Thermal Bending Analysis of Doubly Curved Composite Laminated Shell Panels with General Boundary Conditions and Laminations

Thermal bending analysis of doubly curved laminated shell panels with general boundary conditions and laminations is presented. The equations of equilibrium are derived in the form of two coupled sets of ordinary differential equations based on a general shell theory and solved through the state-space approach in a repeated manner. It is depicted that the results of the present method are in great agreement with analytical solutions. Cylindrical shell panels with general boundary conditions and laminations, where no analytical solution is available, are solved. It is found that the present method exhibits a high convergence rate as well as presenting accurate results in all cases.     

以IBAC为核心处理洗浴废水的试验研究

根据洗浴废水的水质特征,采用原水→混凝沉淀-过滤→固定化生物活性炭(Immobilized Biological Activated Carbon,IBAC)→微滤膜(MF)→UV消毒→出水的工艺流程.混凝沉淀-过滤物化预处理单元可以有效地减少洗浴废水中的各类污染物.IBAC生化处理单元,实现有机污染物、LAS、浴臭等有效去除,是保证出水合格的根本措施.微滤膜发挥物理截留作用、UV消毒杀死细菌和总大肠菌群.出水水质达到＜城市供水水质标准＞(CJ/T 206-2005).     

Optimal H∞ general distance problem with degree constraint

In this paper the optimal H_∞, general distance problem, for continuous-time systems, with a prescribed degree on the solution is studied. The approach is based on designing the Hankel singular values using an imbedding idea. The problem is first imbedded into another problem with desirable characteristics on the Hankel singular values, then the solution to the original problem is retracted via a compression. The result is applicable to both the one-block and the four-block problems. A special case is given for illustration.     

Building a user model implicitly from a cooperative advisory dialog

This paper reviews existing methods for building user models to support adaptive, interactive systems, identifies sigificant problems with these approaches, and describes a new method for implicitly acquiring user models from an ongoing user-system dialog. Existing explicit user model acquisition methods, such as user edited models or model building dialogs put additional burden on the user and introduce artificial model acquisition dialogs. Hand coding stereotypes, another explicit acquisition method, is a tedious and error-prone process. On the other hand, implicit acquisition techniques such as computing presuppositions or entailments either draw too few inferences to be generally useful, or too many to be trusted.In contrast, this paper describes GUMAC, a General User Model Acquisition Component that uses heuristic rules to make default inferences about users' beliefs from their interaction with an advisory expert system. These rules are based on features of human action and conversation that constrain people's behavior and establish expectations about their knowledge. The application of these rules is illustrated with two examples of extended dialogs between users and an investment advisory system. During the course of these conversations, GUMAC is able to acquire an extensive model of the users' beliefs about the aspects of the domain considered in the dialog. These models, in turn, provide the sort of information needed by an explanation generator to tailor explanations the advisory system gives to its users.     

A comparison of backpropagation and general regression neural networks in quantative trace metal analysis using anodic stripping voltammetry and cybernetic instrumentation

A comparison is made between backpropagation and general regression neural networks for the prediction of parts per billion lead concentration when used to process data obtained from digested curry powder by the electrochemical analysis method of differential pulse, anodic stripping at a thin film mercury electrode (TFME). Two data sets are used, one requiring the net to classify an unknown analytical data vector into one of a number of previously learnt concentrations, and one requiring the net to predict the probable concentration of an unknown sample by interpolation of the already learnt concentrations. For both of these data sets the general regression neural network is shown to train faster and to provide results superior to those obtained by backpropagation.     

山坡建厂与高台段的划分——荻港海螺水泥有限公司工程总体局与竖向设计

通过荻港海螺水泥有限公司(2×2500t/d)工程设计、建成投产的实践,阐述了水泥厂建在山坡上的厂址选择,总体规划布局,厂内道路最大坡度确定,高台段划分及边坡爆破,场地整平压实,护坡挡墙与厂房土建基础埋深等技术问题的处理方法,总结其设计成功的经验和不足之处,为同类型工厂总图布置提供借鉴.     

局域网服务器缓冲区容量的Petri网设计方法

本文在分析局域网服务器信息缓冲区、数据包接受和发送缓冲区的相互关系基础上提出一种新的局域网服务器缓冲区设计方法─—广义随机Ｐｅｔｒｉ网方法，并给出了局域网服务器信息缓冲区的广义随机Ｐｅｔｒｉ网模型。该设计方法理论完备、严谨实用，且不再局限于追求某一边界值（上限或下限），并且避免了排队理论处理多级服务的繁琐公式。最后本文用一例题说明了这种方法的应用。     

多目标模糊优选理论在水资源系统中的应用

开放的水资源系统分析理论应是水资源学与系统科学等多种学科的结合 ,介绍一种新兴而实用的水资源系统分析技术———半结构性决策系统模糊优选理论的基本原理及其应用。     

非织造保暖材料在军用服装中的应用

介绍非织造保暖材料军用棉服、军用内衣的制作 ,对不同材料和结构的成品服装的各项性能作了分析和比较。     

A strategy for integrating product conceptualization and bid preparation

Collaboration with other members of the supply chain is one means by which small and medium sized enterprises (SMEs) can compete in today’s global business environment. Thus, early stages of the new product development process involve both technical activities, e.g., product platform definition, and commercial activities, e.g., bidding for contracts. This paper introduces an integrated collaborative bidding and design system (CBDS) to help SMEs coordinate the two aspects. General sorting was employed for initial requirements acquisition and platform definition; while a self-organizing map (SOM) neural network was combined with a concurrent cost-schedule estimation strategy for refinement of design options and bid evaluation/preparation. A case study on cellular phone design was then applied for illustrating the proposed prototype system.