Mathematical Methods for Engineering Applications:
ICMASE 2025, Plovdiv, Bulgaria, July 15–17
DETAILS
-
Title: Mathematical Methods for Engineering Applications: ICMASE 2025, Plovdiv, Bulgaria, July 15–17
-
Editor: Snezhana Gocheva-Ilieva
-
Publisher: Springer
-
ISBN: 9783032250698
-
Format: Hardcover
-
Publication Date: July 23, 2026
-
Conference: ICMASE 2025 (International Conference on Mathematical Methods for Engineering Applications)
-
Language: English
EXPLANATIONS
This volume contains selected and peer-reviewed contributions presented at the International Conference on Mathematical Methods for Engineering Applications (ICMASE 2025) held in Plovdiv, Bulgaria, from July 15–17, 2025. The conference focuses on the application of advanced mathematical techniques to engineering, technology, and applied sciences.
The book is intended for researchers, graduate students, engineers, and applied mathematicians interested in modern mathematical tools used to solve practical engineering problems. Typical topics in such proceedings include:
-
Differential equations and dynamical systems
-
Numerical methods and scientific computing
-
Optimization and control
-
Mathematical modeling
-
Data analysis and machine learning
-
Engineering applications of applied mathematics
-
Computational methods for physical and industrial systems
As a conference proceedings volume, the book brings together contributions from multiple authors, providing a snapshot of current research directions and emerging applications of mathematics in engineering.
TABLE OF CONTENTS
A complete chapter-by-chapter table of contents does not yet appear to be publicly available in the major bibliographic sources currently indexed. However, based on the conference theme and publisher description, the volume is expected to include papers in areas such as:
-
Mathematical Modeling in Engineering
-
Numerical Analysis and Scientific Computing
-
Optimization Methods
-
Control Theory and Applications
-
Computational Mechanics
-
Data-Driven Engineering
-
Artificial Intelligence and Machine Learning Methods
-
Applied Differential Equations
-
Engineering Mathematics
-
Industrial and Technological Applications of Mathematics
At present, only the bibliographic record and publication information have been publicly released; Springer has not yet published a detailed table of contents for the volume.
NOTES
Because this is a conference proceedings volume, the final list of chapters may change slightly before publication. Once Springer releases the official table of contents, a much more detailed chapter listing will become available.
Difference Equations and Discrete Dynamical Systems with Applications:
ICDEA 29, Paris, France, June 24–28, 2024
DETAILS
-
Title: Difference Equations and Discrete Dynamical Systems with Applications: ICDEA 29, Paris, France, June 24–28, 2024
-
Editors: Saber Elaydi, Laura Gardini, René Lozi, Davide Radi
-
Series: Springer Proceedings in Mathematics & Statistics, Volume 556
-
Publisher: Springer Nature Switzerland AG
-
ISBN: 9783032254931
-
Format: Hardcover
-
Language: English
-
Publication Date: July 2026
-
Length: Approximately 373–500 pages (sources vary because the volume was still in pre-publication cataloging when listed).
EXPLANATIONS
This volume contains selected and invited papers from the 29th International Conference on Difference Equations and Applications (ICDEA 29), held in Paris, France, from June 24–28, 2024. It presents recent developments in the theory and applications of difference equations and discrete dynamical systems.
Difference equations are mathematical models that describe phenomena evolving in discrete time. They play a central role in many areas of applied mathematics and are widely used in:
-
Mathematical biology
-
Population dynamics
-
Epidemiology
-
Economics and finance
-
Control theory
-
Numerical analysis
-
Complex systems and chaos theory
-
Engineering applications
The proceedings provide a snapshot of current research directions and bring together contributions from leading specialists and emerging researchers in the field. The ICDEA conference series, organized by the International Society of Difference Equations (ISDE), has been an important international forum since 1994.
TABLE OF CONTENTS
A complete chapter-by-chapter table of contents has not yet been publicly released in the available bibliographic records. However, according to the publisher descriptions, the volume includes invited and contributed papers covering topics such as:
-
Difference Equations
-
Discrete Dynamical Systems
-
Stability Theory
-
Bifurcation Theory
-
Chaos and Complex Dynamics
-
Mathematical Biology Models
-
Population Dynamics
-
Mathematical Economics
-
Numerical Methods for Discrete Systems
-
Applications of Difference Equations
-
Discrete-Time Control Systems
-
Nonlinear Dynamics
-
Computational Methods in Dynamical Systems
RESEARCH AREAS COVERED
-
Discrete Mathematics
-
Dynamical Systems
-
Difference Equations
-
Nonlinear Analysis
-
Mathematical Modeling
-
Mathematical Biology
-
Mathematical Economics
-
Numerical Analysis
-
Chaos Theory
-
Applied Dynamical Systems
-
Computational Mathematics
-
Systems Theory
SIGNIFICANCE
This proceedings volume is particularly useful for researchers and graduate students interested in modern developments in difference equations and discrete dynamical systems. Unlike a textbook, it focuses on current research problems and recent advances, making it a valuable reference for specialists working in nonlinear dynamics and mathematical modeling.
Mathematical Modeling in Physical Sciences:
14th IC-MSQUARE, October 20–23, 2025, Virtual
DETAILS
-
Title: Mathematical Modeling in Physical Sciences: 14th IC-MSQUARE, October 20–23, 2025, Virtual
-
Editor: Dimitrios S. Vlachos
-
Series: Springer Proceedings in Mathematics & Statistics
-
Publisher: Springer Nature Switzerland AG
-
ISBN: 9783032268082
-
Format: Hardcover
-
Language: English
-
Publication Date: August 2026
-
Length: Approximately 435–600 pages (catalogs vary during pre-publication listing)
EXPLANATIONS
This volume contains selected peer-reviewed papers from the 14th International Conference on Mathematical Modeling in Physical Sciences (IC-MSQUARE 2025), held virtually from October 20–23, 2025. The proceedings present recent developments in mathematical modeling across a broad range of scientific disciplines, including physics, chemistry, biology, medicine, economics, environmental science, and engineering.
A major theme of the book is the growing role of artificial intelligence and machine learning in scientific modeling. Contributors explore how modern computational techniques, data-driven methods, and mathematical analysis can be combined to solve complex real-world problems.
The IC-MSQUARE conference series has been held annually since 2012 and serves as an international forum for researchers working at the intersection of mathematics, computation, and the physical sciences. The proceedings are intended for:
-
Applied mathematicians
-
Physicists
-
Computational scientists
-
Engineers
-
Data scientists
-
Researchers in interdisciplinary modeling and simulation
TABLE OF CONTENTS
A complete official table of contents for the 2025 proceedings has not yet been publicly released. However, publisher information indicates that the volume covers the following major areas:
Part I – Mathematics and Mathematical Physics
-
Asymptotic analysis
-
Stability theory
-
Quantum field and plasma models
-
Fourier methods
-
Nonlinear wave equations
-
Lattice Boltzmann methods
-
Optimization and variational problems
-
Algebraic structures and representations
Part II – Machine Learning, Complex Systems and Networks
-
Quantum annealing algorithms
-
Traveling Salesman Problem optimization
-
Neural networks
-
Photonic AI systems
-
Complex network analysis
-
Financial-data modeling
-
Machine-learning applications in science and engineering
Part III – Medical Applications and Epidemiological Modeling
-
Mathematical epidemiology
-
SIR-type infectious-disease models
-
Medical image analysis
-
Cancer research applications
-
Radiotomography and biomedical signal processing
-
Seizure detection using recurrent neural networks
-
Healthcare data modeling
Part IV – Engineering Applications
-
Hyperspectral imaging
-
Quality assessment systems
-
Embedded systems and IoT
-
Robotics and computer architectures
-
Transportation and logistics modeling
-
Heat-exchanger network optimization
-
LIDAR-based detection systems
-
Industrial engineering applications
KEY TOPICS COVERED
-
Mathematical Modeling
-
Applied Mathematics
-
Mathematical Physics
-
Computational Physics
-
Artificial Intelligence
-
Machine Learning
-
Complex Systems
-
Network Science
-
Epidemiological Modeling
-
Biomedical Applications
-
Optimization
-
Engineering Mathematics
-
Scientific Computing
-
Data-Driven Modeling
-
Environmental Modeling
ABOUT THE EDITOR
Dimitrios S. Vlachos received his Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens. His research interests include discrete variational theory, complex networks, evolutionary algorithms, physical and socioeconomic modeling, and machine-learning applications. He has authored more than 110 scientific publications.
This proceedings volume provides a broad overview of contemporary research in mathematical modeling, particularly emphasizing interdisciplinary applications and the increasing influence of AI-based methodologies in the physical sciences.
Chuchu Chen, Tonghe Dang, Jialin Hong, and Guoting Song.
Numerical Analysis of Stochastic Functional Differential Equations:
Longtime Asymptotics and Probabilistic Characteristics
DETAILS
-
Title: Numerical Analysis of Stochastic Functional Differential Equations: Longtime Asymptotics and Probabilistic Characteristics
-
Authors: Chuchu Chen, Tonghe Dang, Jialin Hong, Guoting Song
-
Series: Lecture Notes in Mathematics
-
Publisher: Springer Nature Singapore
-
ISBN: 9789819215911
-
Format: Paperback / Softcover
-
Language: English
-
Publication Date: July–August 2026 (catalog listings vary slightly by region)
-
Length: Approximately 250 pages
-
Subject Areas: Numerical Analysis, Stochastic Analysis, Probability Theory, Ergodic Theory, Malliavin Calculus, Large Deviations.
EXPLANATIONS
This monograph presents recent advances in the numerical analysis of stochastic functional differential equations (SFDEs), a class of differential equations that incorporate both randomness and memory effects. Such equations arise naturally in physics, biology, finance, engineering, and control systems where future evolution depends on both random perturbations and past states.
The book focuses on two major themes:
-
Longtime Asymptotic Behavior of Numerical Methods
-
Strong convergence on infinite time intervals
-
Weak convergence on infinite time intervals
-
Numerical invariant measures
-
Ergodicity of numerical schemes
-
Probabilistic Characteristics of Numerical Solutions
-
Density functions of numerical approximations
-
Central limit theorems
-
Limit distributions
-
Freidlin–Wentzell-type large deviation principles
The authors combine techniques from numerical analysis, stochastic differential equations, probability theory, ergodic theory, and Malliavin calculus to provide a rigorous treatment of both theoretical and computational aspects of SFDEs. The book is intended primarily for researchers and graduate students working in stochastic analysis and numerical mathematics.
TABLE OF CONTENTS
Chapter 1. Stochastic Functional Differential Equation
-
Introduction to SFDEs
-
Mathematical framework
-
Existence and uniqueness results
-
Examples and applications.
Chapter 2. Mean-square Convergence Analysis in the Infinite Time Horizon
-
Strong convergence theory
-
Long-time error estimates
-
Stability properties of numerical methods.
Chapter 3. Invariant Measure and Weak Convergence Analysis in the Infinite Time Horizon
-
Invariant probability measures
-
Weak approximation theory
-
Longtime weak convergence results.
Chapter 4. Numerical Central Limit Theorem
-
Asymptotic distributions
-
Numerical CLT formulations
-
Applications to stochastic dynamics.
Chapter 5. Numerical Density Function and Convergence Analysis
-
Density estimation for numerical solutions
-
Smoothness and approximation properties
-
Convergence analysis.
Chapter 6. Large Deviation Principle of Numerical Solution
-
Freidlin–Wentzell theory
-
Rare-event probabilities
-
Large deviation estimates for numerical approximations.
Appendix A. Basic Inequalities and Some Tools from Martingale Theory
-
Martingale inequalities
-
Auxiliary probabilistic tools.
Appendix B. Markov Semigroups, Invariant Measures, and Ergodicity
-
Markov semigroup theory
-
Ergodic properties
-
Invariant distributions.
Appendix C. Brief Introduction to Malliavin Calculus
-
Malliavin derivatives
-
Probabilistic smoothness techniques
-
Applications to density analysis.
Appendix D. Large Deviation Principle via Weak Convergence Approach
-
Weak convergence methods
-
Large deviation framework
-
Applications to SFDEs.
KEY TOPICS COVERED
-
Stochastic Functional Differential Equations (SFDEs)
-
Numerical Approximation of Stochastic Systems
-
Infinite-Time Convergence Analysis
-
Invariant Measures
-
Ergodic Theory
-
Central Limit Theorems
-
Density Functions of Numerical Solutions
-
Malliavin Calculus
-
Large Deviation Theory
-
Probability Theory
-
Stochastic Numerical Methods.
This book is a specialized research-level treatment of the long-term behavior and probabilistic properties of numerical methods for stochastic delay systems, making it particularly valuable for researchers in stochastic analysis, numerical probability, and applied dynamical systems.
Integrated Calculus:
Single-Variable Differential and Integral Calculus Developed in Parallel
DETAILS
-
Title: Integrated Calculus: Single-Variable Differential and Integral Calculus Developed in Parallel
-
Author: Christopher Goodrich
-
Publisher: Springer Nature Switzerland AG
-
ISBN: 9783032269645
-
Format: Hardcover
-
Publication Date: September 2026
-
Pages: Approximately 1,012–1,017 pages
-
Illustrations: More than 200 illustrations, many in color
-
Language: English
-
Subject Areas: Calculus, Real Analysis, Applied Mathematics, Ordinary Differential Equations, Mathematical Modeling.
EXPLANATIONS
This textbook presents a distinctive approach to introductory and intermediate calculus by treating differentiation and integration as parallel concepts from the very beginning, rather than introducing them in separate stages as is common in traditional calculus texts.
The author emphasizes:
-
Real-world applications and mathematical modeling
-
Conceptual understanding alongside computational techniques
-
Early introduction of sequences and series
-
Connections between calculus and ordinary differential equations
-
Pattern recognition methods for antidifferentiation
-
Careful and gradual introduction of Leibniz notation
-
Analytical and numerical approaches to differential equations.
A major pedagogical goal of the book is to help students understand calculus as a unified subject rather than as a collection of separate topics. Throughout the text, applications motivate theoretical concepts, and a large collection of exercises accommodates students with different backgrounds and levels of preparation.
The book is suitable for:
-
First-year university calculus courses
-
Advanced high-school students
-
Engineering and science students
-
Self-learners seeking a comprehensive calculus text
-
Instructors looking for a nontraditional calculus curriculum.
TABLE OF CONTENTS
Preface
Chapter 1. The Fundamentals
-
Functions
-
Limits
-
Fundamental ideas of differentiation and integration
-
Basic applications.
Chapter 2. Extending the Fundamentals
-
Further differentiation techniques
-
Further integration techniques
-
Applications and examples.
Chapter 3. Qualitative Analysis of the Growth and Decay of Populations
-
Population models
-
Exponential growth and decay
-
Mathematical modeling
-
Dynamical behavior.
Chapter 4. Differentiation and Antidifferentiation Techniques and Applications
-
Rules of differentiation
-
Antiderivative methods
-
Optimization
-
Applied problems.
Chapter 5. Differential Equations: Analytical and Numerical Solution Techniques with Applications
-
First-order differential equations
-
Numerical methods
-
Modeling applications
-
Qualitative behavior of solutions.
Chapter 6. Calculus on Parametrized Curves in the Plane
-
Parametric equations
-
Arc length
-
Curvature
-
Geometric applications.
Chapter 7. Vector-Valued Functions
-
Curves in space
-
Velocity and acceleration
-
Vector calculus concepts
-
Physical applications.
Chapter 8. Power Series and Their Application
-
Sequences and series
-
Taylor polynomials
-
Power series expansions
-
Approximation methods
-
Applications to differential equations and analysis.
Index
KEY FEATURES
-
Differentiation and integration developed simultaneously
-
Early use of sequences and series throughout the text
-
Strong emphasis on applications and modeling
-
Integration of ordinary differential equations into the calculus curriculum
-
Extensive exercise sets for varying levels of difficulty
-
More than 1,000 pages of comprehensive coverage.
MATHEMATICAL TOPICS COVERED
-
Limits and Continuity
-
Differential Calculus
-
Integral Calculus
-
Ordinary Differential Equations
-
Numerical Methods
-
Parametric Curves
-
Vector-Valued Functions
-
Sequences and Series
-
Taylor Polynomials
-
Mathematical Modeling
-
Applied Calculus.
This book stands out among modern calculus texts because it treats differentiation and integration as complementary processes from the outset and integrates differential equations into the learning process much earlier than most standard calculus curricula.