Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

手套箱气氛中氚化水处理的工艺研究

分子筛吸附柱和热金属镁床是手套箱气氛中氚化水 (HTO)搜集和分解处理的一种有效手段。测试了分子筛柱对气氛中水的吸附性能和热金属镁床对HTO的分解性能。结果表明 :分子筛柱对气氛中水的吸附效率 >99 99% ,在空气中水含量为 3 4× 1 0 - 3～ 4 2× 1 0 - 3条件下 ,未发现吸附柱水的贯穿现象 ;热金属镁床对HTO的分解率 >99 9% ,当金属镁的消耗量大于 80 %时 ,未见分解率明显降低。     

计算机技术图书分类标引存在的问题及对策

从文献分类的实践出发，提出了对计算机技术图书分类标引工作存在的问题，分析了问题的原因，提出了解决问题的方法。     

广播电视农村覆盖现状浅析

加强农村广播电视的发展,提高其覆盖率是关键,针对这一问题,阐述了解决农村广播电视覆盖的手段,对农村广播电视覆盖现状做了详细的分析,并提出建议和措施。     

含油污泥焦化处理实验研究

采用焦化方法对含油污泥进行处理。经过筛选选取活性白土作为焦化处理催化剂,分别研究了反应时间、反应温度、氮气吹扫量、加热速率等因素对处理效果的影响。4个影响因素对液相油品收率的影响顺序为:氮气吹扫量>反应温度>反应时间>加热速率;对反应转化率的影响顺序为:反应温度>反应时间>氮气吹扫量>加热速率。较为理想的反应参数:反应温度490℃;反应时间60min;氮气吹扫量90mL.min-1;加热速率4℃.min-1。在此反应条件下,含油污泥液相油品收率>80%,反应转化率>99.9%,经焦化处理后的废渣含油率<3‰,达到农用污泥排放标准,实现了达标排放和回收资源的目的。     

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.     

Astaxanthin Extraction From Shrimp Waste by Lactic Fermentation and Enzymatic Hydrolysis of the Carotenoprotein Complex

ABSTRACT: Natural carotenoids are an alternative to synthetic orange-red pigments. They are present in crustaceans as a protein-pigment complex. In order to extract this highly unstable pigment, crustacean waste must be stabilized; lactic fermentation is a simple and environmentally friendly method to achieve this goal. Shrimp wastes were inoculated with Lactobacillus bacterial cultures. Carotenoids were then extracted with an organic solvent system. Protein-pigment splitting was carried out using a mixture of 4 commercial enzymes; and the protein was separated from the pigment by ultrafiltration. Electrophoretograms showed that the pigment was attached to a 265-kDa protein. Splitting the protein-pigment complex allows studies on pigment absorption, stability and application.     

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.