医院图书馆信息资源价值评估方法的构建

阐述了医院图书馆信息资源价值评估的意义,并在分析国内外公共图书馆和高校图书馆经济价值评估的基础上,选择现阶段在国内外图书馆价值研究中应用颇多的条件价值评估法和投资回报分析法,结合医院图书馆服务的实际,构建了医院图书馆信息资源价值评估方法。

图书馆服务价值量化评估方法的思考

简述图书馆价值评估历程,介绍成本收益法、条件价值法、投资回报法在图书馆价值评估领域中的运用与发展,对比分析三种方法,进一步探索图书馆评估方法发展的新方向。

An algorithm for segmentation of lung ROI by mean-shift clustering combined with multi-scale HESSIAN matrix dot filtering

A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.

Efficiency Rankings of MBA Programs in Indian Top Public Colleges

This study examines the relative efficiency of the top 20 Indian public colleges that offer MBAs. These colleges were chosen from a list provided by Careers 360, a magazine in India known for its university rankings. The purpose of this study was to evaluate the colleges on an efficiency basis rather than on a total score ranking scale as is the common practice of most publications that rank universities or programs. The ranking method used in this study is based on data envelopment analysis （DEA）, a nonparametric procedure for evaluating entities based upon examining inputs in relation to outputs achieved. The rankings using DEA were somewhat different than those given by Careers 360. The results of the DEA analysis of this study rank the universities that are the most efficient at getting students the best salaries and return on investment （ROI） based on the inputs of diversity, work experience, and residency. The authors conclude, as previous studies have shown, that DEA analysis is a useful and non-biased method of comparing university programs.

On Structural Approach for the Valuation of Credit Risk

This paper presents structural approach for the valuation of credit risk. Credit risk arises whenever a borrower is expecting to use future cash flows to pay a current debt. It is closely tied to the potential return of investment, the most notable being that the yields on bonds correlate strongly to their perceived credit risk. Structural approach is based on the volatility of the total value of the firm. The credit risk to this measured in a standard way. The random time of default is defined in an intuition way. The default event is linked to the notion of the firm＇s insolvency. This approach is known to generated low credit spreads for corporate bonds close to maturity. It requires a judicious specification of the default barrier in order to get a good fit to the observed spread curves.

New auto color correction algorithm for microscopic imaging system

trast （HC） method is proposed to define saliency value of each pixel, then auto Grabcut segmenta- tion method is used to segment the salient region so as to obtain a region of interest （ROI）. After that, normalized histograms and cumulative histograms for ROI and region of background （ROB） are calculated. The mapping functions of the corresponding regions are derived from reference image to distorted image through the nearest cumulative histogram matching method, so that color correction can be finally achieved. Experimental results show that benefitting from the separate treatment to ROI and ROB, the proposed color correction method could avoid error propagation between the two different regions, which achieves good color correction result in comparison with other correction methods.

Extended digital image correlation method for micro-region deformation measurement

Extended digital image correlation(X-DIC) method is one novel test method in experimental mechanics.In this paper,the principle of the X-DIC method was introduced in detail.A selection scheme of the initial value of Newton iteration method was proposed when Newton iteration method was applied to solve the partial differential equations.This scheme could make the X-DIC method suitable for the large deformation measurement and avoid the non-convergence phenomenon effectively.The performance of the X-DIC method was verified by simulated images.Since the pixel point with the maximum absolute error occurred mainly at the corner or on the interface of the region of interest(ROI,region used for correlation calculation),measured deformation of the core area(area surrounding the center point of the ROI with a smaller size) was taken as the reliable measured value.The measurement accuracy of the X-DIC method could be improved greatly by using the core area.Combined with a long-distance microscope,the X-DIC method could be used in the deformation measurement of the micro-region.Zero deformation experiment was done to test the precision of the measurement system.Then,the X-DIC method was applied to measure the micro-region deformation of the specimen with a crack.Test value was proved to be in accordance with the actual deformation,showing that the X-DIC method is suitable for the research of microscale mechanical behavior of materials.