基于知识的摩托车发动机设计支持技术分析

在分析当前摩托车发动机设计中存在问题的基础上,论述市场竞争对摩托车发动机设计提出的要求,给出基于知识的发动机设计系统的主要内容。     

应用PFMEA改进产品制造过程设计质量

本文介绍了PFMEA的流程模式，并以BQZA柱塞斜槽加工为例，说明如何应用PFMEA找到过程影响因素，提高过程设计质量。     

二冲程发动机扫气过程试验方法的研究

在Ａ．Ｊａｎｔｅｆ二冲程发动机扫气性能评价方法－－“扫气图”方法的基础同种准稳定流动模型试验的新方法，用“时均流量”评价扫气性能的品质。经过在１５Ａ型和５０Ａ型摩托车发动机上的实机试验，证明了这是一种较好的测试和评价方法。     

迎接知识经济时代搞好设计情报工作

本文说明了知识经济与信息经济的关系,阐述了工程设计在知识经济中的地位和作用,以及搞好设计情报工作的具体方法。     

SPC在半导体晶圆制造厂的应用(上)

由于半导体制造工艺过程的复杂性,一般很难建立其制造模型,不能对工艺过程状态有效地监控,所以迫切需要先进的半导体过程控制技术来严格监控工艺过程状态,而SPC就是其中最重要的一种技术.本文针对SPC做了简要概述,着重论述了根据半导体生产工艺的特点来实现其在半导体晶圆厂的实际应用.     

State and input observability recovering by additional sensor implementation: A graph-theoretic approach

This paper deals with the problem of additional sensor location in order to recover the state and input observability for structured linear systems. The proposed method is based on a graph-theoretic approach and assumes only the knowledge of the system’s structure. It allows one to provide the minimal number of the required sensors and either their pertinent location or a necessary and sufficient condition which allows one to check if a sensor location is adequate or not. We obtain a sensor placement procedure based on classical and well-known graph theory algorithms, which have polynomial complexity orders.     

Emerging organizational structure for knowledge-oriented teamwork using genetic algorithm

Organizations have historically sought efficiency improvements through different combinations of materials, components, production and processes to get better performance. However, in this age of the knowledge economy, the new organizational management has shifted its focus to the proper use of the knowledge of employees to create greater output and performance. There is a recent trend towards flat organizations and team-orientated structures, therefore this study will concentrate on the knowledge-oriented teamwork. To construct the fitting team structure, we solve the problem in two stages. In the first stage, we assign the proper tasks to the proper members to achieve a good match for effective usage of organizational knowledge. In the second stage, we solve the problem of insufficient knowledge within the organizational structure generated in the first stage by adjusting the positions of members to improve the mutual coordination and knowledge sharing and support.We applied a basic genetic algorithm (BGA) to solve the problems in both the stages. Five factors, such as member/task number, the number of knowledge types, the number of task types, the average complexity of each member’s knowledge types and the average complexity of task knowledge types, are considered to generate different types of problems. Computational results show that the BGA is able to find optimal knowledge matching for small-sized problems in the first stage, and that the BGA is able to improve the organizational structure generated in the first stage in order to reduce the communication cost of knowledge support among the members in the second stage.     

Neighbourhood preserving discriminant embedding in face recognition

In this paper, we present an effective technique on discriminative feature extraction for face recognition. The proposed technique incorporates Graph Embedding and the Fisher’s criterion where we call it as Neighbourhood Preserving Discriminant Embedding (NPDE). Utilizing the Graph Embedding criterion, the underlying nonlinear face data structure is revealed as representative and discriminative features for analysis. We employ Neighbourhood Preserving Embedding (NPE) for the purpose. NPE takes into account the restriction that neighbouring points in the high-dimensional space must remain within the same neighbourhood in the low dimension space and be located in a similar relative spatial situation (without changing the local structure of the nearest neighbours of each data point). Furthermore, by taking the advantage of the Fisher’s criterion, the discriminating power of NPDE is further boosted. Based on this intuition, NPDE obtains better discriminative capability and experimentally verified in ORL, PIE and FRGC.     

A Fast Algorithm for Computing the Deficiency Number of a Mahjong Hand

The tile-based multiplayer game Mahjong is widely played in Asia and has also become increasingly popular worldwide.Face-to-face or online,each player begins with a hand of 13 tiles and players draw and discard tiles in turn until they complete a winning hand.An important notion in Mahjong is the deficiency number(a.k.a.shanten number in Japanese Mahjong)of a hand,which estimates how many tile changes are necessary to complete the hand into a winning hand.The deficiency number plays an essential role in major decision-making tasks such as selecting a tile to discard.This paper proposes a fast algorithm for computing the deficiency number of a Mahjong hand.Compared with the baseline algorithm,the new algorithm is usually 100 times faster and,more importantly,respects the agent's knowledge about available tiles.The algorithm can be used as a basic procedure in all Mahjong variants by both rule-based and machine learning-based Mahjong AI.