资源生产率视角的经济增长模型分析

现代经济的增长需要我们从关注资本和劳动生产率转移到关注资源生产率.发展以资源生产率为本质的循环经济,提高资源生产率有助于减缓经济增长中出现的环境问题,以使经济环境可持续发展.     

数控机床功能的扩展

本文主要分析了HEIDENHAIN TNC 310数控铣床系统中圆弧铣削指令及螺纹铣削指令,对螺纹铣削功能进行延伸,扩展到圆弧三轴联动,并对螺纹铣削指令格式进行了修改,从而具有圆弧三轴联动铣削功能。     

圆锥轴受扭时静、动力的传递矩阵法求解

本文提出了圆锥轴受扭时静、动力的传递矩阵。该方法简便实用,适于工程技术人员在微机上应用。     

唐山市农业循环经济发展的对策

通过分析唐山农业发展现状,指出发展农业循环经济的必要性和紧迫性,并在遵循循环经济3R原则的基础上,提出建立农业循环经济发展模式以及保障措施.     

区域工业循环经济发展的综合评价研究——以西安市为例

依据工业循环经济发展的理论和目标以及减量化、资源化和无害化的基本原则，构建区域工业循环经济发展评价指标体系，运用层次分析法测算指标权重，并以西安市为例进行实证研究。研究结果表明，西安市的工业循环经济发展水平与世界发达国家具有明显差距，接近全国平均水平。     

A circular-cone test for testing homogeneity against a simple tree order

Several methods exist for the problem of testing the equality of several treatments against the one-sided alternative that the treatments are better than the control. These methods include Dunnett's test, Bartholomew's likelihood-ratio test, the Abelson-Tukey-Schaafsma-Smid optimal-contrast test, and the multiple-contrast test of Mukerjee, Robertson, and Wright. A new test is proposed based on an approximation of the likelihood-ratio test of Bartholomew. This test involves using a circular cone in place of the alternative-hypothesis cone. The circular-cone test has excellent power characteristics similar to those of Bartholomew's test. Moreover, it has the advantages of being simpler to compute and may be used with unequal sample sizes.     

循环物流系统的概念分析

循环物流系统是循环经济系统的子系统，是为满足循环经济发展模式的物流服务需求，由物流服务需求方、物流服务提供方及其他相关机构形成的一个包含所需物流运作要素的网络。循环物流系统包括企业、产业链、社会三种类型，具有系统目标多元化、系统边界延伸、系统功能扩展等基本特征。     

农村地区建立循环经济模式的研究

随着全球化的不断深入,改变我国传统农业经营模式已显得非常紧迫。通过对农业循环经济的背景、概念、特征和制约因素等的分析,得出农村地区发展农业循环经济模式非常必要的结论,并指出了具体的解决途径。     

基于循环经济理论的产业集群生态化发展评价研究

引入循环经济理念,建立科学评价产业集群生态化发展的体系和方法,对引导产业集群合理有序的发展具有十分重要的意义。从经济效益、环境效益和社会绩效三个方面着手,构建符合循环经济特征的产业集群生态化发展评价指标体系,计算出各指标的评价值及其在评价体系中的权重以后,采用线性加权求和法求得产业集群生态化发展的综合评分值,既可对产业集群某一时期生态化发展水平及三个维度间的关系作出客观的评价,找到存在的问题和差距。     

Model-based clustering of multivariate skew data with circular components and missing values

Motivated by classification issues that arise in marine studies, we propose a latent-class mixture model for the unsupervised classification of incomplete quadrivariate data with two linear and two circular components. The model integrates bivariate circular densities and bivariate skew normal densities to capture the association between toroidal clusters of bivariate circular observations and planar clusters of bivariate linear observations. Maximum-likelihood estimation of the model is facilitated by an expectation maximization (EM) algorithm that treats unknown class membership and missing values as different sources of incomplete information. The model is exploited on hourly observations of wind speed and direction and wave height and direction to identify a number of sea regimes, which represent specific distributional shapes that the data take under environmental latent conditions.