一元整系数多项式一个结论的推广应用

将一元整系数多项式有理根的一个结论在多元多项式上进行了推广,从而得到多元多项式因式分解的一种方法。     

高校财务指标体系的建立及其综合评价

讨论了财务指标作为高校综合评价的可能性及高校财务管理的内涵,在此基础上建立了科学、系统、可操作的财务评价指标体系,确定了各项财务指标的权重.     

合成孔径系统光束的大气传输

利用光束的合成孔径系统,通过控制子孔径系统发射光束的相位,可以实现光束的快速瞄准、跟踪及合成.本文在已开展的真空中合成孔径系统光束控制研究工作的基础上,进一步揭示了光束合成孔径系统可以有效地消除大气湍流对光束传输的影响,给出了数值模拟计算结果和三维图形演示.     

用模糊数学理论对汉诗英译本进行量化评估的初步构想

以模糊数学的理论为基础,初步探索用模糊综合评判定量评价汉诗英译本的基本方法,并对其中的关键步骤-判据集(或称评判因素)的设定和隶属度的确定进行了进一步的讨论.该方法虽然仍离不开人的主观参与,但它比纯粹的定性分析更为科学、系统.     

Model Diagnostics for Remote Access Regression Servers

To protect public-use microdata, one approach is not to allow users access to the microdata. Instead, users submit analyses to a remote computer that reports back basic output from the fitted model, such as coefficients and standard errors. To be most useful, this remote server also should provide some way for users to check the fit of their models, without disclosing actual data values. This paper discusses regression diagnostics for remote servers. The proposal is to release synthetic diagnostics—i.e. simulated values of residuals and dependent and independent variables–constructed to mimic the relationships among the real-data residuals and independent variables. Using simulations, it is shown that the proposed synthetic diagnostics can reveal model inadequacies without substantial increase in the risk of disclosures. This approach also can be used to develop remote server diagnostics for generalized linear models.     

An alternative to model selection in ordinary regression

The weaknesses of established model selection procedures based on hypothesis testing and similar criteria are discussed and an alternative based on synthetic (composite) estimation is proposed. It is developed for the problem of prediction in ordinary regression and its properties are explored by simulations for the simple regression. Extensions to a general setting are described and an example with multiple regression is analysed. Arguments are presented against using a selected model for any inferences.     

欧美合成生物学应用的风险治理经验及启示

合成生物学技术的应用与发展为基础生命科学研究、人类健康、环境保护和经济增长做出了重要贡献。随着合成生物学变得更便宜、更容易使用和更容易获得,亟需建立行之有效的风险治理体系以防控其潜在的伦理道德、生物安全和生物安保风险,促进技术健康发展。通过观照欧美国家风险治理模式,建议预防风险与促进创新并重、伦理治理与法律规制“双管齐下”,以期为我国合成生物学监管提供有益经验、减少风险和控制利益冲突,促进我国合成生物学创新,规范合成生物学研究和生产。     

Simultaneous edit-imputation and disclosure limitation for business establishment data

Business establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.     

Generating synthetic data to produce public-use microdata for small geographic areas based on complex sample survey data with application to the National Health Interview Survey

Small area statistics obtained from sample survey data provide a critical source of information used to study health, economic, and sociological trends. However, most large-scale sample surveys are not designed for the purpose of producing small area statistics. Moreover, data disseminators are prevented from releasing public-use microdata for small geographic areas for disclosure reasons; thus, limiting the utility of the data they collect. This research evaluates a synthetic data method, intended for data disseminators, for releasing public-use microdata for small geographic areas based on complex sample survey data. The method replaces all observed survey values with synthetic (or imputed) values generated from a hierarchical Bayesian model that explicitly accounts for complex sample design features, including stratification, clustering, and sampling weights. The method is applied to restricted microdata from the National Health Interview Survey and synthetic data are generated for both sampled and non-sampled small areas. The analytic validity of the resulting small area inferences is assessed by direct comparison with the actual data, a simulation study, and a cross-validation study.