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Big Data Analysis of Nanoscience Bibliometrics, Patent, and Funding Data (2000-2019) presents an evaluation of nanotechnologies outputs (academic outputs and patents) and their impact from 2000-2019. The evaluation uses Elsevier's Scopus (the largest abstract and citation database of peer-reviewed literature), SciVal (a scientific research analysis platform), Funding Institutional (a funding database), and PatentSight (a patent analysis platform). It covers four key topics regarding nanoscience research, including: 1) An overview of nano-related scholarly output, 2) Nanoscience and its contribution to basic science, 3) Nanoscience and its impact on and collaboration with industry partners, and 4) Key factors that promote the development of nanoscience. - Provides an in-depth, comprehensive and analytical analysis of progress in nanoscience - Highlights the fundamental role of nanoscience in technology and everyday quality of life - Presents an overall explanation of the current status and future development of nanoscience from a macro perspective - Reviews the development of nano research over the past 20 years, revealing the impact of nanoscience on other research fields and clarifying the development of nano research from basic research to industry applications - Summarizes key countries' nano research development strategy based on funding analysis and research focus analysis - Anticipates upcoming frontier research in the nano field
Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era. It is unique in that it presents both hypothesis testing and a data mining approach to holistically dissecting the genetic structure of complex traits and to designing efficient strategies for precision medicine. The general frameworks for association analysis and machine learning, developed in the text, can be applied to genomic, epigenomic and imaging data. FEATURES Bridges the gap between the traditional statistical methods and computational tools for small genetic and epigenetic data analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and variable selection including randomization algorithms, Proximal methods and matrix subset selection Provides real-world examples and case studies Will have an accompanying website with R code The book is designed for graduate students and researchers in genomics, bioinformatics, and data science. It represents the paradigm shift of genetic studies of complex diseases– from shallow to deep genomic analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations to heterogeneous population and pedigree data analysis. Topics covered are: advanced matrix theory, convex optimization algorithms, generalized low rank models, functional data analysis techniques, deep learning principle and machine learning methods for modern association, interaction, pathway and network analysis of rare and common variants, biomarker identification, disease risk and drug response prediction.
This handbook presents the state of the art of quantitative methods and models to understand and assess the science and technology system. Focusing on various aspects of the development and application of indicators derived from data on scholarly publications, patents and electronic communications, the individual chapters, written by leading experts, discuss theoretical and methodological issues, illustrate applications, highlight their policy context and relevance, and point to future research directions. A substantial portion of the book is dedicated to detailed descriptions and analyses of data sources, presenting both traditional and advanced approaches. It addresses the main bibliographic metrics and indexes, such as the journal impact factor and the h-index, as well as altmetric and webometric indicators and science mapping techniques on different levels of aggregation and in the context of their value for the assessment of research performance as well as their impact on research policy and society. It also presents and critically discusses various national research evaluation systems. Complementing the sections reflecting on the science system, the technology section includes multiple chapters that explain different aspects of patent statistics, patent classification and database search methods to retrieve patent-related information. In addition, it examines the relevance of trademarks and standards as additional technological indicators. The Springer Handbook of Science and Technology Indicators is an invaluable resource for practitioners, scientists and policy makers wanting a systematic and thorough analysis of the potential and limitations of the various approaches to assess research and research performance.
Quantitative studies of science and technology represent the research field of utilization of mathematical, statistical, and data-analytical methods and techniques for gathering, handling, interpreting, and predicting a variety of features of the science and technology enterprise, such as performance, development, and dynamics. The field has both strongly developed applied research as well as basic research characteristics.The principal purpose of this handbook is to present this wide range of topics in sufficient depth to give readers a reasonably systematic understanding of the domain of contemporary quantitative studies of science and technology, a domain which incorporates theory, methods and techniques, and applications. In addressing this domain, the handbook aims at different groups of readers: those conducting research in the field of science and technology, including (graduate) students, and those who are to use results of the work presented in this book.
This Element provides an overview of cultural entrepreneurship scholarship and seeks to lay the foundation for a broader and more integrative research agenda at the interface of organization theory and entrepreneurship. Its scholarly agenda includes a range of phenomena from the legitimation of new ventures, to the construction of novel or alternative organizational or collective identities, and, at even more macro levels, to the emergence of new entrepreneurial possibilities and market categories. Michael Lounsbury and Mary Ann Glynn develop novel theoretical arguments and discuss the implications for mainstream entrepreneurship research, focusing on the study of entrepreneurial processes and possibilities.
This book explores vegetable fiber composite as an eco-friendly, biodegradable, and sustainable material that has many potential industrial applications. The use of vegetable fiber composite supports the sustainable development goals (SDGs) to utilize more sustainable and greener composite materials, which are also easy to handle and locally easily available with economical production costs. This book presents various types of vegetable fiber composite and its processing methods and treatments to obtain desirable properties for certain applications. The book caters to researchers and students who are working in the field of bio-composites and green materials.
Consistently practical in its coverage, the book discusses general issues related to forecasting and management; introduces a variety of methods, and shows how to apply these methods to significant issues in managing technological development. With numerous exhibits, case studies and exercises throughout, it requires only basic mathematics and includes a special technology forecasting TOOLKIT for the IBM and compatibles, along with full instructions for installing and running the program.
energy production, environmental management, transportation, communication, computation, and education. As the twenty-first century unfolds, nanotechnology's impact on the health, wealth, and security of the world's people is expected to be at least as significant as the combined influences in this century of antibiotics, the integrated circuit, and human-made polymers. Dr. Neal Lane, Advisor to the President for Science and Technology and former National Science Foundation (NSF) director, stated at a Congressional hearing in April 1998, "If I were asked for an area of science and engineering that will most likely produce the breakthroughs of tomorrow, I would point to nanoscale science and engineering. " Recognizing this potential, the White House Office of Science and Technology Policy (OSTP) and the Office of Management and Budget (OMB) have issued a joint memorandum to Federal agency heads that identifies nanotechnology as a research priority area for Federal investment in fiscal year 2001. This report charts "Nanotechnology Research Directions," as developed by the Interagency W orking Group on Nano Science, Engineering, and Technology (IWGN) of the National Science and Technology Council (NSTC). The report incorporates the views of leading experts from government, academia, and the private sector. It reflects the consensus reached at an IWGN-sponsored workshop held on January 27-29, 1999, and detailed in contributions submitted thereafter by members of the V. S. science and engineering community. (See Appendix A for a list of contributors.
This volume presents a portfolio of cases and applications on technology roadmapping (TRM) for products and services. It provides a brief overview on criteria or metrics used for evaluating the success level of TRM and then offers six case examples from sectors such as transportation, smart technologies and household electronics. A new innovation in this book is a section of detailed technology roadmap samples that technology managers can apply to emerging technologies.