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关键词： Fuzzy classification   Pattern recognition   Magnetic resonance spectroscopy   Cerebrospinal fluid   Fuzzy decision trees   Ordered weighted averaging operators   Classifier fusion  

摘要： This paper presents a method for classifying cerebrospinal fluid (CSF) samples studied by proton magnetic resonance spectroscopy (H-1 MRS) into clinical subgroups by means of a fuzzy classifier. The method focuses on the analysis of a low signal-to-noise region of the spectra and is designed to use a small number of samples because sampling can only be done through an invasive technique. The proposed method involves the fusion of classifiers based on decision trees designed using fuzzy techniques. The fusion step was carried out by ordered weighted averaging (OWA) operators. The quality of the proposed classifier was evaluated by efficiency and robustness quality indexes using a method based on a cross-validation technique. Results show excellent classification levels and satisfactory robustness in both training and test sets. (C) 2011 Elsevier B.V. All rights reserved.

关键词： 企业经济业务   违约金   税务处理   购销业务   会计   履行合同   生产经营过程   合同当事人  

摘要： 违约金是合同当事人在合同中预先约定的当一方不履行合同或不完全履行合同时,由违约的一方支付给对方的一定金额的货币。企业在生产经营过程中,可能会支付各种违约金等,违约金是伴随着企业经济业务而产生,

关键词： BIOLOGY -- Classification   MORPHOLOGY   PLATYHELMINTHES   MULTICOLLINEARITY   EVOLUTION (Biology)   CASE studies  

摘要： Taxonomists and evolutionary biologists frequently use a combination of morphological measurements to distinguish between species and investigate local adaptation. However, the entire set of characters often displays various degrees of collinearity. This paper discusses the effect of using collinear data in morphological taxonomy and ways to handle multicollinearity in a classification context, with special consideration for small sample size. In addition, I propose a robust and easy-to-use combination of dimension reduction using partial least squares (PLS) with traditional discriminant methods for morphological data. To do this, I investigated morphological variation patterns among four monogenean populations from the Pacific Ocean using the correlated morphological features of the sclerotized attachment organ. The new approach yielded better prediction results (lower classification error rates) than the traditional dimension reduction method based on principle component analysis (PCA) and is also much more robust for small sample size. This emphasizes that PLS may be more efficient than PCA in dealing with correlated data and extracting the most relevant morphological differences among groups.

关键词： Nonlinear time series   Sample entropy   Complexity   Ventricular fibrillation   Ventricular tachycardia  

摘要： A study of ventricular fibrillation (VF) and ventricular tachycardia (VT) was undertaken using modified sample entropy analysis. Sample entropy (SampEn) is believed to provide the quantitative information about the complexity of experimental data that is corrupted by noise, short in data length. However, the similarity definition of vectors is based on a Heaviside function, of which the boundary is discontinuous and hard, which may cause the problems in the validity and accuracy of SampEn. To deal with the encountered problems, a modified sample entropy (mSampEn) based on fuzzy membership function was proposed. Its performances on characterizing VF and VT signals, as well as several simulated time series, demonstrate that mSampEn can more efficiently measure the complexity of time series. It is shown that, as a criteria for discriminating between VF and VT, mSampEn provides a significantly (p < 0.0001) higher (99%) accuracy rate than the standard one. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Gene selection   Sample classification   Adaptive genetic algorithm   k-Nearest neighbor   Microarray data  

摘要： Recently, microarray technology has widely used on the study of gene expression in cancer diagnosis. The main distinguishing feature of microarray technology is that can measure thousands of genes at the same time. In the past, researchers always used parametric statistical methods to find the significant genes. However, microarray data often cannot obey some of the assumptions of parametric statistical methods, or type I error may be over expanded. Therefore, our aim is to establish a gene selection method without assumption restriction to reduce the dimension of the data set. In our study, adaptive genetic algorithm/k-nearest neighbor (AGA/KNN) was used to evolve gene subsets. We find that AGA/KNN can reduce the dimension of the data set, and all test samples can be classified correctly. In addition, the accuracy of AGA/KNN is higher than that of GA/KNN, and it only takes half the CPU time of GA/KNN. After using the proposed method, biologists can identify the relevant genes efficiently from the sub-gene set and classify the test samples correctly. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Support vector machine   Rough set   Neighborhood relation   Sample selection   Feature selection  

摘要： Support vector machines (SVMs) are a class of popular classification algorithms for their high generalization ability. However, it is time-consuming to train SVMs with a large set of learning samples. Improving learning efficiency is one of most important research tasks on SVMs. It is known that although there are many candidate training samples in some learning tasks, only the samples near decision boundary which are called support vectors have impact on the optimal classification hyper-planes. Finding these samples and training SVMs with them will greatly decrease training time and space complexity. Based on the observation, we introduce neighborhood based rough set model to search boundary samples. Using the model, we firstly divide sample spaces into three subsets: positive region, boundary and noise. Furthermore, we partition the input features into four subsets: strongly relevant features, weakly relevant and indispensable features, weakly relevant and superfluous features, and irrelevant features. Then we train SVMs only with the boundary samples in the relevant and indispensable feature subspaces, thus feature and sample selection is simultaneously conducted with the proposed model. A set of experimental results show the model can select very few features and samples for training;in the mean time the classification performances are preserved or even improved. (C) 2011 Elsevier B.V. All rights reserved.

关键词： 化学品   CLP   GHS   分类   标签   包装  

摘要： 文章介绍了欧盟(EC)1272/2008"关于物质和昆合物分类、标签和包装法规"(CLP)的形成背景、适用范围、内容、实施时间、适用对象和义务及其与联合国GHS制度和欧盟原有化学品分类、标签与包装体系之间的区别,并就该法规对我国的影响进行了论述。

关键词： 自动分类   饮品包装   中小学校   北京市   回收机   铝   投放   环境保护  

摘要： 美铝中国2011年1月5日宣布,由美铝基金会资助,美铝（中国）投资有限公司与中华环境保护基金会联合实施,向北京市12所中小学校捐赠12台饮品包装自动分类有偿回收机,以支持北京市开展的垃圾分类回收工作。

关键词： 马克思主义中国化   中国具体实际   马克思主义基本原理   检验促进  

摘要： 马克思主义中国化就是将马克思主义基本原理同中国具体实际结合起来,因此,马克思主义基本原理与中国具体实际必然产生相互作用。在它们的相互作用中,中国具体实际对马克思主义基本原理起检验证实、正本清源和丰富发展作用。

关键词： 质量检验   控制   作用  

摘要： 本文简要叙述了质量检验在质量管理过程中的作用以及检验的目的和控制方法。着重阐述了质量检验的控制步骤和检验所达到的目标,说明了正确的检验方法和检验程序能保证产品的稳步提高,产品说明了产品质量的优劣是设计出来的,而不是检验出来的。