Language clusters based on linguistic complex networks

To investigate the feasibility of using complex networks in the study of linguistic typology, this paper builds and explores 15 lin-guistic complex networks based on the dependency syntactic treebanks of 15 languages. The results show that it is possible to classify human languages by means of the following main parameters of complex networks: (a) average degree of the node, (b) cluster coefficients, (c) average path length, (d) network centralization, (e) diameter, (f) power exponent of degree distribution, and (g) the determination coefficient of power law distributions. The precision of this method is similar to the results achieved by means of modern word order typology. This paper tries to solve two problems of current linguistic typology. First, the language sample of a typological study is not real text; second, typological studies pay too much attention to local language structures in the course of choosing typological parameters. This study performs better in global typological features of language and not only enhances typological methods, but it is also valuable for developing the applications of complex networks in the humanities, social, and life sciences.     

免疫危险理论在电子邮件分类中的应用

在对危险理论、人工免疫和云模型的研究基础上,提出了一种基于危险理论的电子邮件分类模型并对模型的框架和工作原理进行了详细的描述.实验证明该模型总体性能优于贝叶斯分类,能有效地识别出有害的非我,达到降低伪肯定率和伪否定率的目的.     

稀疏对数回归及其在基因选择中的应用

针对微阵列分类中涌现出的小样本、超高维问题,提出了一种同时进行基因选择和分类的稀疏对数回归学习机.结合部分自适应弹性网络惩罚与对数似然损失函数,提出了稀疏对数回归学习机,证明了该学习机能激励自适应群体基因选择效应.     

明清拟话本小说中的贞节烈女形象及其类型研究

在明清拟话本小说中，几乎随处可见贞节烈女形象，对如此庞大的形象群进行分类就需要一定的分类标准。以身份作为分类标准，贞节烈女形象可以分为贞女形象、节妇形象和烈女形象；以守贞程度作为分类标准，则可将其分为传统贞节观下的贞节烈女形象和变通贞节观下的贞节烈女形象。     

产生式与判别式分类方法比较研究

分类是数据挖掘领域研究的热点,产生式与判别式是数据挖掘中两种不同的分类模型。产生式模型具有通用性、灵活性及清晰的分层结构,学习得到的模型很容易满足模型解释要求;判别式模型没有明显的对系统中变量的基本分布建模的企图,仅仅对输入到输出之间映射的最优化感兴趣,可以提供更好的分类性能。从准确率、建模时间及渐进误差等方面对产生式与判别式分类方法进行了分析与比较,为研究人员在分类模型的选择上提供了参考。     

Studies of layout of world machine tools industry based on patent analysis

As the foundation of an industrialized country nowadays, machine tools industry is regarded as the engine of industrial development of a country. The developed countries, such as USA, Germany and Japan, have widely deployed the technology of using the patent in order to keep their strength in various fields. This research examins the CNC machine tools industry in the world by using the pa- tent analysis method. It first gives an overview about the world patent application in CNC machine tools industry from 1963 to 2010 and divides the development of the industry into five stages. It also lists the patent application of the world top 20 countries, where the top 5 countries are compared. The patents of the world top 10 companies of machine tools manufacturers are mapped according to the international patent classification （IPC）, and the future trends of world machine tools industry are discussed. Finally conclusions and suggestions are presented.     

织物组织结构分类新探

介绍了织物组织结构的常规分类方法,并提出了一种可对组织进行定量分析的新的分类方法——从浮长的角度分类,对常规分类方法进行了有益的补充.     

HIs classification in HCR model for operator reliability study of nuclear power plants

The human cognition reliability model is used to study time-related human response interaction (HI). The classification of HI types is an important base. At present, the two types of HIS classification (i.e. SRK classification and CP classification) are based on subjective or objective characteristics respectively by which some phenomena can be hardly explained. Since the types were limited, they could not meet the requirements. The integrate approach of HIs classification is compatible with the original methods, and HIs are classified according to subjective and objective characteristics. The integrate approach contains more detailed types and has higher precision. It is more advantageous and convenient for the classification of HIs. The integrate approach has been used in the study of operator reliability for nuclear power plants in China. The results were satisfactory, and by which the integrate approach was verified.     

基于级联卷积神经网络的港口多方向舰船检测与分类

港口舰船目标自动检测的定位和类型分类是一个重要而具有挑战性的问题。针对高分辨率光学遥感影像中多方向性排列密集的近岸舰船目标定位和识别困难的问题,提出基于级联区域卷积神经网络和手工提取特征相结合的近岸舰船检测识别框架。首先,使用级联的区域卷积神经网络对舰船位置进行粗定位并对类别进行估计，得到一系列粗定位的垂直预测框。然后,设计一个可以准确定位舰船的斜框旋转回归器,其将第一阶段所得粗定位垂直矩形框转变为带方向的斜矩形框。最后,使用非极大值抑制的方法去除冗余的预测框。实验采用谷歌地球上采集的数据集进行训练和预测,实验结果表明所提算法在精准率和召回率上均具有较大优势。     

事项会计的事项分类研究

事项会计要从理论走向应用,必须提出一套行之有效的分类体系。事项的分类可以从不同的角度来进行,按照决策树分类思想和业务流程分析理论,事项分类最适当的方法是按业务流程来划分,此种分类方法能将焦点集中于业务事件,并且支持业务过程的简化和变更,能最大限度地发挥事项会计的优势。