高职学生网上评教数据的修正与优化处理研究

针对高职学生网上评教存在的问题,采用评教验证机制设置不合理评教的限制。对学生评教数据先剔除异常值,再分别对不同班级、不同课程和不同院系之间的学生评教数据进行修正与优化处理,得出最终的修正分值,降低了因班级、课程和院系的不同而导致的评教数据的差异性,使学生的网上评教能更准确有效的反应出教师的教学水平。     

大数据推动政府治理创新的目标与路径

大数据的广泛应用对社会产生了深远影响,也对政府治理变革起着重要推动作用,大数据将推动政府治理理念、治理体系、治理方式的创新。政府治理的目标就是应用大数据实现法治政府、创新政府、廉洁政府和服务型政府。在运用大数据推动政府治理创新的过程中,应通过数据共享优化政府治理结构,通过政务形态信息化调整政府治理关系,通过政务平台技术化重塑政府流程,借用大数据来提升政府创新能力,通过数据应用法制化提升政府法治水平。所以,政府必须要主动适应信息公开和数据共享的大趋势,以此推动政府治理的变革与创新,进一步提高政府治理能力。     

A study of DEA models without explicit inputs

In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered. We provide an axiom foundation of these kinds of models, and further discuss how to incorporate value judgments of decision makers into these DEA-WEI models. Several such models are derived. Finally, applications of the DEA-WEI models are presented.     

An efficient polynomial space and polynomial delay algorithm for enumeration of maximal motifs in a sequence

In this paper, we consider the problem of enumerating all maximal motifs in an input string for the class of repeated motifs with wild cards. A maximal motif is such a representative motif that is not properly contained in any larger motifs with the same location lists. Although the enumeration problem for maximal motifs with wild cards has been studied in Parida et al. (2001), Pisanti et al. (2003) and Pelfrêne et al. (2003), its output-polynomial time computability has been still open. The main result of this paper is a polynomial space polynomial delay algorithm for the maximal motif enumeration problem for the repeated motifs with wild cards. This algorithm enumerates all maximal motifs in an input string of length n in O(n ³) time per motif with O(n) space, in particular O(n ³) delay. The key of the algorithm is depth-first search on a tree-shaped search route over all maximal motifs based on a technique called prefix-preserving closure extension. We also show an exponential lower bound and a succinctness result on the number of maximal motifs, which indicate the limit of a straightforward approach. The results of the computational experiments show that our algorithm can be applicable to huge string data such as genome data in practice, and does not take large additional computational cost compared to usual frequent motif mining algorithms. This work is done during the Hiroki Arimura’s visit in LIRIS, University Claude-Bernard Lyon 1, France.     

“大数据”背景下利用扫描数据编制中国CPI问题研究

扫描数据为政府统计源头数据信息化改革与宏观经济测度提供了新的技术范式。基于对世界各国利用扫描数据编制CPI的现状进行梳理研究,并针对中国扫描数据的现状和政府价格统计的特点,提出了一种利用扫描数据编制中国CPI的思路,力图为基于"大数据"的政府统计源头数据信息化改革提供理论和实践参考。     

中国人口终身迁移状况分析

“出生地”是用来收集人口迁移信息最常用的调查项目之一。中国以往的人口普查中一直缺少这一调查项目 ,这使得利用出生地资料对人口迁移状况进行分析在国内一直是个空白。中国第五次人口普查在中国人口普查史上首次调查了人口的出生地信息。本文主要根据第五次人口普查提供的出生地资料 ,对中国各省人口的终身迁移水平、流向以及不同年龄人口的终身迁移状况进行了初步分析。     

Models for measuring and benchmarking olympics achievements

As demonstrated in several recent studies, data envelopment analysis (DEA) is a useful tool for evaluating and comparing the performance of nations competing in the Olympic Games. Assurance regions (ARs) have been used to further refine the DEA results. These AR DEA models assume that ARs apply uniformly across all nations. Such models can have shortcomings in the sense that different nations may impose different ARs, as nations may value gold, silver, and bronze medals differently. This paper extends previous DEA studies by incorporating multiple sets of nation-specific ARs into the DEA. By doing so, we establish fair models for measuring and benchmarking the performance of nations at six summer Olympic Games.     

A generalisation of the Farrell cost efficiency measure applicable to non-fully competitive settings

This paper enhances cost efficiency measurement methods to account for situations where the input prices can depend on negotiation or tend to qualitatively differentiate the resources available at each decision making unit. In these circumstances, there are some shortcomings in the cost efficiency measure described in the data envelopment analysis (DEA) literature. This paper proposes new models and measures for cost efficiency evaluation that overcome the limitations of the existing DEA models. The applicability of the measures developed is illustrated in the context of the analysis of bank branch performance.     

RFID as an Enabler of Improved Manufacturing Performance*

The use of radio frequency identification (RFID) versus bar coding has been debated with little quantitative research about how to best use RFID's capabilities and when RFID is more advantageous. This article responds to that need by qualitatively and quantitatively analyzing how RFID facilitates increased traceability and control in manufacturing, which in turn enables the use of more lot splitting and smaller lot sizes. We develop insights about operating policies (RFID vs. bar‐code tracking mechanisms, extent of lot splitting, and dispatching rules) and an operating condition (setup to processing time ratio) that affect the mean flow time and proportion of jobs tardy in a job shop. A simulation model is used to control factors in the experimental design and the output is evaluated using analysis of variance. The results show the following: (i) performance worsens when bar coding is used with extensive lot splitting, (ii) process changes such as extensive lot splitting may be required to justify RFID use instead of bar coding, (iii) the earliest operation due date dispatching rule offers an attractive alternative to other rules studied in previous lot splitting research, and (iv) the performance improvements with RFID and increased lot splitting are larger when the setup to processing time ratio is smaller. In a broader context, we fill a research void by quantitatively showing how RFID can be used as an advanced manufacturing technology that enables more factory automation and better performance along several dimensions. The article concludes by summarizing the results and identifying ideas for future research.     

Variable precision rough set theory and data discretisation: an application to corporate failure prediction

Since the seminal work of Pawlak (International Journal of Information and Computer Science, 11 (1982) 341–356) rough set theory (RST) has evolved into a rule-based decision-making technique. To date, however, relatively little empirical research has been conducted on the efficacy of the rough set approach in the context of business and finance applications. This paper extends previous research by employing a development of RST, namely the variable precision rough sets (VPRS) model, in an experiment to predict between failed and non-failed UK companies. It also utilizes the FUSINTER discretisation method which neglates the influence of an ‘expert’ opinion. The results of the VPRS analysis are compared to those generated by the classical logit and multivariate discriminant analysis, together with more closely related non-parametric decision tree methods. It is concluded that VPRS is a promising addition to existing methods in that it is a practical tool, which generates explicit probabilistic rules from a given information system, with the rules offering the decision maker informative insights into classification problems.