Computational Modeling by Case Study
Mathematical models power the modern world, but they are all uncertain. This book provides techniques to quantify uncertainty, allowing you to predict and design with confidence. Learn through case studies and reproducible examples in Python adapted for your own problems.
This book compiles technical publications on the nonlinear analysis of icosahedrons. It covers static and dynamic characteristics, with topics ranging from large displacements and rotations to chaotic behaviour, and includes extensive experimentation.
This book tackles the significant challenges of evolutionary processes with memory. It studies their properties by introducing a resolvent family to represent solutions, and explores the dual problem, solvability issues, invariant subspaces, and spectral theory.
This book provides a comprehensive background for analysis of the finite deformation of materials. It covers deformation geometry, stress measures, and balance laws, with applications in rubber elasticity and metal plasticity, including experiments and illustrations.
Master Elementary Algebra to succeed in mathematics. This book bridges the gap between school and university, helping undergraduates pass mathematical analysis courses. This material has been used to improve the skills of first-year engineering students for a decade.
A Concise Course of Mathematics with Applications
This book covers a vast range of mathematics, from logic, number theory, and algebra to calculus, topology, and geometry. It includes complex analysis, differential equations, and matrices, with applications in the natural and social sciences, from physics to economics.
An introduction to Graph Theory and Combinatorics and their Applications. Presented in a simple way with examples, it contains a wide variety of applications to real world Science and Engineering problems and includes multiple choice questions for competitive exams.
This book explains basic concepts of mathematical analysis, including functions, numerical sequences, convergence, and limits. It also covers the continuity and differentiability of functions, their applications, and the graphic representation of parametric functions.
Rigid Body as a Constrained System
This book presents the dynamics of spinning bodies, the most confusing topic in Classical Mechanics. Starting from the variational problem, it treats the rigid body as a system of particles, creating a simple, transparent approach that eliminates the need for extra postulates.
This book develops novel mathematical models to investigate the impacts of GHG emissions on coastal and marine ecosystems. It introduces optimal control strategies to mitigate these impacts, providing new methods for scientists working to maintain a healthy environment.
A Journey into Ambiguous Set Theory
An introduction to the concepts of ambiguous set theory. Through concrete examples, the book demonstrates practical applications in decision-making, control systems, and medical imaging. It is designed to be approachable for students, researchers, and enthusiasts alike.
Sectoral Structures Theory is a novel, interdisciplinary framework for studying arrangements of circular sectors. This work establishes its foundations in geometric combinatorics, graph theory, and number theory, integrating concepts from algebra, topology, and group theory.
Functional analysis studies infinite vector spaces, their topologies, and the operators between them. This book is a collection of notes, expositions, exercises, and lectures on advanced functional analysis, exploring properties such as duality, continuity, and C*-algebras.
The Art of Supposition
What if our reality is shaped by what we suppose? This book introduces a groundbreaking framework, redefining the human experience through the lens of Homo Putans, the “supposing human.” Enter a world where every thought is an invitation to question, explore, and suppose.
This book covers the theory and practice of discrete optimization for mathematics and computer science researchers. It presents new theoretical results, models, and algorithmic approaches for problems in integer programming, combinatorial optimization, scheduling, and logistics.
A Journey into Quantum Wavefunction Optimization Algorithm
Enhance predictive accuracy and optimization efficiency under uncertainty. Discover hybrid and quantum-inspired models for forecasting, classification, and optimization, bridging neutrosophic theory and quantum computation to solve complex problems.