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Mathematics and Computer Science, Volume 1. Edition No. 1

  • Book

  • 560 Pages
  • August 2023
  • John Wiley and Sons Ltd
  • ID: 5842803
MATHEMATICS AND COMPUTER SCIENCE

This first volume in a new multi-volume set gives readers the basic concepts and applications for diverse ideas and innovations in the field of computing together with its growing interactions with mathematics.

This new edited volume from Wiley-Scrivener is the first of its kind to present scientific and technological innovations by leading academicians, eminent researchers, and experts around the world in the areas of mathematical sciences and computing. The chapters focus on recent advances in computer science, and mathematics, and where the two intersect to create value for end users through practical applications of the theory.

The chapters herein cover scientific advancements across a diversified spectrum that includes differential as well as integral equations with applications, computational fluid dynamics, nanofluids, network theory and optimization, control theory, machine learning and artificial intelligence, big data analytics, Internet of Things, cryptography, fuzzy automata, statistics, and many more. Readers of this book will get access to diverse ideas and innovations in the field of computing together with its growing interactions in various fields of mathematics. Whether for the engineer, scientist, student, academic, or other industry professional, this is a must-have for any library.

Table of Contents

Preface xix

1 Error Estimation of the Function by (Z ru ,r ≥ 1) Using Product Means (E,s)( N, pn ,,qn) n of) the Conjugate Fourier Series 1
Aradhana Dutt Jauhari and Pankaj Tiwar

1.1 Introduction 1

1.1.1 Definition 1 2

1.1.2 Definition 2 2

1.1.3 Definition 3 2

1.2 Theorems 5

1.2.1 Theorem 1 5

1.2.2 Theorem 2 5

1.3 Lemmas 6

1.3.1 Lemma 1 6

1.3.2 Lemma 2 6

1.3.3 Lemma 3 9

1.4 Proof of the Theorems 9

1.4.1 Proof of the Theorem 1 9

1.4.2 Proof of the Theorem 2 15

1.5 Corollaries 16

1.5.1 Corollary 1 16

1.5.2 Corollary 2 16

1.6 Example 16

1.7 Conclusion 18

References 18

2 Blow Up and Decay of Solutions for a Klein-Gordon Equation With Delay and Variable Exponents 21
Hazal Yüksekkaya and Erhan Pişkin

2.1 Introduction 21

2.2 Preliminaries 23

2.3 Blow Up of Solutions 26

2.4 Decay of Solutions 36

Acknowledgment 43

References 43

3 Some New Inequalities Via Extended Generalized Fractional Integral Operator for Chebyshev Functional 45
Bhagwat R. Yewale and Deepak B. Pachpatte

3.1 Introduction 45

3.2 Preliminaries 46

3.3 Fractional Inequalities for the Chebyshev Functional 47

3.4 Fractional Inequalities in the Case of Extended Chebyshev Functional 53

3.5 Some Other Fracional Inequalities Related to the Extended Chebyshev Functional 57

3.6 Concluding Remark 63

References 64

4 Blow Up of the Higher-Order Kirchhoff-Type System With Logarithmic Nonlinearities 67
Nazlı Irkil and Erhan Pişkin

4.1 Introduction 67

4.2 Preliminaries 69

4.3 Blow Up for Problem for E (0) < d 78

4.4 Conclusion 84

References 85

5 Developments in Post-Quantum Cryptography 89
Srijita Sarkar, Saranya Kumar, Anaranya Bose and Tiyash Mukherjee

5.1 Introduction 90

5.2 Modern-Day Cryptography 90

5.2.1 Symmetric Cryptosystems 91

5.2.2 Asymmetric Cryptosystems 91

5.2.3 Attacks on Modern Cryptosystems 92

5.2.3.1 Known Attacks 93

5.2.3.2 Side-Channel Attacks 93

5.3 Quantum Computing 93

5.3.1 The Main Aspects of Quantum Computing 94

5.3.2 Shor’s Algorithm 95

5.3.3 Grover’s Algorithm 96

5.3.4 The Need for Post-Quantum Cryptography 96

5.4 Algorithms Proposed for Post-Quantum Cryptography 97

5.4.1 Code-Based Cryptography 97

5.4.2 Lattice-Based Cryptography 98

5.4.3 Multivariate Cryptography 99

5.4.4 Hash-Based Cryptography 99

5.4.5 Supersingular Elliptic Curve Isogeny Cryptography 100

5.4.6 Quantum-Resistant Symmetric Key Cryptography 100

5.5 Launching of the Project Called “Open Quantum Safe” 100

5.6 Algorithms Proposed During the NIST Standardization Procedure for Post-Quantum Cryptography 101

5.7 Hardware Requirements of Post-Quantum Cryptographic Algorithms 101

5.7.1 NTRUEncrypt 101

5.7.1.1 Polynomial Multiplication 102

5.7.1.2 Hardware to Accelerate NTRUEncrypt 103

5.7.2 Hardware-Software Design to Implement PCQ Algorithms 103

5.7.3 Implementation of Cryptographic Algorithms Using HLS 103

5.8 Challenges on the Way of Post-Quantum Cryptography 104

5.9 Post-Quantum Cryptography Versus Quantum Cryptography 105

5.10 Future Prospects of Post-Quantum Cryptography 106

References 107

6 A Statistical Characterization of MCX Crude Oil Price with Regard to Persistence Behavior and Seasonal Anomaly 111
Anindita Bhattacharjee, Jaya Mamta Prosad and M.K. Das

6.1 Introduction 111

6.2 Related Literature 113

6.3 Data Description and Methodology 114

6.3.1 Data 114

6.3.2 Methodology 115

6.3.2.1 Characterizing Persistence Behavior of Crude Oil Return Time Series Using Hurst Exponent 115

6.3.2.2 Zipf Plot 116

6.3.2.3 Seasonal Anomaly in Oil Returns 117

6.4 Analysis and Findings 117

6.4.1 Persistence Behavior of Daily Oil Stock Price 117

6.4.2 Detecting Seasonal Pattern in Oil Prices 121

6.5 Conclusion and Implications 123

References 125

Appendix 128

7 Some Fixed Point and Coincidence Point Results Involving Gα -Type Weakly Commuting Mappings 133
Krishna Kanta Sarkar, Krishnapada Das and Abhijit Pramanink

7.1 Introduction 133

7.2 Definitions and Mathematical Preliminaries 134

7.2.1 Definition: G-metric Space (G-ms) 134

7.2.2 Definition: t-norm 135

7.2.3 Definition: t-norm of Hadžić type (H-type) 135

7.2.4 Definition: G-fuzzy metric space (G-fms) 135

7.2.5 Definition 136

7.2.6 Lemma 136

7.2.7 Lemma 136

7.2.8 Definition 136

7.2.9 Definition 136

7.2.10 Definition: Φ-Function 136

7.2.11 Definition: Ψ-Function 137

7.2.12 Lemma 137

7.2.13 Definition 138

7.2.14 Definition 138

7.2.15 Definition 138

7.2.16 Definition 138

7.2.17 Definition 139

7.2.18 Remarks 139

7.2.19 Lemma 139

7.3 Main Results 140

7.3.1 Theorem 140

7.3.2 Theorem 144

7.3.3 Definition Ψ-Function 151

7.3.4 Theorem 152

7.3.5 Theorem 159

7.3.6 Corollary 167

7.3.7 Corollary 168

7.3.8 Example 169

7.3.9 Example 169

7.3.10 Example 170

7.3.11 Example 170

7.4 Conclusion 170

7.5 Open Question 171

References 171

8 Grobner Basis and Its Application in Motion of Robot Arm 173
Anjan Samanta

8.1 Introduction 173

8.1.1 Define Orderings in K[y1 , ., yn] 174

8.1.2 Introducing Division Rule in K[y1 , ., yn] 174

8.2 Hilbert Basis Theorem and Grobner Basis 175

8.3 Properties of Grobner Basis 175

8.4 Applications of Grobner Basis 176

8.4.1 Ideal Membership Problem 176

8.4.2 Solving Polynomial Equations 177

8.5 Application of Grobner Basis in Motion of Robot Arm 178

8.5.1 Geometric Elucidation of Robots 178

8.5.2 Mathematical Representation 179

8.5.3 Forward Kinematic Problem 179

8.5.4 Inverse Kinematic Problem 182

8.6 Conclusion 189

References 189

9 A Review on the Formation of Pythagorean Triplets and Expressing an Integer as a Difference of Two Perfect Squares 191
Souradip Roy, Tapabrata Bhattacharyya, Subhadip Roy, Souradeep Paul and Arpan Adhikary

9.1 Introduction 191

9.2 Calculation of Triples 193

9.2.1 Calculation for Odd Numbers 193

9.2.2 Calculation for Even Numbers 195

9.2.3 Code Snippet 199

9.2.4 Observation 200

9.3 Computing the Number of Primitive Triples 200

9.3.1 Calculation for Odd Numbers 200

9.3.2 Calculation for Even Numbers 203

9.3.3 Code Snippet 204

9.3.4 Observation 205

9.4 Representation of Integers as Difference of Two Perfect Squares 205

9.4.1 Calculation for Odd Numbers 205

9.4.2 Calculation for Even Numbers 206

9.4.3 Corollaries 208

9.4.4 Code Snippet 210

9.4.5 Output 210

9.5 Conclusion 211

References 211

10 Solution of Matrix Games With Pay‐Offs of Single-Valued Neutrosophic Numbers and Its Application to Market Share Problem 213
Mijanur Rahaman Seikh and Shibaji Dutta

10.1 Introduction 213

10.2 Preliminaries 216

10.3 Matrix Games With SVNN Pay-Offs and Concept of Solution 218

10.4 Mathematical Model Construction for SVNNMG 219

10.4.1 Algorithm for Solving SVNNMG 223

10.5 Numerical Example 224

10.5.1 A Market Share Problem 224

10.5.2 The Solution Procedure and Result Discussion 226

10.5.3 Analysis and Comparison of Results With li and Nan’s Approach 227

10.6 Conclusion 228

References 228

11 A Novel Score Function-Based EDAS Method for the Selection of a Vacant Post of a Company with q-Rung Orthopair Fuzzy Data 231
Utpal Mandal and Mijanur Rahaman Seikh

11.1 Introduction 231

11.2 Preliminaries 234

11.3 A Novel Score Function of q-ROFNs 236

11.3.1 Some Existing q-ROF Score Functions 236

11.3.2 A Novel Score Function of q-ROFNs 237

11.4 EDAS Method for q-ROF MADM Problem 240

11.5 Numerical Example 244

11.6 Comparative Analysis 246

11.7 Conclusions 247

Acknowledgments 248

References 248

12 Complete Generalized Soft Lattice 251
Manju John and Susha D.

12.1 Introduction 251

12.2 Soft Sets and Soft Elements - Some Basic Concepts 252

12.3 gs-Posets and gs-Chains 253

12.4 Soft Isomorphism and Duality of gs-Posets 257

12.5 gs-Lattices and Complete gs-Lattices 259

12.6 s-Closure System and s-Moore Family 264

12.7 Complete gs-Lattices From s-Closure Systems 266

12.8 A Representation Theorem of a Complete gs-Lattice as an s-Closure System 267

12.9 gs-Lattices and Fixed Point Theorem 268

References 269

13 Data Representation and Performance in a Prediction Model 271
Apurbalal Senapati, Soumen Maji and Arunendu Mondal

13.1 Introduction 272

13.1.1 Various Methods for Predictive Modeling 272

13.1.2 Problem Definition 275

13.2 Data Description and Representations 276

13.3 Experiment and Result 281

13.4 Error Analysis 282

13.5 Conclusion 283

References 284

14 Video Watermarking Technique Based on Motion Frames by Using Encryption Method 285
Praful Saxena and Santosh Kumar

14.1 Introduction 286

14.2 Methodology Used 287

14.2.1 Discrete Wavelet Transform 287

14.2.2 Singular-Value Decomposition 289

14.3 Literature Review 289

14.4 Watermark Encryption 290

14.5 Proposed Watermarking Scheme 292

14.5.1 Watermark Embedding 292

14.5.2 Watermark Extraction 294

14.6 Experimental Results 296

14.7 Conclusion 297

References 298

15 Feature Extraction and Selection for Classification of Brain Tumors 299
Saswata Das

15.1 Introduction 299

15.2 Related Work 301

15.3 Methodology 303

15.3.1 Contrast Enhancement 303

15.3.2 K-Means Clustering 303

15.3.3 Canny Edge Detection 305

15.3.4 Feature Extraction 308

15.3.5 Feature Selection 309

15.3.5.1 Genetic Algorithm for Feature Selection 309

15.3.5.2 Particle Swarm Optimization for Feature Selection 311

15.4 Results 313

15.5 Future Scope 313

15.6 Conclusion 314

References 315

16 Student’s Self-Esteem on the Self-Learning Module in Mathematics 6 317
Ariel Gulla Villar and Biswadip Basu Mallik

16.1 Introduction 318

16.1.1 Research Questions 318

16.1.2 Scope and Limitation 319

16.1.3 Significance of the Study 319

16.2 Methodology 320

16.2.1 Research Design 320

16.2.2 Respondents of the Study 320

16.2.3 Sampling Procedure 320

16.2.4 Locale of the Study 320

16.2.5 Data Collection 321

16.2.6 Instrument of the Study 321

16.2.7 Validation of Instrument 321

16.3 Results and Discussion 322

16.4 Conclusion 329

16.5 Recommendation 330

References 331

17 Effects on Porous Nanofluid due to Internal Heat Generation and Homogeneous Chemical Reaction 333
Hiranmoy Mondal and Sharmistha Ghosh

Nomenclature 334

17.1 Introduction 334

17.2 Mathematical Formulations 336

17.3 Method of Local Nonsimilarity 341

17.4 Results and Discussions 342

17.5 Concluding Remarks 348

References 349

18 Numerical Solution of Partial Differential Equations: Finite Difference Method 353
Roushan Kumar, Rakhi Tiwari and Rashmi Prasad

18.1 Introduction 353

18.2 Finite Difference Method 356

18.2.1 Finite Difference Approximations to Derivatives 356

18.2.2 Discretization of Domain 356

18.2.3 Difference Scheme of Partial Differential Equation 358

18.3 Multilevel Explicit Difference Schemes 360

18.4 Two-Level Implicit Scheme 364

18.5 Conclusion 371

References 371

19 Godel Code Enciphering for QKD Protocol Using DNA Mapping 373
Partha Sarathi Goswami and Tamal Chakraborty

19.1 Introduction 374

19.2 Related Work 375

19.3 The DNA Code Set 376

19.4 Godel Code 376

19.5 Key Exchange Protocol 378

19.6 Encoding and Decoding of the Plain Text - The QKD Protocol 378

19.6.1 Plain Text to Encoded Text and Vice-Versa 379

19.6.2 The Proposed Message Passing Scheme 380

19.6.3 Illustration 381

19.7 Experimental Setup 388

19.8 Detection Probability and Dark Counts 389

19.9 Security Analysis of Our Algorithm 390

19.10 Conclusion 393

References 393

20 Predictive Analysis of Stock Prices Through Scikit-Learn: Machine Learning in Python 397
Vikash Kumar Mishra, Richa Binyala, Pratibha Sharma and Simran Singh

20.1 Introduction 397

20.2 Study Area and Dataset 398

20.3 Methodology 399

20.4 Results 401

20.5 Conclusion 402

References 403

21 Pose Estimation Using Machine Learning and Feature Extraction 405
J. Palanimeera and K. Ponmozhi

21.1 Introduction 406

21.2 Related Work 408

21.3 Proposed Work 409

21.3.1 Yoga Posture Identification 410

21.3.1.1 Deep Extraction of a Normal Image 410

21.3.1.2 Human Joints Identification 411

21.3.1.3 Extraction of L-DoD Features 411

21.3.1.4 Extraction of D-GoD Features 415

21.3.2 The Random Forest Classifier’s Design 416

21.3.2.1 Construction of a Random Forest Model 416

21.3.2.2 Random Forest Two-Way Voting 417

21.3.3 Joint Positioning in Humans 418

21.4 Outcome and Discussion 420

21.5 Conclusion 422

References 423

22 E-Commerce Data Analytics Using Web Scraping 425
Vikash Kumar Mishra, Bosco Paul Alapatt, Aaditya Aggarwal and Divya Khemani

22.1 Introduction 425

22.1.1 Uses of Web Scraping 426

22.2 Research Objective 426

22.3 Literature Review 427

22.4 Feasibility and Application 428

22.4.1 Web Scrapers Process 428

22.5 Proposed Methodology 428

22.5.1 Coding Phase 429

22.5.2 Spreadsheet Analysis and Results 432

22.6 Conclusion 433

References 433

23 A New Language-Generating Mechanism of SNPSSP 435
Prithwineel Paul, Soumadip Ghosh and Anjan Pal

23.1 Introduction 436

23.2 Spiking Neural P Systems With Structural Plasticity ((SNPSSP) 437

23.3 Labeled SNPSSP (LSNPSSP) 440

23.3.1 Working of LSNPSSP 441

23.4 Main Results 442

23.5 Conclusion 450

References 450

24 Performance Analysis and Interpretation Using Data Visualization 455
Vikash Kumar Mishra, Iyyappan, M., Muskan Soni and Neha Jain

24.1 Introduction 455

24.2 Selecting Data Set 456

24.3 Proposed Methodology 457

24.4 Results 458

24.5 Conclusion 460

References 460

25 Dealing with Missing Values in a Relation Dataset Using the DROPNA Function in Python 463
Vikash Kumar Mishra, Shoney Sebastian, Maria Iqbal and Yashwin Anand

25.1 Introduction 464

25.2 Background 464

25.3 Study Area and Data Set 464

25.4 Methodology 466

25.5 Results 468

25.6 Conclusion 468

25.7 Acknowledgment 469

References 469

26 A Dynamic Review of the Literature on Blockchain-Based Logistics Management 471
C. Devi Parameswari and M. Ilayaraja

26.1 Introduction 471

26.2 Blockchain Concepts and Framework 473

26.3 Study of the Literature 475

26.3.1 Blockchain Technology and Supply Chain Trust 475

26.4 Challenges and Processes of Supply Chain Transparency 477

26.4.1 Motivation for Transparency in Data 478

26.5 Challenges in Security 478

26.6 Discussion: In Terms of Supply Chain Dynamics, Blockchain Technology and Supply Chain Integration 479

26.7 Conclusion 481

Acknowledgment 481

References 482

27 Prediction of Seasonal Aliments Using Big Data: A Case Study 485
K. Indhumathi and K. Sathesh Kumar

27.1 Introduction 486

27.2 Related Works 486

27.3 Conclusion 489

References 490

28 Implementation of Tokenization in Natural Language Processing Using NLTK Module of Python 493
Vikash Kumar Mishra, Abhimanyu Dhyani, Sushree Barik and Tanish Gupta

28.1 Introduction 493

28.2 Background 494

28.3 Study Area and Data Set 495

28.4 Proposed Methodology 495

28.5 Result 498

28.6 Conclusion 500

28.7 Acknowledgment 501

Conflicts of Interest/Competing Interests 501

Availability of Data and Material 503

References 503

29 Application of Nanofluids in Heat Exchanger and its Computational Fluid Dynamics 505
M. Appadurai, E. Fantin Irudaya Raj and M. Chithambara Thanu

29.1 Computational Fluid Dynamics 506

29.1.1 Continuity Equation 506

29.1.2 Momentum Equation 507

29.1.3 Energy Equation 508

29.1.4 Equations for Turbulent Flows 510

29.2 Nanofluids 510

29.2.1 Viscosity 511

29.2.2 Density 511

29.2.3 Heat Capacity 512

29.2.4 Thermal Conductivity 512

29.3 Preparation of Nanofluids 512

29.3.1 One-Step Method 513

29.3.2 Two-Step Method 514

29.3.3 Nanofluids Implementation in Heat Exchanger 515

29.4 Use of Computational Fluid Dynamics for Nanofluids 517

29.5 CFD Approach to Solve Heat Exchanger 518

29.6 Conclusion 522

References 522

About the Editors 525

Index 527 

Authors

Sharmistha Ghosh M. Niranjanamurthy Krishanu Deyasi Biswadip Basu Mallik Santanu Das