Data Structures Using C

Dynamic stability analysis enables the determination of unstable regions, which adversely affect a structure's durability. Unlike conventional cable-strut frameworks, tensegrity structures are characterized by a system of internal forces that hold the elements in stable equilibrium, so the initial prestress crucially affects the distribution of unstable regions. This book presents both theoretical background and examples to make a full qualitative and quantitative assessment of these structures possible. First, a geometrically non-linear model and the methods used to evaluate the behavior of tensegrity structures are explained, before a broad spectrum of different planar and spatial design solutions is considered. The book moves step-by-step from the simplest two-dimensional structure, for which solutions can be presented in explicit form, to more complex tensegrity structures such as domes, towers, and plates.

This book aims to provide actual methods of calculation and standard details followed by professionals in industrial projects pertaining to Reinforced Cement Concrete (RCC) structures backed by practical design and standard details. It covers engineering properties of soil and types of tests, different types of concrete grades, standard notes and codes, workout examples of piles, foundations, and super structure elements. It provides all the standard construction details including reinforcement arrangement, generally used for RCC works in superstructure and foundations.Features: Provides strength design calculation for foundation and settlement analysis of the founding soil together. Discusses standard details of reinforced concrete joints and reinforcement placement. Describes suitable types of material and selection of structure according to nature founding soil and service life of the plant. Explores standard construction details. Includes solved problems, design and worked out exa

In the era of 'Algorithmic Medicine, ' the integration of Artificial Intelligence (AI) in healthcare holds immense potential to address critical challenges faced by the industry. Drawing upon the expertise and experience of the authors in medicine, data science, medical informatics, administration, and entrepreneurship, this textbook goes beyond theoretical discussions to outline practical steps for transitioning AI from the experimental phase to real-time clinical integration. Using the Translational Science methodology, each chapter of the book concisely and perspicuously addresses the key issues associated with AI implementation in healthcare. Covering technical, clinical, ethical, regulatory, and legal considerations, the authors present evidence-based solutions and frameworks to overcome these challenges. Engaging case studies and a literature review of peer-reviewed studies and official documents from reputed organizations provide a balanced perspective, bridging the gap between

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

Artificial Intelligence-Aided Materials Design: AI-Algorithms and Case Studies on Alloys and Metallurgical Processes describes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the included MATLAB and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference. Offers advantages and limitations of several AI concepts and their proper implementation in various data types generated through experiments and computer simulations and from industries in different file formats Helps readers develop predictive models through AI/ML algorithms by writing their own computer code or usin

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