Exploration on the Construction of University Logistics Information Service Platform

Logistics information construction in colleges and universities is an important part of smart campus. This paper expounds the current situation and existing problems of the logistics information construction in colleges and universities. Taking China University of Geosciences (Beijing) as an example, this paper discusses the construction principles and Personnel organization structure of the logistics information construction, and provides the construction scheme of the logistics information service platform. It can be used for reference for the implementation of logistics information construction in other colleges and universities.

基于Seed-PCG法的列车-轨道-地基土三维随机振动GPU并行计算方法

为了解决列车-轨道-地基土三维有限元模型随机多样本计算效率低的问题,本文提出了一种基于Seed-PCG法的高效并行计算方法。基于有限元法和虚拟激励法建立轨道不平顺激励下的三维列车-轨道-地基土耦合随机振动分析模型;针对车致地基土随机振动分析产生的多右端项线性方程组求解问题,采用Seed-PCG方法进行求解。通过PCG方法求解种子系统得到的Krylov子空间进行投影,以改进其余线性方程组的初始解和对应的初始残量,有效提高了PCG法的收敛速度,最后,在MATLABCUDA混合平台上开发了并行计算程序。数值算例表明:相同计算平台下的该方法相比多点同步算法获得了104.2倍的加速;相比PCG法逐个求解方案减少了18%的迭代次数,获得了1.21倍的加速。

Characteristics of Haze Weather and Its Meteorological In-fluencing Factors in Hangzhou

Based on the observation data of the annual number of haze days,rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed at Hangzhou station from 1960 to 2021,the variation characteristics of haze days and meteorological influencing factors were studied by mathematical statistical methods such as Mann-Kendall nonparametric test,sliding T test,wavelet analysis and Pearson correlation two-tailed test.The results show that the annual number of haze days generally showed an upward trend,and the climate tendency rate was 20 d/a;there was a sudden change around 2001,and it changed from stable to rapid growth;the number of haze days was the largest in spring and winter,followed by autumn,while it was the smallest in summer.The annual number of haze days had a strongly significant period of 40 a and a mesoscale variation period of 13 a.The number of haze days was negatively correlated with the number of rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed,which passed the 0.05 significance test.In recent 60 years,the number of rainy days and gale days,relative humidity,and maximum wind speed in Hangzhou have decreased,resulting in the weakening of atmospheric wet deposition capacity and power transmission conditions,which provided favorable meteorological conditions for the increase of haze weather.

列车-轨道-地基土耦合系统三维随机振动的多GPU并行计算方法

针对列车-轨道-地基土耦合系统随机计算效率低的问题,本文提出了基于多GPU的列车-轨道-地基土随机振动方程的高效并行计算方法。基于OpenMP-CUDA混编技术将虚拟激励法不同频点下的多个线性方程组求解任务分配给多个GPU并行执行;在每块GPU上,采用基于CUDA的预处理共轭梯度法(PCG)并行求解对称正定的等效静力平衡方程。针对耦合系统等效刚度矩阵的稀疏特性,采用行压缩(CSR)格式存储大型稀疏矩阵以节省内存空间。最终通过MATLAB-CUDA混合平台开发并行计算程序,解决了随机振动分析中多个线性方程组串行求解效率低的难题。数值算例表明,基于四GPU节点的多GPU并行算法和单GPU加速PCG算法的计算效率是串行多点同步算法(MPSA)计算效率的22.59倍和3.75倍。

Research on the Path of Digital Transformation of Postgraduate Education in Chinese Universities under the Background of Digital Education Strategy

Digital transformation of education is an important strategic content of information construction in Chinese universities in recent years. Postgraduate education is characterized by many types of postgraduates, complex training links, long training process, and obvious individuation. Its information construction and digital transformation are the difficulties in the construction of smart campus in colleges and universities. This paper discusses the current situation and main problems of postgraduate education informatization in colleges and universities, and puts forward the key points and suggestions of digital transformation of postgraduate education in colleges and universities from the aspects of optimizing the information platform of postgraduate education management and service, driving the modernization and wisdom of postgraduate education with data, constructing the integrated platform of intelligent teaching, and continuously improving the digital literacy of teachers and students.

Research and Practice on High Availability Scheme of Unified Identity Authentication System Based on CAS in Colleges and Universities

Unified identity authentication has become the basic information service provided by colleges and universities for teachers and students. Security, stability, high concurrency and easy maintenance are our requirements for a unified identity authentication system. Based on the practical work experience of China University of Geosciences (Beijing), this paper proposes a high availability scheme of unified identity authentication system based on CAS, which is composed of multiple CAS Servers, Nginx for load balancing, and Redis as a cache database. The scheme has been practiced in China University of Geosciences (Beijing), and the application effect is good, which has practical reference significance for other universities.

Research and Practice of Online Service Hall in Colleges and Universities

The needs of teachers and students, the requirements of educational modernization and informatization and the development of information technology promote the online service hall to become an important part of the smart campus. The online service hall is also a hot spot of information construction in universities in recent years. Taking China University of Geosciences (Beijing) for example, this paper probes into the problems and causes of the current difficulties of teachers and students in complicated school’s business process and puts forward the construction goal and ideas of the online service hall. A four-layer architecture which includes data layer, business service support layer, business service layer and presentation layer for service e-hall is designed and the organization and implementation steps of the online service hall are expounded. In addition, the extended applications such as integrated self-service printing terminal and electronic signature are considered. This paper can be used for reference for the construction and implementation of online service hall in other universities.

Improved ant colony optimization algorithm for the traveling salesman problems

Ant colony optimization （ACO） is a new heuristic algo- rithm which has been proven a successful technique and applied to a number of combinatorial optimization problems. The traveling salesman problem （TSP） is among the most important combinato- rial problems. An ACO algorithm based on scout characteristic is proposed for solving the stagnation behavior and premature con- vergence problem of the basic ACO algorithm on TSP. The main idea is to partition artificial ants into two groups： scout ants and common ants. The common ants work according to the search manner of basic ant colony algorithm, but scout ants have some differences from common ants, they calculate each route＇s muta- tion probability of the current optimal solution using path evaluation model and search around the optimal solution according to the mutation probability. Simulation on TSP shows that the improved algorithm has high efficiency and robustness.

Quantitative relationship between visibility and mass concentration of PM2.5 in Beijing

The pollution of particulate matter less than 2.5μm （PM2.5） is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U,S, national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles （PM2.5） cause atmospheric visibility deterioration through light extinction, The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different： power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5.

Urbanization effect on precipitation over the Pearl River Delta based on CMORPH data

Based on the satellite data from the Climate Prediction Center morphing(CMORPH) at very high spatial and temporal resolution, the effects of urbanization on precipitation were assessed over the Pearl River Delta(PRD) metropolitan regions of China. CMORPH data well estimates the precipitation features over the PRD. Compared to the surrounding rural areas, the PRD urban areas experience fewer and shorter precipitation events with a lower precipitation frequency(ratio of rainy hours, about 3 days per year less); however, short-duration heavy rain events play a more significant role over the PRD urban areas. Afternoon precipitation is much more pronounced over the PRD urban areas than the surrounding rural areas, which is probably because of the increase in short-duration heavy rain over urban areas.

First-principles investigation on stability and electronic structure of Sc-dopedθ′/Al interface in Al−Cu alloys

The properties of Sc-dopedθ′(Al_(2)Cu)/Al interface in Al−Cu alloys were investigated by first-principles calculations.Sc-doped semi-coherent and coherentθ′(Al_(2)Cu)/Al interfaces(Sc doped in Al slab(S1 site),Sc doped inθ′slab(S2 site))were modeled based on calculated results and reported experiments.Through the analysis of interfacial bonding strength,it is revealed that the doping of Sc at S1 site can significantly decrease the interface energy and increase the work of adhesion.In particular,the doped coherent interface with Sc at S1 site which is occupied by interstitial Cu atoms has very good bonding strength.The electronic structure shows the strong Al—Cu bonds at the interfaces with Sc at S1 site,and the Al—Al bonds at the interfaces with Sc at S2 site are formed.The formation of strong Al—Cu and Al—Al bonds plays an important role in the enhancement of doped interface strength.

Earthquake detection in the Jiangsu region, China using graphics-processing-unit-based Match & Locate and rapid earthquake association and location

Earthquake detection and location are essential in earthquake studies,which generally consists of two main classes:waveform-based and pick-based methods.To evaluate the ability of two different methods,a graphicsprocessing-unit-based Match&Locate(GPU-M&L)method and a rapid earthquake association and location(REAL)method are applied to continuous seismic data recorded by 24 digital seismic stations from Jiangsu Seismic Network during 2013 for comparison.GPU-M&L is one of waveform-based methods by waveform cross-correlations while REAL is one of pick-based method to associate arrivals of different seismic phases and locate events through counting the number of P and S picks and travel time residuals.Twenty-six templates are selected from the Jiangsu Seismic Network local catalog by using the GPU-M&L.The number of newly detected and located events is about 2.8 times more than those listed in the local catalog.We both utilize a deep-neural-network-based arrival-time picking method called PhaseNet and a shortterm/long-term average(STA/LTA)trigger algorithm for seismic phase detection and picking by applying the REAL.We then refine seismic locations using a least-squares location method(VELEST)and a high-precision relative location method(hypoDD).By applying STA/LTA and PhaseNet,1006 and 1893 events are associated and located,respectively.The newly detected events are mainly clustered and show steeply dipping fault planes.By analyzing the performance of these methods based on long-term continuous seismic data,the detected catalogs by the GPU-M&L and REAL show that the magnitudes of completeness are 1.4 and 0.8,respectively,which are smaller than 2.6 given by the local catalog.Although REAL provides improvement compared with GPU-M&L,REAL is highly dependent on phase detection and picking which is strongly affected by signal-noise ratio(SNR).Stations at southeast of the study region with low SNR may lead to few detections in the same area.

Research and Implementation of Text Similarity System Based on Power Spectrum Analysis

The paper proposed the research and implement of text similarity system based on power spectrum analysis. It is not difficult to imagine that the signals of brain are closely linked with writing process. So we build text modeling and set pulse signal function to get the power spectrum of the text. The specific detail is getting power spectrum from economic field to build spectral library, and then using the method of power spectrum matching algorithm to judge whether the test text belonged to the economic field. The method made text similarity system finish the function of text intelligent classification efficiently and accurately.

Application of Integrated Reorganization of Science Specimen Data Using Kettle

Standards and specifications are the premise of integrated reorganization of science specimen data, and data integration is the core of the reorganization. ETL [1] which is the abbreviation of extract, transform, and load [2], is very suitable for data integration. Kettle is a kind of ETL software. In this paper, it has been introduced into the integrated reorganization of science specimen data. Multi-source and heterogeneous specimen data are integrated using kettle, and good results have been achieved. It proved the effectiveness of kettle in the integrated reorganization of science specimen data. The application has practical significance, and the method can be referenced when reorganizing other resource data.

Research and Practice on Security Protection and Disaster Recovery Strategy of Oracle Database in Colleges and Universities

Database security protection, database backup and disaster recovery are important tasks for all colleges and universities to ensure the safe and stable operation of information systems. Based on the operating environment of the Oracle production database in China University of Geosciences (Beijing), combined with the practical operation and maintenance experience, this paper provides a design and implementation case of Oracle database security protection system and disaster recovery architecture. The network security protection architecture of the three-layer firewall and fortress machine, the detection and repair of security vulnerabilities, the management of system accounts and permissions, data encryption and database audit constitute the security protection system of the database. Oracle RAC (Real Application Clusters), Oracle DataGuard, redundant backup management and backup recovery constitute the disaster recovery architecture of the database. The case has practical significance for database operation and maintenance management in other colleges and universities.

THE INFLUENCE OF INHOMOGENEOUS WIND DISTRIBUTION ON DATA QUALITY FOR WIND PROFILING RADAR

Horizontal wind measured by wind profiling radar(WPR) is based on uniform wind assumption in volume of lateral beam. However, this assumption cannot completely meet in the real atmosphere. The subject of this work is to analyze the influence of atmospheric inhomogeneities for wind measurement. Five-beam WPR can measure two groups of horizontal wind components U and V independently, using the difference of horizontal wind components U and V can evaluate the influence of the inhomogeneity of the atmospheric motion on wind measurement. The influences can be divided into both inhomogeneous distribution of horizontal motion and vertical motion. Based on wind measurements and meteorological background information, a new means of coordinate rotation the two kinds of inhomogeneous factor was separated, and the impact in different weather background was discussed. From analysis of the wind measured by type of PB-II WPR(445MHz) during 2012 at Yanqing of Beijing, it is shown that the inhomogeneity of horizontal motion is nearly the same in U and V direction. Both the inhomogeneities of horizontal motion and vertical motion have influence on wind measurement, and the degrees of both influences are associated with changes of wind speed. In clear air, inhomogeneity of horizontal motion is the main influence on wind measurement because of small vertical velocity.In precipitation, the two influences are larger than that in clear air.

Predicting heartbeat arrival time for failure detection over internet using auto-regressive exogenous model

Predicting heartbeat message arrival time is crucial for the quality of failure detection service over intemet. However, intemet dynamic characteristics make it very difficult to understand message behavior and accurately predict heartbeat arrival time. To solve this problem, a novel black-box model is proposed to predict the next heartbeat arrival time. Heartbeat arrival time is modeled as auto-regressive process, heartbeat sending time is modeled as exogenous variable, the model＇ s coefficients are estimated based on the sliding window of observations and this result is used to predict the next heartbeat arrival time. Simulation shows that this adaptive auto-regressive exogenous （ARX） model can accurately capture heartbeat arrival dynamics and minimize prediction error in different network environments.

Evaluation of Precipitation in Multi-Generation Reanalyses with Land Observations over Zhejiang Province

Based on various statistical indices,the abilities of multi-generation reanalyses,namely the NCEP/NCAR Reanalysis 1(R1),the NCEP-DOE Reanalysis 2(R2)and the NCEP Climate Forecast System Reanalysis(CFSR),to reproduce the spatiotemporal characteristics of precipitation over Zhejiang Province are comprehensively compared.The mean absolute bias percentages for three reanalyses are 20%(R1),10%(R2)and 37%(CFSR).R2(R1)gives the best(worst)general depiction of the spatial characteristics of the observed precipitation climatology,whereas a significant wet bias is noticed in the CFSR.All reanalyses reasonably reproduce the interannual variability with the correlation coefficients of 0.72(R1),0.72(R2)and 0.84(CFSR).All reanalyses well represent the first two modes of the observed precipitation through Empirical Orthogonal Function analysis,with CFSR giving the best capture of the principal components.The root-mean-square error(RMSE)is the largest(smallest)in the CFSR(R2).The large RMSE of CFSR in summer(especially in June)contributes mostly to its systematic wet bias.After 2001,the wet bias of CFSR substantially weakens,probably attributed to increasing observations assimilated in the CFSR.On a monthly basis,the percentage of neutral bias cases are similar for all reanalyses,while the ratio of positive(negative)bias cases for CFSR is distinctly larger(smaller)than that of R1 and R2.The proportions of negative bias cases for R1 and R2 begin to increase after 2001 while keeping stable for CFSR.On a daily basis,all reanalyses give good performances of reproducing light rain;however,the reflection of moderate rain and heavier rain by the CFSR is better than R1 and R2.Overall,despite being a third-generation reanalysis product,the CRSR does not exhibit comprehensive superiorities over R1 and R2 in all aspects on a regional scale.

A Scheme for Mining State Association Rules of Process Object Based on Big Data

This paper devises a scheme which can discover the state association rules of process object. The scheme aims to dig the hidden close relationships of different links in process object. We adopt a method based on difference and extremum to compute the timing. Clustering is used to classifying the adjusted data, and the next is associating the clusters. Based on the rules of clusters, we produce the rules of links. Association degrees between each two links can be determined. It is easy to get association chains according to the degree. The state association rules that can be obtained in accordance with association rules are the final results. Some industry guidance can be directly summarized from the state association rules, and we can apply the guidance to improve the efficiency of production and operational in allied industries.

The Practice of a Method of Self-Study Students Counting in Classrooms Based on Head Detection in Colleges and Universities

In order to solve the problem that it is difficult for students to find self-study classrooms because of the limited classroom resources, combined with the current situation of informatization in colleges and universities, a feasible method of students counting in classrooms based on head detection is proposed. This method first collects the scene images in the classroom at regular intervals based on the existing examination monitoring system, and then uses the offline trained AdaBoost cascade detector to detect the head candidate region in the images. Then, the trained CNN-SVM model is used to further identify the head, and finally the identification results are processed and the number of students in the classrooms is counted. The test and practice show that the query system for the idle situation of self-study classrooms constructed by coordinating the classroom seat capacity, classroom scheduling data and the students counting in the classroom based on the above method can easily query the current crowded degree of the students in the classrooms, which plays a good guiding role for students to find self-study classrooms. The method has strong reference and promotion significance for solving similar problems in other universities.