多校区办学模式下高校文献信息资源的优化配置

随着我国高等教育体制改革的不断深入以及招生规模的持续扩大,多校区大学日益增多.多校区的运行机制对图书馆提出了更高的要求.如何提高现有文献信息资源的利用效率以满足广大师生日益增长的需求,已成为亟待解决的问题.文章就多校区模式下高校文献信息资源的优化配置问题进行初步探讨.     

Variable kernel density estimation

This paper considers the problem of selecting optimal bandwidths for variable (sample‐point adaptive) kernel density estimation. A data‐driven variable bandwidth selector is proposed, based on the idea of approximating the log‐bandwidth function by a cubic spline. This cubic spline is optimized with respect to a cross‐validation criterion. The proposed method can be interpreted as a selector for either integrated squared error (ISE) or mean integrated squared error (MISE) optimal bandwidths. This leads to reflection upon some of the differences between ISE and MISE as error criteria for variable kernel estimation. Results from simulation studies indicate that the proposed method outperforms a fixed kernel estimator (in terms of ISE) when the target density has a combination of sharp modes and regions of smooth undulation. Moreover, some detailed data analyses suggest that the gains in ISE may understate the improvements in visual appeal obtained using the proposed variable kernel estimator. These numerical studies also show that the proposed estimator outperforms existing variable kernel density estimators implemented using piecewise constant bandwidth functions.     

一类变质物品的最优存贮策略

文章研究了一类变质性物品的最优存贮问题,假定需求率是一个变量,且依赖于库存水平,在瞬时到货和常数变质率的前提下,就允许缺货情形,建立了库存模型,模型解的存在性和唯一性,找到全局最优解,就得到了最优订货策略的求解方法.     

THE OPTIMAL CRITICAL VALUE OF A PRE-TEST FOR AN INEQUALITY RESTRICTION IN A MIS-SPECIFIED REGRESSION MODEL

Optimal critical values are derived for a pre-test of an inequality restriction in a model where relevant regressors are unwittingly omitted. The criterion adopted is either that of the minimum average relative risk, or that of the mini-max regret. The latter approach yields an optimal critical value which is sensitive to the degree of model mis-specification, while the former criterion always leads to the choice of the unrestricted estimator.     

Neoliberal disorientations: changing landscapes of disability and governance in India

This article delves into questions of neoliberal disorientations experienced by disabled people in the context of a participatory development self-help group project from the World Bank in south India. I explore ways in which neoliberal development regimes produce exclusionary forms of inclusion by producing subjects who are ‘able-disabled’. I ethnographically examine ‘who gets counted’ and ‘what gets counted’ within the neoliberal governance framework, and what remains outside. Deconstructing participatory development approaches from a critical disability perspective, the article sheds light on processes of inclusion through exclusion in the neoliberal framework of governance. It highlights what is at stake for disability futures in the context of austerity in the Global South.     

A Pilot Study Evaluating Students' Interest in International Social Work Education

International social work (ISW) has gained traction across the USA with a number of schools taking the lead in promoting the values of social work through exchange programs, service learning, and volunteerism. The internalization of campus through the proactive action of institutions to incorporate global perspectives into teaching, learning, and research in order to build intercultural competence among students, faculty, and staff has received little attention. This paper assesses the level of interest of social work students at a large urban university in the southwestern USA in embracing ISW and how they conceptualized their learning needs. Using a self-administered web-based survey offered to a total of 1,500 social work students with 18% respondent rate, the research determined through a chi-square test that students in Bachelor of Social Work, Master of Social Work, and PhD programs had a significant difference in preferences in areas of interests (χ² = 153, p ≤ 0.000). Overall, students demonstrated interest in direct practice (74.3%) and community and administrative practice (16.6%). Students also differed in their level of interest in participating in international exchange programs (χ² = 9.6, p = 0.047). Discussions address specific and unique interests categorized broadly as ‘globalized social worker,’ ‘humanitarian social worker,’ and ‘policy social worker,’ each of which requires specific skillsets and advanced behavior skills.     

To Regulate Or Not To Regulate? Early Evidence on the Means Used Around the World to Promote Gender Diversity in the Boardroom

Despite the growing public concern in recent years about the place of women in business, gender diversity in corporate governance has made little progress. As a consequence, the issue has captured the worldwide attention of policymakers. Several countries are currently adopting or considering the adoption of laws or regulations to promote gender diversity on corporate boards. The purpose of this paper is to compare the effectiveness of using legislative or regulatory means to increase female representation instead of allowing firms to voluntarily fix their own non‐legally binding targets. We find that the relation between gender diversity and performance is positive in countries using the voluntary approach while it is negative in countries using the regulatory approach. We conclude that public policy aimed at increasing the number of women on corporate boards should be introduced gradually and voluntarily rather than quickly and coercively to avoid sub‐optimal board composition.     

基于人力资本竞优结构的“团队-作业对象”匹配决策模型

针对具有相同职称、学历、年龄、性别等人力资本结构的团队在物资资本投入相同的情况下绩效有别的现象,提出团队人力资本竞优结构的概念、测量模型及团队与作业对象的匹配决策方法.团队人力资本竞优结构能够从单项指标优势度和多指标强弱结构效应两方面体现优势.以团队为整体,从最大程度认可团队价值出发,基于目标规划导引模型,构建团队人力资本竞优结构测量方法,揭示团队人力资本内质差异及其优势特征.在匹配决策中,将显性结构与隐性结构相结合,显性结构作为是否胜任的判据;以隐性的竞优结构相似度为切入点,构建“团队-作业对象”多目标多指标匹配优化模型,实现团队尽其才、资源尽其用的团队指派.通过算例,证明了方法的有效性和可行性.     

Kalman filter-based modelling and forecasting of stochastic volatility with threshold

We propose a parametric nonlinear time-series model, namely the Autoregressive-Stochastic volatility with threshold (AR-SVT) model with mean equation for forecasting level and volatility. Methodology for estimation of parameters of this model is developed by first obtaining recursive Kalman filter time-update equation and then employing the unrestricted quasi-maximum likelihood method. Furthermore, optimal one-step and two-step-ahead out-of-sample forecasts formulae along with forecast error variances are derived analytically by recursive use of conditional expectation and variance. As an illustration, volatile all-India monthly spices export during the period January 2006 to January 2012 is considered. Entire data analysis is carried out using EViews and matrix laboratory (MATLAB) software packages. The AR-SVT model is fitted and interval forecasts for 10 hold-out data points are obtained. Superiority of this model for describing and forecasting over other competing models for volatility, namely AR-Generalized autoregressive conditional heteroscedastic, AR-Exponential GARCH, AR-Threshold GARCH, and AR-Stochastic volatility models is shown for the data under consideration. Finally, for the AR-SVT model, optimal out-of-sample forecasts along with forecasts of one-step-ahead variances are obtained.     

Optimal and Robust Designs for Estimating the Concentration Curve and the AUC

The problem of interest is to estimate the concentration curve and the area under the curve (AUC) by estimating the parameters of a linear regression model with an autocorrelated error process. We introduce a simple linear unbiased estimator of the concentration curve and the AUC. We show that this estimator constructed from a sampling design generated by an appropriate density is asymptotically optimal in the sense that it has exactly the same asymptotic performance as the best linear unbiased estimator. Moreover, we prove that the optimal design is robust with respect to a minimax criterion. When repeated observations are available, this estimator is consistent and has an asymptotic normal distribution. Finally, a simulated annealing algorithm is applied to a pharmacokinetic model with correlated errors.