the particle backflow in the lower furnace,resulting in the particle suspension concentration near the wall region being higher than that in the center ***,the upper furnace still retains the classic core-annulus flow *** addition to increasing solid circulation rate by reducing the average bed-material size,altering primary gas ratio and bed inventory can also exert varying degrees of influence on the gas-solid flow characteristics of the pure-oxygen combustion CFB boiler.

关键词： Circulating fluidized bed Pure-oxygen combustion Gas-solid flow characteristics Simulation CO_(2)capture

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Target Detection Algorithm in Foggy Scenes Based on Dual Subnets

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Computers, Materials & Continua 2024年第2期78卷 1915-1931页

作者： Yuecheng Yu Liming Cai Anqi Ning Jinlong Shi Xudong Chen Shixin Huang School of Computer Science Jiangsu University of Science and TechnologyZhenjiang212100China Information department China Merchants Heavy IndustryNantong226116China

Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven *** this way,the image quality and contrast will *** this case,It is difficult to detect the target in the image by the universal detection ***,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this ***,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy *** the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the ***,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous ***,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is *** this way,the feature extraction ability of the network for deep-level information can be *** experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection *** DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.

关键词： Target detection fog target detection YOLOX twin network multi-task learning

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A hybrid machine learning approach based study of production forecasting and factors influencing the multiphase flow through surface chokes

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Petroleum 2024年第2期10卷 354-371页

作者： Waquar Kaleem Saurabh Tewari Mrigya Fogat Dmitriy A.Martyushev department of Industrial and Manufacturing Engineering The Pennsylvania State University department of Data Sciences Gyan Ganga Institute of Technology and Sciences department of Petroleum and Geo-Engineering Rajiv Gandhi Institute of Petroleum Technology Jais department of Oil and Gas technologies Perm National Research Polytechnic University

Surface chokes are widely utilized equipment installed on wellheads to control hydrocarbon flow *** correlations have been suggested to model the multiphase flow of oil and gas via surface ***, substantial errors have been reported in empirical fitting models and correlations to estimate hydrocarbon flow because of the reservoir's heterogeneity, anisotropism, variance in reservoir fluid characteristics at diverse subsurface depths, which introduces complexity in production data. Therefore,the estimation of daily oil and gas production rates is still challenging for the petroleum ***, hybrid data-driven techniques have been reported to be effective for estimation problems in various aspects of the petroleum domain. This paper investigates hybrid ensemble data-driven approaches to forecast multiphase flow rates through the surface choke(viz. stacked generalization and voting architectures), followed by an assessment of the impact of input production control ***, machine learning models are also trained and tested individually on the production data of hydrocarbon wells located in North Sea. Feature engineering has been properly applied to select the most suitable contributing control variables for daily production rate forecasting. This study provides a chronological explanation of the data analytics required for the interpretation of production data. The test results reveal the estimation performance of the stacked generalization architecture has outperformed other significant paradigms considered for production forecasting.

关键词： Machine learning Tree-based methods Stacking ensemble Multiphase flow Data analytics Wellhead choke variables

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Algorithm for Solving Traveling Salesman Problem Based on Self-Organizing Mapping Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 463-470页

作者：朱江辉叶航航姚莉秀蔡云泽 department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent equipment and System Ministry of EducationShanghai 200240China Huawei technologies Co. Ltd.Shanghai 201206China

Traveling salesman problem(TSP)is a classic non-deterministic polynomial-hard optimization *** on the characteristics of self-organizing mapping(SOM)network,this paper proposes an improved SOM network from the perspectives of network update strategy,initialization method,and parameter *** paper compares the performance of the proposed algorithms with the performance of existing SOM network algorithms on the TSP and compares them with several heuristic *** show that compared with existing SOM networks,the improved SOM network proposed in this paper improves the convergence rate and algorithm *** with iterated local search and heuristic algorithms,the improved SOM net-work algorithms proposed in this paper have the advantage of fast calculation speed on medium-scale TSP.

关键词： traveling salesman problem(TSP) self-organizing mapping(SOM) combinatorial optimization neu-ral network

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A review on the cooling of energy conversion and storage systems using thermoelectric modules

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Journal of Central South University 2024年第6期31卷 1998-2026页

作者： Amirreza IJADI Mehran Rajabi ZARGARABADI Saman RASHIDI Amir Mohammad JADIDI department of Energy Faculty of New Sciences and TechnologiesSemnan UniversitySemnanIran Faculty of Mechanical Engineering Semnan UniversityP.O.B.***SemnanIran

Exploitation of sustainable energy sources requires the use of unique conversion and storage systems,such as solar panels,batteries,fuel cells,and electronic *** load management of these energy conversion and storage systems is one of their challenges and *** this article,the thermal management of these systems using thermoelectric modules is *** results show that by choosing the right option to remove heat from the hot side of the thermoelectric modules,it will be a suitable local cooling,and the thermoelectric modules increase the power and lifespan of the system by reducing the spot *** modules were effective in reducing panel *** increase the time to reach a temperature above 50℃ in batteries by 3 to 4 ***,in their integration with fuel cells,they increase the power density of the fuel cell.

关键词： cooling photovoltaic lithium-ion batteries fuel cell electronic equipment thermoelectric modules

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An Improved Thermal Conductivity Measurement Scheme for Macroscopic Graphitic Films Using the Laser Flash Method

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Journal of Thermal Science 2024年第4期33卷 1480-1490页

作者： ZHANG Peijuan MING Xin LIU Yingjun WANG Xuelong SHI Hang HAO Yuanyuan LU Jiahao LIU Zheng LAI Haiwen ZHANG Ying GAO Weiwei XU Zhen GAO Chao MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and EngineeringKey Laboratory of Adsorption and Separation Materials&Technologies of Zhejiang ProvinceZhejiang UniversityHangzhou310027China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030032China Special equipment Safety Supervision and Inspection Institute of Jiangsu Province National Graphene Products Quality Inspection and Testing Center(Jiangsu)Wuxi214174China Hangzhou Gaoxi Technol Co. LtdHangzhou311113China China Academy of Aerospace Aerodynamics Beijing100074China

Achieving efficient thermal management urges to exploit high-thermal-conductivity materials to satisfy the boosted demand of heat *** is critical to adopt standardized characterization protocols to evaluate the intrinsic thermal conductivity of thermal management ***,for the most representative laser flash method,the lack of standard measurement methodology and systematic description on the thermal diffusivity and influencing factors has led to significant deviations and confusion of the thermal conduction performance in the emerging thermal management ***,the measurement error factors of thermal diffusivity by the common laser flash analyzer(LFA)are *** high-thermal-conductivity graphitic film(GF)as a typical case,the key factors are analyzed to guide the measurement protocol of related carbon-based thermal management *** basic principle of the LFA measurement,actual pre-processing conditions,instrument parameters setting,and data analysis are elaborated for accurate ***,the graphene thick films and common isotropic materials are also extended to meet various thermal measurement *** on the existing practical problems,we propose a feasible test flow to achieve a unified and standardized thermal conductivity measurement,which is beneficial to the rapid development of carbon-based thermal management materials.

关键词： thermal management graphitic film laser flash method thermal conductivity thermal diffusivity

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A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2165-2206页

作者： Qusay M.Salih Md.Arafatur Rahman Ahmad Firdaus Mohammed Rajih Jassim Hasan Kahtan Jasni Mohamad Zain Ahmed Hussein Ali Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)PekanPahang26600Malaysia department of Medical equipment Technology Engineering Al Salam University CollegeBaghdadIraq School of Mathematics and Computer Science University of WolverhamptonWolverhampton01902UK department of Production Engineering and Metallurgy University of TechnologyBaghdadIraq Cardiff School of technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Kompleks Al-KhawarizmiUniversiti Teknologi MARAShah AlamSelangor40450Malaysia department Computer Science Al-Salam University CollegeBaghdadIraq

The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already *** realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ***,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G ***,this study aims to review,examine,and summarize existing studies and research activities in *** study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and ***,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of *** study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.

关键词： 6G bibliometric wireless networks review

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