This book is an introduction to the use of machine learning and data-driven approaches in fluid simulation and animation, as an alternative to traditional modeling techniques based on partial differential equations and numerical methods – and at a lower computational cost. This work starts with a brief review of computability theory, aimed to convince the reader – more specifically, researchers of more traditional areas of mathematical modeling – about the power of neural computing in fluid animations. In these initial chapters, fluid modeling through Navier-Stokes equations and numerical methods are also discussed. The following chapters explore the advantages of the neural networks approach and show the building blocks of neural networks for fluid simulation. They cover aspects related to training data, data augmentation, and testing. The volume completes with two case studies, one involving Lagrangian simulation of fluids using convolutional neural networks and the other using Generative Adversarial Networks (GANs) approaches.
Fascism in Brazil analyzes the long and varied history of the Brazilian extreme right. The book examines integralism, the main historical Brazilian fascist ideology represented by Brazilian integralist Action, the largest fascist movement outside Europe. It analyzes the Integralist tradition from its founding in 1932 to the present day. It examines how Brazilian integralist Action began with its leader Plínio Salgado's trip to Fascist Italy, and how the Popular Representation Party developed integralism in the postwar era. The book also explores the support of integralists for the 1964 military coup and the role of integralists in the dictatorship. The contemporary extreme right in Brazil is still inspired by the integralist slogans of the 1930s as they seek to find political space and to demonstrate their strength. Contemporary turning points in neo-integralism were the involvement of neo-fascist groups, including neo-integralists, in the upheavals that culminated in the election of Brazilian President Jair Bolsonaro, as well as in the attack on the headquarters of comedy group Porta dos Fundos in Rio de Janeiro in 2019. This book will be of interest to students and scholars researching comparative fascist studies, the history of the far right, and Brazilian and Latin American history and politics.
This book is an introduction to the use of machine learning and data-driven approaches in fluid simulation and animation, as an alternative to traditional modeling techniques based on partial differential equations and numerical methods – and at a lower computational cost. This work starts with a brief review of computability theory, aimed to convince the reader – more specifically, researchers of more traditional areas of mathematical modeling – about the power of neural computing in fluid animations. In these initial chapters, fluid modeling through Navier-Stokes equations and numerical methods are also discussed. The following chapters explore the advantages of the neural networks approach and show the building blocks of neural networks for fluid simulation. They cover aspects related to training data, data augmentation, and testing. The volume completes with two case studies, one involving Lagrangian simulation of fluids using convolutional neural networks and the other using Generative Adversarial Networks (GANs) approaches.
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