The author writes with the aim of encouraging the people of God in the 'faith once for all delivered to the saints.' In these days of confusion and uncertainty in the world, he would remind the Church that its 'redemption draws near.' In the light of this awareness, we must strengthen 'those things that remain, ' that we may persevere and so be found faithful at His appearing. To this end he would clarify, augment and hopefully simplify what he wrote in his earlier work, 'He Comes' and 'You shall See His Glory in the Morning.' He also would finish a work that was intended to extend to a few pages but has ended with three volumes. May the God of all grace use this work for the strengthening of His people and the glory of His great and Holy name. James Brown was educated at Edinburgh and Aberdeen. After working in secular occupations for some time, he served as a minister in the Church of Scotland for thirty five years. He now serves as a Locum in the Church. He cannot improve on the the advice given to Robert Murray McCheyne as he entered his ministry by an aunt who urged him, 'Always say a good word for Jesus.' He would like to think that by the grace of God, he has endeavoured throughout the years to do just that.

This book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time. In concrete terms, future robots will have to solve the classification problem represented by scene recognition sufficiently well for them to act independently in human-centered environments. To achieve accurate yet versatile indoor scene recognition, the book presents a hierarchical data structure for scenes – the Implicit Shape Model trees. Further, it also provides training and recognition algorithms for these trees. In general, entire indoor scenes cannot be perceived from a single point of view. To address this problem the authors introduce Active Scene Recognition (ASR), a concept that embeds canonical scene recognition in a decision-making system that selects camera views for a mobile robot to drive to so that it can find objects not yet localized. The authors formalize the automatic selection of camera views as a Next-Best-View (NBV) problem to which they contribute an algorithmic solution, which focuses on realistic problem modeling while maintaining its computational efficiency. Lastly, the book introduces a method for predicting the poses of objects to be searched, establishing the otherwise missing link between scene recognition and NBV estimation.

Ten minibooks in one get you thoroughly caught up on Windows 8.1! With new improvements and changes, Windows 8.1 offers a refreshed user interface, better integration between the new and traditional Windows interfaces, and more. This updated top-selling guide is what you need to get up to speed on everything Windows 8.1. Nine minibooks in one cover such essential topics as navigating the new Start Screen, understanding Windows 8.1 apps, securing Windows 8.1, and much more. Take the guesswork out of Windows 8.1 from day one with this complete, all-in-one resource. Helps you get up to speed on the Windows 8.1 operating system, including its Start Screen, which is a feature sure to please traditional Windows users Provides top-notch guidance from trusted and well-known Windows expert and author Woody Leonhard Covers Windows 8.1 inside and out, including how to customize the Start screen, manage apps, and control privacy Delves into core Windows 8.1 apps such as e-mail, people, and SkyDrive Shows you how to connect online, add hardware, back up and update, and secure Windows 8.1 Discover new improvements, old favorites, and everything in between with Windows 8.1 All-in-One For Dummies.

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

This book unravels the how & why of advertising and places the industry in its social, historical & political context. Focusing on key debates, it explores the competitive practices & discourses which govern the industry & those who work in it.