Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

Review of Language in the Americas.

Reviews the book, Language in the Americas by Joseph H. Greenberg (1987). Greenberg's work on universals of language has crossed disciplinary boundaries to become known to many psychologists interested in language. His equally important work in language classification, of which Language in the Americas is one part, remains unfamiliar to psychologists. This book is a pioneering work in that it is the first genetic classification of the indigenous languages of both North and South America. Greenberg maintains that all of the languages of the Americas belong to three families: Eskimo-Aleut, Na-Dene, and a family that he has named Amerind. This assertion is both important and controversial; the controversy lies in the grouping of most of the languages including all of those of South and Central America into the Amerind family. Most of Language in the Americas consists of the Amerind etymological dictionary, arranged so that the reader can assess lexical similarities within and between subgroups. Greenberg's discussion is informed, articulate, profound, and to the point. He draws on relevant sources and examples from diverse fields of knowledge. The depth and breadth of his scholarship and the clarity of his presentation create a work that is an intellectual pleasure to read. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于神经网络的河道浅滩演变预测模型

河道浅滩演变是一个复杂的非线性动力学过程, 作者借助神经网络处理非线性问题的优势, 在分析影响河道浅滩演变因素的基础上, 建立了预测河道浅淮演变的BP网络模型, 并对模型中的输入因子和样本的提取进行了探讨. 以闽江竹岐至侯官河段为实例,用“试控法”给出了BP网络模型的建模方案, 用正交设计原理选取相应的训练样本集, 利用该样本集对网络进行学习和训练, 并用训练好的BP网络模型预测浅滩上年内最小水深和年平均淤积厚度. 计算结果表明: 模型预测结果与实际值吻合良好. 这为河道浅滩演变预测研究提供了新方法.     

Congestion pricing of multi-modal transportation systems

This paper deals with the pricing and investment decision problem of multi-modal transportation systems in which the congestion is a significant factor in the assessment of system costs. This study approaches this congestion pricing problem with a number of social welfare maximization problems, all of which have the identical structure except financial constraints. One welfare maximization problem examined in this study yields the pricing and investment decision, which can attain the first-best social optimality for multi-modal transportation systems. Other welfare maximization problems show he second-best optimal solutions that can address two policy questions in transportation economics, namely, the cross-subsidy between competing modes and peak-period congestion charges on a single highway link. Received: February 2001/Accepted: December 2001 This work was supported in part by funds from BK21 Research Division of Seoul National University for Social Infrastructure and Construction Technology.     

美国COMSTAC/AST卫星发射市场预测

隶属于美国联邦航空管理委员会（FAA）的美国商业航天运输咨询委员会（COMSTAC）和商业航天运输管理协会（AST）在每年的5-6月份都对未来10年的商业卫星发射市场进行预测。2001年该委员会对商业同步轨道（GEO）和非同步轨道（NGEO）的卫星需求和发射需求都进行了预测。     

Simulation of cup-cone fracture using the cohesive model

The cohesive model is used for the prediction of the crack path during stable crack extension in ductile materials. The problem of crack-path deviation is investigated by means of simulation of crack propagation in a round tensile bar. The respective phenomenon is known as cup-cone fracture. It is shown that the model is able to predict the failure mechanism, which consists of normal fracture in the center and combined normal/shear fracture in the so-called “shear lips” at the specimen’s rim. The damage evolution and crack path predicted by the model are presented. The effect of the normal and shear failure parameters on the crack-deflection point and several aspects of the finite element mesh are discussed.     

Thermomechanical fatigue—damage mechanisms and mechanism-based life prediction methods

An existing extensive database on the isothermal and thermomechanical fatigue behaviour of high-temperature titanium alloy EVII 834 and dispersoid-strengthened aluminum alloy X8019 in SiC particle-reinforced as well as unreinv conditions was used to evaluate both the adaptability of fracture mechanics approaches to TMF and the resulting predictive capabilities of determining material life by crack propagation consideration. Selection of the correct microstructural concepts was emphasised and these concepts were, then adjusted by using data from independent experiments in order to avoid any sort of fitting. It is shown that the cyclic /-integral (δJ_eff concept) is suitable to predict the cyclic lifetime for conditions where the total crack propagation rate is approximately identical to pure fatigue crack growth velocity. In the case that crack propagation is strongly affected by creep, the creep-fatigue damage parameter δ_CF introduced by Riedel can be successfully applied. If environmental effects are very pronounced, the accelerating influence of corrosion on fatigue crack propagation can no longer implicitly be taken into account in the fatigue crack growth law. Instead, a linear combination of the crack growth rate contributions from plain fatigue (determined in vacuum) and from environmental attack is assumed and found to yield a satisfactory prediction, if the relevant corrosion process is taken into account.     

宣汉——达县地区飞仙关组储层预测方法研究

在宣汉-达县地区,以往仅依据地震属性来预测飞仙关组储层分布,钻探结果与实际情况不符,为此本文提出量化分析预测结合主参数分析的新方法和新思路。在量化分析中首先对飞仙关组储层进行高分辨率反演,获得储能系数图;然后结合主振幅剖面和主频率剖面分析,对储层进行预测。在研究区,本方法的预测结果与实钻情况相吻合。     

A Novel Channel Predictor Based on Constrained Hidden Markov Model

1　Introduction　Linkadaptationtechniqueisnowwidelyrecognizedasakeysolutiontoincreasethespectralefficiencyofwire lesssystems[1～ 3] .GPRS ,EDGE ,cdma2 0 0 0andWCDMAallincludelinkadaptationasameanstopro videhigherdatarates[4～ 5] .Torealizethepotentialoflinkadaptation ,reliablechannel predictionisneces sary[6 ] .　Therearemanydifferentchannelpredictionmethodsavailablenow ,suchasLongRangePrediction(LRP) [6 ] ,predictionbasedonsubspacesignalprocess ingalgorithms[7] ,predictionbasedonFinit…     

灰色预测法在西安市农村电话预测中的应用

在对西安市农村电话发展现状分析的基础上 ,运用灰色预测法对西安市农村电话未来发展趋势进行预测 ,为制定西安市农村电话发展策略提供参考