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Titlebook: Industrial Competitiveness and Design Evolution; Takahiro Fujimoto,Fumihiko Ikuine Book 2018 Springer Japan KK, part of Springer Nature 20

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書(shū)目名稱Industrial Competitiveness and Design Evolution
編輯Takahiro Fujimoto,Fumihiko Ikuine
視頻videohttp://file.papertrans.cn/464/463968/463968.mp4
概述Incorporates the concept of design and architecture into the comparative advantage theory of international trade and industrial competitiveness.Treats the concepts of designed artifacts, design inform
叢書(shū)名稱Evolutionary Economics and Social Complexity Science
圖書(shū)封面Titlebook: Industrial Competitiveness and Design Evolution;  Takahiro Fujimoto,Fumihiko Ikuine Book 2018 Springer Japan KK, part of Springer Nature 20
描述This book integrates the concept of design into the existing framework of industrial performance, international trade and comparative advantage in trade and industrial phenomena, which increasingly have been affected by design characteristics of tradable goods. Design, capability and their evolution are introduced into current theories of trade to explain the reality of international trade in the early twenty-first century and the possibility of design-based comparative advantage is explored. Toward that end, the concepts of design, architecture, organizational capability and productivity are introduced, as are their interactions and evolution. The author starts from the fact that firms’ selection of design locations precedes that of production locations and that a new product’s initial production location is usually the same as its design location. In other words, design matters in explaining today’s trade phenomena. Thus, this book analyzes product design and its evolution in the context of the comparative advantage theory. The author argues that the concept of Ricardo’s comparative advantage must be reinterpreted in a more dynamic way than in the past, with changing labor input
出版日期Book 2018
關(guān)鍵詞Capability-building Competition; Design evolution; Design-based comparative advantage; Dynamic interpre
版次1
doihttps://doi.org/10.1007/978-4-431-55145-4
isbn_softcover978-4-431-56859-9
isbn_ebook978-4-431-55145-4Series ISSN 2198-4204 Series E-ISSN 2198-4212
issn_series 2198-4204
copyrightSpringer Japan KK, part of Springer Nature 2018
The information of publication is updating

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for them to be deployed in security-sensitive applications, such as autonomous driving. Image-dependent perturbations can fool a network for one specific image, while universal adversarial perturbations are capable of fooling a network for samples from all classes without selection. We introduce a
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Takahiro Fujimoto work, we explore learning from abundant, randomly generated synthetic data, together with unlabeled or partially labeled target domain data, instead. Randomly generated synthetic data has the advantage of controlled variability in the lane geometry and lighting, but it is limited in terms of photo-
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Hirofumi Tatsumotoailed spectral distribution helping for numerous applications. However, existing HS imaging sensor can only obtain images with low spatial resolution. Thus fusing a low resolution hyperspectral (LR-HS) image with a high resolution (HR) RGB (or multispectral) image into a HR-HS image has received muc
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