On the simulation of the transient temperature field or some viscoelasticity problems by structural analysis program

An idea is presented to solve the parabolic differential equation by the hyperbolic differential equation. We can simulate and compute the transient temperature field problems by a structural analysis program. Using only a single structural analysis program, the users can compute both temperature and thermal stress distributions on the same finite element mesh. The method thus extends the application of the structural analysis programs which have been implemented widely. As an example, the transient temperature field problem of a square plate is computed. The result is consistent with the theoretical result. A similar method for simulating some viscoelasticity problems of Kelvin model is also presented.     

利用Garfield程序模拟Micromegas探测器增益和位置分辨特性

利用Garfield气体探测器模拟程序模拟了不同条件下Micromegas探测器的增益和位置分辨特性. 通过对模拟结果的分析, 得出提高探测器位置分辨和增益的有效途径. 该工作不仅可以优化气体探测器结构设计, 缩短实验周期, 而且还能极大程度的节约经费.     

基于圆环模型的速调管2.5维注波互作用程序

 在高导流系数的宽带速调管中，电子束径向及横向速度都会发生显著变化，运动电子与间隙电场之间的能量交换是非线性的互作用过程。为了能全面描述这些现象，基于圆环模型导出了相应的理论公式，并据此编写了用于速调管注波互作用分析的2.5维程序LSP。随后使用该程序针对一个实际的S波段宽带速调管做了详细计算，与1维程序相比，LSP的计算结果与实测值具有更好的一致性。     

现代数字物理教学连载⑿——一种围绕知识、能力与创新思维的教学方法

介绍在数字教学的模式下,如何去完成对学生的知识教育、能力教育和创新思维的教育,而知识、能力与创新思维是衡量教学质量的三个重要指标.     

通过计算机教育提高学生创新能力

本文从教学实践出发，从更新教育观念、创设新环境、推行问题式教学模式、发挥学生的主体性、训练思维方式和理论实际相结合六个方面阐述了在教学中如何对学生进行创新能力和创新精神的培养，为在基础教育中如何推行创新教育提供了新的思路。     

如何在高等数学教学中培养学生的创新思维

创新是当今的时代精神.创新能力的培养是实施素质教育的重要目标之一.高等数学作为高等教育的重点基础课程,在训练和培养学生创新能力方面具有重要地位.如何在高等数学教学过程中培养学生的创新思维,提高创新能力是我们高等数学教学改革的重要任务.文章通过对当前教育形势的分析以及创新思维的特点的思考,从教学理念、教学模式以及教学内容三个方面讨论了在高等数学教学过程中学生的创新思维的培养问题.     

A completely positive representation of 0–1 linear programs with joint probabilistic constraints

In this paper, we study 0–1 linear programs with joint probabilistic constraints. The constraint matrix vector rows are assumed to be independent, and the coefficients to be normally distributed. Our main results show that this non-convex problem can be approximated by a convex completely positive problem. Moreover, we show that the optimal values of the latter converge to the optimal values of the original problem. Examples randomly generated highlight the efficiency of our approach.     

Nonnegative Generalized Inverses and Interval Linear Programs

Connections between nonnegative generalized inverses and interval linear programs form the subject matter of this article. Characterizations of nonnegativity of the Moore–Penrose inverse and the group inverse are presented and their role in the study of a special class of optimization spaces, namely, Ben-Israel–Charnes spaces is brought out. The interplay between Ben-Israel–Charnes spaces and other notions of generalized inverse positivity are also studied.     

基于师范生创新能力培养的化学教学论实验课程教学研究*

依托“化学教学论实验”课程教学,在探究性学习理念指导下,通过师范生对主题实验在扎实、全面的文献梳理基础上,重点从仪器、药品及实验方案等维度进行创新性改进和设计活动,达成创新能力培养的教学目标。实践证明,发挥实验在化学学科教学中的重要价值,凸显教师主导和学生主体的教学模式,不仅有利于提升师范生对学习和教学的内涵理解,更有利于在真实参与的学习活动中培养和提高创新思维及能力。     

An Extension of Sums of Squares Relaxations to Polynomial Optimization Problems Over Symmetric Cones

This paper is based on a recent work by Kojima which extended sums of squares relaxations of polynomial optimization problems to polynomial semidefinite programs. Let and be a finite dimensional real vector space and a symmetric cone embedded in ; examples of and include a pair of the N-dimensional Euclidean space and its nonnegative orthant, a pair of the N-dimensional Euclidean space and N-dimensional second-order cones, and a pair of the space of m × m real symmetric (or complex Hermitian) matrices and the cone of their positive semidefinite matrices. Sums of squares relaxations are further extended to a polynomial optimization problem over , i.e., a minimization of a real valued polynomial a(x) in the n-dimensional real variable vector x over a compact feasible region , where b(x) denotes an - valued polynomial in x. It is shown under a certain moderate assumption on the -valued polynomial b(x) that optimal values of a sequence of sums of squares relaxations of the problem, which are converted into a sequence of semidefinite programs when they are numerically solved, converge to the optimal value of the problem. Research supported by Grant-in-Aid for Scientific Research on Priority Areas 16016234.