全站仪的误差分析及精度控制在水利工程测量中的研究

水利工程是国民经济建设过程中非常重要的建设内容,能够为人们的生产生活提供极大的便利,这就需要保证水利工程测量工作的准确性。在水利工程测量过程中,常用的测量工具就是全站仪,做好其误差分析与精度控制工作是非常必要的,本文就主要针对此予以简单分析。     

GPS在土地测绘中的应用

在经济飞速发展的21世纪,土地测绘的技术也在快速发展着。因为该技术应用于各个领域,其中,GPS技术起到了十分关键的作用,不仅为各个领域的发展提供了充足的准备和保障,也就奠定了GPS成为最基础的科学的地位。     

加强校企合作 完善实训基地建设——甘肃钢铁职业技术学院实训基地现状的调查与思考

本文通过对学院实训基地的调研,总结目前甘肃钢铁职业技术学院校企合作的现状、存在的问题,进而分析所应该采取的措施。     

Stochastic model specification search for Gaussian and partial non-Gaussian state space models

Model specification for state space models is a difficult task as one has to decide which components to include in the model and to specify whether these components are fixed or time-varying. To this aim a new model space MCMC method is developed in this paper. It is based on extending the Bayesian variable selection approach which is usually applied to variable selection in regression models to state space models. For non-Gaussian state space models stochastic model search MCMC makes use of auxiliary mixture sampling. We focus on structural time series models including seasonal components, trend or intervention. The method is applied to various well-known time series.     

矿井地面变电所智能无线实时温度在线监测系统

介绍了智能无线实时温度在线监测系统的原理、结构、功能、特点。该系统对电力设备接触部位温度进行实时追踪监测,可以有效防止设备超负荷运行引发的电气事故,确保了矿井安全供电。     

浅谈语境设置在英美概况课中的应用

本文通过了解语境这一概念以及语境设置的意义来分析语境的设置在大学英美概况课程中的应用,说明了语境的设置对英美概况教学中学生能力的培养具有非常重要的作用。     

The Impact of Non-Normality and Estimation Methods in SEM on Satisfaction Research in Marketing

This paper discusses consequences of violating the normal distribution assumption imbedded in Structural Equation Modeling (SEM). Based on real data from a large sample customer satisfaction survey we follow the procedures as suggested in leading textbooks. We document consequences of this practice and discuss its impact on decision making in marketing.     

浅谈问卷调查中模糊性问题的处理方法

在社会经济中,存在着大量的模糊事件。传统的统计思想和方法对此往往无能为力,这就需要引入模糊数学的思想和方法。本文对问卷调查中模糊性产生的原因进行简要的概括,对其处理方法进行了初步的探讨。     

A two-stage realized volatility approach to estimation of diffusion processes with discrete data

This paper motivates and introduces a two-stage method of estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as developed in [Jacod, J., 1994. Limit of random measures associated with the increments of a Brownian semiartingal. Working paper, Laboratoire de Probabilities, Universite Pierre et Marie Curie, Paris] and [Barndorff-Nielsen, O., Shephard, N., 2002. Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society. Series B, 64, 253–280], to provide a regression model for estimating the parameters in the diffusion function. In the second stage, the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite sample performance of the proposed method is compared with that of the approximate maximum likelihood method of [Aït-Sahalia, Y., 2002. Maximum likelihood estimation of discretely sampled diffusion: A closed-form approximation approach. Econometrica. 70, 223–262].     

Networks in Public Administration: Current scholarship in review

Abstract

Network-focused research in public administration has expanded rapidly over the past two decades. This rapid growth has created come confusion about terminology and approaches to research in the field. We organize the network literature in public administration using compact citation networks to identify coherent subdomains focused on (1) policy formation, (2) governance and (3) policy implementation. We trace how these domains differ in their approach to defining the role of networks, relationships and actors and to what extent the articles apply formal network analysis techniques. Based on a subsequent content analysis of the sample articles, we identify promising research avenues focused on the wider adoption of methods derived from social network analysis and the conditions under which networks actually deliver improved results.