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Writing a Graduate Thesis or Dissertation by
Writing A Graduate Thesis or Dissertation is a comprehensive guide to the stages of working through the rigors of writing and defending a graduate degree from the initial stages of choosing a thesis topic and supervisor, right through to the defense of the work. Each chapter can be consulted separately, or the whole book read to give a wide-ranging understanding of the issues most pertinent to writing and defending a thesis. This book provides something for everyone involved in that process. Both graduate students and their supervisors will find this a refreshing and thorough collection that addresses the topic across a wide range of disciplines.
Big Data Analytics for Large-Scale Multimedia Search by
A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.
Inventing Temperature by
What is temperature, and how can we measure it correctly? These may seem like simple questions, but the most renowned scientists struggled with them throughout the 18th and 19th centuries. In Inventing Temperature, Chang examines how scientists first created thermometers; how they measuredtemperature beyond the reach of standard thermometers; and how they managed to assess the reliability and accuracy of these instruments without a circular reliance on the instruments themselves.In a discussion that brings together the history of science with the philosophy of science, Chang presents the simple eet challenging epistemic and technical questions about these instruments, and the complex web of abstract philosophical issues surrounding them. Chang's book shows that many itemsof knowledge that we take for granted now are in fact spectacular achievements, obtained only after a great deal of innovative thinking, painstaking experiments, bold conjectures, and controversy. Lurking behind these achievements are some very important philosophical questions about how and whenpeople accept the authority of science.
A Practical Guide to Ecological Modelling by
Mathematical modelling is an essential tool in present-day ecological research. Yet for many ecologists it is still problematic to apply modelling in their research. In our experience, the major problem is at the conceptual level: proper understanding of what a model is, how ecological relations can be translated consistently into mathematical equations, how models are solved, steady states calculated and interpreted. Many textbooks jump over these conceptual hurdles to dive into detailed formulations or the mathematics of solution. This book attempts to fill that gap. It introduces essential concepts for mathematical modelling, explains the mathematics behind the methods, and helps readers to implement models and obtain hands-on experience. Throughout the book, emphasis is laid on how to translate ecological questions into interpretable models in a practical way. The book aims to be an introductory textbook at the undergraduate-graduate level, but will also be useful to seduce experienced ecologists into the world of modelling. The range of ecological models treated is wide, from Lotka-Volterra type of principle-seeking models to environmental or ecosystem models, and including matrix models, lattice models and sequential decision models. All chapters contain a concise introduction into the theory, worked-out examples and exercises. All examples are implemented in the open-source package R, thus taking away problems of software availability for use of the book. All code used in the book is available on a dedicated website.
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