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Kopczewska K: Modelling Spatial Density

Modelling Spatial Density

Data, Methods, and R Applications in Statistics, Econometrics, and Machine Learning

The book presents a detailed discussion of nanomaterials, nanofluids, application of nanofluids as a coolant to reduce heat transfer. It presents a detailed approach to the formulation of mathematical modelling applicable to any type of case study with a validation approach and sensitivity and optimization.

Mathematical Modelling of Heat Transfer Performance of Heat Exchanger using Nanofluids

This book is the first one that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. They develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.

Neural networks and neural dynamics are powerful approaches for the online solution of mathematical problems arising in many areas of science, engineering, and business. Compared with conventional gradient neural networks that only deal with static problems of constant coefficient matrices and vectors, the authors’ new method called zeroing dynamics solves time-varying problems. Zeroing Dynamics, Gradient Dynamics, and Newton Iterations is the first book that shows how to accurately and efficiently solve time-varying problems in real-time or online using continuous- or discrete-time zeroing dynamics. The book brings together research in the developing fields of neural networks, neural dynamics, computer mathematics, numerical algorithms, time-varying computation and optimization, simulation and modeling, analog and digital hardware, and fractals.The authors provide a comprehensive treatment of the theory of both static and dynamic neural networks. Readers will discover how novel theoretical results have been successfully applied to many practical problems. The authors develop, analyze, model, simulate, and compare zeroing dynamics models for the online solution of numerous time-varying problems, such as root finding, nonlinear equation solving, matrix inversion, matrix square root finding, quadratic optimization, and inequality solving.

Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

This book explores the design and analysis of fractional-order and active disturbance rejection control, examining both the theoretical foundations and their practical applications.

Fractional Order PID and ADR Controls

Number Systems: A Path into Rigorous Mathematics aims to introduce number systems to an undergraduate audience in a way that emphasises the importance of rigour, and with a focus on providing detailed but accessible explanations of theorems and their proofs.

A Path into Rigorous Mathematics

Number Systems

This book covers a broad range of questions related to the importance of cell geometry in many areas, including nuclear positioning, chromosome dynamics, cytoskeletal remodeling, tissue patterning, cell-matrix and multicellular contacts. It also addresses medical implications, from its implication in the development of tumors to its role in fibrosis. Together, the chapters in this book will highlight current knowledge and modern approaches to investigating the biophysical design principles underlying key biological functions, with the overall goal of elucidating the connections between cell geometry and nuclear mechanics.

This book covers a broad range of questions related to the importance of cell geometry in many areas, including nuclear positioning, chromosome dynamics, cytoskeletal remodeling, tissue patterning, cell-matrix and multicellular contacts. It also addresses medical implications, from its implication in the development of tumors to its role in fibrosis. Together, the chapters in this book will highlight current knowledge and modern approaches to investigating the biophysical design principles underlying key biological functions, with the overall goal of elucidating the connections between cell geometry and nuclear mechanics.

Cell Geometry

This textbook offers a concise but self-contained introduction to the art of numerical modelling in sciences. It discusses all the steps, from the mathematical foundations of the model to the solution procedures that are commonly used by advanced practitioners.

Introduction to Numerical Modeling in the Earth Sciences

A Comprehensive Practical Guide for Graduates and Young Academics in Science and Engineering

The Doctorate Blueprint

Series in Materials Science and Engineering

This book provides an introduction to the geometrical and topological methods that have become essential tools for soft condensed matter physicists. The emphasis is on providing mathematical tools in clear but precise language, focusing on fundamental concepts using real examples to illustrate for readers in vivid, three-dimensional fashion. The motivation is clearly provided using problems from soft condensed matter, from the packing of colloids to liquid crystals and thermal fluctuations of lipid membranes.

This book provides an introduction to the geometrical and topological methods that have become essential tools for soft condensed matter physicists. The emphasis is on providing mathematical tools in clear but precise language, focusing on fundamental concepts using real examples to illustrate for readers in vivid, three-dimensional fashion. The motivation is clearly provided using problems from soft condensed matter, from the packing of colloids to liquid crystals and thermal fluctuations of lipid membranes.

Geometry and Topology of Soft Materials

This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.

Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems

Oxford Series in Ecology and Evolution

Aimed at a broad audience of graduate students and researchers in ecology and evolution, this novel creates a persuasive argument that an explicit consideration of history will often lead to a deeper, more nuanced understanding of almost every eco-evolutionary system.

Aimed at a broad audience of graduate students and researchers in ecology and evolution, this novel creates a persuasive argument that an explicit consideration of history will often lead to a deeper, more nuanced understanding of almost every eco-evolutionary system.

Historical Approaches to Ecology and Evolution

Beyond Equilibria

Modelling Spatial Density

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