编外人员“分类—分层”困境的组织解码:基于条块关系的视角

对于编外人员问题,可以基于组织条块结构的题中之义而由条块关系维度展开组织解码。伴随政府机构编外人员的扩张态势,出现了编内编外人员类别划分因非对等地位而异化为层级区分的“分层—分类”现象。在组织源头上,编外人员分层困境可溯源于政府条块关系的双重“割裂”效应,其在强化垂直管理中凸显了条块管理的层级制特征。为此,应在组织体制重构下寻找条块关系张力中的平衡点,在实现党政统合中由侧重分层对待转向专注分类规划。

Application of PCA and HCA to the Structure-Activity Relationship Study of Fluoroquinolones

Density functional theory （DFT） was used to calculate molecular descriptors （properties） for 12 fluoro-quinolone with anti-S.pneumoniae activity. Principal component analysis （PCA） and hierarchical cluster analysis （HCA） were employed to reduce dimensionality and investigate in which variables should be more effective for classifying fluoroquinolones according to their degree of an-S.pneumoniae activity. The PCA results showed that the variables ELUMO, Q3, Q5, QA, logP, MR, VOL and △EHL of these compounds were responsible for the anti-S.pneumoniae activity. The HCA results were similar to those obtained with PCA.The methodologies of PCA and HCA provide a reliable rule for classifying new fluoroquinolones with antiS.pneumoniae activity. By using the chemometric results, 6 synthetic compounds were analyzed through the PCA and HCA and two of them are proposed as active molecules with anti-S.pneumoniae, which is consistent with the results of clinic experiments.

Classification of tight sandstone reservoirs based on NMR logging

The traditional reservoir classification methods based on conventional well logging are inefficient for determining the properties,such as the porosity,shale volume,J function,and flow zone index,of the tight sandstone reservoirs because of their complex pore structure and large heterogeneity.Specifically,the method that is commonly used to characterize the reservoir pore structure is dependent on the nuclear magnetic resonance(NMR)transverse relaxation time(T2)distribution,which is closely related to the pore size distribution.Further,the pore structure parameters(displacement pressure,maximum pore-throat radius,and median pore-throat radius)can be determined and applied to reservoir classification based on the empirical linear or power function obtained from the NMR T2 distributions and the mercury intrusion capillary pressure ourves.However,the effective generalization of these empirical functions is difficult because they differ according to the region and are limited by the representative samples of different regions.A lognormal distribution is commonly used to describe the pore size and particle size distributions of the rock and quantitatively characterize the reservoir pore structure based on the volume,mean radius,and standard deviation of the small and large pores.In this study,we obtain six parameters(the volume,mean radius,and standard deviation of the small and large pores)that represent the characteristics of pore distribution and rock heterogeneity,calculate the total porosity via NMR logging,and classify the reservoirs via cluster analysis by adopting a bimodal lognormal distribution to fit the NMR T2 spectrum.Finally,based on the data obtained from the core tests and the NMR logs,the proposed method,which is readily applicable,can effectively classify the tight sandstone reservoirs.

Two-level fuzzy evaluation for classification of credits

In this paper, classification models are used as tools to make final decision. Fuzzy method provides the mathematical tools for quantitative analysis and dealing with ambiguous concepts. Analytic Hierarchy Process (AHP) is used to obtain the weight of each index and enables examiners to visualize the decision process and obtain more reasonable evaluation values to solve some problems. An example is given at the end of this paper.

Analyzing Motion Patterns in Crowded Scenes via Automatic Tracklets Clustering

Crowded scene analysis is currently a hot and challenging topic in computer vision field. The ability to analyze motion patterns from videos is a difficult, but critical part of this problem. In this paper, we propose a novel approach for the analysis of motion patterns by clustering the tracklets using an unsupervised hierarchical clustering algorithm, where the similarity between tracklets is measured by the Longest Common Subsequences. The tracklets are obtained by tracking dense points under three effective rules, therefore enabling it to capture the motion patterns in crowded scenes. The analysis of motion patterns is implemented in a completely unsupervised way, and the tracklets are clustered automatically through hierarchical clustering algorithm based on a graphic model. To validate the performance of our approach, we conducted experimental evaluations on two datasets. The results reveal the precise distributions of motion patterns in current crowded videos and demonstrate the effectiveness of our approach.

RESEARCH AND APPLICATION OF A NEURAL NETWORK CLASSIFIER BASED ON DYNAMIC THRESHOLD

In this study, a Multi-Layer BP neural network(MLBP) with dynamic thresholds is employed to build a classifier model.As to the design of the neural network structure, theoretical guidance and plentiful experiments are combined to optimize the hidden layers' parameters which include the number of hidden layers and their node numbers.The classifier with dynamic thresholds is used to standardize the output for the first time, and it improves the robustness of the model to a high level.Finally, the classifier is applied to forecast box office revenue of a movie before its theatrical release.The comparison results with the MLP method show that the MLBP classifier model achieves more satisfactory results, and it is more reliable and effective to solve the problem.

Hierarchical Semantic-Category-Tree Model for Chinese-English Machine Translation

We introduce a novel Sermntic-Category- Tree （SCT） model to present the sen-antic structure of a sentence for Chinese-English Machine Translation （MT）. We use the SCT model to handle the reordering in a hierarchical structure in which one reordering is dependent on the others. Different from other reordering approaches, we handle the reordering at three levels： sentence level, chunk level, and word level. The chunk-level reordering is dependent on the sentence-level reordering, and the word-level reordering is dependent on the chunk-level reordering. In this paper, we formally describe the SCT model and discuss the translation strategy based on the SCT model. Further, we present an algorithm for analyzing the source language in SCT and transforming the source SCT into the target SCT. We apply the SCT model to a role-based patent text MT to evaluate the ability of the SCT model. The experimental results show that SCT is efficient in handling the hierarehical reordering operation in MT.

Comparative analysis on soil engineering classifications of China and America

Based on China National Standard of Soil Engineering Classification (GB/T 50145-2007) and the Unified Soil Classification System of American Society for Testing Materials (ASTM D-2478), two kinds of soil laboratory engineering classification methods were discussed and analyzed from the aspects of the definition in particle fraction, classification of soil type and evaluation standard for soil gradation. There is a same limit of fine grains fraction in the two standards, and there are three main types of soil in GB/T 50145-2007 and two in ASTM D-2487. Different evaluation standards of gradation are put forward for gravels and sands in ASTM D-2487. Same criteria of A line, B line and controlling value of plastic index are in the plasticity chart of both standards.

Component analysis of Chinese medicine and advances in fuming-washing therapy for knee osteoarthritis via unsupervised data mining methods

OBJECTIVE: To analyze the component law of Chinese medicines in fuming-washing therapy for knee osteoarthritis(KOA), and develop new fuming-washing prescriptions for KOA through unsupervised data mining methods.METHODS: Chinese medicine recipes for fuming-washing therapy for KOA were collected and recorded in a database. The correlation coefficient among herbs, core combinations of herbs, andnew prescriptions were analyzed using modified mutual information, complex system entropy cluster, and unsupervised hierarchical clustering, respectively.RESULTS: Based on analysis of 345 Chinese medicine recipes for fuming-washing therapy, 68 herbs occurred frequently, 33 herb pairs occurred frequently, and 12 core combinations were found.Five new fuming-washing recipes for KOA were developed.CONCLUSION: Chinese medicines for fuming-washing therapy of KOA mainly consist of wind-dampness-dispelling and cold-dispersing herbs, blood-activating and stasis-resolving herbs,and wind-dampness-dispelling and heat-clearing herbs. The treatment of fuming-washing therapy for KOA also includes dispelling wind-dampness and dispersing cold, activating blood and resolving stasis, and dispelling wind-dampness and clearing heat. Zhenzhutougucao(Herba Speranskiae Tuberculatae), Honghua(Flos Carthami), Niuxi(Radix Achyranthis Bidentatae), Shenjincao(Herba Lycopodii Japonici), Weilingxian(Radix et Rhizoma Clematidis Chinensis), Chuanwu(Radix Aconiti), Haitongpi(Cortex Erythrinae Variegatae), Ruxiang(Olibanum),Danggui(Radix Angelicae Sinensis), Caowu(Radix Aconiti Kusnezoffii), Moyao(Myrrha), and Aiye(Folium Artemisiae Argyi) are the main herbs used in the fuming-washing treatment for KOA.