Effect of vibration condition and inter-particle frictions on the packing of uniform spheres

We present a numerical study of the packing of uniform spheres under three-dimensional vibration using the discrete element method (DEM), focusing on the effects of vibration condition (amplitude and frequency) and inter-particle frictions (sliding and rolling frictions). The results are analysed in terms of packing density, coordination number (CN), radial distribution function (RDF) and pore structure. It is shown that increasing either the vibration amplitude or frequency causes packing density to increase initially to a maximum and then decrease. Both vibration frequency and amplitude should be considered to characterize the effect of vibration process on packing structure. The sliding and rolling frictions between particles can decrease packing density since they dissipate energy, although the effect of rolling friction is less significant. In line with the change of packing density, microstructural properties such as CN, RDF and pore distribution also change: a looser packing often corresponds to smaller CN, less peaked RDF and larger but more widely distributed pores.     

Finger assignment schemes for RAKE receivers with multiple-way soft handover

We propose and analyze new finger assignment techniques that are applicable for RAKE receivers in the soft handover (SHO) region. Specifically, extending the results for the case of two-base station (BS), we consider the multi-BS situation, attack the statistics of several correlated generalized selection combining (GSC) stages, and provide closed-form expressions for the statistics of the output signal-to-noise ratio (SNR). By investigating the tradeoff among the error performance, the average number of required path estimations/comparisons, and the SHO overhead, we show through numerical examples that the new schemes offer commensurate performance in comparison with more complicated GSC-based diversity systems while requiring a smaller estimation load and SHO overhead.     

镁钴铝类水滑石催化合成安息香甲醚

采用共沉淀法制备了镁钴铝类水滑石化合物(MgCoAl-HTLcs),并用 X 射线衍射、扫描电子显微镜、NH_3程序升温脱附等方法对 MgCoAl-HTLcs 进行了表征,并以 MgCoAl-HTLcs 为催化剂催化苯甲醛与甲醇反应合成安息香甲醚,研究了n(Mg):n(Co):n(Al)、催化剂用量、原料配比、反应温度、反应时间对合成反应的影响。表征结果显示,MgCoAl-HTLcs 的晶相完整,表面主要为弱酸、弱碱性。催化合成安息香甲醚的适宜条件为:MgCoAl-HTLcs 催化剂用量0.10 g(约为原料总质量的0.23%),n(Mg):n(Co):n(Al)=0.4:1.6:1.0,V(苯甲醛):V(甲醇)=3:50,反应温度50℃,反应时间150 min。在此条件下,苯甲醛的平衡转化率达77.49%,安息香甲醚选择性接近100%。为洁净合成安息香甲醚开辟了一条新的途径。     

陶艺的文化性与功能

中国古陶艺制品造型,釉色,装饰等艺术符号都与每时期的阶段性精神和物质生活相联系,但在"现代艺术"文化认识领域中,往往从理论思维角度把陶艺实用目的的物质性排斥在文化范畴之外。艺术常常强调物质的观赏性,而陶艺的实用功能就是这种文化类型的主体,陶艺的文化性和功能性,具有实用和审美文化的高度叠合,永久地承载着实用功能和精神功能两大内容。     

B737机务CBT系统建设方案的探讨

通过对AICC制订的CBT课件开发规范的探讨，阐述了CBT的基本概念和波音737飞机机务CBT的开发制作过程，以及利用Authorware开发软件制作多媒体课件的技术难点。     

A Tutorial on GrÖbner Bases With Applications in Signals and Systems

This paper is a tutorial on GrÖbner bases and a survey on the applications of GrÖbner bases in the broad field of signals and systems. A reasonably detailed review is given of several fundamental theoretical issues that occur in the use of GrÖbner bases in multidimensional signals and systems applications. These topics include the primeness of multivariate polynomial matrices, multivariate unimodular polynomial matrix completion, and prime factorization of multivariate polynomial matrices. A brief review is also presented on the wide-ranging applications of GrÖbner bases in multidimensional as well as one-dimensional circuits, networks, control, coding, signals, and systems and other related areas like robotics and applied mechanics. The impact and scope of GrÖbner bases in signals and systems are highlighted with respect to what has already been accomplished as a stepping stone to expanding future research.      

公司大门工程建设施工

大门小品建筑属多项目综合性工程。本文作者从管理者的角度 ,通过对公司大门及附属工程施工质量控制的总结 ,说明了质量控制应贯穿于工程施工的全过程     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced