Hiroshi Ishikawa

The most comprehensive text and definitive guide for nearly 30 years about optical coherence tomography (OCT) imaging in ophthalmology, Optical Coherence Tomography of Ocular Diseases, Fourth Edition covers a range of subjects, from principles and operation techniques to clinical interpretation and the latest innovations in OCT. Written by the pioneers of OCT technologies and the world-renowned OCT researchers Drs. Joel S. Schuman, James G. Fujimoto, Jay S. Duker, Hiroshi Ishikawa, and Gadi Wollstein, Optical Coherence Tomography of Ocular Diseases, Fourth Edition is an essential text for imaging technology. OCT now occupies a dominant role as a diagnostic tool for retinal conditions and glaucoma. At the same time, the technology continues to show potential for emerging clinical and research applications across all the ophthalmological subspecialties. To reflect these rapid advances, this new edition of Optical Coherence Tomography of Ocular Diseases features a complete and thorough revision of the existing text as well as the addition of cutting-edge content to bring this classic resource completely up to date. New content in the Fourth Edition includes:• OCT angiography• Swept-source OCT• OCT in multimodal imaging• Clinical utility of OCT in glaucoma prediction and progression detection • OCT for neuro-ophthalmology Optical Coherence Tomography of Ocular Diseases, Fourth Edition is the one and only book needed by practitioners who use OCT for clinical eye care.

This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications.

This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest.

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data. This book is different from other similar books in that presents the overall picture of social big data from fundamental concepts to applications while standing on academic bases.

This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains analytical techniques such as modeling, data mining, and multivariate analysis for social big data. This book is different from other similar books in that presents the overall picture of social big data from fundamental concepts to applications while standing on academic bases.

Computer Science Workbench is a monograph series which will provide you with an in­ depth working knowledge of current developments in computer technology. Every volume in this series will deal with a topic of importance in computer science and elaborate on how you yourself can build systems related to the main theme. You will be able to develop a variety of systems, including computer software tools, computer graphics, computer animation, database management systems, and computer-aided design and manufacturing systems. Computer Science Workbench represents an important new contribution in the field of practical computer technology. Tosiyasu L. Kunii Preface The goal of this book is to give concrete answers to questions such as what object­ oriented databases are, why they are needed, how they are implemented, and how they are applied, by describing a research prototype object-oriented database system called Jasmine. That is, this book is aimed at creating a consistent view to object-oriented databases. The contents of this book are directly based on the results of the Jasmine project conducted at Fujitsu Laboratories, Ltd. The book is a polished version of my doctoral dissertation, which includes research papers which I have authored and published.