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计算机科学导论 英中双语版pdf电子书版本下载

计算机科学导论  英中双语版
  • (英)邓辉舫,邹才凤,(巴基)娜西娅·安瓦编著 著
  • 出版社: 北京:人民邮电出版社
  • ISBN:9787115435507
  • 出版时间:2016
  • 标注页数:268页
  • 文件大小:83MB
  • 文件页数:280页
  • 主题词:计算机科学-高等学校-教材-汉、英

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图书目录

Unit 1 Introduction 1

1.1 What Is Computer Science? 1

1.2 Von Neumann Model 1

1.3 Computer Components 2

1.4 History and Development Trends 3

1.5 Frontiers of Computer Technology 5

1.6 Major Fields of Computer Science 12

1.7 References and Recommended Readings 13

1.8 Summary 14

1.9 Practice Set 14

Unit 2 Number Systems and Conversions 16

2.1 Introduction 16

2.2 Positional Number Systems 17

2.3 Non-Positional Number Systems 26

2.4 References and Recommended Readings 27

2.5 Summary 28

2.6 Practice Set 28

Unit 3 Data Storage and Compression 30

3.1 Bit Pattern 30

3.2 Integer in Computer 31

3.3 Floating-Point in Computer 34

3.4 Data Storage 36

3.5 Cloud Storage and Big Data Storage 44

3.6 References and Recommended Readings 48

3.7 Summary 49

3.8 Practice Set 51

Unit 4 Data Operations 54

4.1 Logical Operations 54

4.2 Arithmetic Operations 59

4.3 Shift Operations 64

4.4 References and Recommended Readings 66

4.5 Summary 66

4.6 Practice Set 67

Unit 5 Computer Components 70

5.1 Three Main Components 70

5.2 Components Interconnection 80

5.3 Machine Cycle 82

5.4 Computer Architectures 83

5.5 References and Recommended Readings 84

5.6 Summary 85

5.7 Practice Set 86

Unit 6 Computer Networks 88

6.1 Types of Networks 88

6.2 TCP/IP Model 91

6.3 Devices in Networks 95

6.4 New Development in Networks 96

6.5 References and Recommended Readings 104

6.6 Summary 104

6.7 Practice Set 106

Unit 7 Operating Systems 108

7.1 Categories 109

7.2 Components 111

7.3 Popular Operating Systems 118

7.4 References and Recommended Readings 121

7.5 Summary 121

7.6 Practice Set 122

Unit 8 Algorithm 125

8.1 What Is Algorithm? 125

8.2 Three Constructs 126

8.3 How to Evaluate Algorithms 127

8.4 Algorithm Representation 128

8.5 Basic Algorithms 129

8.6 Classification of Algorithm 136

8.7 References and Recommended Readings 140

8.8 Summary 140

8.9 Practice Set 141

Unit 9 Programming Languages 143

9.1 Development 143

9.2 Program Translation 145

9.3 Languages'Latest Ranking,Categories and Features 146

9.4 Common Concepts of Programming Languages 151

9.5 Severe Software Errors 153

9.6 References and Recommended Readings 156

9.7 Summary 156

9.8 Practice Set 157

Unit 10 Software Engineering 159

10.1 Introduction 159

10.2 Software Development Life Cycle 160

10.3 Software Development Models 165

10.4 CMMI and Software Process Management 167

10.5 Importance of Documentation 169

10.6 Service-Oriented Architecture 170

10.7 References and Recommended Readings 170

10.8 Summary 171

10.9 Practice Set 172

Unit 11 Data and File Structures 173

11.1 Abstract Data Types 173

11.2 List 174

11.3 Stack 177

11.4 Queue 177

11.5 Tree and Graph 178

11.6 File Structure 180

11.7 References and Recommended Readings 184

11.8 Summary 184

11.9 Practice Set 185

Unit 12 Databases 187

12.1 Introduction 187

12.2 Database Management Systems 188

12.3 Database Architecture 189

12.4 The History of Database Systems 189

12.5 Database Model 191

12.6 Relational Operations 195

12.7 Databases for Big Data 196

12.8 References and Recommended Readings 197

12.9 Summary 198

12.10 Practice Set 198

Unit 13 Security 200

13.1 Security Goals 200

13.2 Security Threats 201

13.3 Security Services 206

13.4 Cryptography 210

13.5 References and Recommended Readings 215

13.6 Summary 215

13.7 Practice Set 216

Unit 14 Theory of Computation 218

14.1 The Turing Machine 218

14.2 Halting Problem 222

14.3 Solvable Problems 224

14.4 References and Recommended Readings 225

14.5 Summary 226

14.6 Practice Set 226

Unit 15 Artificial Intelligence 228

15.1 Introduction 228

15.2 Knowledge Representation and Expert Systems 229

15.3 Perception 231

15.4 Reasoning 238

15.5 Nature Inspired Computation 242

15.6 References and Recommended Readings 247

15.7 Summary 248

15.8 Practice Set 248

Unit 16 Internet of Things,Cloud Computing and Data Science 250

16.1 Introduction 250

16.2 Opportunities in IoT,Cloud,and Data Science 254

16.3 Challenges and Research Directions 257

16.4 IoT Applications 260

16.5 Cloud Application Service Models 261

16.6 Cloud Application Deployment Models 262

16.7 Big Data Tools and Techniques 263

16.8 Integration of IoT,Cloud Computing,and Big Data 264

16.9 References and Recommended Readings 265

16.10 Summary 266

16.11 Practice Set 267

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