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2023 international conference on Smart Electrical Grid and Renewable Energy, SEGRE 2023

作者： Zhang, Ziting Chi, Xiaoyu Wang, Tao Meng, Rui Jin, Liang Zeng, Yu China Telecom Research Institute Ai Research Centre Beijing China Beijing University of Posts and Telecommunications Beijing China Big Data and Ai Center China Telecom Corporation Limited China Beijing University of Posts and Telecommunications Big Data and Ai Center Beijing China

ISBN: (纸本)9798350323269

data centers (DCs) have become the foundation of cloud computing technology by providing powerful computing capabilities. To ensure supplemental power supply timely in case of a power outage, batteries are widely used in the power supply system in the DCs. Thus, The precise remaining useful life prediction of the batteries can enable the DCs to operate safely and energy-efficiently. This paper proposes a life cycle prediction scheme for batteries, which designs an AI-aided union-long-short term memory (un-LSTM) algorithm for the stationary stage and the sudden drop stage of battery performance. To reduce the prediction error, pre-processing is designed to provide an accurate start time for battery life prediction. Furthermore, the multidimensional failure analysis increases the dimensionality of the features of the life prediction samples. Through the introduction of fault analysis, the life prediction part can well predict the curve types with large difference in characteristics. The simulation results demonstrate that compared with the base LSTM operation and maintenance (O&M) and expert experience O&M, un-LSTM saves 6.8% and 64.2% of the O&M costs. In addition, the prediction accuracy of the life curve has also increased by 15.9%, which also presents a well performance of the proposed scheme in preventing security risks of data centers. © 2023 IEEE.

关键词： Energy conservation

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Design and simulation analysis of Weeding Machine Chassis Based on CATIA and ADAMS

Design and Simulation Analysis of Weeding Machine Chassis Ba...

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2023 international conference on Electronics and Devices, Computational Science, ICEDCS 2023

作者： Jiao, Peigang Li, Yinnan Liu, Yang Shandong Jiaotong University Dept. of Engineering Machinery Jinan China Shandong Jiaotong University Dept. of Automotive Engineering Jinan China

ISBN: (纸本)9798350343038

T Virtual prototype simulation analysis based on 3D modeling software and dynamic simulation software is a high-efficiency and low-cost product development model. The design and assembly of the chassis mechanism of the weeding machine are carried out in the 3D drawing software CATIA. The chassis of the weeding machine is imported into ADAMS and the constraints between the components are added to establish a virtual prototype for simulation. A variety of convex terrains are set for simulation analysis in ADAMS. The curve data is exported in the PostProcess module of ADAMS, and the comparison curve is established in Origin for analysis. The results show that the obstacle-crossing performance of the chassis of the weeding machine in the orchard meets the design requirements. The double-wishbone suspension applied to the chassis of the weeding machine can significantly improve its passing ability and stability. © 2023 IEEE.

关键词： Chassis

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Study on simulation analysis of Secondary Board Card with Multi-Physical Field Coupling 3

Study on Simulation Analysis of Secondary Board Card with Mu...

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3rd IEEE international conference on Information Technology, big data and Artificial Intelligence, ICIBA 2023

作者： Li, Dan Pan, Guangze Luo, Qin China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou China Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology Guangzhou China

ISBN: (纸本)9781665490788

To predict and evaluate the change model of secondary board card which is sensitive to various physical fields such as temperature and stress, this paper conducted a thorough research on the simulation technology with multi-physical field coupling for the secondary board card, around the practical need to improve the reliability in MMC (modular multilevel converter) which is a component in flexible DC transmission system. According to the characteristics of MMC secondary board card, it was studied on the coupling mechanism between temperature and vibration, and an analysis approach of thermal-structural coupling was proposed. Based on this approach, an analysis application concerned thermal vibration coupling was developed, and a unit control board from MMC power module was adopted in thermal-structural simulation tests. The design defects of secondary board card were discovered, and corresponding suggestions were put forth. All these test results demonstrate that the reliability level of MMC secondary board card can be effectively improved by the proposed method - simulation test of multi-physical field coupling. © 2023 IEEE.

关键词： Electric power transmission

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UNCERTAINTY AND SENSITIVITY analysis OF PHEBUS FPT-1 EXPERIMENT BASED ON SEVERE ACCIDENT analysis CODE ISAA 31

UNCERTAINTY AND SENSITIVITY ANALYSIS OF PHEBUS FPT-1 EXPERIM...

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31st international conference on Nuclear Engineering (ICONE) - 24/7 Clean Nuclear Energy - Solution for Global Warming

作者： Yang, Hao Zhang, Bin Li, Jishen Gao, Pengcheng Zhang, Zhiran Miao, Fan Xi An Jiao Tong Univ Sch Nucl Sci & Technol Xian Peoples R China Xi An Jiao Tong Univ State Key Lab Multiphase Flow Power Engn Xian Peoples R China

ISBN: (纸本)9780791888315

Since the Three Mile Island nuclear accident, international research on severe accidents has advanced through a combination of experimental studies and numerical simulations. The intricate physical processes and chemical phenomena involved in severe reactor accidents have led to a heavy reliance on empirical parameters in existing severe accident analysis programs, generating significant uncertainties. As a result, there is growing interest in applying systematic analysis programs combined with uncertainty quantification methods to evaluate potential severe accident consequences, a topic receiving considerable attention among researchers in severe accident analysis. In 2019, Europe initiated the MUSA project, an international collaboration focusing on severe accident management and uncertainty. The project centers on a series of severe accident uncertainty analysis studies based on the Phebus FPT1 experiment. This serves as a valuable tool for assessing severe accident analysis code effectiveness in simulating severe reactor accident progression and offers an opportunity to analyze and enhance code physical models. Previous numerical analysis studies using the integrated severe accident analysis program ISAA for the FPT experiment revealed the necessity for significant estimations, particularly in core degradation and source term release. This underscores the importance of conducting uncertainty and sensitivity studies on parameters affecting numerical simulation results using advanced uncertainty analysis methods. In this study, we employed a self-developed uncertainty analysis tool to conduct random sampling analysis based on Latin hypercube sampling for various uncertainty parameters, including experimental modeling data and code model parameters. Utilizing the Wilks theory, the study conducted uncertainty quantification studies on the thermalhydraulic results and hydrogen production in the FPT1 experiment. data comparison shows the current oxidation model of ISA

关键词： Severe Accident ISAA Phebus FPT1 Wilks' formula Uncertainty analysis Sensitivity analysis

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Trends in Computational Science: Natural Language Processing and Network analysis of 23 Years of ICCS Publications 24th

Trends in Computational Science: Natural Language Processing...

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24th international conference on Computational Science (ICCS)

作者： Luo, Lijing Kovalchuk, Sergey Krzhizhanovskaya, Valeria Paszynski, Maciej de Mulatier, Clelia Dongarra, Jack Sloot, Peter M. A. Univ Amsterdam Amsterdam Netherlands AGH Univ Krakow Krakow Poland Univ Tennessee Knoxville TN USA

ISBN: (纸本)9783031637537;9783031637513

We analyze 7826 publications from the international conference on Computational Science (ICCS) between 2001 and 2023 using natural language processing and network analysis. We categorize computer science into 13 main disciplines and 102 sub-disciplines sourced from Wikipedia. After lemmatizing full texts of these papers, we calculate the similarity scores between the papers and each sub-discipline using vectors built with TF-IDF evaluation. Among the 13 main disciplines, machine learning & AI have become the most popular topics since 2019, surpassing parallel & distributed computing, which peaked in the early 2010 s. modeling & simulation, and algorithms & data structure have always been popular disciplines in ICCS over the past 23 years. The most frequently researched sub-disciplines, on average, are algorithms, numerical analysis, and machine learning. Deep learning shows the most rapid growth, while parallel computing has declined over the past 23 years in ICCS publications. The network of sub-disciplines exhibits a scale-free distribution, indicating certain disciplines are more connected than others. We also present correlation analysis of sub-disciplines, both within the same main disciplines and between different main disciplines.

关键词： natural language processing topic modelling computational science graph theory network analysis scientometrics ICCS

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A Knowledge Graph-Based Deep Learning Framework for Efficient Content Similarity Search of Sustainable Development Goals data

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data Intelligence 2023年第3期5卷 663-684页

作者： Irene Kilanioti George A.Papadopoulos School of Electrical and Computer Engineering National Technical University of Athens9 Heroon Polytechneiou St.Zografou Campus Athens15780Greece Department of Computer Science University of Cyprus1 University AvenueAglantziaCY-2109NicosiaCyprus

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'*** Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future *** can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this *** propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph ***,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is ***,a thorough case study in a distributed knowledge graph environment experimentally evaluates our *** results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare *** approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval *** facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

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BMDP:Blockchain-Based Multi-Cloud Storage data Provenance 26

BMDP:Blockchain-Based Multi-Cloud Storage Data Provenance

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26th international conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Feiyu Zhou, Jian-Tao Guo, Xu Inner Mongolia University College of Computer Science Inner Mongolia Hohhot China Inner Mongolia Key Laboratory of Social Computing and Data Processing Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Engineering Research Center of Ecological Big Data Ministry of Education Natl. Loc. Jt. Eng. Research Center of Intelligent Information Processing Technology for Mongolian Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software China

ISBN: (纸本)9798350331684

In a multi-cloud storage system, provenance data records all operations and ownership during its lifecycle, which is critical for data security and audibility. However, recording provenance data also poses some challenging security and storage issues. In this paper, we present a secure and efficient multi-cloud storage data source scheme, BMDP. We use blockchain technology to ensure the secure storage of provenance data and design a smart contract to utilize the provenance data to ensure the proper operation of the multi-cloud storage system. Finally, we analyze the scheme's safety and do simulation experiments to show that the scheme has practicality. © 2023 IEEE.

关键词： Smart contract

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simulation Calculation of National Compulsory Education Information Infrastructure Construction Based on data Mining Algorithm

Simulation Calculation of National Compulsory Education Info...

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2023 international conference on Electronics and Devices, Computational Science, ICEDCS 2023

作者： Han, Suman Gao, Mengxuan Shanghai Normal University Tianhua College Department of Early Years Education Shanghai China

ISBN: (纸本)9798350343038

With the maturity of computer technology, the popularization and application of database and Internet technology in various fields such as finance, production, marketing, education and so on, the accumulation of data by human beings is also surging. School informatization construction has developed from digital campus stage to smart campus stage, and the era of school big data has arrived. The informatization infrastructure construction in the stage of national compulsory education includes five dimensions: computer room area (square meters), number of computers (including teaching computers and tablets), network multimedia classrooms, number of schools with campus network and number of schools with Internet access. According to the statistics of the above five dimensions, combined with the data mining algorithm, this paper makes statistics and evaluation on the construction of school information infrastructure in the national compulsory education stage in the past five years (2015-2019). It is found that the total number of five infrastructure projects is increasing. The gap between urban and rural areas in compulsory education information infrastructure construction is narrowing, and the Internet access rate of urban and rural primary and secondary schools is relatively balanced. In the process of education system innovation, a detailed analysis of the operation of big data and the integration of education system will help to promote the overall effect of education and fully meet the diversified needs of education development. © 2023 IEEE.

关键词： Informatization

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analysis and Research on students' classroom behaviour data based on LSTM 3

Analysis and Research on students' classroom behaviour data ...

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2022 3rd international conference on Computer Information and big data Applications, CIBDA 2022

作者： Zhu, Lin Niu, Wenrui Tang, Mingwei Zhao, Ziguo School of Computer and Software Engineering Xihua University Chengdu610039 China

ISBN: (纸本)9783800758760

In the subject, the research and analysis of big data individual behavior big data is helpful to the cultivation of students' ability and the improvement of teachers' teaching. This is also one of the key concerns of researchers in this field. This paper presents the modeling and analysis of students' classroom behavior data based on LSTM. The experimental results show that our method is helpful to the cultivation of College Students' ability and the improvement of teachers' teaching. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Students

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Stability analysis of Connected Automated Vehicle Platoon Controller under Unreliable Communication Conditions 26

Stability Analysis of Connected Automated Vehicle Platoon Co...

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IEEE 26th international conference on Intelligent Transportation Systems (ITSC)

作者： Yang, Lei Liu, Yafei Sun, Zhanbo Yan, Qiruo Qin, Ziye Wang, Xuting Southwest Jiaotong Univ Sch Transportat & Logist Natl Engn Lab Integrated Transportat Big Data App Chengdu Peoples R China

ISBN: (纸本)9798350399462

The paper investigates the longitudinal control problem of a connected automated vehicle (CAV) platoon operating under the multiple-predecessor following (MPF) topology, while considering unreliable communication circumstances characterized by random packet loss and heterogeneous time-varying delay. To model random packet loss, a Bernoulli probabilistic distribution is employed, where the packet loss rate is influenced by the communication distance. A linear feedback controller is then developed to handle such packet loss and delay. The sufficient conditions for the asymptotic stability of the platoon controller are derived using linear matrix inequalities and a Lyapunov-based approach. The delay margin condition is obtained, which is associated with the packet loss rate and the number of consecutive packet losses. The string stability of the platoon with delay and packet loss is also analyzed by the transfer function. simulation experiments demonstrate that the proposed method approach effectively maintains the stability of the platoon in the presence of delay and packet loss.

关键词： Packet loss

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