"Food," says Ruby Ann Boxcar, "is one thing all trailer park people have in common, followed by their undyin' love of Elvis and the reproduction of ugly children." The recipes of trailer dwellers are unlike any others. Its been known to make men turn championship wrestling off, large women in double knit polyester slacks dance, and derelict children smile. That's why Ruby Ann has taken the time to write down her favorite recipes in an easy to read cookbook (The Down Home Trailer Park Cookbook; A Twister Of Tasty Treats). This cookbook gives the reader a titillating guide to handed down recipes and an insider's look at Ruby Ann's fellow residents at the 20 lot "High Chaparral Trailer Park" in Pangburn, Arkansas. Along with good food and gossip, the reader will come face to face with sex, murder, topless dancing, Baptist ministers, adultery, and political secrets. The fact that Ruby Ann Boxcar has lived her entire life in a trailer, and her updo hairstyle, cat eyed glasses, and blue eye shadow insures the reader she knows what she's talking about when it comes to trailer park living. Her 300-pound figure speaks for itself on the question of her cooking credentials.

Discusses techniques, tools, and terms of barbecue cooking, and offers trailer decoration advice and recipes for dishes including Baptist burgers, ambrosia pound cake, and Dr Pepper BBQ sauce.

Even those who live in a house without wheels can now share in the very special lifestyle afforded by the unique trailer park milieu. Ruby Ann shares her secrets for livin' life to the fullest along with anecdotes from the vaults of the High Chaparral trailer park where hot sex, warm spam and cold beer are just the beginning. With b/w photos throughout.

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

This book is composed of a selection of articles from The 2021 World Conference on Information Systems and Technologies (WorldCIST'21), held online between 30 and 31 of March and 1 and 2 of April 2021 at Hangra de Heroismo, Terceira Island, Azores, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges of modern information systems and technologies research, together with their technological development and applications. The main topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; N) Technologies for Biomedical Applications.