Modular design of product families for quality and cost

The purpose of this article is to help managers early in the design of new product families. Based on product structures, sales forecasts, and constraints imposed by the marketplace, like quality and cost, the proposed method selects the product modules that meet customer requirements for the products, while respecting those constraints. The proposal includes a single-level module design formulation that considers quality and cost simultaneously. The method for testing the proposed algorithm is based on a case study of an electro–mechanical assembly device (headlamp). The performance of the algorithm is compared to that of the zero module case, where often the constraint problem cannot be resolved. The main result is a model and an algorithm that optimise quality and cost under the constraints of quality and cost. It shows what modules to manufacture, in what quantities, and in which products to use them. The output also provides the predicted quality and cost, based on improvements made to the modules. To conclude, this research enables the joint optimisation of quality and cost by defining the modules to be manufactured. It provides input for managers seeking modules designed for their supply chain. The algorithm provides key input for managing production ramp-up.     

山钢集团新一代数据中心建设实践

山钢集团按国家及行业A类机房现行标准,基于全新理念的模块化设计,高质量地完成了新一代数据中心建设,其核心技术是模块化UPS系统、水冷式空调系统和云平台系统的集成与应用。解决了数据中心过度投资和“高能耗、低效率”的问题,真正实现了企业私有云计算平台的落地,提高了资源利用率,节省软硬件投入,减少电力消耗及运维成本,保证了企业数据中心能够高效、安全和低碳运行。     

基于多粒度结构的网络表示学习

图卷积网络（GCN）能够适应不同结构的图,但多数基于GCN的方法难以有效地捕获网络的高阶相似性。简单添加卷积层将导致输出特征过度平滑并使它们难以区分,而且深层神经网络更难训练。本文选择将网络的多粒度结构和图卷积网络结合起来用于学习网络的节点特征表示,提出基于多粒度结构的网络表示学习方法Multi-GS。首先,基于模块度聚类和粒计算思想,用分层递阶的多粒度空间替代原始的单层网络拓扑空间;然后,利用GCN模型学习不同粗细粒度空间中粒的表示;最后,由粗到细将不同粒的表示组合为原始空间中节点的表示。实验结果表明:Multi-GS能够捕获多种结构信息,包括一阶和二阶相似性、社团内相似性（高阶结构）和社团间相似性（全局结构）。在绝大多数情况下,使用多粒度的结构可改善节点分类任务的分类效果。     

应用网络模块度的航天测控地面站网分析

航天测控地面站网作为一个实际网络,它具有网络的相关属性。首先通过复杂网络方法构建了航天测控天地一体化二分网络,然后在二分网络基础上,提出了各专用测控系统的专用性参数α和通用性参数β来描述和区分不同的专用测控系统,利用Kendall相关系数和定义的相关性阈值K构建了航天测控地面站相关性网络。以美国航天测控地面站网现状为例,对所提网络模型的有效性进行了仿真验证,应用相关性阈值(K)和网络模块度(Q)曲线(K-Q曲线)分析了网络模型参数。研究结果表明,所提的相关性网络模型能较好的模拟测控地面站网络现状;网络模块度的峰值与|α-β|呈正相关,当|α-β|较大时,K-Q曲线整体呈现出正态分布特性。     

Attractor Spaces as Modules: A Semi-Eliminative Reduction of Symbolic AI to Dynamic Systems Theory

I propose a semi-eliminative reduction of Fodors concept of module to the concept of attractor basin which is used in Cognitive Dynamic Systems Theory (DST). I show how attractor basins perform the same explanatory function as modules in several DST based research program. Attractor basins in some organic dynamic systems have even been able to perform cognitive functions which are equivalent to the If/Then/Else loop in the computer language LISP. I suggest directions for future research programs which could find similar equivalencies between organic dynamic systems and other cognitive functions. This type of research could help us discover how (and/or if) it is possible to use Dynamic Systems Theory to more accurately model the cognitive functions that are now being modeled by subroutines in Symbolic AI computer models. If such a reduction of subroutines to basins of attraction is possible, it could free AI from the limitations that prompted Fodor to say that it was impossible to model certain higher level cognitive functions.     

On the modularization and reuse of exception handling with aspects

This paper presents an in‐depth study of the adequacy of the AspectJ language for modularizing and reusing exception‐handling code. The study consisted of refactoring existing applications so that the code responsible for implementing error‐handling strategies was moved to newly created exception handler aspects. We have performed quantitative assessments of five systems—four object‐oriented and one aspect‐oriented—based on four key quality attributes, namely separation of concerns, coupling, cohesion, and conciseness. Our investigation also included a multi‐perspective analysis of the refactored systems, including (i) the extent to which error‐handling aspects can be reused, (ii) the beneficial and harmful aspectization scenarios for exception handling, and (iii) the scalability of AOP to support the modularization of exception handling in the presence of other aspects. Copyright © 2009 John Wiley & Sons, Ltd.     

基于谱分析的无线传感器网络模块度分簇算法

基于谱分析与模块度,提出一种无线传感器网络分簇算法(CHSM).首先利用非平凡特征向量获得传感器网络的原始簇结构;然后借助模块度的增量来评估、合并原始簇,从而形成一个与真实网络相匹配的簇结构;同时设计了一种能量异配度函数,并利用各节点的能量异配度及其剩余能量在各个簇内选取簇头节点.仿真结果表明,CHSM算法找到的簇结构具有更高的模块度,其选取的簇头节点具有更高的能量异配度,进而表明了所提出的算法能有效延长网络的寿命.     

动态加权网络中的演化社区发现算法研究

在动态网络中发现社区结构是一个非常复杂而有意义的过程,可以更好地观察和分析网络的演化情况。针对动态加权网络中的社区发现问题,提出了一种结合历史网络社区结构的算法,叫做动态加权网络中的演化社区发现算法（ECDA）。该算法分为两步：结合历史社区和网络结构信息,计算当前时间跳的输入矩阵;然后通过该输入矩阵计算得到结合历史时间跳信息的社区划分结果。该算法有以下优点：可以自动发现动态加权网络中每个时间跳的社区结构;对网络结构的变化和社区结构的变化具有较高的敏锐性。在人工数据集和真实数据集中进行了实验,实验结果证明该算法可以有效地发现动态加权网络中的社区结构,与其他算法相比具有较好的竞争力。     

基于信号传递与层次聚类的社团发现算法

社团是社会网络的一个重要特征,社团发现是近年来研究的热点问题之一。通过在复杂网络上传递信号,获得各节点对网络的影响向量,从而把网络中节点的拓扑性质转化为代数空间上向量的几何关系,然后用结合模块度的层次聚类挖掘社会网络中的社团结构。该算法优点是不需要预先知道社团的数量或社团内节点的数量,用Zachary空手道俱乐部网络、大学足球赛网络以及海豚关系网络的数据进行验证,该算法划分的社团准确性超过了Newman的结论。     

基于 ADUC7060的多功能气体检测仪的设计*

检测仪以ADUC7060为核心控制器,采用电化学气体传感器对不同组分气体识别并进行浓度检测,以 TFT点阵式液晶显示模块进行显示,设计测量电路以及数据处理电路以及相应的程序,制作出的气体检测仪在实际运用中相对精度高,软件采用模块化编程思想,完成对气体的识别和检测,并对测量数据进行存储和显示。采用软件的参数模型方法进行零点校正,并且采用低功耗的技术延长该检测仪的电池更换时间和寿命。和其它同类检测仪相比,该设计具有很好的实用价值和应用价值,稳定性好、精度高、反应灵敏。