Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications

275 Pages·2022·9.117 MB·English

by  Debabrata Samanta, Naveen Chilamkurti, Mohammad Hammoudeh, SK Hafizul Islam

Data Analytics,
Computational Statistics,
and Operations
Research for Engineers

Data Analytics,
Computational Statistics,
and Operations Research
for Engineers
Methodologies and Applications
Edited by
Debabrata Samanta, SK Hafzul Islam,
Naveen Chilamkurti, and Mohammad Hammoudeh
First edition published 2022
by CRC Press
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and by CRC Press
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© 2022 selection and editorial matter, Debabrata Samanta, SK Hafzul Islam, Naveen Chilamkurti,
and Mohammad Hammoudeh; individual chapters, the contributors
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Library of Congress Cataloging‑in‑Publication Data
Names: Samanta, Debabrata, 1987– editor.
Title: Data analytics, computational statistics, and operations research for engineers :
methodologies and applications / edited by Debabrata Samanta, SK Hafzul Islam, Naveen
Chilamkurti, and Mohammad Hammoudeh.
Description: First edition. | Boca Raton, FL : CRC Press, [2022] | Includes bibliographical
references and index.
Identifers: LCCN 2021046713 (print) | LCCN 2021046714 (ebook) | ISBN 9780367715113 (hbk) |
ISBN 9780367715120 (pbk) | ISBN 9781003152392 (ebk)
Subjects: LCSH: Engineering—Data processing.
Classifcation: LCC TA345 .D28 2022 (print) | LCC TA345 (ebook) | DDC 620.001/51—dc23/
eng/20211118
LC record available at https://lccn.loc.gov/2021046713
LC ebook record available at https://lccn.loc.gov/2021046714
ISBN: 978-0-367-71511-3 (hbk)
ISBN: 978-0-367-71512-0 (pbk)
ISBN: 978-1-003-15239-2 (ebk)
DOI: 10.1201/9781003152392
Typeset in Times
by Apex CoVantage, LLC
To my parents Mr. Dulal Chandra Samanta, Mrs. Ambujini
Samanta, my elder sister Mrs. Tanusree Samanta, and
daughter Ms. Aditri Samanta
Dr. Debabrata Samanta
To my son Mr. Enayat Rabbi
Dr. SK Hafzul Islam

Contents
Preface ....................................................................................................... xvii
Acknowledgments ...................................................................................... xxiii
Editor Biographies ...................................................................................... xxv
Chapter 1 Hyperspectral Imagery Applications for Precision Agriculture:
A Systemic Survey ...............................................................................1
Chanki Pandey, Yogesh Kumar Sahu, Prabira Kumar Sethy,
and Santi Kumari Behera
1.1 Introduction ...............................................................................1
1.1.1 The Main Contribution of the Chapter.........................3
1.2 Hyperspectral Imaging Technology..........................................4
1.3 Agricultural Applications..........................................................6
1.3.1 Soil Analysis.................................................................8
1.3.2 Contaminants and Nutrient Estimation...................... 10
1.3.3 Inland Water and Moisture Estimation......................12
1.3.4 Crop Yield Estimation................................................16
1.3.5 Plant Disease Monitoring, Insect Pesticide
Monitoring, and Invasive Plant Species..................... 19
1.3.6 Agricultural Crop Classifcation ................................22
1.4 Conclusion and Future Scope..................................................23
References ..........................................................................................26
Chapter 2 Early Prediction of COVID-19 Using Modifed Convolutional
Neural Networks ................................................................................39
Asadi Srinivasulu, Umesh Neelakantan, Tarkeswar Barua,
Srinivas Nowduri, and MM Subramanyam
2.1 Introduction .............................................................................40
2.1.1 Graph for Deaths........................................................40
2.2 What We Cover In................................................................... 43
2.3 Literature Survey.....................................................................43
2.4 Related Work...........................................................................45
2.4.1 Existing System..........................................................45
2.5 Proposed System .....................................................................46
2.6 System Design and Implementation ........................................47
2.7 Paper Implementation Details................................................. 47
2.7.1 System Modules ......................................................... 47
2.7.1.1 Collecting Data Sources ............................. 47
2.7.1.2 Data in Structured....................................... 47
2.7.1.3 Preprocessing Datasets ............................... 47
vii
viii Contents
2.7.1.4 Feature Learning ........................................48
2.7.2 Implementing Using Structured Data ........................48
2.7.3 K-Nearest Neighbor....................................................49
2.7.3.1 Data Input ...................................................49
2.7.3.2 Output .........................................................49
2.7.3.3 Method........................................................49
2.7.3.4 Neural Networks.........................................49
2.7.3.5 Procedure....................................................50
2.7.3.6 Step 1: Representation of Text Data............50
2.7.3.7 Step 2: Convolution Layer of Text
MCNN ........................................................50
2.7.3.8 Step 3: POOL Layer of Text-Modifed
CNN............................................................ 51
2.7.3.9 Step 4: Full Connection Layer
of Text-Modifed CNN................................ 51
2.7.3.10 Step 5: Modifed CNN Classifer................51
2.7.4 Logical Flow of Neural Network ............................... 52
2.8 Results ..................................................................................... 52
2.9 Conclusion ............................................................................... 55
References ..........................................................................................59
Chapter 3 Blockchain for Electronic Voting System .......................................... 61
Subba Reddy Bonthu, Suchismitaa Chakraverty, Nadimpalli
siva subrahmanya Varma, Ramani S, and Marimuthu Karuppiah
3.1 Introduction ............................................................................. 62
3.2 Methods Used for Voting ........................................................63
3.2.1 Paper Ballots ..............................................................63
3.2.2 E-Voting......................................................................63
3.2.3 I-Voting.......................................................................64
3.3 Current E-Voting System Gaps ...............................................64
3.3.1 Deploying Proprietary Software ................................64
3.3.2 Nontransparency in Enlisting Software Version........65
3.3.3 Minimal Security against Day-to-Day Attacks..........65
3.3.4 Incompatibility of Voting Machine and Voting
Software .....................................................................65
3.4 Introduction to Blockchain ......................................................65
3.4.1 Blockchain Network...................................................67
3.4.2 Countries that Used Blockchain for Voting ...............69
3.4.2.1 Sierra Leone................................................70
3.4.2.2 Russia..........................................................70
3.5 Working of E-Voting Using Blockchain..................................71
3.5.1 Requesting for Vote....................................................71
3.5.2 Casting the Vote......................................................... 71
3.5.3 Encrypting Votes........................................................72
3.5.4 Appending the Vote ....................................................72
Contents ix
3.6 Blockchain as a Service...........................................................72
3.6.1 Smart Contracts..........................................................72
3.6.2 Noninteractive Zero Knowledge Proof ......................72
3.7 Blockchain as a Service for E-Voting ......................................73
3.7.1 Election as a Smart Contract......................................73
3.7.2 Election Roles.............................................................73
3.7.2.1 Election administrators...............................73
3.7.2.2 Voters..........................................................73
3.7.2.3 District nodes..............................................73
3.7.2.4 Bootnodes................................................... 74
3.7.3 Election Process ......................................................... 74
3.7.3.1 Election Creation ........................................ 74
3.7.3.2 Voter Registration.......................................74
3.7.3.3 Vote Transaction......................................... 74
3.7.3.4 Tallying the Results .................................... 75
3.7.3.5 Verifying the Vote ...................................... 75
3.7.4 Evaluating Blockchain as a Service for E-Voting ...... 75
3.7.4.1 Exonum.......................................................75
3.7.4.2 Quorum....................................................... 75
3.7.4.3 Geth ............................................................ 76
3.8 Current Proposed Solutions in E-Voting System..................... 76
3.8.1 General....................................................................... 76
3.8.2 Coin Based .................................................................77
3.8.3 Integrity of the Data...................................................77
3.8.4 Consensus...................................................................77
3.8.5 Competitive Consensus .............................................. 78
3.8.6 Proof of Work.............................................................78
3.8.7 Proof of Stake............................................................. 78
3.8.8 Delegated Proof of Stake............................................79
3.8.9 Noncompetitive Consensus ........................................80
3.9 Benefts of Blockchain-Based E-Voting System......................80
3.9.1 Challenges for Blockchain-Based E-Voting
System......................................................................... 81
3.10 Security Analysis and Legal Issues.........................................82
3.10.1 Possible Attacks on Blockchain Network...................82
3.10.1.1 Distributed Denial of Service.....................82
3.10.1.2 Routing Attacks ..........................................82
3.10.1.3 Sybil Attacks...............................................83
3.10.2 Anonymity..................................................................83
3.10.3 Confdentiality............................................................83
3.10.4 Ballot Manipulation....................................................83
3.10.5 Transparency ..............................................................83
3.10.6 Auditability. ................................................................84
3.10.7 Nonrepudiation...........................................................84
3.11 Conclusion ...............................................................................84
References ..........................................................................................85