Pattern Classification Using Ensemble Methods

This book is designed to provide students, teachers, and researchers with a text that includes a full range of statistical methods available to address commonly encountered research problems. Many textbooks for introductory, intermediate, and advanced statistics courses focus heavily on parametric methods. However, in practice the assumptions underlying these methods are frequently not met, therefore calling into question their use. This book addresses this issue by presenting parametric, nonparametric, robust, and Bayesian techniques that are appropriate for research scenarios often encountered in practice and typically found in statistics courses. For each of these major topics, the standard parametric approach is presented, along with the assumptions underlying it and the methods used to assess the viability of these assumptions. Next, a set of alternative techniques for the research scenario is presented and applied to the motivating example that begins each chapter. Each chapter c

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

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

This book presents methods for the summation of infinite and finite series and the related identities and inversion relations. The summation includes the column sums and row sums of lower triangular matrices. The convergence of the summation of infinite series is considered. The author's focus is on symbolic methods and the Riordan array approach. In addition, this book contains hundreds summation formulas and identities, which can be used as a handbook for people working in computer science, applied mathematics, and computational mathematics, particularly, combinatorics, computational discrete mathematics, and computational number theory. The exercises at the end of each chapter help deepen understanding.Much of the materials in this book has never appeared before in textbook form. This book can be used as a suitable textbook for advanced courses for high lever undergraduate and lower lever graduate students. It is also an introductory self-study book for re- searchers interested in t

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

Bringing together a wealth of knowledge, Environmental Management Handbook, Second Edition, gives a comprehensive overview of environmental problems, their sources, their assessment, and their solutions. Through in-depth entries and a topical table of contents, readers will quickly find answers to questions about environmental problems and their corresponding management issues. This six-volume set is a reimagining of the award-winning Encyclopedia of Environmental Management, published in 2013, and features insights from more than 400 contributors, all experts in their field. The experience, evidence, methods, and models used in studying environmental management are presented here in six stand-alone volumes, arranged along the major environmental systems. Features The first handbook that demonstrates the key processes and provisions for enhancing environmental management Addresses new and cutting-edge topics on ecosystem services, resilience, sustainability, food-energy-water nex