Since the pioneering work of Joseph Schumpeter (1942), it has been assumed that innovations typically play a key role in firms’ competitiveness. This assumption has been applied to firms in both developed and developing countries. However, the innovative capacities and business environments of firms in developing countries are fundamentally different from those in developed countries. It stands to reason that innovation and competitiveness models based on developed countries may not apply to developing countries. In this volume, Vivienne Wang and Elias G. Carayannis apply both theoretical approaches and empirical analysis to explore the dynamics of innovation in developing countries, with a particular emphasis on R&D in manufacturing firms. In so doing, they present an alternative to Michael Porter’s Competitive Advantage Model—a Competitive Position Model that focuses on incremental and adaptive innovations that are more appropriate than radical innovations for developing countries. Their research addresses such questions as: Do innovations advance the competitive positions of manufacturing firms in developing countries? Does the pace of innovation matter, in particular, in socio-economic and socio-political contexts? To what degree can national innovation systems and policies influence development? To what extent do a firm’s innovation commitments correlate with the protection of intellectual property rights? What roles do foreign direct investment and relationships with clusters and networks play? The resulting analysis not only challenges traditional theoretical approaches to innovation, but provides suggestions for improving business practice and policymaking.
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.
In recent decades various versions of Chinese medicine have begun to be widely practised in Western countries, and the academic study of the subject is now well established. However, there are still few scholarly monographs that describe the history of Chinese medicine and there are none at all on the medieval period. This collection represents the kind of international collaboration of research teams, centres and individuals that is required to begin to study the source materials adequately. The first book in English to discuss this fascinating material in the century since the Dunhuang library was discovered, the text provides a unique and fascinating interpretation of Chinese medical history.
The essential subject knowledge text for primary English. Secure subject knowledge and understanding is the foundation of confident, creative and effective teaching. The trainee teacher′s guide to all the subject knowledge required to teach primary English. Includes practical and reflective tasks to help deepen your understanding and self assessment tests to check your knowledge and identify areas where more study is needed. This 10th edition has been updated throughout and is now linked to the ITT Core Content Framework.
Since the pioneering work of Joseph Schumpeter (1942), it has been assumed that innovations typically play a key role in firms’ competitiveness. This assumption has been applied to firms in both developed and developing countries. However, the innovative capacities and business environments of firms in developing countries are fundamentally different from those in developed countries. It stands to reason that innovation and competitiveness models based on developed countries may not apply to developing countries. In this volume, Vivienne Wang and Elias G. Carayannis apply both theoretical approaches and empirical analysis to explore the dynamics of innovation in developing countries, with a particular emphasis on R&D in manufacturing firms. In so doing, they present an alternative to Michael Porter’s Competitive Advantage Model—a Competitive Position Model that focuses on incremental and adaptive innovations that are more appropriate than radical innovations for developing countries. Their research addresses such questions as: Do innovations advance the competitive positions of manufacturing firms in developing countries? Does the pace of innovation matter, in particular, in socio-economic and socio-political contexts? To what degree can national innovation systems and policies influence development? To what extent do a firm’s innovation commitments correlate with the protection of intellectual property rights? What roles do foreign direct investment and relationships with clusters and networks play? The resulting analysis not only challenges traditional theoretical approaches to innovation, but provides suggestions for improving business practice and policymaking.
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