Background information Croydon city in the south east of England Victorian house Sash-window General School Certificate

Section C Information Storage and Transfer信息的储存与传递 C5 Control of gene expression 基因表达的调控

Section C Information Storage and Transfer信息的储存与传递 C1 Structure and organization of DnA DNA的结构与组装

Integration.Smart/Optical Cards Matthew e. Baretich 117.2 Hospital Information Systems niversity of Colorado The Clinical Environment Healthcare Codes and Standards 117.1 Clinical Information Systems Luis Kun The main objective of this section is to provide the reader with a summary of areas that relate to clinical

People send information in three steps and through two types of memory, short term and long term. Physical experiments on short-term memory are carried out. They indicate that even slight delays or interruption can prevent information from being

《情报科学原理 Principles of Information Science（PIS）》课程PPT教学课件：Chapter 3 Measures of Information

《情报科学原理 Principles of Information Science（PIS）》课程PPT教学课件：Chapter 1 An Outline of Information Science

1.Understand the uses and limitations of an income statement. 2.Prepare a single-step income statement. 3.Prepare a multiple-step income statement. 4.Explain how to report irregular items. 5.Explain intraperiod tax allocation. 6.Identify where to report earnings per share information. 7.Prepare a retained earnings statement. 8.Explain how to report other comprehensive income

1.Describe the usefulness of a conceptual framework. 2.Describe the FASB's efforts to construct a conceptual framework. 3.Understand the objectives of financial reporting. 4.Identify the qualitative characteristics of accounting information. 5.Define the basic elements of financial statements. 6.Describe the basic assumptions of accounting. 7.Explain the application of the basic principles of accounting. 8.Describe the impact that constraints have on reporting accounting information

针对分类数据, 通过数据对象在属性值上的集中程度定义了新的基于属性值集中度的类内相似度(similarity based on concentration of attribute values, CONC), 用于衡量聚类结果中类内各数据对象之间的相似度; 通过不同类的特征属性值的差异程度定义了基于强度向量差异的类间差异度(dissimilarity based on discrepancy of SVs, DCRP), 用于衡量两个类之间的差异度.基于CONC和DCRP提出了新的分类数据聚类有效性内部评价指标(clustering validation based on concentration of attribute values, CVC), 它具有以下3个特点: (1)在评价每个类内相似度时, 不仅依靠类内各数据对象的特征, 还考虑了整个数据集的信息; (2)采用几个特征属性值的差异评价两个类的差异度, 确保评价过程不丢失有效的聚类信息, 同时可以消除噪音的影响; (3)在评价类内相似度及类间差异度时, 消除了数据对象个数对评价过程的影响.采用加州大学欧文分校提出的用于机器学习的数据库(UCI)进行实验, 将CVC与类别效用(category utility, CU)指标、基于主观因素的分类数据指标(categorical data clustering with subjective factors, CDCS)指标和基于信息熵的内部评价指标(information entropy, IE)等内部评价指标进行对比, 通过外部评价指标标准交互信息(normalized mutual information, NMI)验证内部评价效果.实验表明相对其他内部评价指标, CVC指标可以更有效地评价聚类结果.此外, CVC指标相对于NMI指标, 不需要数据集以外的信息, 更具实用性