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.     

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。     

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)     

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。     

Step response classification for model-based autotuning via polygonal curve approximation

A model-based autotuning method consists of an identification and a regulator tuning phase. To achieve satisfactory performance and robustness, it is advisable that both phases be tailored a priori to the characteristics of the observed process dynamics. Such characteristics include, but are not limited to, the model structure. For example, overdamped and underdamped models with the same pole-zero structure are parametrised and controlled in different ways. Step response data, that are typically used for the identification phase in the autotuning context, can also be pre-processed to reveal those characteristics. This paper presents a step response classification method suitable for the above purpose. The method is based on a polygonal curve approximation technique for data pre-processing, followed by a neural network classifier. Only normalised I/O data are employed, so that the neural network can be trained off-line with simulated data. Simulation results are reported to show the effectiveness of the proposed classification method in terms of the achievable tuning results.     

Technical Note: Selecting a Classification Method by Cross-Validation

If we lack relevant problem-specific knowledge, cross-validation methods may be used to select a classification method empirically. We examine this idea here to show in what senses cross-validation does and does not solve the selection problem. As illustrated empirically, cross-validation may lead to higher average performance than application of any single classification strategy, and it also cuts the risk of poor performance. On the other hand, cross-validation is no more or less a form of bias than simpler strategies, and applying it appropriately ultimately depends in the same way on prior knowledge. In fact, cross-validation may be seen as a way of applying partial information about the applicability of alternative classification strategies.     

货运调车场减速顶噪声及治理的探讨

铁路货物运输枢纽的调车场中，驼峰调车是主要的调车手段，为提高生产效率和确保安全，沿驼峰下滑道布置的减速器（减速闸，减速顶）的噪声是调车场噪声的主要声源之一，本文通过对昆明东站铁路降噪工程的观测试验项目，探讨了减速顶噪声的特性及治理措施。     

A stability classification method and its application to pipelined solution of linear recurrences

A new method of classification for numerical stability of parallel algorithms is proposed based on the theoretical foundation of forward error analysis. It partitions the algorithms according to their asymptotic stability—a measure introduced to relate the limiting behavior of the stability to the size of the problem. Using this method, the stability aspect of the pipelined solution technique for first-order and second-order linear recurrences—the core of a tridiagonal linear equation solver—is studied. In particular, it shows that the pipelined solution method of the first-order linear recurrences has the same degree of stability as the commonly used sequential evaluation algorithms. The stability problems of sequential and pipelined solution methods of the second-order linear recurrences are also studied.