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Reactor field reconstruction from sparse and movable sensors using Voronoi tessellation-assisted convolutional neural networks

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Nuclear science and Techniques 2024年第5期35卷 173-185页

作者： He-Lin Gong Han Li Dunhui Xiao Sibo Cheng Paris Elite Institute of Technology Shanghai Jiao Tong UniversityShanghai 200240China School of Mathematical sciences Tongji UniversityShanghai 200092China Department of Computing Data Science InstituteImperial College LondonLondon SW72AZUK

The aging of operational reactors leads to increased mechanical vibrations in the reactor *** vibration of the incore sensors near their nominal locations is a new problem for neutronic field *** field-reconstruction methods fail to handle spatially moving *** this study,we propose a Voronoi tessellation technique in combination with convolutional neural networks to handle this *** from movable in-core sensors were projected onto the same global field structure using Voronoi tessellation,holding the magnitude and location information of the *** convolutional neural networks were used to learn maps from observations to the global *** proposed method reconstructed multi-physics fields(including fast flux,thermal flux,and power rate)using observations from a single field(such as thermal flux).Numerical tests based on the IAEA benchmark demonstrated the potential of the proposed method in practical engineering applications,particularly within an amplitude of 5 cm around the nominal locations,which led to average relative errors below 5% and 10% in the L_(2) and L_(∞)norms,respectively.

关键词： Voronoi tessellation Field reconstruction Nuclear reactors Reactor physics On-line monitoring

Influencing Factors of Healthy Aging Risk Assessed Using Biomarkers:A Life Course Perspective

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China CDC weekly 2024年第11期6卷 219-224,I0014-I0017页

作者： Cedric Zhang Bo Lua Yajie Gao Jinming Li Xingqi Cao Xinwei Lyu Yinuo Tu Shuyi Jin Zuyun Liu Center for Clinical Big data and Analytics of the Second Affiliated Hospital and Department of Big Data in Health Science School of Public Healththe Key Laboratory of Intelligent Preventive Medicine of Zhejiang ProvinceZhejiang University School of MedicineHangzhou CityZhejiang ProvinceChina Institute of Epidemiology and Health Care University College LondonLondonUK College of Chemical and Biological Engineering Zhejiang UniversityHangzhou CityZhejiang ProvinceChina

Assessing individual risks of healthy aging using biomarkers and identifying associated factors have become important areas of *** this study,we conducted a literature review of relevant publications between 2018 and 2023 in both Chinese and English *** studies have predominantly used single biomarkers,such as C-reactive protein,or focused on specific life course stages and factors such as socioeconomic status,mental health,educational levels,and unhealthy *** summarizing the progress in this field,our study provides valuable insights and future directions for promoting healthy aging from a life course perspective.

关键词： such insight directions

DCEL:classifier fusion model for Android malware detection

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Journal of Systems Engineering and Electronics 2024年第1期35卷 163-177页

作者： XU Xiaolong JIANG Shuai ZHAO Jinbo WANG Xinheng Jiangsu Key Laboratory of Big data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computer science Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computing and Engineering University of West LondonLondon W55RFUK

The rapid growth of mobile applications,the popularity of the Android system and its openness have attracted many hackers and even criminals,who are creating lots of Android ***,the current methods of Android malware detection need a lot of time in the feature engineering ***,these models have the defects of low detection rate,high complexity,and poor practicability,*** analyze the Android malware samples,and the distribution of malware and benign software in application programming interface(API)calls,permissions,and other *** classify the software’s threat levels based on the correlation of ***,we propose deep neural networks and convolutional neural networks with ensemble learning(DCEL),a new classifier fusion model for Android malware ***,DCEL preprocesses the malware data to remove redundant data,and converts the one-dimensional data into a two-dimensional gray ***,the ensemble learning approach is used to combine the deep neural network with the convolutional neural network,and the final classification results are obtained by voting on the prediction of each single *** based on the Drebin and Malgenome datasets show that compared with current state-of-art models,the proposed DCEL has a higher detection rate,higher recall rate,and lower computational cost.

关键词： Android malware detection deep learning ensemble learning model fusion

Predictors of Global Disparities in COVID-19 Vaccination Coverage — 219 Countries and Territories, December 2020–July 2022

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China CDC weekly 2024年第15期6卷 318-323,I0006,I0007页

作者： Ying Zhang Shujie Zang Xu Zhang Zhiqiang Qu Xinyu Zhou Leesa Lin Zhiyuan Hou School of Public Health and Global Health InstituteFudan UniversityShanghaiChina Department of Infectious Disease Epidemiology London School of Hygiene&Tropical MedicineLondonUnited Kingdom Laboratory of data Discovery for Health(D24H) Hong Kong Science ParkHong Kong Special Administrative RegionChina

What is already known about this topic?The significant disparities in global coronavirus disease 2019(COVID-19)vaccine coverage hamper the pace of epidemic *** is a need to better understand the factors contributing to disparities in COVID-19 vaccination rates across *** is added by this report?This report revealed significant associations between vaccination coverage and various country-level *** pandemic preparedness,higher levels of trust,and a lower proportion of young population aged 0–14 were strongly correlated with higher COVID-19 vaccination *** are the implications for public health practices?Our findings emphasize the need for enhanced pandemic preparedness and governance,coupled with building trust in government and healthcare *** also needs to address the hesitancy of vaccinating children and adolescents aged 0–14 as the vaccination campaign progresses.

关键词： vaccination vaccine COV

The stance and factors of international organizations towards countries from a Chinese perspective

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data Intelligence 2024年第1期6卷 158-182页

作者： Qin Zhang Haili Xue Yaotian Wang Yao Wang Ziqin Zhang Qinghua Qin Haoguang Liang National science Library Chinese Academy of Sciences100190China China Center for Modernization Research 100190China Beijing International Studies University 100024China Beijing Key Laboratory of National Belt and Road data Analysis and Decision Support 100024China University College london WC1E 6BTUK

The degree and scope of constraints imposed by International Organizations(IOs)on States are increasing,and identifying the factors affecting the IOs’stances on States is helpful to enhance the state's discourse power and influence in the international ***,by coding the records of Regular Press Conferences of the Speaking Office of the Chinese Ministry of Foreign Affairs during the period of 20182022,we obtained a dataset of IOs’stances on China-related ***,we constructed political relation,economic relation,and humanistic relation indicators to complement the influence factors,adopted the Bayesian logit model,and applied the Monte Carlo Markov chain algorithm and Gibbs sampling to analyze the probability of IOs’positive stances towards *** result shows that IOs’category,length of establishment,functional position,and relationship with China are all related to their tendency of making a statement about *** terms of the heterogeneity of event types,forum-type IOs are significantly inclined to give positive assessment compared to service-type IOs on events focusing on China's own *** analysis reveals that the model for analyzing and predicting the attitudes of IOs is more effective when the international situation is in a stable period.

关键词： Bayesian Logit Model IOs' stances Attitude analysis Monte Carlo Markov chain International relation indicator

AI Fairness-From Machine Learning to Federated Learning

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1203-1215页

作者： Lalit Mohan Patnaik Wenfeng Wang Consciousness Studies Program School of HumanitiesNational Institute of Advanced StudiesBangalore560012India Research Institute of Intelligent Engineering and data Applications Shanghai Institute of TechnologyShanghai201418China Research Center of Ecology and Environment of Central Asia Chinese Academy of SciencesUrumqi830011China Applied Nonlinear science Lab Anand International College of EngineeringJaipur391320India london Institute of Technology The ASE-London CTI of SCOLondonCR26EQUK Sino-Indian Joint Research Center of AI and Robotics The IMT InstituteBhubaneswar752054India

This article reviews the theory of fairness in AI-frommachine learning to federated learning,where the constraints on precision AI fairness and perspective solutions are also *** a reliable and quantitative evaluation of AI fairness,many associated concepts have been proposed,formulated and ***,the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure *** privacy worries induce the data unfairness and hence,the biases in the datasets for evaluating AI fairness are *** imbalance between algorithms’utility and humanization has further reinforced *** for federated learning systems,these constraints on precision AI fairness still *** solution is to reconcile the federated learning processes and reduce biases and imbalances accordingly.

关键词： Formulation evaluation classification constraints imbalance biases

Forecasting measured responses of structures using temporal deep learning and dual attention

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 832-850页

作者： Viet-Hung DANG Trong-Phu NGUYEN Thi-Lien PHAM Huan X.NGUYEN Department of Structural Mechanics Hanoi University of Civil EngineeringHanoi 11600Vietnam Faculty of Applied science University of Economics-Technology for IndustriesHanoi 11600Vietnam london Digital Twin Research Centre Faculty of Science and TechnologyMiddlesex UniversityLondon NW44BTUK International School Vietnam National UniversityHanoi 11600Vietnam

The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random *** key idea is to design a deep learning architecture to leverage the relationships,between external excitations and structure's vibration signals,and between historical values and future values,within multiple time-series *** proposed method consists of two main steps:the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture;the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future *** viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional(3D)reinforced concrete structure and experimental data from an 18-story steel ***,comparison and robustness studies are carried out,showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic time-varying excitation deep learning signal processing response forecasting

Preface to the Special Issue on Modeling and data Analysis Methods for the SMILE mission

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Earth and Planetary Physics 2024年第1期8卷 1-4页

作者： TianRan Sun Hyunju Connor Andrey Samsonov National Space science Center Chinese Academy of SciencesBeijing 100190China NASA Goddard Space Flight Center US Mullard Space science Laboratory University College LondonUK

The SMILE(Solar wind Magnetosphere Ionosphere Link Explorer)project(http://***/smile/,https://***/web/smile/mission)is a joint spacecraft mission of the European Space Agency(ESA)and the Chinese Academy of sciences(CAS)with an expected launch in *** aims to study the global interactions of solar wind–magnetosphere–ionosphere innovatively by imaging the Earth’s magnetosheath and cusps in soft X-rays and the northern auroral region in ultraviolet(UV)while simultaneously measuring plasma and magnetic field parameters in the solar wind and magnetosheath along a highly-elliptical and highly-inclined *** special issue is composed of 22 articles,presenting recent progress in modeling and data analysis techniques developed for the SMILE *** this preface,we categorize the articles into the following seven topics and provide brief summaries:(1)instrument descriptions of the Soft X-ray Imager(SXI),(2)numerical modeling of the X-ray signals,(3)data processing of the X-ray images,(4)boundary tracing methods from the simulated images,(5)physical phenomena and a mission concept related to the scientific goals of SMILE-SXI,(6)studies of the aurora,and(7)ground-based support for SMILE.

关键词： SMILE X-ray imaging magnetosphere auroral ionosphere

Development of a scintillating-fiber-based beam monitor for the coherent muon-to-electron transition experiment

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Nuclear science and Techniques 2024年第4期35卷 156-164页

作者： Yu Xu Yun-Song Ning Zhi-Zhen Qin Yao Teng Chang-Qing Feng Jian Tang Yu Chen Yoshinori Fukao Satoshi Mihara Kou Oishi School of Physics Sun Yat-sen UniversityGuangzhou 510275China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China Department of Modern Physics University of Science and Technology of ChinaHefei 230026China High Energy Accelerator Research Organization(KEK) Ibaraki 305‑0801Japan Department of Physics Imperial College LondonLondon SW72AZUK

The coherent muon-to-electron transition(COMET)experiment is a leading experiment for the coherent conversion of μ^(-)N→e^(-)N using a high-intensity pulsed muon beamline,produced using innovative slow-extraction ***,it is critical to measure the muon beam *** set up a muon beam monitor(MBM),where scintillating fibers woven in a cross shape were coupled to silicon photomultipliers to measure the spatial profile and timing structure of the extracted muon beam for the *** MBM detector was tested successfully with a proton beamline at the China Spallation Neutron Source and took data with good performance in the commissioning *** development of the MBM,including its mechanical structure,electronic readout,and beam measurement results,are discussed.

关键词： Beam instrumentation Profile monitor Scintillating fiber Silicon photomultipliers