On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong,...On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.展开更多
微调后的大语言模型(Large language models,LLMs)在多任务中表现出色,但集中式训练存在用户隐私泄漏的风险。联邦学习(Federated learning,FL)通过本地训练避免了数据共享,但LLMs庞大的参数量对资源受限的设备和通信带宽构成挑战,导致...微调后的大语言模型(Large language models,LLMs)在多任务中表现出色,但集中式训练存在用户隐私泄漏的风险。联邦学习(Federated learning,FL)通过本地训练避免了数据共享,但LLMs庞大的参数量对资源受限的设备和通信带宽构成挑战,导致在边缘网络中部署困难。结合分割学习(Split learning,SL),联邦分割学习可以有效解决这一问题。基于模型深层权重的影响更为显著,以及对部分层的训练准确率略低于整体模型训练的发现,本文按照Transformer层对模型进行分割,同时引入低秩适应(Low⁃rank adaption,LoRA)进一步降低资源开销和提升安全性。因此,在设备端,仅对最后几层进行低秩适应和训练,然后上传至服务器进行聚合。为了降低开销并保证模型性能,本文提出了基于联邦分割学习与LoRA的RoBERTa预训练模型微调方法。通过联合优化边缘设备的计算频率和模型微调的秩,在资源受限的情况下最大化秩,提高模型的准确率。仿真结果显示,仅训练LLMs最后3层的情况下,在一定范围内(1~32)增加秩的取值可以提高模型的准确率。同时,增大模型每轮的容忍时延和设备的能量阈值可以进一步提升模型的准确率。展开更多
In this paper, we have introduced a shell-model of Kraichnan＇s passive scalar problem. Different from the original problem, the prescribed random velocity field is non-Gaussian and σ correlated in time, and its intr...In this paper, we have introduced a shell-model of Kraichnan＇s passive scalar problem. Different from the original problem, the prescribed random velocity field is non-Gaussian and σ correlated in time, and its introduction is inspired by She and Levveque （Phys. Rev. Lett. 72, 336 （1994））. For comparison, we also give the passive scalar advected by the Gaussian random velocity field. The anomalous scaling exponents H（p） of passive scalar advected by these two kinds of random velocities above are determined for structure function with values of p up to 15 by Monte Carlo simulations of the random shell model, with Gear methods used to solve the stochastic differential equations. We find that the H（p） advected by the non-Gaussian random velocity is not more anomalous than that advected by the Gaussian random velocity. Whether the advecting velocity is non-Gaussian or Gaussian, similar scaling exponents of passive scalar are obtained with the same molecular diffusivity.展开更多
文摘On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.
基金Project supported by the Major Program of the National Natural Science Foundation （Grant No 10335010） and the National Natural Science Foundation-the Science Foundation of China Academy of Engineering Physics NSAF （Grant No 10576005）.Acknowledgement We are grateful to Professor She Zhen-Su for useful suggestions and Dr Sun Peng and Dr Zhang Xiao- Qiang for extensive discussion.
文摘In this paper, we have introduced a shell-model of Kraichnan＇s passive scalar problem. Different from the original problem, the prescribed random velocity field is non-Gaussian and σ correlated in time, and its introduction is inspired by She and Levveque （Phys. Rev. Lett. 72, 336 （1994））. For comparison, we also give the passive scalar advected by the Gaussian random velocity field. The anomalous scaling exponents H（p） of passive scalar advected by these two kinds of random velocities above are determined for structure function with values of p up to 15 by Monte Carlo simulations of the random shell model, with Gear methods used to solve the stochastic differential equations. We find that the H（p） advected by the non-Gaussian random velocity is not more anomalous than that advected by the Gaussian random velocity. Whether the advecting velocity is non-Gaussian or Gaussian, similar scaling exponents of passive scalar are obtained with the same molecular diffusivity.
