新常态下高校形势与政策课程模式改革探析

在新常态的话语背景下,传统高校形势与政策课程模式越来越不适应现代需求,与教学对象的新特点存在若干不协调、不衔接、不到位之处。为适应新常态,改进高校形势与政策课程模式,提升实效性,文章从宏观层面分析新常态下高校形势与政策课程目标及现实困境,认为需要从优化教学力量构成、改进理论教学体系、拓展实践教学平台及构建管理保障机制等方面做出改进。     

中国法治政府的演化博弈模型构建

演化博弈论在中国法治政府研究中具有很好的适用性,可以据此构建“复制动态”的中国法治政府的演化博弈模型,证明“内生演化”的法治能够从根本上解决政府“权力悖论”。中国法治政府建设需要围绕约束规范公权力的主题,确立互动平衡精神和采取渐进主义策略,以改进转型中国的法治秩序。     

论旅游民生：概念界定与解析

当代中国已站在旅游社会门口, 全民旅游时代正在到来, 旅游民生需求日益急迫。 学术界尚未对旅游民生概念进行科学界定, 只有搞清楚何为旅游民生, 廓清其内涵和外延, 才能对相关政策的制定、 实施及旅游社会建设提供理论指导。 基于当前社会背景, 从词汇本意、 概念发展、 现实含义等角度, 层层辨析民生、 旅游、 旅游民生各语词, 从而界定出旅游民生概念, 进一步分析了现阶段我国旅游民生的内涵, 认为旅游民生同样具有生存、 社会融入、 发展的本质属性, 指出促进旅游民生改善是政府职责所在。     

双电机驱动自同步振动磨动力响应研究

以双电机驱动自同步振动磨为研究对象,对其进行简化处理,建立力学模型。通过对其施加X,y方向的简谐激 振力,建立无阻尼系统强迫振动和有阻尼系统强迫振动的数学模型,在此基础上,确定Rayleigh阻尼的常数α和β,利用 有限元ANSYS软件进行瞬态动力学分析,研究其在动载荷作用下的变形情况。研究结果表明：在工况频率16 Hz下,节 点运动轨迹更接近圆形,距理想粉碎效果的圆形轨迹较近,粉碎效果较好,进入稳定期的时间较快;在共振频率42 Hz 下,节点轨迹振幅更大,进入稳定期较慢,阻尼对振动的衰减作用较强;不同阻尼比对振动的衰减作用成正比关系。因 此,可以通过控制阻尼比等参数获得更有利的研磨效果,提高研磨效率。     

基于环境传感器和穿戴式传感器的行为异常检测

针对独居老人频繁出现行为异常的情况,提出了基于热释电红外传感器和穿戴式传感器的老人行为异常检测系 统。设计了行为异常检测的硬件环境,介绍了红外传感器和穿戴式传感器的工作原理,提出了依据重力加速度所在轴向 检测老人躺下位置是否发生异常的方法,并融合了红外传感器和穿戴式传感器的信息对躺下位置异常进行检测。在1 居室的家庭环境中对位置异常检测的方法进行验证,通过实验的方法验证了算法的可行性,并确定了检测躺下状态的阈 值。系统能有效实现对独居老人是否发生躺下位置异常进行检测。     

基于灰色系统的小型精密机床热误差模型

为减少热误差对数控机床加工精度的影响,文章利用灰色系统研究热误差建模。初步分析机床热源后,应用灰 色关联度分析结合模糊分类方法优化得到13组关键温度测点,结合小型精密五轴机床处于实际加工状态时的实验数 据,应用GM(I,N)灰色结构进行建模。将实际数据与拟合数据进行对比分析,结果表明此灰色系统模型具有计算方法 成熟、鲁棒性强的特点,适用于机床热误差研究。     

Empirical Likelihood for the Additive Hazards Model with Current Status Data

We investigate empirical likelihood for the additive hazards model with current status data. An empirical log-likelihood ratio for a vector or subvector of regression parameters is defined and its limiting distribution is shown to be a standard chi-squared distribution. The proposed inference procedure enables us to make empirical likelihood-based inference for the regression parameters. Finite sample performance of the proposed method is assessed in simulation studies to compare with that of a normal approximation method, it shows that the empirical likelihood method provides more accurate inference than the normal approximation method. A real data example is used for illustration.     

Testing Serial Correlation in Partially Linear Additive Errors-in-variables Models

This article considers testing serial correlation in partially linear additive errors-in-variables model. Based on the empirical likelihood based approach, a test statistic was proposed, and it was shown to follow asymptotically a chi-square distribution under the null hypothesis of no serial correlation. Finally, some simulation studies are conducted to illustrate the performance of the proposed method.     

Uncertainty Analysis for Functional Computer Output: A Simulation Study in Inverse Problems

Computer models with functional output are omnipresent throughout science and engineering. Most often the computer model is treated as a black-box and information about the underlying mathematical model is not exploited in statistical analyses. Consequently, general-purpose bases such as wavelets are typically used to describe the main characteristics of the functional output. In this article we advocate for using information about the underlying mathematical model in order to choose a better basis for the functional output. To validate this choice, a simulation study is presented in the context of uncertainty analysis for a computer model from inverse Sturm-Liouville problems.     

Robust Smoothed Rank Estimation Methods for Accelerated Failure Time Model Allowing Clusters

Smoothed Gehan rank estimation methods are widely used in accelerated failure time (AFT) models with/without clusters. However, most methods are sensitive to outliers in the covariates. In order to solve this problem, we propose robust approaches based on the smoothed Gehan rank estimation methods for the AFT model, allowing for clusters by employing two different weight functions. Simulation studies show that the proposed methods outperform existing smoothed rank estimation methods regarding their biases and standard deviations when there are outliers in the covariates. The proposed methods are also applied to a real dataset from the “Major cardiovascular interventions” study.