Numerical analysis Books

Book SynopsisThis book constitutes the refereed proceedings of the 17th International Conference on Learning and Intelligent Optimization, LION-17, held in Nice, France, during June 4–8, 2023.The 40 full papers presented have been carefully reviewed and selected from 83 submissions. They focus on all aspects of unleashing the potential of integrating machine learning and optimization approaches, including automatic heuristic selection, intelligent restart strategies, predict-then-optimize, Bayesian optimization, and learning to optimize.Table of ContentsAnomaly Classification to Enable Self-Healing in Cyber Physical Systems using Process Mining.- Hyper-box Classification Model using Mathematical Programming.- A leak localization algorithm in water distribution networks using probabilistic leak representation and optimal transport distance.- Fast and Robust Constrained Optimization via Evolutionary and Quadratic Programming.- Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing.- A Bayesian optimization algorithm for constrained simulation optimization problems with heteroscedastic noise.- Hierarchical Machine Unlearning.- Explaining the Behavior of Reinforcement Learning Agents using Explaining the Behavior of Reinforcement Learning Agents using.- Deep Randomized Networks for Fast Learning.- Generative models via Optimal Transport and Gaussian Processes.- Real-world streaming process discovery from low-level event data.- Robust Neural Network Approach to System Identification in the High-Noise Regime.- GPU for Monte Carlo Search.- Learning the Bias Weights for Generalized Nested Rollout Policy Adaptation.- Heuristics selection with ML in CP Optimizer.- Model-based feature selection for neural networks: A mixed-integer programming approach.- An Error-Based Measure for Concept Drift Detection and Characterization.- Predict, Tune and Optimize for Data-Driven Shift Scheduling with Uncertain Demands.- On Learning When to Decompose Graphical Models.- Inverse Lighting with Differentiable Physically-Based Model.- Repositioning Fleet Vehicles: a Learning Pipeline.- Bayesian Decision Trees Inspired from Evolutionary Algorithms.- Towards Tackling MaxSAT by Combining Nested Monte Carlo with Local Search.- Relational Graph Attention-based Deep Reinforcement Learning: An Application to Flexible Job Shop Scheduling with Sequence-dependent Setup Times.- Experimental Digital Twin for Job Shops with Transportation Agents.- Learning to Prune Electric Vehicle Routing Problems.- A matheuristic approach for electric bus fleet scheduling.- Class GP: Gaussian Process Modeling for Heterogeneous Functions.- Surrogate Membership for Inferred Metrics in Fairness Evaluation.- The BeMi Stardust: a Structured Ensemble of Binarized Neural Network.- Discovering explicit scale-up criteria in crisis response with decision mining.- Job Shop Scheduling via Deep Reinforcement Learning: a Sequence to Sequence approach.- Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks.- Multi-Task Predict-then-Optimize.- Integrating Hyperparameter Search into Model-Free AutoML with Context-Free Grammars.- Improving subtour elimination constraint generation in Branch-and-Cut algorithms for the TSP with Machine Learning.- Learn, Compare, Search: One Sawmill’s Search for the Best Cutting Patterns Across And/or Trees.- Dynamic Police Patrol Scheduling with Multi-Agent Reinforcement Learning.- Analysis of Heuristics for Vector Scheduling and Vector Bin Packing.- Unleashing the potential of restart by detecting the search stagnation.

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Book SynopsisThis book constitutes the refereed proceedings of the 5th Iberoamerican Conference and 4th Indo-American Conference on Knowledge Graphs and Semantic Web, KGSWC 2023, held jointly in Zaragoza, Spain, during November 13–15, 2023.The 18 full and 2 short papers presented were carefully reviewed and selected from 50 submissions. They focus on the following topics: knowledge representation; natural language processing/text mining; and machine/deep learning research.Table of ContentsAn ontology for Tuberculosis Surveillance System.- Should I Stay or Should I Go: A New Reasoner for Description Logic.- An Intelligent Article Knowledge Graph Formation Framework using BM25 Probabilistic Retrieval Model.- Defeasible Reasoning with Knowledge Graphs.- Recommendation of Learning Paths based on Open Educational Resources.- An enterprise architecture for interpersonal activity knowledge management.- Unlocking the Power of Semantic Interoperability in Industry 4.0: A Comprehensive Overview.- On the Representation of Dynamic BPMN Process Executions in Knowledge Graphs.- Towards a Framework for Seismic Data.- Using Pregel to create Knowledge Graphs subsets described by non-recursive Shape Expressions.- ITAQ : Image Tag Recommendation Framework for Aquatic Species integrating Semantic Intelligence via Knowledge Graph.- Automatic Semantic Typing of Pet E-Commerce Products Using Crowdsourced Reviews: An Experimental Study.- A Modular Ontology for MODS – Metadata Object Description Schema.- A Topic Model for the Data Web.- Automating the Generation of Competency Questions for Ontologies with AgOCQs.- KnowWhereGraph-Lite: A Perspective of the KnowWhereGraph.- Ontology-Based Models of Chatbots for Populating Knowledge Graphs.- An Ontology for Reasoning about Fairness in Regression and Machine Learning.- SCIVO: Skills to Career with Interests and Values Ontology.- Topic Modeling for Skill Extraction from Job Postings.

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Book SynopsisThe book is made up by several worked out problems concerning the application of reduced order modeling to different parametric partial differential equations problems with an increasing degree of complexity.This work is based on some experience acquired during lectures and exercises in classes taught at SISSA Mathematics Area in the Doctoral Programme Mathematical Analysis, Modelling and Applications, especially in computational mechanics classes, as well as regular courses previously taught at EPF Lausanne and during several summer and winter schools. The book is a companion for master and doctoral degree classes by allowing to go more deeply inside some partial differential equations worked out problems, examples and even exercises, but it is also addressed for researchers who are newcomers in computational mechanics with reduced order modeling. In order to discuss computational results for the worked out problems presented in this booklet, we will rely on the RBniCS Project. The

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Book SynopsisPart I Invited Articles: C. A. Beschle, A. Barth, Quasi Continuous Level Monte Carlo for Random Elliptic PDEs.- M. B. Giles, MLMC Techniques for Discontinuous Functions.- T. Helin, A. M. Stuart, A. L. Teckentrup, K. C. Zygalakis, Introduction to Gaussian Process Regression in Bayesian Inverse Problems, with new Results on Experimental Design for Weighted Error Measures.- V. Kaarnioja, Frances Y. Kuo, Ian H. Sloan, Lattice-Based Kernel Approximation and Serendipitous Weights for Parametric PDEs in Very High Dimensions.- E. Novak, Optimal Algorithms for Numerical Integration: Recent Results and Open Problems.- Chris. J. Oates, Minimum Kernel Discrepancy Estimators.- Gabriel Stoltz, Error Estimates and Variance Reduction for Nonequilibrium Stochastic Dynamics.- Part II Contributed Articles: F. Bernal, A. Berridi, Heuristics for the Probabilistic Solution of BVPs with Mixed Boundary Conditions.- Sou-Cheng T. Choi, Y. Ding, Fred J. Hickernell, J. Rathinavel, Aleksei G. Sorokin, Challenge

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Book SynopsisThe methodology has important and varied applications in machine learning, medicine, robotics, biology, computer vision, human biometrics, nanomanufacturing, signal processing, and image analysis, etc.The first chapter gives motivation examples, a wide range of applications, raised challenges, raised challenges, and some concerns.

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Book SynopsisChapter 1. Introduction to Elastic Postbuckling Behavior of Structures.- Chapter 2. A Co-Rotation-Based Secant Matrix Procedure for the Elastic Postbuckling Analysis of Truss Structures.- Chapter 3. Variable Order Secant Matrices for the Kinematically Exact Postbuckling Analysis of Beams and Frames.- Chapter 4. Variable Order Secant Matrices for Geometric Nonlinear Analysis of Thin-Walled Open Sections.- Chapter 5. Improved secant matrices for the postbuckling analysis of thin initially imperfect plates.- Chapter 6. Postbuckling Analysis of Shallow Shells Using Secant Matrices Based on Marguerre's Shell Theory.- Chapter 7. Closing Remarks.

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Book SynopsisThis new edition is a concise introduction to the basic methods of computational physics. Readers will discover the benefits of numerical methods for solving complex mathematical problems and for the direct simulation of physical processes. The book is divided into two main parts: Deterministic methods and stochastic methods in computational physics. Based on concrete problems, the first part discusses numerical differentiation and integration, as well as the treatment of ordinary differential equations. This is extended by a brief introduction to the numerics of partial differential equations. The second part deals with the generation of random numbers, summarizes the basics of stochastics, and subsequently introduces Monte-Carlo (MC) methods. Specific emphasis is on MARKOV chain MC algorithms. The final two chapters discuss data analysis and stochastic optimization. All this is again motivated and augmented by applications from physics. In addition, the book offers a number of appendices to provide the reader with information on topics not discussed in the main text. Numerous problems with worked-out solutions, chapter introductions and summaries, together with a clear and application-oriented style support the reader. Ready to use C++ codes are provided online.Table of ContentsSome Basic Remarks.- Part I Deterministic Methods.- Numerical Differentiation.- Numerical Integration.- The KEPLER Problem.- Ordinary Differential Equations – Initial Value Problems.- The Double Pendulum.- Molecular Dynamics.- Numerics of Ordinary Differential Equations - Boundary Value Problems.- The One-Dimensional Stationary Heat Equation.- The One-Dimensional Stationary SCHRÖDINGER Equation.- Partial Differential Equations.- Part II Stochastic Methods.- Pseudo Random Number Generators.- Random Sampling Methods.- A Brief Introduction to Monte-Carlo Methods.- The ISING Model.- Some Basics of Stochastic Processes.- The Random Walk and Diffusion Theory.- MARKOV-Chain Monte Carlo and the POTTS Model.- Data Analysis.- Stochastic Optimization.- Appendix: The Two-Body Problem.- Solving Non-Linear Equations. The NEWTON Method.- Numerical Solution of Systems of Equations.- Fast Fourier Transform.- Basics of Probability Theory.- Phase Transitions.- Fractional Integrals and Derivatives in 1D.- Least Squares Fit.- Deterministic Optimization.

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Book SynopsisTable of Contents1. Einleitung.- 2. Algebraische Grundlagen.- 3. Geringte Räume.- 4. Supermannigfaltigkeiten.- 5. Analysis auf Supergebieten.- 6. Anwendungen.- 7. Lie—Algebren und Grundbegriffe der Darstellungstheorie.- 8. Höchstgewichtsdarstellungen der Virasoro-Algebra.- 9. Vertexoperatoren.- 10. Beweis der Kac’schen Determinantenformel.- 11. Konstruktion singulärer Vektoren im Fockraum.- 12.Unitäre Höchstgewichtsdarstellungen der Virasoro-Algebra.

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Book SynopsisDas Buch ist ein Hilfsmittel zur Bearbeitung von Übungsaufgaben bzw. zur Vorbereitung auf die Prüfung zur Vorlesung in Numerischer Mathematik bzw. wissenschaftliches Rechnen. Es ist unabhängig von einem bestimmten Lehrbuch konzipiert und umfaßt den Standardstoff einer einführenden Vorlesung in Numerik oder in das wissenschaftliche Rechnen. Es ist in Paragraphen gegliedert, welche jeweils einem bestimmten Sachgebiet der Numerik entsprechen. Jedem Paragraphen ist in ein bis zwei Seiten eine kurze Zusammenstellung der wichtigsten Tatsachen und Formeln vorangestellt, die als Arbeitsgrundlage und Verweismöglichkeit bei den Aufgaben dient. Jeder Paragraph enthält eine Sammlung für das Gebiet typischer Übungsaufgaben mit mustergültig ausgearbeiteten Lösungen.Table of ContentsRechnerarithmetik - Polynome und Interpolation - Numerische Differentiation und RICHARDSON-Extrapolation - BANACHscher Fixpunktsatz und Konvergenzordnung - Nichtlineare Gleichungen - Matrixanalyse und Normen - Lineare Gleichungssysteme

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Book SynopsisI. In this second volume, we continue at first the study of non­ homogeneous boundary value problems for particular classes of evolu­ tion equations. 1 In Chapter 4 , we study parabolic operators by the method of Agranovitch-Vishik [lJ; this is step (i) (Introduction to Volume I, Section 4), i.e. the study of regularity. The next steps: (ii) transposition, (iii) interpolation, are similar in principle to those of Chapter 2, but involve rather considerable additional technical difficulties. In Chapter 5, we study hyperbolic operators or operators well­ defined in thesense of Petrowski or Schroedinger. Our regularity results (step (i)) seem to be new. Steps (ii) and (iii) are all3.logous to those of the parabolic case, except for certain technical differences. In Chapter 6, the results of Chapter'> 4 and 5 are applied to the study of optimal control problems for systems governed by evolution equations, when the control appears in the boundary conditions (so that non-homogeneous boundary value problems are the basic tool of this theory). Another type of application, to the characterization of "all" well-posed problems for the operators in question, is given in the Ap­ pendix. Still other applications, for example to numerical analysis, will be given in Volume 3.Table of Contents4 Parabolic Evolution Operators. Hilbert Theory.- 1. Notation and Hypotheses. First Regularity Theorem.- 1.1 Notation.- 1.2 Statement of the Problems.- 1.3 (Formal) Green’s Formulas.- 1.4 First Existence and Uniqueness Theorem (Statement).- 1.5 Orientation.- 2. The Spaces Hr, s(Q). Trace Theorems. Compatibility Relations.- 2.1 Hr, s-Spaces.- 2.2 First Trace Theorem.- 2.3 Local Compatibility Relations.- 2.4 Global Compatibility Relations for a Particular Case.- 2.5 General Compatibility Relations.- 3. Evolution Equations and the Laplace Transform.- 3.1 Vector Distribution Solutions.- 3.2 L2-Solutions.- 4. The Case of Operators Independent of t.- 4.1 Hypotheses.- 4.2 Basic Inequalities.- 4.3 Solution of the Problem.- 5. Regularity.- 5.1 Preliminaries.- 5.2 Basic Inequalities.- 5.3 An Abstract Result.- 5.4 Solution of the Boundary Value Problem.- 6. Case of Time-Dependent Operators. Existence of Solutions in the Spaces H2r m, m(Q), Real r ? 1.- 6.1 Hypotheses. Statement of the Result.- 6.2 Local Result in t.- 6.3 Proof of Theorem 6.1.- 6.4 Regular Non-Homogeneous Problems.- Adjoint Isomorphism of Order r.- 7.1 The Adjoint Problem.- 7.2 Adjoint Isomorphism of Order r.- 8. Transposition of the Adjoint Isomorphism of Order r. (I): Generalities.- 8.1 Transposition.- 8.2 Orientation.- 8.3 The Spaces H??, ??(Q), H??, ??(?), ?, ? ? 0.- 8.4 (Formal) Choice of L.- 9. Choice of f. The Spaces ?2rm,r(Q).- 9.1 The Space ?2rm,r(Q).- 9.2 The Space ??2rm,?r(Q).- 9.3 Choice of f. The Space D?(r?1)(P)(Q).- 10. Trace Theorems for the Spaces D?(r?1)(P)(Q), r ? 1.- 10.1 Density Theorem.- 10.2 Trace Theorem on ?.- 10.3 Continuity of the Trace on Surfaces Neighbouring ?.- 10.4 Trace Theorem on ?0.- 10.5 Continuity of the Trace on Sections Neighbouring ?.- 11. Choice of gj and uo. The Spaces H2?m ??(?).- 11.1 The Spaces H2?m ??(?).- 11.2 Choice of gj.- 11.3 Choice of uo.- 12. Transposition of the Adjoint Isomorphism of Order ?. (II): Results; Existence of Solutions in H2mr,r(Q)-Spaces, Real r ? 0.- 12.1 Final Choice of L.- 12.2 Results.- 12.3 Complements.- 13. State of the Problem. Complements on the Transposition of the Adjoint Isomorphism of Order 1.- 13.1 State of the Problem.- 13.2 Complements on the Transposition of the Adjoint Isomorphism of Order 1.- 13.3 Orientation.- 14. Some Interpolation Theorems.- 14.1 Notation. Statement of the Main Result.- 14.2 Outline of the Proof.- 14.3 First Auxiliary Interpolation Theorem.- 14.4 Second Auxiliary Interpolation Theorem.- 14.5 Third Auxiliary Interpolation Theorem.- 14.6 Proof of Theorem 14.1.- 15. Final Results; Existence of Solutions in the Spaces H2mr,r(Q), 0 < r < 1. Applications.- 15.1 Application of the Results of Section 14.- 15.2 Examples; Generalities.- 15.3 Examples (I).- 15.4 Examples (II).- 15.5 Some Complements on the Dirichlet Problem.- 16. Comments.- 17. Problems.- 5 Hyperbolic Evolution Operators, of Petrowski and of Schroedinger. Hilbert Theory.- 1. Application of the Results of Chapter 3 and General Remarks.- 1.1 Notation. Hypotheses.- 1.2 Application of the Results of Chapter 3.- 1.3 A Counter-Example.- 2. A Regularity Theorem (I).- 3. Regular Non-Homogeneous Problems.- 3.1 Statement of the Problem.- 3.2 The Compatibility Relations.- 3.3 The Case of the Dirichlet Problem.- 4. Transposition.- 4.1 Adjoint Isomorphism.- 4.2 Transposition.- 4.3 Choice of L.- 4.4 Conclusion.- 5. Interpolation.- 5.1 Statement of the Problem.- 5.2 Some Interpolation Results.- 5.3 Consequences.- 5.4 The Case of the Dirichlet Problem.- 6. Applications and Examples.- 6.1 General Results.- 6.2 Examples.- 7. Regularity Theorem (II).- 7.1 Statement.- 7.2 Proof of Theorem 7.1.- 8. Non-Integer Order Regularity Theorem.- 8.1 Orientation.- 8.2 Interpolation in r.- 8.3 Interpretation of the Space V(2r?1)m,2r(Q), r ? 1.- 9. Adjoint Isomorphism of Order r and Transposition.- 9.1 Adjoint Isomorphism of Order r.- 9.2 Transposition.- 9.3 Formal Choice of L.- 10. Choice of f, $$ \vec g $$, u0, u1.- 10.1 Choice of f.- 10.2 The Space $$ D_{A + D_t^2}^{ - \left( {2r - 1} \right)}\left( Q \right) $$.- 10.3 Choice of gj.- 10.4 Choice of u0, u1.- 10.5 Conclusion.- 11. Trace Theorems in the Space $$ D_{A + D_t^2}^{ - \left( {2r - 1} \right)}\left( Q \right) $$.- 11.1 Density Theorem.- 11.2 Traces on ?.- 11.3 Continuity of the Trace on Neighbouring Surfaces.- 11.4 Traces on ?0.- 11.5 Continuity of the Trace on Sections Neighbouring ?0.- 11.6 Remark.- 12. Schroedinger Type Equations.- 12.1 Notation.- 12.2 First Regularity Theorem. Parabolic Regularization.- 12.3 Second Regularity Theorem.- 12.4 r-Isomorphism Theorem.- 12.5 Choice of L.- 12.6 Trace Theorem.- 13. Comments.- 14. Problems.- 6 Applications to Optimal Control Problems.- 1. Statement of the Problems for the Linear Parabolic Case.- 1.1 Notation.- 1.2 Optimization Problems.- 2. Choice of the Norms in the Cost Function.- 2.1 Reminder. Condition on K1(Q).- 2.2 Space Described by $$ \vec S\,y $$. Conditions on K2(?).- 2.3 Space Described by y(x, T; u). Condition on K3(?).- 3. Optimality Condition for Quadratic Cost Functions.- 3.1 Notation.- 3.2 Optimality Condition.- 4. Optimality Condition and Green’s Formula.- 4.1 Optimality Condition. Application of Section 3.2.- 4.2 The Isomorphisms ?i.- 4.3 The “Adjoint” Problem.- 4.4 New Form of the Optimality Condition.- 5. The Particular Case $$ \mu \,\, = \,\,m\,\, + \,\,\frac{1}{2} $$, E3 ? 0.- 5.1 Properties of y.- 5.2 Choice of K1(Q).- 5.3 Choice of K2(?) and K3(?).- 5.4 Adjoint Problem and Optimality Condition.- 6. Consequences of the Optimality Condition (I).- 6.1 Generalities.- 6.2 Consequences of Theorem 6.1.- 7. Consequences of the Optimality Condition (II).- 7.1 Additional Hypotheses.- 7.2 Optimality Condition.- 8. Complements on the Choice of the Spaces Ki.- 8.1 Orientation.- 8.2 Choice of K1(Q).- 8.3 Choice of K2(?).- 8.4 Choice of K3(?).- 9. Examples.- 10. Non-Parabolic Cases. Statement of the Problems. Generalities.- 10.1 Notation.- 10.2 Cost Function.- 10.3 Optimality Condition (I).- 10.4 Adjoint Problem.- 10.5 Green’s Formula.- 10.6 Optimality Condition (II).- 10.7 Consequences.- 11. Applications. Examples.- 11.1 Control in the Boundary Conditions.- 11.2 Choice of K1.- 11.3 Choice of K2.- 11.4 Examples.- 12. Comments.- 13. Problems.- Boundary Value Problems and Operator Extensions.- 1. Statement of the Problem. Well-Posed Spaces.- 1.1 Notation.- 2. Abstract Boundary Conditions.- 2.1 Boundary Spaces and Operators.- 2.2 Characterization of Well-Posed Spaces.- 3. Example 1. Elliptic Operators.- 3.1 Notation.- 3.2 The Boundary Operators and Spaces.- 3.3 Consequences.- 3.4 Various Remarks.- 4. Example 2. Parabolic Operators.- 4.1 Notation.- 4.2 The Boundary Operators and Spaces.- 4.3 Consequences.- 5.1 Notation.- 5.2 Formal Results.- 6. Comments and Problems.

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Book SynopsisDieses Lehrbuch vermittelt die Wirkungsweise vieler unterschiedlicher Grundbausteine numerischer Algorithmen. Übergeordnete Zielsetzung ist die Stärkung der Fähigkeit, numerische Ergebnisse einschätzen und bewerten zu können, sowie die numerischen Werkzeuge auch in komplexeren Anwendungsszenarien flexibel und sachgemäß kombinieren und anpassen zu können. Besonderer Wert wird dabei von Anfang an auf ein solides Verständnis der Konzepte Kondition (eines Problems) und Stabilität (eines Lösungsverfahrens) gelegt. Aufgrund der Vielzahl der in der Praxis benötigten numerischen Bausteine wird eine methodenorientierte Einführung zu den relevanten Themenschwerpunkten angeboten: Direkte und iterative Verfahren zur Lösung von Gleichungssystemen, Ausgleichsrechnung, Singulärwertzerlegung, Eigenwertberechnung, Interpolation, schnelle Fouriertransformation, numerische Integration sowie numerische Verfahren für gewöhnliche Differentialgleichungen. Zahlreiche illustrierende Beispiele vermitteln den konkreten Ablauf von Verfahren und verdeutlichen neue Konzepte, abschließende Übungsaufgaben runden die Kapitel ab. Die Inhalte selbst sind – soweit möglich – so gestaffelt, dass den „Pflichtinhalten“ optionale Vertiefungen folgen, in denen konzeptionelle Gesichtspunkte, übergreifende Zusammenhänge sowie rigorose Begründungen stärker betont werden. Das Buch eignet sich daher sowohl als Grundlage einer einsemestrigen einführenden als auch einer weiterführenden Numerik-Vorlesung im Ingenieurstudium, bietet aber auch die konzeptionellen Grundlagen für die Numerikausbildung im Mathematikstudium.Die Autoren stellen auf Ihrer Webseite zusätzlich Vorlesungsfolien für Dozenten, Multiple-Choice-Aufgaben sowie Matlabdemos bereit.Für die 3. Auflage wurde das Buch vollständig überarbeitet und noch besser strukturiert.Table of ContentsEinleitung.- Fehleranalyse: Kondition, Rundungsfehler, Stabilität.- Lineare Gleichungssysteme.- Lineare Ausgleichsrechnung.- Nichtlineare Gleichungssysteme.- Nichtlineare Ausgleichsrechnung.- Eigenwertprobleme.- Interpolation.- Splinefunktionen.- Numerische Integration.- Gewöhnliche Differentialgleichungen.

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Book SynopsisThe book serves as an introductory course for undergraduate and graduate students in engineering, science, and mathematics, encompassing all disciplines. It addresses key topics, such as numerical computation, linear systems of equations, algebraic and transcendental equation solutions, numerical differentiation, finite differences and interpolation, curve fitting, regression and correlation, numerical integration, and ordinary and partial differential equation solutions. The books language is simple and easy to understand, presented in a systematic and student-friendly manner, with a focus on numerical problem-solving. The balance between theory and practical examples is well-maintained. Each concept is supported by examples, which are unavailable in other books, helping students to better understand and remember the material. Exercise questions are provided at the end of each chapter for further practice.

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Book Synopsis1 Lezione 1 - Lo spazio e le curve.- 2 Lezione 2 - Funzioni di più variabili.- 3 Lezione 3 - Calcolo differenziale e approssimazioni.- 4 Lezione 4 - Massimi e minimi.- 5 Lezione 5 - Integrali curvilinei.- 6 Lezione 6 - Integrali doppi.- 7 Lezione 7 - Integrali tripli.- 8 Lezione 8 - Superficie parametriche.- 9 Lezione 9 - Teoremi della divergenza e di Green Stokes.- 10 Lezione 10 - Equazioni differenziali.

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Book SynopsisUnderstanding earth systems and its dynamic behavior requires objective insights into the complex observational data sets and their interrelationships. Drawing meaningful inferences from such data is not always an easy task as the deterministic relationships between various geological variables often remain obscured. These interrelationships need to be determined empirically through the analysis of a large set of data and validated through numerical simulations. The ever widening horizon of techniques of numerical analysis and simulation now provides a good number of tools to aid the interpretation. However, due to the inherent complexity of earth science data, expert supervision is required at all stages of analysis from collection to dissemination. This ensures that the most appropriate methodology is adopted and the results remain consistent with the geological principles. Discussions on these practical issues often lie beyond the scope of textbooks and this is precisely where this book is placed. In this book eminent geoscientists present their experiences in analyzing and managing earth science data as well as in designing numerical models to simulate earth processes. Apart from giving a discourse of their own approach towards a particular research problem they also discuss at length the relative merits of alternative methodologies. These seven authoritative articles, richly illustrated, will be a valuable resource for research students and professionals interested in research and teaching in various branches of earth science like, tectonics, GPS geodesy, sedimentology, geographical information science, and evolutionary biology.Table of Contents1. Active deformation in the Darjiling-Sikkim Himalaya based on 2000-2004 geodetic global positioning system measurements. 2. Preliminary results of a study of crustal deformation in the Himalayan Frontal zone in North Bengal using GPS Geodesy. 3. Spatial and temporal variations of the strain fields in orogenic belts: an analysis based on kinematic models. 4. Grain size distribution patterns of some rivers in the light of three model distributions. 5. Estimation of shape changes of skull roof bones in Benthosuchus Sushkini, a Temnospondyl amphibian from the Triassic of Russia. 6. Spatial mathematical models for mineral potential mapping. 7. Enterprise GIS in Geological Survey of India.

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Book SynopsisThis two-volume book provides an insight into the 10th International Conference on Soft Computing for Problem Solving (SocProS 2020). This international conference is a joint technical collaboration of Soft Computing Research Society and Indian Institute of Technology Indore. The book presents the latest achievements and innovations in the interdisciplinary areas of soft computing. It brings together the researchers, engineers and practitioners to discuss thought-provoking developments and challenges, in order to select potential future directions. It covers original research papers in the areas including but not limited to algorithms (artificial immune system, artificial neural network, genetic algorithm, genetic programming and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). The book will be beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.Table of ContentsA deep semi-supervised approach for multi-label land-cover classification under scarcity of labelled images.- Role of individual samples in Modified Possibilistic c-Means classifier for handling heterogeneity within mustard crop.- Specially Structured Flow Shop Scheduling Models with processing times as Trapezoidal Fuzzy Numbers to optimize Waiting time of Jobs.- Potential Fishing Zone Characterization in the Indian Ocean by Machine Learning Approach.- A novel method to optimize interval length for intuitionistic fuzzy time series.- Low Altitude Unmanned Aerial Vehicle For Real Time Green House Plant Disease Monitoring Using Convolutional Neural Network.

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Book SynopsisThis book collects select papers presented at the International Conference on Applications of Basic Sciences, held at Tiruchirappalli, Tamil Nadu, India, from 19-21 November 2019. The book discusses topics on singular perturbation problems, differential equations, numerical analysis, fuzzy logics, fuzzy differential equations, and mathematical physics, and their interdisciplinary applications in all areas of basic sciences: mathematics, physics, chemistry, and biology. It will be useful to researchers and scientists in all disciplines of basic sciences. This book will be very useful to know the different scientific approaches for a single physical system.Table of Contents1. Virtual Element Method for Singularly Perturbed Reaction-Diffusion Problems on Polygonal Domains: J.L. Gracia and D. Irisarri.- 2. Global Uniform Convergence for Weakly Coupled System of Singularly Perturbed Convection Diffusion Problems: S. Chandra Sekhara Rao, Varsha Srivastava, and Abhay Kumar Chaturvedi.- 3. A Parameter Uniform Fitted Mesh Method for a Weakly Coupled System of Three Partially Singularly Perturbed Convection-Diffusion Equations: Valarmathi Sigamani, Saravana Sankar Kalaiselvan, John J H Miller.- 4. Numerical Method for a Boundary Value Problem for a Linear System of Partially Singularly Perturbed Parabolic Delay Differential Equations of Reaction-Diffusion Type: Parthiban Saminathan and Franklin Victor.- 5. A First-Order Convergent Parameter Uniform Numerical Method for a Singularly Perturbed Second-Order Delay-Differential Equation of Reaction-Diffusion Type with a Discontinuous Source Term: Manikandan Mariappan, John J H Miller, Valarmathi Sigamani.- 6. Fitted Numerical Method with Linear Interpolation for Third-Order Singularly Perturbed Delay Problems: R. Mahendran and V. Subburayan.- 7. A Parameter Uniform Essentially First-Order Convergence of a Fitted Mesh Method for a Class of Parabolic Singularly Perturbed Robin Problem for a System of Reaction-Diffusion Equations: R. Ishwariya, Valarmathi Sigamani, John J H Miller.- 8. Finite Difference Method and Analysis for First-Order Hyperbolic Delay Differential Equations: S. Karthick and V. Subburayan.- 9. Fitted Mesh Methods for a Class of Weakly Coupled System of Singularly Perturbed Convection-Diffusion Equations: Saravana Sankar Kalaiselvan, Valarmathi Sigamani, John J H Miller.- 10. Numerical Analysis of a Finite Difference Method for a Linear System of Singularly Perturbed Parabolic Delay Differential Reaction-Diffusion Equations with Discontinuous Source Terms: Parthiban Saminathan and Franklin Victor.

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Book SynopsisThis book contains select papers on mathematical analysis and modeling, discrete mathematics, fuzzy sets, and soft computing. All the papers were presented at the international conference on FIM28-SCMSPS20 virtually held at Sri Sivasubramaniya Nadar (SSN) College of Engineering, Chennai, India, and Stella Maris College (Autonomous), Chennai, from November 23–27, 2020. The conference was jointly held with the support of the Forum for Interdisciplinary Mathematics. Both the invited articles and submitted papers were broadly grouped under three heads: Part 1 on analysis and modeling (six chapters), Part 2 on discrete mathematics and applications (six chapters), and Part 3 on fuzzy sets and soft computing (three chapters).Table of ContentsPART I ANALYSIS AND MODELLINGThe Second- and Third-order Hermitian Toeplitz Determinants for Some Subclasses of Analytic Functions Associated with Exponential Function,P.Gurusamy, R. Jayasankar and S. SivasubramanianSome Results on a Starlike Class with Respect to $(j, m) $-symmetric FunctionsK. Renuka Devi, S. Sivasubramanian, Hamid Shamsan and S. LathaExperimental Evaluation of Four Intermediate Filters to Improve the Motion Field EstimationVanel Lazcano and Claudio Isa-MohorOn the $s^{th}$ Derivative of a PolynomialBarchand Chanam and Kshetrimayum KrishnadasOn the Problem of Pricing a Double Barrier Option in a Modified Black–Scholes Environment G. Venkiteswaran and S. UdayabaskaranCaputo Sequential Fractional Differential Equations with ApplicationsAghalaya S. Vatsala and Govinda PageniPART II DISCRETE MATHEMATICS AND APPLICATIONSHerscovici’s Conjecture on Product of Some Complete Bipartite GraphsA. Lourdusamy and S. Saratha NellainayakiOn Fault-Tolerant Metric Dimension of Heptagonal Circular Ladder and Its Related GraphsSunny Kumar Sharma and Vijay Kumar BhatBKS Fuzzy Inference Employing h-ImplicationsSayantan Mandal and Balasubramaniam Jayaram Note on Distributivity of Different String Operations over Language SetsUjjwal Kumar Mishra, Kalpana Mahalingam and Rama RaghavanA Generalization of Chi-binding FunctionsM. A. Shalu and T. P. SandhyaA Short Proof of Ore’s f-factor Theorem using FlowsSriraman Sridharan and Patrick VilamajoPART III FUZZY SETS AND SOFT COMPUTINGA Decision-making Problem Involving Soft Fuzzy Number Valued Information System: Energy Efficient Light Emitting Diode BlubsFelbin C. Kennedy, Masilla Moses Kennedy, Arul Roselet Meryline S. andJayachandiran M.Role of Single-valued Linear Octagonal Neutrosophic Numbers in Multi-attribute Decision-making ProblemsSubasri S., Arul Roselet Meryline S. and Felbin C. Kennedy

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Book SynopsisThis book publishes select papers presented at the 4th International Conference on Frontiers in Industrial and Applied Mathematics (FIAM-2021), held at the Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India, from 21–22 December 2021. Most of the papers deal with mathematical theory embedded with its applications to engineering and sciences. This book illustrates numerical simulation of scientific problems and the state-of-the-art research in industrial and applied mathematics, including various computational and modeling techniques with case studies and concrete examples. Graduate students and researchers, who are interested in real applications of mathematics in the areas of computational and theoretical fluid dynamics, solid mechanics, optimization and operations research, numerical analysis, bio-mathematics, fuzzy, control and systems theory, dynamical systems and nonlinear analysis, algebra and approximation theory, will find the book useful. Table of ContentsC. Özman, T. Saner, F. Gül, M. Diederich, A. C. Benim, and U. Janoske, Computational and Experimental Investigation of Flow and Convective Heat Transfer along Rough Surfaces.- M. Kumar, Neelesh S. Upadhye, and A. K. B. Chand, Distribution of Noise in Linear Recurrent Fractal Interpolation Functions for Data Sets with α-Stable Noise.- Maggie E. Habeeb, Oblivious Transfer using Non-abelian Groups.- P. Kushwah and J. Saha, Solution of Population Balance Equation using Homotopy Analysis Method.- V. Singh, Waseem A. Khan, and A. Sharma, Certain Properties and their Volterra Integral Equation Associated with the Second-Kind Chebyshev Matrix Polynomials in Two Variables.- R. Saranya, N. Annapoorani, and J. Saha, Blow-up Analysis and Global Existence of Solutions for a Fractional Reaction-Diffusion Equation.- N. Rani and V. Mishra, Ways of Constructing Multiplicative Magic Cubes.- S. Singh Rawat and Komal, Novel q-Rung Orthopair Fuzzy Hamacher Dual Muirhead Mean Operator for Multi-Attribute Decision Making.- A. Srivastava and B. S. Bhadauria, Convective Instability in a Composite Nanofluid Layer under Local Thermal Non-equilibrium.- N. Madaan and S. Sharma, Investigation of Traffic Dynamics Considering Driver’s Characteristics and Downstream Traffic Conditions.- R. Pasupathi, M. A. Navascués, and A. K. B. Chand, Fractal Convolution Bessel Sequences on Rectangle.- S. Devaiya and S. K. Srivastava, Uniform Approximation of Functions Belonging to L[0,∞)-space Using Cγ.T Means of Fourier-Laguerre Series.- M. Diederich, F. Gül, C. Özman, A. C. Benim, L. Ihringer, and D. Möller, Numerical Modelling and Experimental Validation of Mechanical Separation of Helminth Eggs for Wastewater Purification.- H. A. Kumara Swamy, Sankar Mani, N. Keerthi Reddy, and S. R. Sudheendra, Heat Transfer and Second Law Analysis of Ag-water Nanoliquid in a Non-Uniformly Heated Porous Annulus.- Anjali and M. K. Singh, Qualitative Analysis of Peer Influence Effects on Testing of Infectious Disease Model.- R. Goel, R. C. Mittal, and N. Ahlawat, B-Splines Collocation Approach to Simulate Secondary Dengue Virus (DENV) Infection Model with Diffusion.- A. Kumar, B.S Bhadauria, and A. Srivastava, Study of Heat and Mass Transfer in a Composite Nanofluid Layer.- Bhagwat R. Yewale and Deepak B. Pachpatte, On the Existence and Stability Analysis for Ψ-Caputo Fractional Boundary-value Problem.- R. Rath and K. Sharma, Alternative Crack-tip Enrichment Functions for XFEM in Arbitrary Polarized Piezoelectric Media.- S. C. Sekhara Rao and A. K. Chaturvedi, Convergence Analysis of a Layer Resolving Numerical Technique for a Class of Coupled System of Singularly Perturbed Parabolic Convection-Diffusion Equations having an Interface.- P. Megha and G. Chandhini, Filtering in Time-dependent Problems.- N. Gupta and N. Kanth, Heat Transfer Model for Silk Finishing Calendar.- H. D. Arora, A. Naithani, and Aakanksha, A Multi-attribute Decision Making Approach for Fuzzy Divergence Measure in Selection of Covid-19 Vaccine.- N. Singh and Manish K. Khandelwal, Magnetohydrodynamic Mixed Convection Flow in a Vertical Channel Filled with Porous Media.- A. Ali, R. P. Sharma, and A. Zishan, Group Action on Fuzzy Ideals of Near-Rings.- R. Revathi, D. Narsimhulu, and A. Ramu, Effect of Viscosity on the Spherical Shock Wave Propagation in a Dusty Gas with Radiation Heat Flux and Exponentially Varying Density.- M. Arora and R. Bajaj, On the Stability of a Heated Inclined Fluid Layer with Gravity Modulation.- S. C. Srivastava, N. K. Thakur, and A. Pramanayagam, Dynamical Study of an Epidemiological Model with Harvesting and Infection in Prey Population.- G. Raiya and M. Mittal, Joint Decisions on Imperfect Production Process and Carbon Emission Reduction Under Carbon Regulations.- S. Naskar, N. Islam, R. Gayen, and R. Datta, Propagation of Water Waves in the Presence of a Horizontal Plate Submerged in a Two-layer Fluid.- P. Saini, Transversely Isotropic Homogeneous Medium with Absorbing Boundary Conditions: Elastic Wave Propagation using Spectral Element Method.- K. B. Devi, Reingachan N., and T. B. Singh, Growth of Polynomials having No-zero Inside a Circle.- V. Siwach, Manju S. Tonk, and H. Poonia, Simulation of Queues in Sugar Mills using Monte-Carlo Technique.- R. Singla, G. Singh, and V. Kanwar, An Adaptive Step-size Optimized Seventh-order Hybrid Block Method for Integrating Differential Systems Efficiently.- M. Diederich, L. Di Bartolo, and A. C. Benim, Comparison of Prediction Accuracy between Interpolation and Artificial Intelligence Application of CFD Data for 3D Cavity Flow.- J. Tushar, A. Kumar, and S. Kumar, Virtual Element Methods for Optimal Control Problems Governed by Elliptic Interface Problems.- Vijay and A.K.B. Chand, Positivity Preserving Rational Quartic Spline Zipper Fractal Interpolation Functions.- Z. Mkhize, N. Parumasurand, and P. Singh, Heptic Hermite Collocation on Finite Elements.- J. Raj Sharma and H. Singh, A Computationally Efficient Sixth-order Method for Nonlinear Models.- S. Panday, W. H. Chanu, and Y. N. Devi, New Higher Order Iterative Method for Multiple Roots of Nonlinear Equations.- M. Singh and A. Gupta, Separation Axioms in Bipolar Fuzzy Topological Spaces.- V. Singh and B. Singh, A Study of Ciric Type Generalized Contraction via B-contraction with Application.- D. Amin and D. B. Singh, Evolution of Weak Discontinuities in a Perfectly Conducting Mixture of Gas and Dust Particles.- S. Chawla and S. C. Sekhara Rao, Numerical Treatment for a Coupled System of Singularly Perturbed Reaction Diffusion Equations with Robin Boundary Conditions and having Boundary and Interior Layers.- M. Arora, M. Danesh, and A. Rana, Double-Diffusive Convection with the Effect of Rotation in Magnetic Nanofluids.- R. Sasikumar and P. Arriyamuthu, Modeling for Implications of Covid-19 Pandemic on Healthcare System in India.

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Book SynopsisThis open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA.Table of ContentsIntroduction.- Sine Cosine Algorithm.- Sine Cosine Algorithm for Multi-Objective Optimization.- Sine Cosine Algorithm for Discrete Optimization Problems.- Advancements in the Sine Cosine Algorithm.- Conclusion and Further Research Directions.

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Book SynopsisThis book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors' latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided in this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors' latest achievements or new methods around the practical industrial needs. In my opinion, this book can be assimilated by advanced undergraduates and graduate students, as well as statisticians, because of the new tools in data analysis, applied mathematics experts, because of the novel theories and techniques that we propose, engineers, above all for the applications in control, system identification, computer vision, and signal processing.

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Book SynopsisThis book collects select papers presented at the 7th International Arab Conference on Mathematics and Computations (IACMC 2022), held from 11–13 May 2022, at Zarqa University, Zarqa, Jordan. These papers discuss a new direction for mathematical sciences. Researchers, professionals and educators will be exposed to research results contributed by worldwide scholars in fundamental and advanced interdisciplinary mathematical research such as differential equations, dynamical systems, matrix analysis, numerical methods and mathematical modelling. The vision of this book is to establish prototypes in completed, current and future mathematical and applied sciences research from advanced and developing countries. The book is intended to make an intellectual contribution to the theory and practice of mathematics. This proceedings would connect scientists in this part of the world to the international level.Table of ContentsA. S. Salama and R. Abu Gdair: Generalized Neighborhood Systems Approach for Information Retrieval Systems.- Emad A. Kuffi, E. S. Abbas and S. F. Maktoof: Applying “Emad–Sara” Transform on Partial Differential Equations.- A. Al-Swaftah, A. Burqan and M. Khandaqji: Estimations of the Bounds for the Zeros of Polynomials Using Matrices.- B. Ghazal, R. Saadeh and G. Gharib: Applications on Formable Transform in Solving Integral Equations.- O. Tug: On the Eigenvalue of a Norlund Type Matrix as an Operator on the Sequence Spaces L1 and bv.- N. Tahat, Obaida M. Al-hazaimeh and S. Shatnawi: A New Authentication Scheme Based on Chaotic Maps and Factoring Problems.- R. B. Albadarneh, A. M. Adawi, Sa'ud Al-Sa'di, I. M. Batiha and S. Momani: A pro rata Definition of the Fractional-order Derivative.- S. Ibrahim, M. Muhammed Al-Kassab and M. Qasim Al-Awjar: Investigating Multicollinearity in Factors Affecting Number of Born Children in Iraq.- T. Alkharabsheh, K. shebrawi and M. Abu-sSaleem: Hilbert–Schmidt Numerical Radius Inequalities For Certain 2 x 2 Operator Matrices.- Y. A. Sabawi, Mardan A. Pirdawood, Hemn M. Rasool and S. Ibrahim: Model Reduction and Implicit–Explicit Runge–Kutta Schemes for Nonlinear Stiff Initial-value Problems.- G. M. Gharib, Maha S. Alsauodi, A. Guiatni, Mohammad A. Al-Omari and A. Al-Rahman M. Malkawi: Using Atomic Solution Method to Solve the Fractional Equations.- S. Ramadan: Analysis in the Algebra A(E).- S. rasem, A. Dababneh and Ma’mon Abu Hammad: Applications of Conformable Fractional Weibull Distribution.- O. Ramadan: Stable Second-order Explicit Runge–Kutta Finite Difference Time Domain Formulations for Modeling Graphene Nano-material Structures.- Ali Shehab, Ahmed M. R. El-Baz and A. M. Elmarhomy: Hydrodynamic Analysis and CFD Modeling of PAWEC Interacted with Regular Waves Using CFX.- M. Muhammed Al-Kassab and S. Ibrahim: Using Ridge Regression to Estimate Factors Affecting the Number of Births: A Comparative Study.- T. Hamadneh, J. Merker and G. Schuldt: Discrete Maximum Principle and Positivity Certificates for the Bernstein Dual Petrov–Galerkin Method.- A. Burqan, A. Sarhan and R. Saadez: Analytical Solutions of the Fractional Riccati Differential Equations Using Laplace Residual Power Series Method.- D. Andrica and O. Bagdasa: On the Dynamic Geometry of Kasner Triangles with Complex Parameter.- D. Amr and Ma’mon Abu Hammad: Application of Conformable Fractional Nakagami Distribution.- Rawya Al-deiakeh, Maha S. Alsauodi, S. Momani, Gharib M. Gharib and T. B. Salameh: Application of Laplace Residual Series Method for Solving Time-fractional Fisher Equation.- M. Hassen Eid Abu-Sei'leek: Self-consistent Single-particle Spectra with Delta Excitations.- I. M. Batiha, N. Djenina, A. Ouannas and T. E. Oussaeif: Fractional-order SEIR Covid-19 Model: Discretization and Stability Analysis.- A. Alsoboh and M. Darus: A q-Starlike Class of Harmonic Meromorphic Functions Defined by q-Derivative Operator.- J. Oudetallah, Z. Chebana, Taki-Eddine Oussaeif, A. Ouannas and I. M. Batiha: Theoretical Study of Explosion Phenomena for a Semi-parabolic Problem.- L. Szala: Explicit Formulae of Linear Recurrences.- R. Abu Sallik, J. Al Jaraden: The Influence of S-quasinormal Subgroups on the Structure of Finite Groups.- S. J. Ansari and V. R. Lakshmi Gorty: Two-sided Clifford Wavelet Function in Cl(p, q).- L. Nemeth and L. Szalay: Generalizations of the Fibonacci Sequence with Zig-zag Walks.- D. Wafula Waswa and M. Muhammed Al-Kassab: Mathematics Learning Challenges and Difficulties: A Students’ Perspective.- V.R. Ibrahimov, G.Yu. Mehdiyeva, Xiao-Guang Yue and M.N. Imanova: Finding Solution to the Initial Value Problem for ODEs First and Second Order by One and the Same Method.- Doaa Al-Saan: On Symmetric Matrices with One Positive Eigenvalue and the Interval Property of Some Matrix Classes.- N. Anakira, A. Hioual, A. Ouannas, Taki-Eddine Oussaeif and Iqbal M. Batiha: Global Asymptotic Stability for Discrete-time SEI Reaction-diffusion Model.- G. Eid, I. Jebril, Ma’mon Abu Hammad and D. AbuJudeh: Atomic Solution of Euler Equation.- Worood A. AL-hakim, Maha S. Alsauodi, Gharib M. Gharib, Fatima Alqasem and May Abu Jalbosh: Solving Nonlinear Fractional Coupled Burgers Equation by Sub-equation Method.- S. M. Alshorm: Groups in which the Commutator Subgroup is Cyclic.- M. A. Amleh: On Point Prediction of New Lifetimes under a Simple Step-stress Model for Censored Lomax Data.- Tareq M. Al-shami and Radwan Abu-Gdairi: Infra Soft B-open Sets and Their Applications on Infra Soft Topological Spaces.- Raed M. Khalil: An Algorithm of the Prey and Predator Struggle to Survive as a Random Walk Simulation Case Study.- W. Beghami, B. Maayah and S. Bushnaq: Numerical Study of a Nonlinear Fractional Mathematical Model of the Tumor Cells Chemotherapy Effect.- O. Ababneh and K. Al-Boureeny: New Modification Methods for Finding Zeros of Nonlinear Function.- Ioan-Lucian Popa, T. Ceausu, L. Elena Biris and A. Zada: On Tempered Exponential Trisplitting for Random Semi-Dynamical Systems.- H. El-Metwally, F. M. Masood, R. Abu-Gdairi and Tareq M. Al-shami: On q-Laplace Transforms.- N. R. Anakira, G.F. Bani-Hani and O. Ababneh: An Effective Procedure for Solving Linear and Non-linear Volterra Integro-differential Equations.- S. Alkhalely, A. Burqan and M. Muhammed Al-Kassab: New Estimations for Zeros of Polynomials Using Numerical Radius and Similarity of Matrices.- J. Jawdat: Strong Coproximinal Subspaces in Köthe Function Spaces.- E. Savas: A New Paranormed Sequence Spaces and Invariant Means.

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Book SynopsisThis open access book introduces the fundamentals of the space–time conservation element and solution element (CESE) method, which is a novel numerical approach for solving equations of physical conservation laws. It highlights the recent progress to establish various improved CESE schemes and its engineering applications. With attractive accuracy, efficiency, and robustness, the CESE method is particularly suitable for solving time-dependent nonlinear hyperbolic systems involving dynamical evolutions of waves and discontinuities. Therefore, it has been applied to a wide spectrum of problems, e.g., aerodynamics, aeroacoustics, magnetohydrodynamics, multi-material flows, and detonations. This book contains algorithm analysis, numerical examples, as well as demonstration codes. This book is intended for graduate students and researchers who are interested in the fields such as computational fluid dynamics (CFD), mechanical engineering, and numerical computation.Table of ContentsIntroduction.- Non-dissipative Core Scheme of CESE Method.- CESE Schemes with Numerical Dissipation.- Multi-Dimensional CESE Schemes on Cartesian Meshes.- CESE Schemes on Unstructured Meshes.- High-Order CESE Schemes.- Numerical Features of CESE Schemes.- Application: Hypersonic Aerodynamics.- Application: Compressible Multi-Fluid.- Other Applications.- Summary.

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Book Synopsis​This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming.Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.Trade Review“This book provides a detailed guide to Pyomo for beginners and advanced users from undergraduate students to academic researchers to practitioners. … the book is a good software guide which I strongly recommend to anybody interested in looking for an alternative to commercial modeling languages in general or in learning or intensifying their Pyomo skills in particular.” (Christina Schenk, SIAM Review, Vol. 61 (1), March, 2019)Table of Contents1. Introduction.- Part I. An Introduction to Pyomo.- 2. Mathematical Modeling and Optimization.- 3. Pyomo Overview.- 4. Pyomo Models and Components.- 5. The Pyomo Command.- 6. Data Command Files.- Part II. Advanced Features and Extensions.- 7. Nonlinear Programming with Pyomo.- 8. Structured Modeling with Blocks.- 9. Generalized Disjunctive Programming.- 10. Stochastic Programming Extensions.- 11. Differential Algebraic Equations.- 12. Mathematical Programs with Equilibrium Constraints.- 13. Bilevel Programming.- 14. Scripting.- A. A Brief Python Tutorial.- Index.

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a huge range and FREE tracked UK delivery on ALL orders.

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Book SynopsisThis textbook offers a guided tutorial that reviews the theoretical fundamentals while going through the practical examples used for constructing the computational frame, applied to various real-life models.Computational Optimization: Success in Practice will lead the readers through the entire process. They will start with the simple calculus examples of fitting data and basics of optimal control methods and end up constructing a multi-component framework for running PDE-constrained optimization. This framework will be assembled piece by piece; the readers may apply this process at the levels of complexity matching their current projects or research needs.By connecting examples with the theory and discussing the proper communication between them, the readers will learn the process of creating a big house. Moreover, they can use the framework exemplified in the book as the template for their research or course problems they will know how to change theTable of ContentsChapter 1. Introduction to Optimization. Chapter 2. Minimization Approaches for Functions of One Variable. Chapter 3. Generalized Optimization Framework. Chapter 4. Exploring Optimization Algorithms. Chapter 5. Line Search Algorithms. Chapter 6. Choosing Optimal Step Size. Chapter 7. Trust Region and Derivative-Free Methods. Chapter 8. Large-Scale and Constrained Optimization. Chapter 9. ODE-based Optimization. Chapter 10. Implementing Regularization Techniques. Chapter 11. Moving to PDE-based Optimization. Chapter 12. Sharing Multiple Software Environments.

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Book SynopsisThis textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics, engineering, and computer science.Features: No previous experience in Python is required. Includes simplified computer code for fast-paced learning and transferable skills development. Includes practical problems ideal for project assignments and distance learning. Presents both intuitive and rigorous faces of modern scientific computing. Provides an introduction to neural networks and machine learning. Table of Contents1. Introduction to Python. 2. Matrices and Python. 3. Scientific computing. 4. Calculus facts. 5. Roots of equations. 6. Interpolation and approximation. 7. Numerical integration. 8. Numerical differentiation and applications to differential equations. 9. Numerical linear algebra. 10. Best approximations. 11. Unconstrained optimization and neural networks. 12. Eigenvalue problems.

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