Design And Modeling for Computer Experiments

Theories of social-ecological resilience have developed over the past decades and rapidly become an important framework for governance of complex non-linear environmental problems. This book explores the resilience theories and their compatibility with law, it identifies corresponding legal features. The legal features identified, including legal measures, mechanisms, principles and approaches, form a legal design for social-ecological resilience. A legal design that can be applied to different governance situations. It can be a tool both for designing new laws, as well as for assessing the effectiveness of current laws and legal systems. In many ways environmental law has adjusted and developed new approaches to meet complex environmental problems, but law is still challenged by the complexity that characterize environmental problems and the environmental change connected with the Anthropocene. This book provides a comprehensive review of the most fundamental components of the governa

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing

Natural language generation (NLG) is the process wherein computers produce output in readable human languages. Such output takes many forms, including news articles, sports reports, prose fiction, and poetry. These computer-generated texts are often indistinguishable from human-written texts, and they are increasingly prevalent. NLG is here, and it is everywhere. However, readers are often unaware that what they are reading has been computer-generated. This Element considers how NLG conforms to and confronts traditional understandings of authorship and what it means to be a reader. It argues that conventional conceptions of authorship, as well as of reader responsibility, change in instances of NLG. What is the social value of a computer-generated text? What does NLG mean for modern writing, publishing, and reading practices? Can an NLG system be considered an author? This Element explores such question, while presenting a theoretical basis for future studies.

'Phase-only Fresnel holograms,' which can be displayed on a single SLM without the need for lenses or complicated optical accessories, substantially simplifies 3-D holographic display systems. Exploring essential concepts, theories, and formulations of these phase-only Fresnel holograms, this book provides comprehensive coverage of modern methods for generating such holograms, which pave the way for commercial products such as compact holographic projectors, heads-up displays, and data security enhancement. Relevant MATLAB codes are provided for readers to implement and evaluate the theories and formulations of different methods, and can be used as a quick start framework for further research and development. This is a crucial and up-to-date treatment of phase-only Fresnel holograms for students and researchers in electrical and electronic engineering, computer science/engineering, applied physics, information technology, and multimedia technology, as well as engineers and scientists

Imagine a world where machines can see and understand the world the way humans do. Rapid progress in artificial intelligence has led to smartphones that recognize faces, cars that detect pedestrians, and algorithms that suggest diagnoses from clinical images, among many other applications. The success of computer vision is founded on a deep understanding of the neural circuits in the brain responsible for visual processing. This book introduces the neuroscientific study of neuronal computations in visual cortex alongside of the psychological understanding of visual cognition and the burgeoning field of biologically-inspired artificial intelligence. Topics include the neurophysiological investigation of visual cortex, visual illusions, visual disorders, deep convolutional neural networks, machine learning, and generative adversarial networks among others. It is an ideal resource for students and researchers looking to build bridges across different approaches to studying and developing