Data Science in Engineering and Management

Book description

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis.

Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively.

This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Table of contents

  1. Cover
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Editors
  8. Contributors
  9. 1 Concepts for Effective Mobile Device Management in an Enterprise Environment
    1. 1.1 Introduction
    2. 1.2 Review of the Literature
    3. 1.3 Problem Statement
    4. 1.4 Methodology
    5. 1.5 Experimental Analysis
    6. 1.6 Results Obtained from Experimentation
    7. 1.7 Discussion and Future Directions
    8. 1.8 Conclusion
    9. References
  10. 2 Prioritization of Informational Factors and Query Intensification Using a Meta-Heuristic Approach
    1. 2.1 Introduction
    2. 2.2 Review of Literature
    3. 2.3 Schema Update and Modification with Heterogeneity
    4. 2.4 Allocation of Dynamically Linked Queries
    5. 2.5 Significance of Join Ordering Algorithms
      1. 2.5.1 Algorithm: Implementation Using the Iterative Approach
      2. 2.5.2 Intensification of Queries in Databases
    6. 2.6 Implementation of a Meta-heuristic Approach
      1. 2.6.1 Application of Firefly Algorithms
      2. 2.6.2 Pseudo-Code for Query Intensification Using the Firefly Approach
      3. 2.6.3 Algorithm: Implementation Using the Firefly Approach
      4. 2.6.4 Query Response Time and Linkage to Query Intensification
    7. 2.7 Discussion and Future Directions
    8. 2.8 Conclusion
    9. References
  11. 3 Estimation and Potential Evaluation of Data Linked to Virtual Machines Using a Computational Approach
    1. 3.1 Introduction
    2. 3.2 Review of Literature
    3. 3.3 Implementation Using Particle Swarm Optimization
    4. 3.4 Accumulation of Materialized Data by Selecting and Implementing Particle Swarm Optimization
      1. 3.4.1 Procedure for Importing and Accessing Data
      2. 3.4.2 Algorithm to Implement Data Using PSO
      3. 3.4.3 Algorithm to Initialize Swarm Variables to Update Particle Position
    5. 3.5 Experimental Analysis
    6. 3.6 Discussion and Future Directions
    7. 3.7 Conclusion
    8. References
  12. 4 Potential Applications of Blockchain Technology in the Construction Sector
    1. 4.1 Introduction
    2. 4.2 Review of Literature
    3. 4.3 Overview of Blockchain in Construction
    4. 4.4 Potential Applications of Blockchain Technology in Construction
      1. 4.4.1 Smart Contracts
      2. 4.4.2 Combining Smart Contracts to Create a Decentralized Autonomous Organization
      3. 4.4.3 Building Information Modeling
      4. 4.4.4 Decentralized Network Management of Devices
      5. 4.4.5 Rationalization of Financing and Payments
      6. 4.4.6 Compliance Simplification
      7. 4.4.7 Supply Chain Management (Origin and Traceability)
      8. 4.4.8 3D Printing of New Construction Parts
    5. 4.5 Conclusion
    6. References
  13. 5 Artificial Neural Network Applications in Social Media Activities: Impact on Depression during the COVID-19 Pandemic
    1. 5.1 Introduction
    2. 5.2 Methods
      1. 5.2.1 Data Collection
      2. 5.2.2 Data Analysis
    3. 5.3 Results
      1. 5.3.1 Regression Model
      2. 5.3.2 Classification Models
    4. 5.4 Discussion
    5. Bibliography
  14. 6 Analysis of CCT through ANFIS for a Grid-Connected SPV System
    1. 6.1 Introduction
    2. 6.2 Fuzzy Control Techniques
      1. 6.2.1 Proposed Control Strategies
    3. 6.3 Design of THE Fuzzy Logic Controller for THE Inner Current Control Loop
      1. 6.3.1 Design of the Fuzzy Logic Controller for the Outer Voltage Control Loop
      2. 6.3.2 Design of the ANFIS Controller
    4. 6.4 Analysis of Results
    5. 6.5 Conclusion
    6. Bibliography
  15. 7 Frequency Analysis of Human Brain Response to Sudarshan Kriya Meditation
    1. 7.1 Introduction
      1. 7.1.1 Brain State/Human State of Mind
    2. 7.2 Levels of Consciousness
    3. 7.3 Discussion of Techniques Available to Record the Human Brain Response
    4. 7.4 Objective
    5. 7.5 Literature Survey
    6. 7.6 Contributory work
    7. 7.7 Experimental Setup
    8. 7.8 Conclusion
    9. 7.9 Future Work
    10. Acknowledgments
    11. References
  16. 8 Coordinated Control Action between a DFIG-Grid Interconnected System Using a PI-Based SVM Controller
    1. 8.1 Introduction
    2. 8.2 Problem Formulation and Solution
    3. 8.3 Analysis of Results
    4. 8.4 Conclusion
    5. Acknowledgment
    6. Bibliography
  17. 9 Acceptance of New Schools in Semi-Urban Areas of India: An Application of Data Mining
    1. 9.1 Introduction
    2. 9.2 Literature Review
    3. 9.3 Cluster Analysis
    4. 9.4 Proposed Model
    5. 9.5 Information Gain
    6. 9.6 Experimental Setup
      1. 9.6.1 Pseudo-Code
      2. 9.6.2 Benefits of C4.5 Compared with Other Existing Decision Tree Systems
    7. 9.7 Results and Analysis
    8. 9.8 Conclusion and Future Scope
    9. Bibliography
  18. 10 Two-Phase Natural Convection of Dusty Fluid Boundary Layer Flow over a Vertical Plate
    1. 10.1 Introduction
    2. 10.2 Mathematical Formulation
    3. 10.3 Method of Solution
    4. 10.4 Results and Discussion
    5. References
  19. 11 An Interactive Injection Mold Design with CAE and Moldflow Analysis for Plastic Components
    1. 11.1 Introduction
    2. 11.2 Injection Molding
    3. 11.3 Injection Mold Design
    4. 11.4 Moldflow Analysis
    5. 11.5 Results and Discussion
    6. 11.6 Conclusion
    7. References
  20. 12 Study of Collaborative Filtering-Based Personalized RecommendationsQuality, Relevance, and Timing Effect on Users’ Decision to Purchase
    1. 12.1 Introduction
    2. 12.2 Related Work
      1. 12.2.1 Personalized Recommendations on Amazon.in Website
    3. 12.3 Research Framework and Hypotheses
      1. 12.3.1 Personalized Recommendations, Privacy Concerns
      2. 12.3.2 Personalized Recommendations and Trust
      3. 12.3.3 Privacy Concerns and Trust
      4. 12.3.4 Privacy Concerns and Purchase Intentions
      5. 12.3.5 Trust and Purchase Intentions
    4. 12.4 Research Method
      1. 12.4.1 Data Collection and Sampling
      2. 12.4.2 Measurement Model
        1. 12.4.2.1 Structural Equation Modeling
    5. 12.5 Results and Discussion
    6. 12.6 Conclusions and Future Scope of Research
    7. References
  21. Index

Product information

  • Title: Data Science in Engineering and Management
  • Author(s): Zdzislaw Polkowski, Sambit Kumar Mishra, Julian Vasilev
  • Release date: December 2021
  • Publisher(s): CRC Press
  • ISBN: 9781000520842