在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索...在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索的改进差分进化算法(LNS_DE),引入大邻域搜索的破坏与修复思想及一批基于随机、基于最大代价贡献和基于集中批次的移除算子以及新的插入算子组件,以最小化订单总延迟时间为目标建立订单分批优化模型,并针对不同订单规模算例进行实验仿真.仿真结果表明,所提出的订单分批优化算法较差分进化算法(DE)相比求解质量更优,性能更稳定、收敛速度更快,尤其当订单数量增大时,LNS_DE算法解的平均值优化比例不断扩大,这为提高RMFS系统拣选效率,实现订单快速响应提供有效决策指导.展开更多
本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值...本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值。随后利用神经网络对单核子分离能的理论值进行了优化训练,降低了单核子分离能的理论预测值与实验值之间的均方根偏差(RMSD),并在此基础上进行了两种分区优化,分别为质子和中子的幻数分区,分区优化训练后进一步降低了RMSD。单核子分离能分区训练后的RMSD比整体直接训练的效果更好,特别能显著降低轻核区的RMSD,单中子分离能进行中子幻数分区训练的效果更好,单质子分离能进行质子幻数分区训练的效果更好。This research is based on three representative theoretical models: the Relativistic Continuum Hartree-Bogoliubov (RCHB) theory, Relativistic Mean Field (RMF) theory, and Skyrme-Hartree-Fock-Bogoliubov (SHFB) model. First, the Artificial Neural Network (ANN) method was introduced to calculate theoretical predictions of single-nucleon separation energies for these three models. Subsequently, the neural network was employed to optimize and train the theoretical values of single-nucleon separation energies, reducing the root mean square deviation (RMSD) between theoretical predictions and experimental values. Two partitioning optimization schemes were then implemented: proton magic number partitioning and neutron magic number partitioning. The partitioned optimization training further reduced RMSD values. The partitioned training of single-nucleon separation energies demonstrated better performance than direct global training, particularly in significantly reducing RMSD in the light nuclei region. Specifically, neutron magic number partitioning showed superior effectiveness for optimizing single-neutron separation energies, while proton magic number partitioning yielded better results for single-proton separation energies.展开更多
The field-reversed configuration(FRC)plasma thruster driven by rotating magnetic field(RMF),abbreviated as the RMF-FRC thruster,is a new type of electric propulsion technology that is expected to accelerate the deep s...The field-reversed configuration(FRC)plasma thruster driven by rotating magnetic field(RMF),abbreviated as the RMF-FRC thruster,is a new type of electric propulsion technology that is expected to accelerate the deep space exploration.An experimental prototype,including diagnostic devices,was designed and constructed based on the principles of the RMF-FRC thruster,with an RMF frequency of 210 kHz and a maximum peak current of 2 kA.Under the rated operating conditions,the initial plasma density was measured to be 5×10^(17)m^(-3),and increased to 2.2×10^(19)m^(-3)after the action of RMF.The coupling efficiency of RMF was about 53%,and the plasma current reached 1.9 kA.The axial magnetic field changed in reverse by 155 Gauss,successfully reversing the bias magnetic field of 60 Gauss,which verifies the formation of FRC plasma.After optimization research,it was found that when the bias magnetic field is 100 Gauss,the axial magnetic field reverse variation caused by FRC is the highest at 164 Gauss.The experimental results are discussed and strategies are proposed to improve the performance of the prototype.展开更多
Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Dop...Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.展开更多
Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publicati...Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.展开更多
采用数字孪生技术对货到人拣货机器人系统RMFS(the robotic mobile fulfillment systems)进行研究,提出了针对RMFS系统的数字孪生模型构建方法并给出了数字孪生实例。实验数据表明,所构建的数字孪生系统可更好地描述RMFS系统AV(automati...采用数字孪生技术对货到人拣货机器人系统RMFS(the robotic mobile fulfillment systems)进行研究,提出了针对RMFS系统的数字孪生模型构建方法并给出了数字孪生实例。实验数据表明,所构建的数字孪生系统可更好地描述RMFS系统AV(automatic vehicle)死锁和冲突的规律,可方便地随物理RMFS系统重构而重构,实现系统共生。数字孪生系统可为更好地理解RMFS系统内在规律,指导电商企业更好地使用RMFS系统提供帮助。展开更多
文摘在全球零售额和当天交货量不断增长的时代,实现订单的快速交付和优质分批是影响移动机器人履行系统(Robotic Mobile Fulfillment Systems,RMFS)拣选效率的关键因素.为构造高质量订单分配批次、提升RMFS系统拣选效率,提出融合大邻域搜索的改进差分进化算法(LNS_DE),引入大邻域搜索的破坏与修复思想及一批基于随机、基于最大代价贡献和基于集中批次的移除算子以及新的插入算子组件,以最小化订单总延迟时间为目标建立订单分批优化模型,并针对不同订单规模算例进行实验仿真.仿真结果表明,所提出的订单分批优化算法较差分进化算法(DE)相比求解质量更优,性能更稳定、收敛速度更快,尤其当订单数量增大时,LNS_DE算法解的平均值优化比例不断扩大,这为提高RMFS系统拣选效率,实现订单快速响应提供有效决策指导.
文摘本研究基于三个具有代表性的理论模型:相对论连续谱Hartree-Bogoliubov (RCHB)理论,相对论平均场(RMF)理论,Skyrme-Hartree-Fock-Bogoliubov (SHFB)模型,首先介绍了人工神经网络(ANN)方法,计算出了三个模型的单核子分离能的理论预测值。随后利用神经网络对单核子分离能的理论值进行了优化训练,降低了单核子分离能的理论预测值与实验值之间的均方根偏差(RMSD),并在此基础上进行了两种分区优化,分别为质子和中子的幻数分区,分区优化训练后进一步降低了RMSD。单核子分离能分区训练后的RMSD比整体直接训练的效果更好,特别能显著降低轻核区的RMSD,单中子分离能进行中子幻数分区训练的效果更好,单质子分离能进行质子幻数分区训练的效果更好。This research is based on three representative theoretical models: the Relativistic Continuum Hartree-Bogoliubov (RCHB) theory, Relativistic Mean Field (RMF) theory, and Skyrme-Hartree-Fock-Bogoliubov (SHFB) model. First, the Artificial Neural Network (ANN) method was introduced to calculate theoretical predictions of single-nucleon separation energies for these three models. Subsequently, the neural network was employed to optimize and train the theoretical values of single-nucleon separation energies, reducing the root mean square deviation (RMSD) between theoretical predictions and experimental values. Two partitioning optimization schemes were then implemented: proton magic number partitioning and neutron magic number partitioning. The partitioned optimization training further reduced RMSD values. The partitioned training of single-nucleon separation energies demonstrated better performance than direct global training, particularly in significantly reducing RMSD in the light nuclei region. Specifically, neutron magic number partitioning showed superior effectiveness for optimizing single-neutron separation energies, while proton magic number partitioning yielded better results for single-proton separation energies.
基金supported by National Natural Science Foundation of China (NSFC) (Nos.62201217 and 51821005)。
文摘The field-reversed configuration(FRC)plasma thruster driven by rotating magnetic field(RMF),abbreviated as the RMF-FRC thruster,is a new type of electric propulsion technology that is expected to accelerate the deep space exploration.An experimental prototype,including diagnostic devices,was designed and constructed based on the principles of the RMF-FRC thruster,with an RMF frequency of 210 kHz and a maximum peak current of 2 kA.Under the rated operating conditions,the initial plasma density was measured to be 5×10^(17)m^(-3),and increased to 2.2×10^(19)m^(-3)after the action of RMF.The coupling efficiency of RMF was about 53%,and the plasma current reached 1.9 kA.The axial magnetic field changed in reverse by 155 Gauss,successfully reversing the bias magnetic field of 60 Gauss,which verifies the formation of FRC plasma.After optimization research,it was found that when the bias magnetic field is 100 Gauss,the axial magnetic field reverse variation caused by FRC is the highest at 164 Gauss.The experimental results are discussed and strategies are proposed to improve the performance of the prototype.
基金supported in part by the National Natural Foundation of China(No.62027801).
文摘Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.
文摘Healthcare security and privacy breaches are occurring in the United States (US), and increased substantially during the pandemic. This paper reviews the National Institute of Standards and Technology (NIST) publication base as an effective solution. The NIST Special Publication 800-66 Revision 1 was an essential standard in US healthcare, which was withdrawn in February 2024 and superseded by SP 800-66 Revision 2. This review investigates the academic papers concerning the application of the NIST SP 800-66 Revision 1 standard in the US healthcare literature. A systematic review method was used in this study to determine current knowledge gaps of the SP 800-66 Revision 1. Some limitations were employed in the search to enforce validity. A total of eleven articles were found eligible for the study. Consequently, this study suggests the necessity for additional academic papers pertaining to SP 800-66 Revision 2 in the US healthcare literature. In turn, it will enhance awareness of safeguarding electronic protected health information (ePHI), help to mitigate potential future risks, and eventually reduce breaches.
