《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（习题，原书第4版）chapter 5 Predictive Analytics II：Text, Web, and Social Media Analytics

Definitions – Digital Signature - a data string which associates a message with some originating entity – Digital Signature Generation Algorithm – a method for producing a digital signature – Digital signature verification algorithm - a method for verifying that a digital signature is authentic (i.e., was indeed created by the specified entity)

1. 1 数据处理及数据管理 1.1.1、信息与数据 1.1.2、数据处理及数据管理 1. 2 数据库系统组成 1.2.1 组成数据库系统的5个主要部分 1.2.2 数据库系统对软、硬件要求 1.2.3 数据库系统的特点 1.3 数据模型（Data Model） 1.3.1 实体联系模型（ER模型） 1.3.2 数据模型 1.3.3 关系具有的性质 1.3.4 关系运算

1. Pointers and Linked Structures 2. Linked Stacks 3. Linked Stacks with Safeguards 4. Linked Queues 5. Application: Polynomial Arithmetic 6. Abstract Data Types and Implementations 7. Pointers and Pitfalls

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）08 Future Trends, Privacy and Managerial Considerations in Analytics

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）06 Prescriptive Analytics：Optimization and Simulation

《商务智能：数据分析的管理视角 Business Intelligence, Analytics, and Data Science：A Managerial Perspective》教学资源（教师手册，原书第4版）05 Predictive Analytics II：Text, Web, and Social Media Analytics

1. Mathematical Background 2. Computer Representation 3. Graph Traversal 4. Topological Sorting 5. A Greedy Algorithm: Shortest Paths 6. Minimal Spanning Trees 7. Graphs as Data Structures

《复合材料 Composites》课程教学资源（学习资料）第二章 增强体_glass fiber-19 The Single Fiber Composite Test：A Comparison of E-Glass Fiber Fragmentation Data with Statistical Theories

6.1 Understand the applications of prescriptive analytics techniques in combination with reporting and predictive analytics 6.2 Understand the basic concepts of analytical decision modeling 6.3 Understand the concepts of analytical models for selected decision problems, including linear programming and simulation models for decision support 6.4 Describe how spreadsheets can be used for analytical modeling and solutions 6.5 Explain the basic concepts of optimization and when to use them 6.6 Describe how to structure a linear programming model 6.7 Explain what is meant by sensitivity analysis, what-if analysis, and goal seeking 6.8 Understand the concepts and applications of different types of simulation 6.9 Understand potential applications of discrete event simulation