基于并行群体模拟退火算法的蛋白质折叠研究

蛋白质折叠研究对于揭示蛋白结构和功能关系,进而了解相关疾病的致病机理意义重大。蛋白质折叠已被证明是 NP-完全问题。本文针对蛋白质折叠研究中的能量最小化问题,提出了一种新的并行群体模拟退火算法（Parallel Group Simulated Annealing,PGSA）及其改进型算法（PGSA_1/K)。该算法使用了降温因子加速收敛精度,并采用 MPI 消息传递并行编程技术加快蛋白质结构空间搜索以及能量最小化寻找速度。以 Met_Enkephalin 蛋白为对象的计算机模拟仿真结果表明,我们提出的算法及其改进型有很好的扩展性,可以高效搜索蛋白结构空间,从而找到相关蛋白的最小能量结构。     

淮北平原主要农作物涝渍灾害 损失评估研究

针对淮北平原除涝减灾综合治理与规划中缺乏主要农作物受涝损失调查与评估基础资料的实 际问题,于2010年9月初区域降雨成灾之际,对受涝区进行主要农作物受涝经济损失调查。依据实 地调研成果,通过综合统计分析推求了不同耕地类型不同暴雨强度下的受涝损失率,在此基础上实现 了对淮北平原受涝经济损失的合理评估。     

大采高综放开采煤岩损伤统计力学模型

根据特厚煤层大采高综放开采煤壁前方支承压力的分布特征,从煤岩内部缺陷的随机性分布特征出发,基于反映煤岩内部缺陷的微元强度服从韦布分布的概念,建立了支承压力作用下煤岩的损伤统计力学模型,确定了特厚煤层大采高综放面在煤壁片帮不影响生产的情况下的合理采高,并分析了特厚煤层大采高综放面合理采高与煤壁片帮程度、煤层内摩擦角、煤层...     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

A Comparative study on multiobjective reliable and robust optimization for crashworthiness design of vehicle structure

Design optimization without considering uncertainties of system variables and parameters can be problematic in real life. In order to take into account the effect of uncertainties, reliable and robust design schemes have proven effective, but limited studies have been reported to compare their difference in a multiobjective framework. This paper takes a typical vehicle structure subject to offset frontal crashing scenario as an example to compare reliable and robust designs with their deterministic counterpart. The thicknesses of some key components of vehicle frontal structures were selected as design variables, the vehicle weight and energy absorption as the objectives, deceleration and firewall intrusion as the constraints. The deterministic multiobjective optimization problem was first solved by adopting Design of Experimental (DOE), metamodels and Non-dominated Sorting Genetic Algorithm II (NSGA-II). Take into account the uncertainties, a Monte Carlo Simulation (MCS) is adopted to generate random distributions of the objective and constraint functions for each design. For the reliability-based optimization the desired reliabilities of 90 %, 95 % and 99 % are considered, respectively. For the robustness-based optimization, two different formulation strategies are adopted. The optimization showed that the reliable and robust Pareto fronts are shifted away from their deterministic counterpart due to uncertainties. The different Pareto fronts yielded from the deterministic, reliable and robust designs are compared to provide some quantitative insights into how to apply these different design schemes for resolving uncertainty problems. It is shown that, compared with the baseline design, the optimizations enhance the crashworthiness of vehicle, though more conservative solutions could have been generated from the reliable and robust optimizations.     

Tripartite entanglement of a spin star model with Dzialoshinski–Moriya interaction

The effect of Dzialoshinski–Moriya (DM) interaction on the tripartite thermal entanglement of a spin-star model with four spins has been analyzed by an entanglement measure of the tripartite negativity. Our results imply that the tripartite thermal entanglement can be established among the three surrounding parties which do not interact with each other but interact with the central party independently. From the results, we find that the strong DM interaction can enhance the tripartite thermal entanglement while the high temperature can shrink it. The effect of the inhomogeneous coupling on the tripartite thermal entanglement is also discussed.     

基于用户查询日志的命名实体挖掘

针对大规模查询日志中丰富的命名实体的挖掘是数据挖掘领域中的重要研究课题。已有的研究工作提出了一种基于种子实体的抽取框架,利用实体间的分布相似度进行挖掘。然而该工作只有当种子实体仅属于单个语义类别时才能取得好的结果,实际上命名实体往往可能从属于多个类别。该文通过引入一个弱指导话题模型,利用少量的人工指导信息,很好地解决了实体的类别模糊性,提高了挖掘的有效性。实验表明该文提出的方法在实体挖掘性能上显著优于已有的方法。     

Web信息抽取及知识表示系统的研究与实现

研究了从数据密集型Web页面中自动提取结构化数据并形成知识表示系统的问题。基于知识数据库实现动态页面获取,进行预处理后转换为XML文档,采用基于PAT-array的模式发现算法自动发现重复模式,结合基于本体的关键词库自动识别页面数据显示结构模型,利用XML的对象-关系映射技术将数据存入知识数据库,由此实现Web数据自动抽取。同时,利用知识数据库已有知识从互联网抽取新知识,达到知识数据库的自扩展。以交通信息自动抽取及混合交通出行方案生成与表示系统进行的实验表明该系统具有高抽取准确率和良好的适应性。     

PBB/VPLS双栈技术及其效率分析

PBB技术和VPLS技术是城域以太网技术发展的两个方向,PBB/VPLS双栈技术通过PBB与VPLS报文之间的互相转换实现了网络融合。文章从VPN中主机之间互相学习MAC地址的角度研究了PBB/VPLS双栈网络的效率;通过理论上的分析计算,得出了当所有主机获取其他主机MAC地址之后ARP报文被公网设备转发的次数和;对组网方式进行了研究,旨在减少公网设备转发ARP报文的次数,提升双栈网络的效率。     

基于直接连接的分布式数据库查询优化实现方法研究

首先对分布式数据库查询执行代价模型进行分析,然后对直接连接中的连接运算的方法、连接关系的传输方法和执行场地等问题进行研究,并计算所有评估方法的执行代价,从中选择出最小执行代价的执行方法,最终确定了执行的场地、连接的方法和传输方法.