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Graphs have become a fixture of everyday life, used in scientific and business publications, in magazines and newspapers, on television, on billboards, and even on cereal boxes. Nonetheless, surprisingly few graphs communicate effectively, and most graphs fail because they do not take into account the goals, needs, and abilities of the viewers. In raph Design for Eye and Mind, Stephen Kosslyn addresses these problems by presenting eight psychological principles for constructing effective graphs. Each principle is solidly rooted both in the scientific literature on how we perceive and comprehend graphs and in general facts about how our eyes and brains process visual information. Kosslyn then uses these eight psychological principles as the basis for hundreds of specific recommendations that serve as a concrete, step-by-step guide to deciding whether a graph is an appropriate display to use, choosing the correct type of graph for a specific type of data and message, and then constructing graphs that will be understood at a glance. Kosslyn also includes a complete review of the scientific literature on graph perception and comprehension, and appendices that provide a quick tutorial on basic statistics and a checklist for evaluating computer-graphics programs. Graph Design for Eye and Mind is an invaluable reference for anyone who uses visual displays to convey information in the sciences, humanities, and businesses such as finance, marketing, and advertising.
As in previous editions, the symbols used on paper nautical charts produced by NOAA and the NGA and digital raster representations of those charts, such as NOAA Raster Nautical Chart (NOAA RNC's), are presented in lettered sections organized in categories, such as Landmarks, Depths, and Lights.
The design of a highway drainage channel to carry a given discharge is accomplished in two parts. The first part of the design involves the computation of a channel section which will carry the design discharge on the available slope. This chapter briefly discusses the principles of flow in open channels and the use of the Manning equation for computing the channel capacity. The second part of the design is the determination of the degree of protection required to prevent erosion in the drainage channel. This can be done by computing the velocity in the channel at the design discharge, using the Manning equation, and comparing the calculated velocity with that permissible for the type of channel lining used. A change in the type of channel lining will require a change in channel size unless both linings have the same roughness coefficient.
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Whether out for an afternoon's sail or embarking on a long offshore passage, there is always an element of chance and uncertainty about being at sea. To be responsible for the wellbeing of both crew and vessel, a good skipper needs to know their limitations and ensure they are operating well within the margins of safety. Safe Skipper is a practical and thought provoking guide for yacht skippers of all levels of experience, full of invaluable advice and tips on how to reduce to the minimum the risks of mishaps and equipment failure at sea. There's a wide range of information on seamanship, preparation, seaworthiness, gear, boat handling, leadership, teamwork, watch keeping, communications, navigation, weather and emergency procedures, all delivered in a highly practical, lively, non-preachy fashion. Included throughout are useful checklists, box-outs and case studies of accidents and their causes, with survivors' testimonials and explanations of how disasters were avoided, or could have been, all of which provides valuable lessons for everyone who goes to sea.
Chart Number One is essential to correct and accurate use of nautical charts. More than a chart, it is a book that defines the symbols, abbreviations and terms used on charts. It also provides important information about buoys, light visibility (range) and aids to navigation. This new and improved edition from Paradise Cay is a complete and accurate high quality reproduction of information provided by NOAA and NIMA.
This authoritative, reader-friendly text presents core principles of good map design that apply regardless of production methods or technical approach. The book addresses the crucial questions that arise at each step of making a map: Who is the audience? What is the purpose of the map? Where and how will it be used? Students get the knowledge needed to make sound decisions about data, typography, color, projections, scale, symbols, and nontraditional mapping and advanced visualization techniques. Pedagogical Features: *Over 200 illustrations (also available at the companion website as PowerPoint slides), including 23 color plates *Suggested readings at the end of each chapter. *Recommended Web resources. *Instructive glossary