An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

论行业语境下高校校友资源的开发与利用

校友资源是高校最富饶的人才资源。本文试图在行业语境中，讨论高校发展与校友资源之间的辩证关系，并以此为基础，提出开发和利用高校校友资源的对策。     

试论民族地区数字图书馆建设的意义

数字图书馆是信息时代的产物,是图书馆发展历史上的一次深刻革命。数字图书馆不仅代表着图书馆发展的最新方向,而且为文献信息的开发与利用提供了新的机遇。民族地区的数字图书馆建设是民族地区全面建设小康社会、适应信息社会以及进一步开发民族文化资源的迫切需要。     

再谈西平亭与西平郡城

该文对西汉元鼎年间所设的西平亭的性质、设立时间、位置及其与东汉建安年间所设的西平郡的位置和相关方位做了简要考证,针对不同意见,提出了西平亭与西平郡在方位上有凭依关系,位置在西宁明清城恒之内的学术观点。     

关于宗教与社会主义社会相适应的思考

引导宗教与社会主义社会相适应是我国宗教工作的出发点和落脚点,是我国宗教工作方针的重要组成部分。本文从宗教与其所处的社会相适应是宗教历史和发展的必然、引导宗教与社会主义社会相适应原则的确立是马克思主义宗教观的丰富和发展、宗教从其自身条件来看是能够与社会主义社会相适应的以及探索宗教与社会主义社会相适应的途径和方法四个方面阐述了宗教与社会主义社会相适应这一论断的科学内涵和现实意义。     

明清时期瑶族地区的学校教育

明清时期,瑶族地区的学校教育得到了前所未有的发展,封建统治阶级在瑶族地区大力兴办儒学、社学、义学,推动了瑶族子弟向学之风的形成,培养了一批瑶族知识分子。但受瑶族社会经济发展不平衡性的影响,瑶族地区教育发展的不平衡性亦十分突出,并一直影响至今。     

图书馆的知识管理与可持续发展策略

新世纪图书馆具有与过去迥然不同的特征,在知识经济的背景下,图书馆要拓展发展空间,实现可持续发展,就必须与时俱进,积极实施知识管理,不断提高知识创新和知识服务能力。本文从管理观念创新、管理模式创新、管理体制创新、管理内容创新四个方面论述了知识经济时代图书馆管理创新的重要性。并阐述了图书馆可持续发展的重要性及实现图书馆可持续发展的具体措施。     

Understanding Estimators of Treatment Effects in Regression Discontinuity Designs

In this paper, we propose two new estimators of treatment effects in regression discontinuity designs. These estimators can aid understanding of the existing estimators such as the local polynomial estimator and the partially linear estimator. The first estimator is the partially polynomial estimator which extends the partially linear estimator by further incorporating derivative differences of the conditional mean of the outcome on the two sides of the discontinuity point. This estimator is related to the local polynomial estimator by a relocalization effect. Unlike the partially linear estimator, this estimator can achieve the optimal rate of convergence even under broader regularity conditions. The second estimator is an instrumental variable estimator in the fuzzy design. This estimator will reduce to the local polynomial estimator if higher order endogeneities are neglected. We study the asymptotic properties of these two estimators and conduct simulation studies to confirm the theoretical analysis.     

Computing the log concave NPMLE for interval censored data

In analyzing interval censored data, a non-parametric estimator is often desired due to difficulties in assessing model fits. Because of this, the non-parametric maximum likelihood estimator (NPMLE) is often the default estimator. However, the estimates for values of interest of the survival function, such as the quantiles, have very large standard errors due to the jagged form of the estimator. By forcing the estimator to be constrained to the class of log concave functions, the estimator is ensured to have a smooth survival estimate which has much better operating characteristics than the unconstrained NPMLE, without needing to specify a parametric family or smoothing parameter. In this paper, we first prove that the likelihood can be maximized under a finite set of parameters under mild conditions, although the log likelihood function is not strictly concave. We then present an efficient algorithm for computing a local maximum of the likelihood function. Using our fast new algorithm, we present evidence from simulated current status data suggesting that the rate of convergence of the log-concave estimator is faster (between \(n^{2/5}\) and \(n^{1/2}\)) than the unconstrained NPMLE (between \(n^{1/3}\) and \(n^{1/2}\)).