高校新校区校园文化建设多层次模糊综合评价

为了加快高校新校区的发展,综合考虑了高校新校区校园文化发展的各方面影响因素,构建了符合高校新校区校园文化发展的评价体系,结合层次分析法和模糊数学理论建立了高校新校区校园文化建设多层次综合评价模型,实证分析结果与社会评价结果一致,验证了所建模型的可靠性和正确性。     

On the best linear unbiased estimator and the linear sufficiency of a general growth curve model

Growth curve models are used to analyze repeated measures data (longitudinal data), which are functions of time. In this paper, some necessary and sufficient conditions for linear function B₁YB₂ to be the best linear unbiased estimator (BLUE) of estimable functions X₁ΘX₂ (or K₁ΘK₂) under the general growth curve model were established. In addition, the representations of BLUE(K₁ΘK₂) (or BLUE(X₁ΘX₂)) were derived when the conditions are satisfied. Two special notions of linear sufficiency with respect to the general growth curve model are given in the end. The findings of this paper enrich some known results in the literature.     

Leadership succession and the performance of nonprofit organizations: A fuzzy‐set qualitative comparative analysis

Leadership succession is critical to the performance of nonprofit organizations. Existing research has mostly treated leadership succession as an instantaneous event, and it has examined the independent effects of certain factors on organizational performance. However, little research has focused on the combinations of causally relevant factors. This article integrated organizational life cycle, resource dependence, and institutional theories, as well as the organizational fit literature, to explain how contextual and strategic factors combine to affect postsuccession performance. A fuzzy‐set qualitative comparative analysis (fsQCA) was used to analyze 15 succession events in Chinese environmental nongovernmental organizations (NGOs). The study identified four pathways to good NGO performance after succession. It also highlighted that it is not succession per se but the succession context (i.e. founders' control, board governance, professionalization, and political environment) and the strategic orientations of the successor that affect postsuccession performance in nonprofit organizations.     

Fuzzy integrated QFD,FMEA framework for the selection of lean tools in a manufacturing organisation

Lean Manufacturing (LM) is a well-established system to improve performance of any manufacturing industry by eliminating wastes through globally accepted tools and techniques. Industries are trying to adapt lean principles in order to optimise the resources like people, equipment, material and schedule for being efficient in the competitive market. This paper proposes an integrated approach for selecting appropriate lean tools in reliable lean perspective to enhance these critical resources. The approach exercise a hybrid model which uses fuzzy QFD to prioritise the critical resources in relation with identified wastes and fuzzy FMEA to assess the risk associated with each sub elements to address lean implementation. For waste identification, plant layout and Value Stream Mapping are considered. The model is demonstrated based on the data collected from a manufacturing industry to illustrate the application. Significant improvements are quantified with the help of future state map and plant layout.     

Improving the biomarker diagnostic capacity via functional transformations

The use of the area under the receiver-operating characteristic, ROC, curve (AUC) as an index of diagnostic accuracy is overwhelming in fields such as biomedical science and machine learning. It seems that a larger AUC value has become synonymous with a better performance. The functional transformation of the marker values has been proposed in the specialized literature as a procedure for increasing the AUC and therefore the diagnostic accuracy. However, the classification process is based on some regions (classification subsets) which support the decision made; one subject is classified as positive if its marker is within this region and classified as negative otherwise. In this paper we study the capacity of improving the classification performance of univariate biomarkers via functional transformations and the impact of this transformation on the final classification regions based on a real-world dataset. Particularly, we consider the problem of determining the gender of a subject based on the Mode frequency of his/her voice. The shape of the cumulative distribution function of this characteristic in both the male and the female groups makes the resulting classification problem useful for illustrating the differences between having useful diagnostic rules and obtaining an optimal AUC value. Our point is that improving the AUC by means of a functional transformation can produce classification regions with no practical interpretability. We propose to improve the classification accuracy by making the selection of the classification subsets more flexible while preserving their interpretability. Besides, we provide different graphical approximations which allow us a better understanding of the classification problem.     

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Abstract

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective. It will help industries to develop strategies for managing the SC effectively and ensuring improvement in performance continuously. To achieve this, this work proposes to use a two-phase research methodology. First, 36 SC performance improvement indicators are recognised from a literature survey and from field and industrial expert’s inputs. Secondly, a structural model is proposed using the fuzzy analytical hierarchy process (AHP) to prioritise the indicators strategically to improve the SC performance. The fuzzy AHP method helps determine the priority of concerns of the identified indicators under fuzzy surroundings. Inputs in this research are taken from four ancillary Indian plastic manufacturing firms. Research findings indicate that collaborations and information exchange dimension indicators obtained the highest priority in improving SC performance. The model proposed is considered very useful for the SC managers/practitioners/decision-makers to understand better and distinguish the essential SC performance improvement indicators and to take systematic decisions specifically to improve the performance of business in a SC context. Sensitivity analysis was conducted to examine the priority ranking of the indicators.     

基于模糊计算矩阵的产品智能审美评价系统研究

文章讨论了产品智能审美评价系统,即将产品审美评价体系与计算机技术、模糊计算技术相结合,利用计算机数据库将传统评价方式中主观、定性的评价指标转化为客观、定量的评价指标,借助数据库的模糊计算矩阵,对从产品中提取的数据进行计算,从而对产品方案进行客观精确的评价。     

凸模糊数值函数的判定定理

利用本文所定义的上(下)半连续,在一种新序关系下讨论了凸模糊数值函数的若干判定定理.     

分割指数构建的一种新方法

分割指数(Segregation Index)是度量群体分割程度的统计指标,其理论、方法和应用是西方学术界的研究热点,而国内目前较少有专门针对分割指数的系统介绍和研究。文章梳理了相关研究文献,介绍并分析了各种已有分割指数的构建方法及其性质,勾勒出一幅较为全面的研究图谱;提出并论证了一种新方法,在已有指数的基础上构建了相应的加权分割指数。最后,对2013—2017年我国城镇职工的行业分割情况进行了测算,例示了各种分割指数的应用,验证了加权分割指数应用的良好效果。