转型时期社会运行的序间状态及其对策研究

转型时期社会运行的序间状态及其对策研究贾高建一一定时期社会运行的状态无疑首先取决于这一社会的基本结构体系本身的状况。一种成型的、现实的社会结构体系（不论其价值意义如何）总是通过自己系统内部的各种相关机制规定着系统运行的秩序，使之呈现出某种相应状态──...

转型期利益集团对民主政治的正面影响

一首先对转型社会作一简单的描述性界定。转型社会即指那些正处于由传统向现代转变过程中的社会。这其中包含的涵义较为宽泛，比如经济体制、思想文化、社会结构、政治制度的转变等。缘于此，其特征所指范围也相应地较为广阔，学者们各有不同的评论。这里，本文同样对其特...

转型期利益集团对民主政治的正面影响浅析

一转型社会即指那些正处于传统向现代转变过程的社会。关于转型社会的特征，中外有许多学者较为深刻的分析一般认为转型社会处于“序间状态”。所谓“序间状态”即原有的秩序无法维持，而新的秩序的产生又需要一个过程。由于“序间状态”的作用，转型社会的政治生活呈现出...

析“职位消费”

析“职位消费”林忠耿所谓职位消费，是指公职人员、经营管理者除货币报酬之外的按其职位所享有的待遇．在我国社会转型的特定历史时期，＂职位消费＂演化变异，远远超越了所谓工作需要的合理度。这种无度的职位消费的膨胀，已经成为滋长腐败的营养源和一种社会病态。透过...

Remaining Useful Life Prediction of Aeroengine Based on Principal Component Analysis and One-Dimensional Convolutional Neural Network

In order to directly construct the mapping between multiple state parameters and remaining useful life(RUL),and reduce the interference of random error on prediction accuracy,a RUL prediction model of aeroengine based on principal component analysis(PCA)and one-dimensional convolution neural network(1D-CNN)is proposed in this paper.Firstly,multiple state parameters corresponding to massive cycles of aeroengine are collected and brought into PCA for dimensionality reduction,and principal components are extracted for further time series prediction.Secondly,the 1D-CNN model is constructed to directly study the mapping between principal components and RUL.Multiple convolution and pooling operations are applied for deep feature extraction,and the end-to-end RUL prediction of aeroengine can be realized.Experimental results show that the most effective principal component from the multiple state parameters can be obtained by PCA,and the long time series of multiple state parameters can be directly mapped to RUL by 1D-CNN,so as to improve the efficiency and accuracy of RUL prediction.Compared with other traditional models,the proposed method also has lower prediction error and better robustness.

Research on the Summer Drought in Chongqing Using MODIS-EVI Time Series Data

MODIS-EVI time series data from 2000 to 2009 in Chongqing were selected for this study.By the use of best index slope extraction （BISE） method for cloud elimination,analysis on the change vector of EVI time series data were conducted to investigate the EVI response on drought; then,four typical regions were selected to study the relationship between precipitation,temperature and EVI when the sever drought occurred in 2006; finally,based on the time series of vegetation condition index （VCI） and precipitation abnormity percentage,the temporal and spatial distributions of drought were studied.The results showed that,the EVI value of the summer in 2006 was significantly lower than the average EVI at the corresponding period of the other years in Chongqing.In addition,summer drought occurred mainly during the hot and dry weather.Except the southeast area,most of the other regions in Chongqing were all under severe drought.

Effects of Snow Cover on Ground Thermal Regime： A Case Study in Heilongjiang Province of China

The important effects of snow cover to ground thermal decades. In the most of previous research, the effects were usually regime has received much attention of scholars during the past few evaluated through the numerical models and many important results are found. However, less examples and insufficient data based on field measurements are available to show natural cases. In the present work, a typical case study in Mohe and Beijicun meteorological stations, which both are located in the most northern tip of China, is given to show the effects of snow cover on the ground thermal regime. The spatial （the ground profile） and time series analysis in the extremely snowy winter of 2012-2013 in Heilongjiang Province are also performed by contrast with those in the winter of 2011-2012 based on the measured data collected by 63 meteorological stations, Our results illustrate the positive （warmer） effect of snow cover on the ground temperature （GT） on the daily basis, the highest difference between GT and daily mean air temperature （DGAT） is as high as 32.35℃. Moreover, by the lag time analysis method it is found that the response time of GT from 0 cm to 20 cm ground depth to the alternate change of snow depth has 10 days lag, while at 40 cm depth the response of DGAT is not significant. This result is different from the previous research by modeling, in which the resnonse denth of ground to the alteration of snow depth is far more than 40 cm.

Translating Linear Temporal Logic Formula s into Automata

To combat the well-known state-space explosion problem in Prop ositional Linear T emp o- ral Logic （PLTL） model checking, a novel algo- rithm capable of translating PLTL formulas into Nondeterministic Automata （NA） in an efficient way is proposed. The algorithm firstly transforms PLTL formulas into their non-free forms, then it further translates the non-free formulas into their Normal Forms （NFs）, next constructs Normal Form Graphs （NFGs） for NF formulas, and it fi- nally transforms NFGs into the NA which ac- cepts both finite words and int-mite words. The experimental data show that the new algorithm re- duces the average number of nodes of target NA for a benchmark formula set and selected formulas in the literature, respectively. These results indi- cate that the PLTL model checking technique em- ploying the new algorithm generates a smaller state space in verification of concurrent systems.

Real-time road traffic states estimation based on kernel-KNN matching of road traffic spatial characteristics

The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.

Comparative Study of Changes in Stress-drop of the Jinggu MS6.6 and Ludian MS6.5 Earthquake Sequences

The earthquake stress-drop values of two sequences were accurately calculated after taking away the effects due to regional earthquake anelastic attenuation and station site response,using waveform data and seismic phase data of sequences of the Jinggu M_S6. 6,and Ludian M_S6. 5 earthquakes in Yunnan. These results show that the stress drop with magnitude increases within the scope of this study of magnitude. After eliminating the influence of the magnitude,the average value of stress-drop in the Jinggu sequence is higher than that of the Ludian sequence at the same magnitude range. This may be related to the stress state in different regions. In terms of the changes of time and space of stress-drop,before M_S5. 8 strong aftershock,the stress-drop is "slowing down-turning up-keeping a high value"after the mainshock,meanwhile,almost all of the abnormally high stress drop value is distributed around the M_S5. 8 strong aftershock, showing that the stress environment in the region was increasing after the mainshock. And after the M_S5. 9 strong aftershock,stress-drop rapidly declines to a relatively stable state,meanwhile,the high value of stress-drop is distributed around the strong aftershock,showing that the regional tectonic stress gets more fully release,its stress environment begins to rapidly decrease.For the Ludian sequence without a strong aftershock occurring,the average value of stress drop is lower than that of the Jinggu earthquake sequence at the same magnitude range,while at the same time,the stress-drop of the aftershock sequence almost hasn't changed much. In the time after the mainshock,combined with the release characteristics of the main energy,the stress in the region is excessively released,the subsequent stress in the region gradually returns to normal. This may be the reason why the activity of Ludianaftershocks significantly was weaker and subsequently there were no strong aftershocks occurred.

当前中国社会转型问题研究综述

当前中国社会转型问题研究综述范燕宁（首都师范大学政法系）近年来，我国理论界对当前中国社会转型问题表现出越来越多的关注，进行了多方面的研究，取得了颇多成果，也存在若干争论，所涉及的内容主要有以下几个方面。一、当前中国社会转型范畴的理论界定目前，国内学者...

社会转型中的失范问题

社会失范是现阶段社会发展进程中一个值得关注的社会问题。这一问题的发生,是与当代中国社会双重转型时期的序间状态直接相关的。我们必须在认真研究的基础上,采取适宜对策,有效地加以控制和解决。

An investigation of the persistence property of wind power time series

Mining the inherent persistence property of the time series of wind power is crucial for forecasting and controlling wind power.Few common methods exist that can fully depict and quantify the persistence property.Based on the definition of the active power output state of a wind farm,this paper describes the statistical persistence property of the duration time and state transition.Based on the results of our analysis of significant amounts of wind power field measurements,it is found that the duration time of wind power conforms to an inverse Gaussian distribution.Additionally,the state transition matrix of wind power is discovered to yield a ridge property,the gradient of which is related to the time scale of interest.A systemaic methodology is proposed accordingly,allowing the statistical characteristics of the wind power series to be represented appropriately.

Homogenization of climate series:The basis for assessing climate changes

Long-term meteorological observation series are fundamental for reflecting climate changes.However,almost all meteorological stations inevitably undergo relocation or changes in observation instruments,rules,and methods,which can result in systematic biases in the observation series for corresponding periods.Homogenization is a technique for adjusting these biases in order to assess the true trends in the time series.In recent years,homogenization has shifted its focus from the adjustments to climate mean status to the adjustments to information about climate extremes or extreme weather.Using case analyses of ideal and actual climate series,here we demonstrate the basic idea of homogenization,introduce new understanding obtained from recent studies of homogenization of climate series in China,and raise issues for further studies in this field,especially with regards to climate extremes,uncertainty of the statistical adjustments,and biased physical relationships among different climate variables due to adjustments in single variable series.