用模糊聚类分析法建立神经网络岩土本构模型

针对岩土类材料本构关系复杂的情况 ,采用BP网络建立了其本构模型 ,并从神经网络隐层的本质特征出发 ,对样本数据 (应力和应变信息 )采用模糊聚类分析法进行特征抽取 ,以确定隐层节点数目 .算例结果表明 ,该方法是可行的 ,并具有较直观的物理意义 ,可为样本的选取提供指导作用 .     

基于Cache网络数据的数据缓存技术研究

通过对目前数据缓存技术的分析和研究，提出和设计了一种针对于高速局域网分布式数据缓存系统，即基于Cache网的数据缓存系统。旨在进一步提高数据缓存系统的性能，通过减少网络传输时间，均衡网络负载，实现提高客户机／服务器网络系统的检索效率。其主要思想是在网络的各个节点上建立数据缓存区，并实现对这些缓存区统一调配和管理。文中对其缓存性能进行了分析，并和其它缓存系统进行了比较，从而论证了该缓存系统的有效性。     

彩色纹影技术在复杂流场显示中的应用

该文论述了两种彩色滤光片/刀口法纹影技术在复杂流场显示中的应用。用该方法获得了底部排气弹超音速风洞试验的彩色纹影图片,并按照纹影技术理论对结果进行了分析和计算。     

数字化文献——《中国期刊全文数据库（CJFD）》

系统地介绍了《中国期刊全文数据库(CArt)》的特点、应用、服务方式以及检索界面、检索使用方法和全文浏览器的下栽安装，旨在使更多的人了解CJFD，掌握CJFD的使用方法。提高CJFD的利用率。     

A single positively selected West Nile viral mutation confers increased virogenesis in American crows

West Nile virus (WNV), first recognized in North America in 1999, has been responsible for the largest arboviral epiornitic and epidemic of human encephalitis in recorded history. Despite the well-described epidemiological patterns of WNV in North America, the basis for the emergence of WNV-associated avian pathology, particularly in the American crow (AMCR) sentinel species, and the large scale of the North American epidemic and epiornitic is uncertain. We report here that the introduction of a T249P amino acid substitution in the NS3 helicase (found in North American WNV) in a low-virulence strain was sufficient to generate a phenotype highly virulent to AMCRs. Furthermore, comparative sequence analyses of full-length WNV genomes demonstrated that the same site (NS3-249) was subject to adaptive evolution. These phenotypic and evolutionary results provide compelling evidence for the positive selection of a mutation encoding increased viremia potential and virulence in the AMCR sentinel bird species.     

A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase

Grain weight is one of the most important components of grain yield and is controlled by quantitative trait loci (QTLs) derived from natural variations in crops. However, the molecular roles of QTLs in the regulation of grain weight have not been fully elucidated. Here, we report the cloning and characterization of GW2, a new QTL that controls rice grain width and weight. Our data show that GW2 encodes a previously unknown RING-type protein with E3 ubiquitin ligase activity, which is known to function in the degradation by the ubiquitin-proteasome pathway. Loss of GW2 function increased cell numbers, resulting in a larger (wider) spikelet hull, and it accelerated the grain milk filling rate, resulting in enhanced grain width, weight and yield. Our results suggest that GW2 negatively regulates cell division by targeting its substrate(s) to proteasomes for regulated proteolysis. The functional characterization of GW2 provides insight into the mechanism of seed development and is a potential tool for improving grain yield in crops.     

非最小相位系统传递函数的演化模型降阶

针对非最小相位系统传递函数的模型降阶工作,通过对频域误差平方和加权的形式,提出了同时考虑频域幅值与相位因素的多目标参数优化指标。针对传统的求解多目标优化方法的不足,提出应用演化算法对此复杂的目标函数进行优化的策略。计算实例说明,使用演化优化方法可以获得幅值与相位特性均较好的降阶模型。     

基于构件建造信息系统的自适应体系结构

本文基于Ｈ．Ａ．Ｓｉｍｏｎ的决策认知过程分析,提出了一种用构件组装方式产生适应不同需求的信息系统。为了提高研制效率,给出了信息系统及其构件的形式化描述。在软件集成块 Ｓｏｆｔｗａｒｅ－ＩＣ的思路影响下提出了一种系统构成的自组织方法。     

基于伍德沃德-劳森抽样方法的阵列平顶波束综合

为获得高增益和强方向性,阵列天线应运而生,波束赋形技术在降低阵列副瓣电平、扩大阵列角度覆盖范围、抑制干扰等方面具有重要意义。其中,具有平顶形状波束的天线可辐射具有相同增益的波束,实现宽角度覆盖,且伍德沃德-劳森抽样具有方法简单、抽样点少、运算速度快的优势。因此,运用伍德沃德-劳森抽样方法对均匀直线阵列进行平顶波束赋形。通过计算抽样点数和抽样点位置,得到激励系数,确定阵元位置,计算出激励电流,从而求得各单元的电流分布,计算出阵列的方向图函数,利用MATLAB编程绘制方向图,并分析其基本特性,同时用控制变量法分析不同参数变化对方向图基本特性的影响。研究结果表明：综合的线阵单元数越多,抽样点就越多,综合得到的方向图就越接近预期,综合后方向图主瓣范围内的波纹起伏越小,副瓣电平越低。此外,定向辐射的平顶波束赋形天线在点对多点的无线通信中发挥着重要作用,也可以应用在车载和机载防撞天线、自动驾驶和飞行器等安全控制中心的核心组件中,市场前景广阔。     

A new adaptive state space construction method for the mobile robot navigation

In order to solve the combinative explosion problems in a continuous and high dimensional state space, a function approximation approach is usually used to represent the state space. The normalized radial basis function （NRBF） was adopted as the local function approximator and a kind of adaptive state space construction strategy based on the NRBF （ASC-NRBF） was proposed, which enables the system to allocate appropriate number and size of the basis functions automatically. Combined with the reinforce- ment learning method, the proposed ASC-NRBF method was applied to the robot navigation problem. Simulation results illustrate the performance of the proposed method.