Mathematical modelling

This book highlights a comprehensive overview of research and technical advances related to parametric array loudspeakers (PALs), covering modeling and simulation, measurements, signal processing, beamsteering, and their implementations and applications.

This book is a collection of research papers from the “7th International Conference on Mathematical Modelling, Applied Analysis and Computation” organized by Lebanese American University, Beirut, Lebanon from April 18–20, 2024.

This book is a collection of research papers from the “7th International Conference on Mathematical Modelling, Applied Analysis and Computation” organized by Lebanese American University, Beirut, Lebanon from April 18–20, 2024.

This book highlights a comprehensive overview of research and technical advances related to parametric array loudspeakers (PALs), covering modeling and simulation, measurements, signal processing, beamsteering, and their implementations and applications.

This book is a theoretical and pragmatic tool that applies mathematical modelling in understanding and managing diabetes and related complications such as diabetes predisposition, diabetes onset, regular glycaemic monitoring, glycated haemoglobin HbA1c, diabetes homeostasis, gestational diabetes and other associated diseases and conditions.

This book is a collection of research papers from the “7th International Conference on Mathematical Modelling, Applied Analysis and Computation” organized by Lebanese American University, Beirut, Lebanon from April 18–20, 2024.

This book introduces approaches to generalize the benefits of equivariant deep learning to a broader set of learned structures through learned homomorphisms.

Optimization problems are widespread in the mathematical modeling of real world systems and their applications arise in all branches of science, applied science and engineering.

This book uses blending theory in math cognition, and assesses the main aspect of this theory, called image schema theory.

This book describes novel ways of using deep learning to solve real-world problems.

'I have a truly marvellous demonstration of this proposition which this margin is too narrow to contain.