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)     

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.     

éditorial.

This issue begins with an invited paper by Ronald Melzack, continuing the "Distinguished Contribution Series" begun in 1990 by my predecessor, Gordon Winocur. Professor Melzack is known world-wide for his research on pain. In 1965, together with Patrick Wall, he proposed the gate control theory, an entirely new conception of pain. For the first time, there was an explicit physiological model emphasizing the role played by the brain as well as by the spinal cord, leading to a new integration of psychological and physiological contributions to pain, as well as to new avenues for the control of pain. This theory has been highly influential, as a quick look in virtually any textbook in biology or medicine will confirm. Professor Melzack's continuing development of his ideas is presented with remarkable clarity in his books and in his many journal articles. It is, therefore, especially exciting for CJEP to be the first to publish a sketch of his new neuromatrix theory. When the book developing this theory is published, it too will no doubt have an immediate and major impact. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

雷达目标识别技术综述

针对雷达自动目标识别技术进行了简要回顾。讨论了目前理论研究和应用比较成功的4类目标识别方法：基于目标运动的回波起伏和调制谱特性的目标识别方法、基于极点分布的目标识别方法、基于高分辨雷达成像的目标识别方法和基于极化特征的目标识别方法，同时讨论了应用于雷达目标识别中的4种模式识别技术：统计模式识别方法、模糊模式识别方法、基于模型和基于知识的模式识别方法以及神经网络模式识别方法。最后分析了问题的可能解决思路。     

虚拟现实技术的若干问题及发展展望

虚拟现实技术是上个世纪后50年发展起来的一门新兴边缘学科,本文对虚拟现实技术的概念、分类、研究现状、其关键技术及技术难题等方面做了阐述,并对虚拟现实技术的发展进行展望。     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.     

"Learning myopia: An adaptive recency effect in category learning": Correction to Jones and Sieck (2003).

Reports an error in "Learning myopia: An adaptive recency effect in category learning" by Matt Jones and Winston R. Sieck (Journal of Experimental Psychology: Learning, Memory, and Cognition, 2003[Jul], Vol 29[4], 626-640). On page 633, Table 2, the values in columns (T, P) and (P, T) in the dual condition row incorrectly read .10 and .90, respectively. The correct values are .90 and .10, respectively. (The following abstract of the original article appeared in record 2003-06626-013.) Recency effects (REs) have been well established in memory and probability learning paradigms but have received little attention in category learning research. Extant categorization models predict REs to be unaffected by learning, whereas a functional interpretation of REs, suggested by results in other domains, predicts that people are able to learn sequential dependencies and incorporate this information into their responses. These contrasting predictions were tested in 2 experiments involving a classification task in which outcome sequences were autocorrelated. Experiment 1 showed that reliance on recent outcomes adapts to the structure of the task, in contrast to models' predictions. Experiment 2 provided constraints on how sequential information is learned and suggested possible extensions to current models to account for this learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

文本索引词项相对权重计算方法与应用

文本索引词权重计算方法决定了文本分类的准确率。该文提出一种文本索引词项相对权重计算方法,即文本索引词项权重根据索引词项在该文本中的出现频率与在整个文本空间出现的平均频率之间的相对值进行计算。该方法能有效地提高索引词对文本内容识别的准确性。