开元棋牌

报告人：徐洪坤教授（台湾中山大学西湾讲座教授，南非科开元棋牌院士）题目: Convex Relaxations for Recovering Sparse Signals with Noise时间：2011年9月1日(星期四)下午4：30—5：30地点：数学系致远楼107欢迎各位参加

报告人：Prof. Tzon-Tzer Lu（National Sun Yat-sen University）题目：Convergent Behaviors of Trefftz Method on Laplace BVPs with Singularities时间：2011年7月14日，星期四下午3：30—4：30地点：数学系致远楼102欢迎各位参加

报告人：Prof. Lee Tsung-Lin（National Sun Yat-sen University）题目：TBA时间：2011年7月14日，星期四下午4：30—5：30地点：数学系致远楼102欢迎各位参加

题 目：Approximation Properties for Group C*-algebras报告人：阮忠进教授University of Illinois, USA浙江大学求是特聘教授时 间：7月17日9:00-10:00, Part I10:30-11:30, Part II地 点：致远楼102欢迎广大师生参加！

报告人：郑惠恒教授（帝国理工）题目：Recent Advance in Utility Optimazation Protfilio时间：2011年7月11日，星期一下午2：30—3：30地点：数学系致远楼102欢迎各位参加

报告人： Professor Li Deli(加拿大Lakehead大学数学科学系教授）报告(一)题目：New Version of Some ClassicalStochastic Inequalities(一些经典随机不等式的新形式)时间：2011年6月17日（周五）下午 3:30报告(二)题目：A Strong Law of Large Numbersfor Weighted U-Statistics(加权U统计量的强大数定律)时间：2011年6月20日（周一）下午 3:30地点：数学系致远楼 107欢迎广大师生前来参

Component-based software development has been well recognized as an effective methodology in software engineering. Components constraints play critical role to high quality software product development. In this presentation, a systematic approach for component-based software architectural modeling, constraints specifica- tion and consistency verification is introduced. In this approach, computational tree logic and Petri Nets are used as the underlying formalisms to describe software constraints and design compositions, respectively. System-wide constraints are decomposed to component constraints. The consistency between system-wide constraints and component constraints are verified purely on Petri net models after replacing black-box components with equivalent Petri nets while preserving component properties specified by the constraints.

Suppose an agent has positions of various assets. As time goes by, the corresponding total wealth varies. Since the agent would like to keep the positions of the different assests for various different time periods, the position process will not be adapted. A natural question is how one can measure the dynamic risk of such kind of position process? It turns out that the theory of backward stochastic Volterra integral equations (BSVIEs, for short) presents a suitable framework for dynamic risk measures. In this talk, we will briefly present the relevant results on BSVIEs and construct a class of dynamic risk measures.