对梅山技工培训工作方向之浅见

根据梅山公司发展的需要，以提高技工岗位绩效和缩小技工现有技能水平与理想绩效行为差距为目的，对技工培训的今后工作方向提出了个人的看法。要想促进技工培训工作更上一层楼，必须进一步完善培训体系，遵循ADIE进行运作；按需求分析，确立培训目标，制定切实可行的计划，编制针对性和可操作性强的技工培训教材，以“请进来、送出去”的方法培训和优化师资力量，不断改进教学方法。     

守望春天

2004年12月22日，北京降下了这一年的首场大雪，整个北京城银装素裹。与此同时，人民大会堂里热气腾腾，中国室内设计学会成立15周年的庆典正在举行。作为个新型的学会，中国室内设计学会发展的进程紧紧跟随着我国改革开放和经济发展的步伐，我们用了二十年的时间达到了别的国家上百年时间才能达到的规模。中国室内设计学会已经逐步走入它的辉煌时代，正呈现着副朝气蓬勃的春天景象。     

人工神经网络A／D变换器

本文对［５］的４位人工神经网络Ａ／Ｄ变换器进行了研究．指出按其方法推广实现多位Ａ／Ｄ时存在突触电阻大小以至无法实现且抗干扰能力也不好的问题并给出了解决办法．同时对如何改善神经元转移特性的硬限幅曲线作了简单讨论．     

Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis

High-dimensional data appear in many applications of data mining, machine learning, and bioinformatics. Feature reduction is commonly applied as a preprocessing step to overcome the curse of dimensionality. Uncorrelated Linear Discriminant Analysis (ULDA) was recently proposed for feature reduction. The extracted features via ULDA were shown to be statistically uncorrelated, which is desirable for many applications. In this paper, an algorithm called ULDA/QR is proposed to simplify the previous implementation of ULDA. Then, the ULDA/GSVD algorithm is proposed, based on a novel optimization criterion, to address the singularity problem which occurs in undersampled problems, where the data dimension is larger than the sample size. The criterion used is the regularized version of the one in ULDA/QR. Surprisingly, our theoretical result shows that the solution to ULDA/GSVD is independent of the value of the regularization parameter. Experimental results on various types of data sets are reported to show the effectiveness of the proposed algorithm and to compare it with other commonly used feature reduction algorithms.     

Specifying transformer winter and summer peak-load limits

This paper presents a methodology for specifying the winter and summer peak-load limits for substation transformers that carry a temperature-sensitive load, taking into account the random nature of load and ambient temperature as well as their correlation. With this methodology, we can easily and accurately specify the peak-load limits for each substation transformer once the historical ambient temperature and load data are available. Also, we can collectively specify the peak-load limits for the transformer of each cooling type (OA, OA/FA, or OA/FA/FA) in a geographic region based on the mean and standard deviation of ambient temperatures in that region. Such peak-load limits are useful for power system planning.     

As,Sb,Sn对30CrMnSiA钢力学性能的影响

在３０ＣｒＭｎＳｉＡ钢中加入不同量的Ａｓ，Ｓｂ，Ｓｎ元素，研究了这些元素单独存在及复合存在时对钢的强度，塑性，冲击韧度及韧脆转变温度的影响规律，并用扫描电镜及俄歇能谱分析了Ａｓ，Ｓｂ，Ｓｎ导致晶界脆化的机理。     

A minimum cost assessment method for composite generation andtransmission system expansion planning

Composite generation and transmission system expansion analysis should take into account both economic considerations and adequacy requirements. An optimum expansion plan should achieve the minimum total investment, operation and damage cost. A minimum cost assessment method for composite system expansion planning, which can be used to consider generation expansion and transmission expansion simultaneously, is presented. The minimization model proposed to incorporate both operating and outage costs can recognize different customer damage functions at different load buses and includes the duration of the simulated contingency system states . A computer program based on the presented method has been developed to provide a set of line, load bus, generator bus and system indices which can be used to select optimal expansion plans at different load growth levels. Case studies in which the method is applied to the IEEE Modified Reliability Test System indicate its effectiveness     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.