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Temperature effects on atmospheric continuous-variable quantum key distribution

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Chinese Physics B 2019年第8期28卷 56-61页

作者： Shu-Jing Zhang Hong-Xin Ma Xiang Wang Chun Zhou Wan-Su Bao Hai-Long Zhang Henan Key Laboratory of Quantum information and Cryptography Zhengzhou Information Science and Technology Institute

Compared with the fiber channel,the atmospheric channel offers the possibility of a broader geographical coverage and more flexible transmission for continuous-variable quantum key distribution(CVQKD).However,the fluctuation of atmospheric conditions will lead to the loss of performance in atmospheric quantum *** this paper,we study how temperature affects atmospheric *** mainly consider the temperature effects on the transmittance and interruption *** the numerical simulation analysis,it can be shown that the performance of atmospheric CVQKD is improved as temperature increases,with the other factors ***,the results in this work can be used to evaluate the feasibility of the experimental implementation of the atmospheric CVQKD protocols.

关键词： atmospheric continuous-variable quantum key distribution temperature effects performance secret key rate

Benchmarking in-memory database

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Frontiers of Computer science 2016年第6期10卷 1067-1081页

作者： Cheqing JIN Yangxin KONG Qiangqiang KANG Weining QIAN Aoying ZHOU institute for data science and Engineering School of Computer Science and Software EngineeringEast China Normal University

We have witnessed exciting development of RAM technology in the past *** memory size grows rapidly and the price continues to decrease,so that it is feasible to deploy large amounts of RAM in a computer *** companies and research institutions have devoted a lot of resources to develop in-memory databases(IMDB) that implement queries after loading data into(virtual) memory in *** bloom of various in-memory databases pursues us to test and evaluate their performance objectively and *** the existing database benchmarks like Wisconsin benchmark and TPC-X series have achieved great success,they cannot suit for in-memory databases due to the lack of consideration of unique characteristics of an *** this study,we propose MemTest,a novel benchmark that concerns some major characteristics of an in-memory *** benchmark constructs particular metrics,which cover processing time,compression ratio,minimal memory space and column strength of an in-memory *** design a data model based on inter-bank transaction applications,and a data generator to support uniform and skew data *** MemTest workload includes a set of queries and transactions against the metrics and data ***,we illustrate the efficacy of MemTest through the implementations on two different in-memory databases.

关键词： benchmark in-memory database memory

Theoretical optoelectronic analysis of intermediate-band photovoltaic material based on ZnY_(1-x) O_x(Y = S,Se,Te) semiconductors by first-principles calculations

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Chinese Physics B 2013年第10期22卷 463-468页

作者：吴孔平顾书林叶建东汤琨朱顺明周孟然黄友锐张荣郑有炓 School of Electrical and information Engineering Anhui University of Science and Technology Nanjing National Laboratory of Microstructures School of Electronic Science and EngineeringNanjing University data Storage institute A*STARSingapore 117608Singapore

The structural, energetic, and electronic properties of lattice highly mismatched ZnY1-xOx （Y = S, Se, Te） ternary alloys with dilute O concentrations are calculated from first principles within the density functional theory. We demonstrate the formation of an isolated intermediate electronic band structure through diluted O-substitute in zinc-blende ZnY （Y = S, Se, Te） at octahedral sites in a semiconductor by the calculations of density of states （DOS）, leading to a significant absorption below the band gap of the parent semiconductor and an enhancement of the optical absorption in the whole energy range of the solar spectrum. It is found that the intermediate band states should be described as a result of the coupling between impurity O 2p states with the conduction band states. Moreover, the intermediate bands （IBs） in ZnTeO show high stabilization with the change of O concentration resulting from the largest electronegativity difference between O and Te compared with in the other ZnSO and ZnSeO.

关键词： intermediate band (IB) electronic band structure optical properties electronegativity

Relationship between air temperature oscillations and solar variability on short and medium time scales

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science China Earth sciences 2011年第6期54卷 912-923页

作者： YANG ChunXia WU HongFa HU DanTing institute of information and System science Nanjing University of Information Science and Technology Nanjing 210044 China

The contemporary science of climate change is increasingly focusing on the temporal and spatial characteristics of temperature oscillations and determining possible underlying *** particular,the effect of variations in solar irradiance on the variability of the climate remains a hot topic of *** studies focus on the effects of solar variation on the Earth's climate on long time *** study presents the responses of regional climates to solar variations on shorter time scales using two datasets:one for the air temperature in Nanjing and the Greenwich sunspot number,and the other for the air temperature in Shijiazhuang and the United States sunspot *** empirical mode decomposition,both the 11-year quasi-period of the sunspot number and similar periods including approximately 5.5-and 10.5-year cycles of the air temperature in Nanjing and Shijiazhuang are ***,correlation analysis of similar periodic components for the sunspot number and air temperature indicates that changes in the air temperature on short and medium time scales are not linked to solar *** is further confirmed by a test of whether a mode component is a stochastic noise *** shorter periods are also found at the 95% confidence level;in particular,the 3.1-year period of the Nanjing air temperature coincides with a previously obtained empirical ***,no temperature variations on shorter time scales correlate with solar variability.

关键词： climate change temperature multi-scale variations solar cycle

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping Lin Jun Xu Delong Jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Lithium-ion battery State-of-health estimation data-driven Machine learning Ensemble learning Ensemble diversity

The Kernel Dynamics of Convolutional Neural Networks in Manifolds

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Chinese Journal of Electronics 2020年第6期29卷 1185-1192页

作者： WU Wei JING Xiaoyuan DU Wencai School of Computer science Wuhan University institute of Deep-sea science and Engineering Chinese Academy of Sciences institute of data science City University of Macau

We propose a novel expression from manifolds to define Convolutional neural network(CNN).The layered structure is proceeded by integration in limited space continuously,with weights adjusted including value and direction in neural *** transfer functions are proposed to simulate the kernel dynamics as a control *** theoretically analyze the stability and controllability of kernel-based CNNs,and verify our findings by numerical experiments.

关键词： convolutional neural nets learning (artificial intelligence) kernel-based CNN convolutional neural network kernel dynamics status transfer functions neural manifolds layered structure Convolutional neural networks Kernelbased convolution Learning dynamics Neural manifolds

Spatial distribution order parameter prediction of collective system using graph network

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Chinese Physics B 2023年第5期32卷 566-572页

作者：赵慧敏王瑞赵偲郑文 institute of Public-Safety and Big data College of Data ScienceTaiyuan University of TechnologyTaiyuan 030024China Center of information Management and Development Taiyuan University of TechnologyTaiyuan 030024China Center for Healthy Big data Changzhi Medical CollegeChangzhi 046000China

In the past few decades, the study of collective motion phase transition process has made great progress. It is also important for the description of the spatial distribution of particles. In this work, we propose a new order parameter φ to quantify the degree of order in the spatial distribution of particles. The results show that the spatial distribution order parameter can effectively describe the transition from a disorderly moving phase to a phase with a coherent motion of the particle distribution and the same conclusion could be obtained for systems with different sizes. Furthermore, we develop a powerful molecular dynamic graph network(MDGNet) model to realize the long-term prediction of the self-propelled collective system solely from the initial particle positions and movement angles. Employing this model, we successfully predict the order parameters of the specified time step. And the model can also be applied to analyze other types of complex systems with local interactions.

关键词： order parameter graph network collective system active matter

Graph dynamical networks for forecasting collective behavior of active matter

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Chinese Physics B 2022年第11期31卷 438-444页

作者： Yanjun Liu Rui Wang Cai Zhao Wen Zheng institute of Public-Safety and Big data College of Data ScienceTaiyuan University of TechnologyTaiyuan 030024China Center of information Management and Development Taiyuan University of TechnologyTaiyuan 030024China Center for Healthy Big data Changzhi Medical CollegeChangzhi 046000China

After decades of theoretical studies,the rich phase states of active matter and cluster kinetic processes are still of research *** to efficiently calculate the dynamical processes under their complex conditions becomes an open ***,machine learning methods have been proposed to predict the degree of coherence of active matter *** this way,the phase transition process of the system is quantified and *** this paper,we use graph network as a powerful model to determine the evolution of active matter with variable individual velocities solely based on the initial position and state of the *** graph network accurately predicts the order parameters of the system in different scale models with different individual velocities,noise and density to effectively evaluate the effect of diverse *** with the classical physical deduction method,we demonstrate that graph network prediction is excellent,which could save significantly computing resources and *** addition to active matter,our method can be applied widely to other large-scale physical systems.

关键词： active matter graph network improvement of Vicsek collective motion

A Transmission and Transformation Fault Detection Algorithm Based on Improved YOLOv5

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Computers, Materials & Continua 2023年第9期76卷 2997-3011页

作者： Xinliang Tang Xiaotong Ru Jingfang Su Gabriel Adonis School of information science and Engineering Hebei University of Science and TechnologyShijiazhuang050000China Department of Computer science and information Systems Birkbeck Institute for Data AnalyticsLondonB100ABWC1E 7HXUK

On the transmission line,the invasion of foreign objects such as kites,plastic bags,and balloons and the damage to electronic components are common transmission line *** these faults is of great significance for the safe operation of power ***,a YOLOv5 target detection method based on a deep convolution neural network is *** this paper,Mobilenetv2 is used to replace Cross Stage Partial(CSP)-Darknet53 as the *** structure uses depth-wise separable convolution to reduce the amount of calculation and parameters;improve the detection *** the same time,to compensate for the detection accuracy,the Squeeze-and-Excitation Networks(SENet)attention model is fused into the algorithm framework and a new detection scale suitable for small targets is added to improve the significance of the fault target area in the *** pictures of foreign matters such as kites,plastic bags,balloons,and insulator defects of transmission lines,and sort theminto a data *** experimental results on datasets show that themean Accuracy Precision(mAP)and recall rate of the algorithm can reach 92.1%and 92.4%,*** the same time,by comparison,the detection accuracy of the proposed algorithm is higher than that of other methods.

关键词： Transmission line YOLOv5 multi-scale integration SENet