Programming HTML5 Applications

The science of rheology and its applications have grown steadily. Although polymers dominated in the past, the applications to foods have become increasingly important over the last four decades. The complexity of food rheology has not only generated increased interest among academics, but it has also led to an increased recognition of its importance in the food industry. Emphasizing physics rather than mathematics, Polymer and Food Rheology: Volume 1, Applications to Single-Phase Systems focuses on rheological characteristics and properties of single substances and homogeneous mixtures. It introduces fundamental principles, types of flows, types of instruments, their theory, capabilities, limitations, and sources of error. Both sophisticated rheometers and simple devices and their uses are considered.- Discusses the types of material functions (properties) obtained from the different types of measurements and techniques: shear viscosity, normal stress differences, dynamic mechanical p

As an introduction to Python, this book allows readers to take a slow and steady approach to understanding Python code, explaining concepts, connecting programming with real-life examples, writing Python programs, and completing case studies.While there are many books, websites, and online courses about the topic, we break down Python programming into easily digestible lessons of less than 5 minutes each, following our BiteSize approach. Each lesson begins with a clear and short introduction to the topic. This gives you a strong base to start from and gets you ready for deeper learning. Then, you will see coding demonstrations that show the ideas discussed. These examples are simple and useful, helping you really understand the concepts. You'll then practice tasks at different difficulty levels, so you can test your knowledge and increase your confidence. You'll also play with case studies to solve real-world problems. Tips are included to show how you can incorporate generative AI int

The book builds on an analogy between social groups and assemblies of molecules to introduce the concepts of statistical mechanics, machine learning and data science. The idea is to bolster students' interest by proposing a new take on the topic that draws on a data analytics approach of molecules. Specifically, how the analysis of their individual features, as well as of interactions and "communication" processes can predict their properties and collective behavior, just as polling and social networking shed light on the behavior of social groups. Applications to systems at the cutting-edge of research e.g. environmental and energy applications, will be used.Key Features: Draws on a data analytics approach of molecules Covers hot topics such as artificial intelligence and machine learning of molecular trends Applications to systems at the cutting-edge of research e.g. environmental and energy applications, are used Discusses molecular simulation and links with other important, emergin

This reference book provides updated information on the production and industrial significance of bacterial cellulose. Bacterial cellulose is a natural fiber produced by certain microbes, mainly bacteria which belong to the Acetobacter genera. The book discusses its applications in different industrial sectors like food, pharmaceutical, energy and wastewater treatment. It covers the production of cellulose from conventional and renewable feedstocks. It includes topics like downstream processing, characterization, and chemical modification of bacterial cellulose. Key features- Addresses the challenge on the production technologies of bacterial cellulose up to pilot-scale Discusses cost-effective, green processes using agri-processing residues and medium formulation Includes efficient preparation of nano-composite using in vitro and in vivo methods Provides latest applications of bacterial cellulose in food and pharmaceuticals fields Reviews the production of bacterial fro

Finance students and practitioners may ask: can machines learn everything? Could AI help me? Computing students or practitioners may ask: which of my skills could contribute to finance? Where in finance should I pay attention? This book aims to answer these questions. No prior knowledge is expected in AI or finance.Including original research, the book explains the impact of ignoring computation in classical economics; examines the relationship between computing and finance and points out potential misunderstandings between economists and computer scientists; and introduces Directional Change and explains how this can be used.To finance students and practitioners, this book will explain the promise of AI, as well as its limitations. It will cover knowledge representation, modelling, simulation and machine learning, explaining the principles of how they work. To computing students and practitioners, this book will introduce the financial applications in which AI has made an impact. This

Conventional Flowmeters, Volume II covers origin, principle of operation, development, advantages and disadvantages, applications, and frontiers of research for conventional technology flowmeters, which include differential pressure and primary elements, positive displacement, turbine, open channel, and variable area.There are more conventional technology meters being used in the field than new-technology meters. New developments, such as more accurate pressure transmitters, new primary elements like cone elements, reversible flow, and dual rotor turbine meters, and variable area meters with transmitters and a signal output, are discussed.Features: Offers a working knowledge of the origin and development of the more traditional technology flowmeters: differential pressure and primary elements, positive displacement, turbine, open channel, and variable area. Describes how these conventional meters still fit into what is being called Industry 4.0. Discusses the advantages and disa

Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.Key features: Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.Explains and provides examples of deploying TensorFlow and Keras in several projects.Explains the fundamentals of Artificial Neural Networks (ANNs).Presents several examples and applications of ANNs.Learning the most popular DL algorithms features.Explains and provides examples for the DL algorithms that are presented in this book.Analyzes the DL network's parameter and hyperparameters.Reviews state-of-the-art DL examples.Necessary and main steps for DL modeling.Implements a Virtual Assistant Robot (VAR) using DL methods.Necessary and fundamental information to choose a proper DL algorithm.Gives instructions to learn how to optimize your DL model IN PRACTICE.This book is useful for undergraduate and graduate students, as well as practitioners in industry