Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination...Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression.General health indicators are extracted from the partial discharge process.The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction.The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic.Besides,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction.Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging experiment.Thus,it largely reduces the time and labor for battery pack investigation.The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.展开更多
In quantum mechanics,when an electron is quickly ripped off from a molecule,a superposition of new eigenstates of the cation creates an electron wave packet that governs the charge flow inside,which has been called ch...In quantum mechanics,when an electron is quickly ripped off from a molecule,a superposition of new eigenstates of the cation creates an electron wave packet that governs the charge flow inside,which has been called charge migration(CM).Experimentally,extracting such dynamics at its natural(attosecond)timescale is quite difficult.We report the first such experiment in a linear carbon-chain molecule,butadiyne(C_(4)H_(2)),via high-harmonic spectroscopy(HHS).By employing advanced theoretical and computational tools,we showed that the wave packet and the CM of a single molecule are reconstructed from the harmonic spectra for each fixed-in-space angle of the molecule.For this onedimensional molecule,we calculate the center of charge <x>(t) to obtain v_(cm),to quantify the migration speed and how it depends on the orientation angle.The findings also uncover how the electron dynamics at the first few tens to hundreds of attoseconds depends on molecular structure.The method can be extended to other molecules where the HHS technique can be employed.展开更多
针对预拷贝算法在起始、迭代、结尾3个阶段所表现出的不同特点,提出了基于运行阶段特征的虚拟机实时迁移技术(LMCOS,live migration based on the characteristics of the operation stages)。起始阶段引入比对初始内存页的变量传输技...针对预拷贝算法在起始、迭代、结尾3个阶段所表现出的不同特点,提出了基于运行阶段特征的虚拟机实时迁移技术(LMCOS,live migration based on the characteristics of the operation stages)。起始阶段引入比对初始内存页的变量传输技术以避免未改变内存部分的传输;迭代阶段引入计数排序传输方法以减少内存页的重传;结尾阶段引入调减虚拟机CPU时间片的策略以缩短停机时间。与预拷贝算法相比,LMCOS使停机时间平均减少53%,总迁移时间平均减少65%。展开更多
IT infrastructures have been widely deployed in datacentres by cloud service providers for Infrastructure as a Service (IaaS) with Virtual Machines (VMs). With the rapid development of cloud-based tools and techniques...IT infrastructures have been widely deployed in datacentres by cloud service providers for Infrastructure as a Service (IaaS) with Virtual Machines (VMs). With the rapid development of cloud-based tools and techniques, IaaS is changing the current cloud infrastructure to meet the customer demand. In this paper, an efficient management model is presented and evaluated using our unique Trans-Atlantic high-speed optical fibre network connecting three datacentres located in Coleraine (Northern Ireland), Dublin (Ireland) and Halifax (Canada). Our work highlights the design and implementation of a management system that can dynamically create VMs upon request, process live migration and other services over the high-speed inter-networking Datacentres (DCs). The goal is to provide an efficient and intelligent on-demand management system for virtualization that can make decisions about the migration of VMs and get better utilisation of the network.展开更多
To effectively track the impact of population migration between regions on the spread of infectious diseases, this paper proposes a visualized analysis and prediction system of infectious diseases based on the improve...To effectively track the impact of population migration between regions on the spread of infectious diseases, this paper proposes a visualized analysis and prediction system of infectious diseases based on the improved SIR model. The research contents including: using the multi graph link interaction mode, visualizing the space-time distribution and development trend of infectious diseases;The LightGBM model is used to track the changes of infection rate and recovery rate, and the Mi/Mo SIR model is constructed according to the initial data of different populations;Mi/Mo SIR model is used to predict infectious diseases in combination with visual panel, providing users with tools to analyze and explain the space-time characteristics and potential laws of infectious diseases. The study found that the closure of cities and the restriction of personnel mobility were necessary and effective, and the system provided an important basis for the prediction and early warning of infectious diseases.展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51875054,U1864212)Graduate Research and Innovation Foundation of Chongqing+2 种基金China(Grant No.CYS20018)Chongqing Municipal Natural Science Foundation for Distinguished Young Scholars of China(Grant No.cstc2019jcyjjq X0016)Chongqing Science and Technology Bureau of China。
文摘Aging diagnosis of batteries is essential to ensure that the energy storage systems operate within a safe region.This paper proposes a novel cell to pack health and lifetime prognostics method based on the combination of transferred deep learning and Gaussian process regression.General health indicators are extracted from the partial discharge process.The sequential degradation model of the health indicator is developed based on a deep learning framework and is migrated for the battery pack degradation prediction.The future degraded capacities of both battery pack and each battery cell are probabilistically predicted to provide a comprehensive lifetime prognostic.Besides,only a few separate battery cells in the source domain and early data of battery packs in the target domain are needed for model construction.Experimental results show that the lifetime prediction errors are less than 25 cycles for the battery pack,even with only 50 cycles for model fine-tuning,which can save about 90%time for the aging experiment.Thus,it largely reduces the time and labor for battery pack investigation.The predicted capacity trends of the battery cells connected in the battery pack accurately reflect the actual degradation of each battery cell,which can reveal the weakest cell for maintenance in advance.
基金supported by the National Key Research and Development Program of China (No. 2019YFA0308300)the National Natural Science Foundation of China (Nos. 91950202, 12225406, 12074136, 12021004, and 11934006)+2 种基金the Natural Science Foundation of Hubei Province (No. 2021CFB330)supported by the Chemical Sciences, Geosciences, and Biosciences Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (No. DE-FG0286ER13491)supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (No. DE-SC0023192)
文摘In quantum mechanics,when an electron is quickly ripped off from a molecule,a superposition of new eigenstates of the cation creates an electron wave packet that governs the charge flow inside,which has been called charge migration(CM).Experimentally,extracting such dynamics at its natural(attosecond)timescale is quite difficult.We report the first such experiment in a linear carbon-chain molecule,butadiyne(C_(4)H_(2)),via high-harmonic spectroscopy(HHS).By employing advanced theoretical and computational tools,we showed that the wave packet and the CM of a single molecule are reconstructed from the harmonic spectra for each fixed-in-space angle of the molecule.For this onedimensional molecule,we calculate the center of charge <x>(t) to obtain v_(cm),to quantify the migration speed and how it depends on the orientation angle.The findings also uncover how the electron dynamics at the first few tens to hundreds of attoseconds depends on molecular structure.The method can be extended to other molecules where the HHS technique can be employed.
基金Projects(2019YFC1803600,2018YFC1800400)supported by the National Key R&D Program of ChinaProject(2023ZZTS0727)supported by the Fundamental Research Funds for the Central Universities,China。
文摘针对预拷贝算法在起始、迭代、结尾3个阶段所表现出的不同特点,提出了基于运行阶段特征的虚拟机实时迁移技术(LMCOS,live migration based on the characteristics of the operation stages)。起始阶段引入比对初始内存页的变量传输技术以避免未改变内存部分的传输;迭代阶段引入计数排序传输方法以减少内存页的重传;结尾阶段引入调减虚拟机CPU时间片的策略以缩短停机时间。与预拷贝算法相比,LMCOS使停机时间平均减少53%,总迁移时间平均减少65%。
文摘IT infrastructures have been widely deployed in datacentres by cloud service providers for Infrastructure as a Service (IaaS) with Virtual Machines (VMs). With the rapid development of cloud-based tools and techniques, IaaS is changing the current cloud infrastructure to meet the customer demand. In this paper, an efficient management model is presented and evaluated using our unique Trans-Atlantic high-speed optical fibre network connecting three datacentres located in Coleraine (Northern Ireland), Dublin (Ireland) and Halifax (Canada). Our work highlights the design and implementation of a management system that can dynamically create VMs upon request, process live migration and other services over the high-speed inter-networking Datacentres (DCs). The goal is to provide an efficient and intelligent on-demand management system for virtualization that can make decisions about the migration of VMs and get better utilisation of the network.
文摘To effectively track the impact of population migration between regions on the spread of infectious diseases, this paper proposes a visualized analysis and prediction system of infectious diseases based on the improved SIR model. The research contents including: using the multi graph link interaction mode, visualizing the space-time distribution and development trend of infectious diseases;The LightGBM model is used to track the changes of infection rate and recovery rate, and the Mi/Mo SIR model is constructed according to the initial data of different populations;Mi/Mo SIR model is used to predict infectious diseases in combination with visual panel, providing users with tools to analyze and explain the space-time characteristics and potential laws of infectious diseases. The study found that the closure of cities and the restriction of personnel mobility were necessary and effective, and the system provided an important basis for the prediction and early warning of infectious diseases.
