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There are three standard methods to visually represent a building: the plan, elevation, and section. The section drawing is a vertical slice of a building, depicting the relationships between interior and exterior as well as any level changes. While the section can serve as merely a functional drawing for construction, it can also be an exciting, revelatory drawing that can artfully depict a building, landscape, or object. Visual Discoveries: A Collection of Sections is an image-forward book that is devoted to showcasing notable section drawings throughout history and demonstrating that the section drawing, while having roots in architecture, has spread to many other professions and disciplines. These professions include medicine, transportation, product design, geology, and landscape architecture. Architects and designers featured in the book include Paul Rudolph, OMA, Zaha Hadid Architects, Diller Scofidio + Renfro, Renzo Piano Building Workshop, Foster + Partners, Weiss/Manfredi, and Mecanoo. The book also features cross sections created by Leonardo da Vinci, Charles Darwin, and Robert Fulton.
From the wheel to the worldwide web, our planet has been transformed by science. Now you can travel through time to experience centuries of invention and innovation on this spectacular visual voyage of discovery. Starting in ancient times and ending up in the modern world, you'll explore scientific history showcased in stunning images and captivating text. An easy-to-follow illustrated timeline runs throughout the ebook, keeping you informed of big breakthroughs and key developments. Get to grips with revolutionary ideas like measuring time or check out amazing artifacts like flying machines. Great geniuses, including Marie Curie, Albert Einstein, and Charles Darwin are introduced alongside their most important ideas and inventions, all shown in glorious detail. Hundreds of pages of history are covered in Timelines of Science, with global coverage of scientific advances. Whether you're joining in with eureka moments, inspecting engines, or learning about evolution, all aspects of science are covered from the past, present, and future.
From water, air, and fire to tennessine and oganesson, celebrated science writer Philip Ball leads us through the full sweep of the field of chemistry in this exquisitely illustrated history of the elements. The Elements is a stunning visual journey through the discovery of the chemical building blocks of our universe. By piecing together the history of the periodic table, Ball explores not only how we have come to understand what everything is made of, but also how chemistry developed into a modern science. Ball groups the elements into chronological eras of discovery, covering seven millennia from the first known to the last named. As he moves from prehistory and classical antiquity to the age of atomic bombs and particle accelerators, Ball highlights images and stories from around the world and sheds needed light on those who struggled for their ideas to gain inclusion. By also featuring some elements that aren’t true elements but were long thought to be—from the foundational prote hyle and heavenly aetherof the ancient Greeks to more recent false elements like phlogiston and caloric—The Elements boldly tells the full history of the central science of chemistry.
Good graphs make complex problems clear. From the weather forecast to the Dow Jones average, graphs are so ubiquitous today that it is hard to imagine a world without them. Yet they are a modern invention. This book is the first to comprehensively plot humankind's fascinating efforts to visualize data, from a key seventeenth-century precursor--England's plague-driven initiative to register vital statistics--right up to the latest advances. In a highly readable, richly illustrated story of invention and inventor that mixes science and politics, intrigue and scandal, revolution and shopping, Howard Wainer validates Thoreau's observation that circumstantial evidence can be quite convincing, as when you find a trout in the milk. The story really begins with the eighteenth-century origins of the art, logic, and methods of data display, which emerged, full-grown, in William Playfair's landmark 1786 trade atlas of England and Wales. The remarkable Scot singlehandedly popularized the atheoretical plotting of data to reveal suggestive patterns--an achievement that foretold the graphic explosion of the nineteenth century, with atlases published across the observational sciences as the language of science moved from words to pictures. Next come succinct chapters illustrating the uses and abuses of this marvelous invention more recently, from a murder trial in Connecticut to the Vietnam War's effect on college admissions. Finally Wainer examines the great twentieth-century polymath John Wilder Tukey's vision of future graphic displays and the resultant methods--methods poised to help us make sense of the torrent of data in our information-laden world.
This book is the only account of what honeybees actually see. Bees detect some visual features such as edges and colours, but there is no sign that they reconstruct patterns or put together features to form objects. Bees detect motion but have no perception of what it is that moves, and certainly they do not recognize "things" by their shapes. Yet they clearly see well enough to fly and find food with a minute brain. Bee vision is therefore relevant to the construction of simple artificial visual systems, for example for mobile robots. The surprising conclusion is that bee vision is adapted to the recognition of places, not things. In this volume, Adrian Horridge also sets out the curious and contentious history of how bee vision came to be understood, with an account of a century of neglect of old experimental results, errors of interpretation, sharp disagreements, and failures of the scientific method. The design of the experiments and the methods of making inferences from observations are also critically examined, with the conclusion that scientists are often hesitant, imperfect and misleading, ignore the work of others, and fail to consider alternative explanations. The erratic path to understanding makes interesting reading for anyone with an interest in the workings of science but particularly those researching insect vision and invertebrate sensory systems.
Data is powerful. It separates leaders from laggards and it drives business disruption, transformation, and reinvention. Today’s most progressive companies are using the power of data to propel their industries into new areas of innovation, specialization, and optimization. The horsepower of new tools and technologies have provided more opportunities than ever to harness, integrate, and interact with massive amounts of disparate data for business insights and value – something that will only continue in the era of the Internet of Things. And, as a new breed of tech-savvy and digitally native knowledge workers rise to the ranks of data scientist and visual analyst, the needs and demands of the people working with data are changing, too. The world of data is changing fast. And, it’s becoming more visual. Visual insights are becoming increasingly dominant in information management, and with the reinvigorated role of data visualization, this imperative is a driving force to creating a visual culture of data discovery. The traditional standards of data visualizations are making way for richer, more robust and more advanced visualizations and new ways of seeing and interacting with data. However, while data visualization is a critical tool to exploring and understanding bigger and more diverse and dynamic data, by understanding and embracing our human hardwiring for visual communication and storytelling and properly incorporating key design principles and evolving best practices, we take the next step forward to transform data visualizations from tools into unique visual information assets. Discusses several years of in-depth industry research and presents vendor tools, approaches, and methodologies in discovery, visualization, and visual analytics Provides practicable and use case-based experience from advisory work with Fortune 100 and 500 companies across multiple verticals Presents the next-generation of visual discovery, data storytelling, and the Five Steps to Data Storytelling with Visualization Explains the Convergence of Visual Analytics and Visual discovery, including how to use tools such as R in statistical and analytic modeling Covers emerging technologies such as streaming visualization in the IOT (Internet of Things) and streaming animation
Why do certain geometric patterns appear to pulsate? What makes your eyes see color where there is none? How do colorful rings appear on a spinning black-and-white disk? These questions and more are answered at the Exploratorium, San Francisco's renowned hands-on science museum. Now readers can bring the experience home through 30 mind-boggling experiments that will wow science geeks of all ages. Seeing comes with almost everything needed to experience the amazing effects--including spinner, reflective sheet, straws, and pipe cleaners--and the tear-out pages make it easy to share the fun with friends!
This book presents a systematic study of visual pattern discovery, from unsupervised to semi-supervised manner approaches, and from dealing with a single feature to multiple types of features. Furthermore, it discusses the potential applications of discovering visual patterns for visual data analytics, including visual search, object and scene recognition. It is intended as a reference book for advanced undergraduates or postgraduate students who are interested in visual data analytics, enabling them to quickly access the research world and acquire a systematic methodology rather than a few isolated techniques to analyze visual data with large variations. It is also inspiring for researchers working in computer vision and pattern recognition fields. Basic knowledge of linear algebra, computer vision and pattern recognition would be helpful to readers.
What factors affect creativity and the generation of creative images? What factors affect the ability to reinterpret those images? Research described in this book indicates that expectations constrain both of these attributes of creativity. Characteristics of the imagined pattern, such as cohesiveness or its psychological goodness, also affect image generation and reinterpretation. Other evidence indicates that images can be combined mentally to yield new, manipulable composites. Cognitive models encompass the research and extend it to fields as diverse as architecture, music, and problem solving.
This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.