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Concise guide to computing foundations [electronic resource] : core concepts and select scientific applications

Concise guide to computing foundations [electronic resource] : core concepts and select scientific applications

자료유형
E-Book(소장)
개인저자
Brewer, Kevin. Bareiss, Cathy.
서명 / 저자사항
Concise guide to computing foundations [electronic resource] : core concepts and select scientific applications / by Kevin Brewer, Cathy Bareiss.
발행사항
Cham :   Springer International Publishing :   Imprint: Springer,   2016.  
형태사항
1 online resource (xv, 191 p.) : ill. (some col.).
ISBN
9783319299549
요약
This unique textbook pioneers a new approach to educating the general student about computing to practically address the needs of today’s society. This approach provides an accessible introduction to the key concepts in computer science and how these are applied to support other areas of science, highlighting the important interconnections between the different disciplines. Topics and features: Provides a strong interdisciplinary introduction to computational science Discusses such issues as the use of computer simulations, the limits of precision in a computer, and the amount of work performed by software to complete a task Covers the cross-disciplinary application of data representation, algorithms, self-defining data, and performance complexity Examines the close links between computer science and such scientific and engineering fields as bioinformatics, chemical kinetics, hydrogeological modeling, and mechanics of materials Describes the contributions of computer science to engineering analysis, GIS, flow analysis, solving equations, curve fitting, optimization, and data acquisition Contains review questions, exercises, and discussion prompts throughout the text, together with chapter objectives and an appendix on using LabQuest This classroom-tested and activity-based textbook has been developed for teaching second-semester freshmen and sophomore non-computer science STEM majors, structured around a discovery learning approach. The work is also ideal for self-teaching. Dr. Kevin Brewer is Co-Chair and Professor in the Department of Engineering in the Walker School of Engineering at Olivet Nazarene University, Bourbonnais, IL, USA. Dr. Cathy Bareiss is a Professor of Computer Science at the same institution.
일반주기
Title from e-Book title page.  
내용주기
Introduction to Computational Science -- Types of Visualization and Modeling -- Data Types: Representation, Abstraction, Limitations -- Scientific Data Acquisition -- Procedures: Algorithms and Abstraction -- Solving Equations -- Iterative Solutions -- Solving Sets of Equations -- Procedures: Performance and Complexity -- Self-Defining Data: Compression, XML and Databases -- Searching -- Curve Fitting -- Optimization -- Data Organization and Analysis -- Appendix A: NetLogo -- Appendix B: LabQuest -- Appendix C: GIS.
서지주기
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
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007 cr
008 200508s2016 sz a ob 001 0 eng d
020 ▼a 9783319299549
040 ▼a 211009 ▼c 211009 ▼d 211009
082 0 4 ▼a 005.743 ▼2 23
084 ▼a 005.743 ▼2 DDCK
090 ▼a 005.743
100 1 ▼a Brewer, Kevin.
245 1 0 ▼a Concise guide to computing foundations ▼h [electronic resource] : ▼b core concepts and select scientific applications / ▼c by Kevin Brewer, Cathy Bareiss.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2016.
300 ▼a 1 online resource (xv, 191 p.) : ▼b ill. (some col.).
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
505 0 ▼a Introduction to Computational Science -- Types of Visualization and Modeling -- Data Types: Representation, Abstraction, Limitations -- Scientific Data Acquisition -- Procedures: Algorithms and Abstraction -- Solving Equations -- Iterative Solutions -- Solving Sets of Equations -- Procedures: Performance and Complexity -- Self-Defining Data: Compression, XML and Databases -- Searching -- Curve Fitting -- Optimization -- Data Organization and Analysis -- Appendix A: NetLogo -- Appendix B: LabQuest -- Appendix C: GIS.
520 ▼a This unique textbook pioneers a new approach to educating the general student about computing to practically address the needs of today’s society. This approach provides an accessible introduction to the key concepts in computer science and how these are applied to support other areas of science, highlighting the important interconnections between the different disciplines. Topics and features: Provides a strong interdisciplinary introduction to computational science Discusses such issues as the use of computer simulations, the limits of precision in a computer, and the amount of work performed by software to complete a task Covers the cross-disciplinary application of data representation, algorithms, self-defining data, and performance complexity Examines the close links between computer science and such scientific and engineering fields as bioinformatics, chemical kinetics, hydrogeological modeling, and mechanics of materials Describes the contributions of computer science to engineering analysis, GIS, flow analysis, solving equations, curve fitting, optimization, and data acquisition Contains review questions, exercises, and discussion prompts throughout the text, together with chapter objectives and an appendix on using LabQuest This classroom-tested and activity-based textbook has been developed for teaching second-semester freshmen and sophomore non-computer science STEM majors, structured around a discovery learning approach. The work is also ideal for self-teaching. Dr. Kevin Brewer is Co-Chair and Professor in the Department of Engineering in the Walker School of Engineering at Olivet Nazarene University, Bourbonnais, IL, USA. Dr. Cathy Bareiss is a Professor of Computer Science at the same institution.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
700 1 ▼a Bareiss, Cathy.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-29954-9
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 005.743 등록번호 E14021713 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

컨텐츠정보

목차

CONTENTS
1 Introduction to Computational Science = 1
 1.1 Objectives = 1
 1.2 Definitions = 1
 1.3 Introductory Example = 2
 1.4 Another Example = 4
 1.5 What Is Computational Science? = 6
 1.6 Related Modules = 8
 References = 8
2 Types of Visualization and Modeling = 9
 2.1 Objectives = 9
 2.2 Definitions =. 9
 2.3 Motivation = 9
 2.4 Introduction = 10
 2.5 Agent-Based Chemical Kinetics = 11
 2.6 Systems Dynamics Chemical Kinetics = 15
  2.6.1 Simple First Order Reaction = 15
  2.6.2 Reversible First Order Reactions = 18
 2.7 Computing Questions = 19
 2.8 Related Modules = 19
 References = 20
3 Data Types : Representation, Abstraction, Limitations = 21
 3.1 Objectives = 21
 3.2 Definitions = 21
 3.3 Motivation = 22
 3.4 Abstraction = 22
 3.5 Limitations and Space Issues = 24
 3.6 Limits and Errors = 26
 3.7 Order of Operation = 28
 3.8 Accuracy and Speed = 29
 3.9 Collecting Groups of Similar Data = 32
 3.10 Adding Structure to the Homogeneous : Trees = 35
 3.11 Adding Structure to the Homogeneous Collections : Graphs = 36
 3.12 Adding Structure to Homogeneous Collections : Stacks and Queues = 37
 3.13 Related Modules = 38
 References = 38
4 Scientific Data Acquisition = 39
 4.1 Objectives = 39
 4.2 List of Terms = 39
 4.3 Motivation = 39
 4.4 A First Problem – Introduction = 40
 4.5 Sensor Considerations = 41
 4.6 Computing Issues = 42
 4.7 A Second Problem – Design = 43
 4.8 A Third Problem – Bonus = 44
 4.9 Computing Questions = 44
 4.10 Related Modules = 44
5 Procedures : Algorithms and Abstraction = 45
 5.1 Objectives = 45
 5.2 Definitions = 45
 5.3 Motivation = 45
 5.4 Procedures = 46
 5.5 Control Structure Example = 47
 5.6 Procedural Abstraction = 48
 5.7 Theater Lights Part 1 = 48
 5.8 Theater Lights Part 2 = 51
 5.9 Leaves on the River Part 1 = 52
 5.10 Leaves on the River Part 2 = 55
 5.11 Related Modules = 57
 References = 57
6 Solving Equations = 59
 6.1 Objectives = 59
 6.2 List of Terms = 59
 6.3 Motivation = 59
 6.4 Discussion = 60
 6.5 Computing Questions = 62
 6.6 Related Modules = 63
 Web Resources = 63
7 Iterative Solutions = 65
 7.1 Objectives = 65
 7.2 List of Terms = 65
 7.3 Motivation = 65
 7.4 An Example : Have a Hang-Up = 66
 7.5 Another Design : Out on a Limb = 70
 7.6 The Solution Is at Hand… with Solver = 74
 7.7 But Wait, There''''s More! = 78
 7.8 Integers Are Not Real...Numbers = 80
 7.9 Computing Questions = 80
 7.10 Related Modules = 81
 References = 81
8 Solving Sets of Equations = 83
 8.1 Objectives = 83
 8.2 Definitions = 83
 8.3 Motivation = 84
 8.4 Problem Definition = 84
 8.5 Boundary Conditions = 85
 8.6 Solution Methods = 86
 8.7 Numerical Aspects = 86
 8.8 An Excel Solution = 89
 8.9 Setting Up Excel for Iterative Calculation = 90
 8.10 A Matrix Solution = 92
 8.11 The Modeling Process = 94
 8.12 Computing Questions = 95
 8.13 Related Modules = 95
 Further Study = 95
9 Procedures : Performance and Complexity = 97
 9.1 Objectives = 97
 9.2 Definitions = 97
 9.3 Motivation = 97
 9.4 Simulation Model Performance = 98
 9.5 Example of Computational Complexity : Tick Marks = 99
 9.6 Another Example of Computational Complexity : Color a Square of Patches in NetLogo = 102
 9.7 Example of Computational Complexity : Merge Sort = 103
 9.8 Standard Big-Oh Function Classifications for Comparing Algorithms = 105
 9.9 Related Modules = 107
 References = 107
10 Self-Defining Data : Compression, XML and Databases = 109
 10.1 Objectives = 109
 10.2 Definitions = 109
 10.3 Motivation = 109
 10.4 Self-Defining Type 1 : Compression = 110
 10.5 Self-Defining Type 2 : XML = 112
 10.6 Self-Defining Type 3 : Databases = 112
 10.7 Self-Defining Type 3 Part 2 : Data Warehouses = 115
 10.8 Self-Defining Type 3 Part 3 : Other Database Types = 117
 10.9 Related Modules = 118
 Reference = 118
11 Searching = 119
 11.1 Objectives = 119
 11.2 Definitions = 119
 11.3 Motivation = 120
 11.4 Searching Amino Acids = 120
 11.5 BLASTP Algorithm = 123
 11.6 Computing Questions = 125
 11.7 Related Modules = 126
 Ten Protein Sequences of 99 Amino Acids = 126
 References = 127
12 Curve Fitting = 129
 12.1 Objectives = 129
 12.2 Definitions = 129
 12.3 Motivation = 129
 12.4 Fitting "By Hand" = 130
 12.5 Fitting By Hand with Graphing Aid = 131
 12.6 Fitting via Numerical Analysis (Regression) = 132
 12.7 Fitting via Excel = 133
 12.8 Computing Questions = 134
 12.9 Related Modules = 134
13 Optimization = 135
 13.1 Objectives = 135
 13.2 Definitions = 135
 13.3 Motivation = 135
 13.4 What Makes Up an Optimization Problem? = 136
 13.5 What Is the "Language" of an Optimization Problem? = 136
 13.6 Working Through the Setup of an Optimization Problem = 137
 13.7 Solving an Optimization Problem = 139
 13.8 Simulated Annealing = 139
 13.9 Genetic Algorithm = 142
 13.10 Linear Programming = 145
 13.11 Simplex Method = 146
 13.12 Computing Questions = 148
 13.13 Related Modules = 149
 References = 149
14 Data Organization and Analysis = 151
 14.1 Objectives = 151
 14.2 Definitions = 151
 14.3 Motivation = 152
 14.4 Spatial Data Representation = 152
 14.5 Joining Data = 152
 14.6 Spatial Joining = 156
 14.7 Computing Questions = 156
 14.8 Related Modules = 157
 Reference = 157
Appendix : NetLogo Tutorial = 159
Appendix : LabQuest Tutorial = 165
Appendix : GIS Tutorial = 173
Definitions = 181
Index = 189

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