Böcker utgivna av Institute of Physics Publishing

A fear of physics can be problematic for both students and citizens when making science-based decisions. This book discusses reasons behind this fear and the remedies to counter it in terms of attitudes, course planning and execution, laboratory work, information technology, and more.

Semidefinite programming is a class of optimisation problem with application in physics, engineering and mathematics It is particularly suited to problems in quantum physics and quantum information science. This book is a self-contained introduction to semidefinite programming and its widespread application in quantum information science.

This book focuses on major trends and challenges in the area of diagnosing breast and bladder cancer using artificial intelligence tools. It presents work aimed to identify new techniques and their use in biomedical analysis.

This book has been developed from the author's undergraduate module on the frontiers of physics - the intention of which is to ground students in the latest research and understanding. Introducing a broad range of core physics, including quantum mechanics, van der Waals forces and atomic potentials, tying it to up-to-date research and making heavy use of multimedia as well as Python simulations.

This book addresses the challenges of implementation of deep learning techniques, computation time, and the complexity of reasoning and modelling different type of data.

This book provides an extensive inquiry to determine the degree of understanding of the processes leading to lithium creation, destruction and preservation in the Universe.

Artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. The book provides applications of artificial intelligence (AI) in radiation therapy according to the clinical radiotherapy workflow. An introductory section explains the necessity of AI regarding accuracy and efficiency in clinical settings followed by a basic learning method and introduction of potential applications in radiotherapy. Some chapters also include typical source codes which the reader may use in their original neural network. This book would be an excellent text for more experienced practitioners and researchers and members of medical physics communities, such as AAPM, ASTRO, and ESTRO. Students and graduate students who are focusing on medical physics would also benefit from this text.Key Features: Systematic chapters are designed over the radiotherapy workflow.Describes in detail how AI contributes to a perspective in the future radiotherapy.Typical source codes are included to implement a neural network.The book supports the reader as a developer of AI.

This book provides an overview for all current applications of magnetic resonance imaging (MRI) as a diagnostic and monitoring method for the lifelong debilitating disease multiple sclerosis (MS).

Astronomers are in a unique position to help people understand the danger of climate change and what we can do about it. This book is intended to help astronomers to be better educators and communicators about the causes and consequences of climate change, as well as better advocates for solutions.

This monograph introduces several recently developed and applied analytical-based theoretical approaches and practical techniques for uncertainty evaluation and probabilistic design optimisation for the robustness and reliability of technical systems of various complexity and applications. This is enhanced by the inclusion of relevant real-world case studies.The book will be useful for researchers, engineers, and designers of complex, multi-parameter technical systems that must guarantee a specified level of functional reliability. It presents several real-world case studies helping to comprehend in detail the developed techniques and their benefits. In addition, it offers free access to the online toolboxes developed by the authors to support the calculation of uncertainties and guides the readers on the practical use of such tools.Key Features: Cohesively combines three important research, development, and real-world engineering practice areas (i) uncertainty and its evaluation, propagation, modelling, etc., and, (ii) complex technical systems design optimisation involving advanced probabilistic theories, techniques, and tools, and (iii) development of such theoriesThis is arguably the first monograph systematically and comprehensively presenting the new area of moment-based uncertainty propagation and its practical applications.The book offers a significant volume of additional explanations, guidelines and tools enabling the readers to utilise the presented material in their research, design, and engineering practice.It provides free access to developed application-specific online tools and benchmark test distributions for expanded uncertainty.The practical application section of the monograph presents several real-world case study solutions.

Optical Cryptosystems introduces the subject of optical cryptography and provides up-to-date coverage of optical security schemes. Optical principles, approaches, and algorithms are discussed as well as applications, including image/data encryption-decryption, watermarking, image/data hiding, and authentication verification.

The biological evaluation of materials involves the characterisation of materials using biological methods. At present, new materials are typically characterised using physicochemical methods. Such approaches don't account for the interactions that materials have with living organisms in their environment. This reference text covers the emerging field of materiomics: the holistic study of material function and behaviour using both physicochemical and biological methods.The book presents a comprehensive strategy for the identification, characterisation and grouping of nanomaterials[BWI1] [BWI2] using biological methods. The focus is on methods from molecular biology, and complementary methods derived from quantum physics. The work discusses the interaction of materials with their environment, the field of materiomics, the biological recognition of materials, and the quantum basis of materials recognition by cells. The discussion of quantum mechanisms enables a deeper understanding of the interaction of biological objects with materials.The key audience for this book includes researchers involved in the characterisation of materials, particularly biomaterials researchers and those interested in the interaction of materials science and the life sciences. The book will also be a valuable reference for postgraduate students and practitioners working in the fields of materials characterisation and biomaterials.Key Features: Presents a comprehensive strategy for the identification, characterisation and grouping of nanomaterials using molecular biology, and complementary methods derived from quantum physicsProvides coverage of the emerging field of materiomicsFollows an interdisciplinary approach and does not require advanced understanding of mathematicsHighly useful to all researchers involved in characterising new materials, particularly biomaterials researchers and those interested in the interaction of materials science and the life sciences

This edition presents microscopic and spectroscopic techniques and their applications in Archaeological and cultural heritage research.

This book explores the neglected notion of creative thinking in physics in universities and describes how to embed opportunities for students to develop their creative competence in class.

In this book, the interactions between printing method, ink and substrate surface are discussed in order to achieve optimal results and durability.

This research and reference text explores the finer details of Deep Learning models. It provides a brief outline on popular models including convolution neural networks (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.This reference text is highly relevant for medical professionals and researchers in the area of AI in medical imaging. Key Features: Discusses various diseases related to lung, heart, peripheral arterial imaging, as well as gene expression characterization and classificationExplores imaging applications, their complexities and the Deep Learning models employed to resolve them in detailProvides state-of-the-art contributions while addressing doubts in multimodal researchDetails the future of deep learning and big data in medical imaging

This book is a multidisciplinary introduction to quantum field theory. The topics covered in the second volume include advanced material, such as phase transitions, the renormalization group, fermions, gauge theories, the 1/N expansions, anomalies, soliton and instantons, and field theory at nonzero temperature and density.