元认知与大学英语网络自主学习

目前我们汉译英的课堂教学模式过于简单且效率低下,本文提出了一种针对低学业成就者的、基于学习策略培训的汉译英SB I教学模式,从汉语语义结构分析、英语句子结构定型、英语词汇选择以及检查核对等多方面尝试将汉译英学习策略的培训渗透到汉译英的课堂教学活动中,以期提高这些学习者的汉译英技能,帮助他们掌握必要的语言学习策略,培养他们的自主学习能力,改善课堂教学效果。     

金融资产收益跳跃行为的微观机制

文章发展了一个均衡模型,从微观机理角度解释了为什么资产价格会发生不频繁的跳跃行为.在该模型中,投资者学习不可直接观测的、真实的经济系统状态并为此支付成本的行为诱发了资产价格的跳跃行为.而投资者是否选择学习的行为则取决于投资者的偏好参数和收入的条件波动率.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

高等农业职业教育《淡水养殖水化学》开展研究性学习的探索

国际 2 1世纪教育委员会的报告《教育———财富蕴藏其中》中提出面对未来社会的发展的 4种基本要求———学会认知、学会做事、学会共处、学会生存。这说明 ,在现代教育中 ,必须以学生发展为中心 ,开展研究性学习。我国实施的研究性学习就是改变我国传统的以教师为中心的教学模式 ,突出学生在学习中的主导地位。从贯彻素质教育的宗旨出发 ,在学科教学中渗透研究性学习 ,是培养学生综合能力的一种尝试和实践。     

Facility Location with Dynamic Distance Functions

Facility location problems have always been studied with theassumption that the edge lengths in the network are static anddo not change over time. The underlying network could be used to model a city street networkfor emergency facility location/hospitals, or an electronic network for locating information centers. In any case, it is clear that due to trafficcongestion the traversal time on links changes with time. Very often, we have estimates as to how the edge lengths change over time, and our objective is to choose a set of locations (vertices) ascenters, such that at every time instant each vertex has a center close to it (clearly, the center close to a vertex may change over time). We also provide approximation algorithms as well as hardness results forthe K-center problem under this model. This is the first comprehensive study regarding approximation algorithmsfor facility location for good time-invariant solutions.     

聚焦中国英语课堂:影响学生参与讨论的因素—— 一次采用定性分析法进行本土化研究的尝试

通过课堂观察及课后的学生采访,本文采用定性研究法考察了决定英语课堂上中国学生讨论情况的因素。　　本文的主要发现是：（１） 中国文化推崇的谦虚美德明显地妨碍了学生们抒发己见;（２） 学生推理能力和英语表达能力之间的鸿沟是引起表达焦虑的主要原因;（３） 教师的角色左右学生讨论中表现。基于上述发现,本文认为,课堂学习由民族性格、教育体制、口语习得心理以及教师角色所决定。因此建议,今后要注意研究课堂学习和其他影响因素之间的关系     

Semiparametric estimation of plane similarities: application to fast computation of aeronautic loads

In the big data era, it is often needed to resolve the problem of parsimonious data representation. In this paper, the data under study are curves and the sparse representation is based on a semiparametric model. Indeed, we propose an original registration model for noisy curves. The model is built transforming an unknown function by plane similarities. We develop a statistical method that allows to estimate the parameters characterizing the plane similarities. The properties of the statistical procedure are studied. We show the convergence and the asymptotic normality of the estimators. Numerical simulations and a real-life aeronautic example illustrate and demonstrate the strength of our methodology.     

An Algorithm for Unconstrained Quadratically Penalized Convex Optimization

Estimators are often defined as the solutions to data dependent optimization problems. A common form of objective function (function to be optimized) that arises in statistical estimation is the sum of a convex function V and a quadratic complexity penalty. A standard paradigm for creating kernel-based estimators leads to such an optimization problem. This article describes an optimization algorithm designed for unconstrained optimization problems in which the objective function is the sum of a non negative convex function and a known quadratic penalty. The algorithm is described and compared with BFGS on some penalized logistic regression and penalized L ^3/2 regression problems.     

Measures of uniformity in experimental designs: A selective overview

ABSTRACT

Discrepancies are measures which are defined as the deviation between the empirical and the theoretical uniform distribution. In this way, discrepancy is a measure of uniformity which provides a way of construction a special kind of space filling designs, namely uniform designs. Several discrepancies have been proposed in recent literature. A brief, selective review of these measures including some construction algorithms are given in this paper. Furthermore, a critical discussion along with some comparisons is provided, as well.     

An improved comorbidity summary score for measuring disease burden and predicting mortality with applications to two national cohorts

Abstract

Research involving administrative healthcare data to study patient outcomes requires the investigator to account for the patient’s disease burden in order to reduce the potential for biased results. Here we develop a comorbidity summary score based on variable importance measures derived from several statistical and machine learning methods and show it has superior predictive performance to the Elixhauser and Charlson indices when used to predict 1-year, 5-year, and 10-year mortality. We used two large Veterans Administration cohorts to develop and validate the summary score and compared predictive performance using the area under ROC curve (AUC) and the Brier score.