Utvidet returrett til 31. januar 2024

Bøker i Kaist Research-serien

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  • av Ji-Ho Song & Chung-Youb Kim
    1 544,-

    This book demonstrates fatigue crack growth under random loading graphically. This state-of-the-art monograph introduces an expert system for crack growth predictions, particularly based on crack closure. The system is developed after years of research by the authors by using the Math-type software consisting of 5 parts. This system is unique as it is fundamentally different from previous systems as it focuses on fatigue crack growth predictions based on fatigue crack closure. This book can be a useful guide for practicing engineers, researchers, and students in the fields of mechanical, aerospace, or civil engineering.

  • av Ji-Hyun Lee
    1 447,-

    This book consists of some selected papers presented at the 4th cultural DNA workshop. The papers include topics from three different perspectives: insightful analysis, intelligent synthesis and cutting-edge tools to better understand cultural DNA.It is this diverse perspective toward cultural DNA that makes this book special and suggestive. This book can be suggestive especially for the designers trying to find the very essence, the archetype, and the building blocks of our environment for the incorporation of social and cultural factors into their designs.This book consists of some selected papers presented as first drafts at the 4th cultural DNA workshop. The papers include topics from three different perspectives: insightful analysis, intelligent synthesis and cutting-edge tools to better understand cultural DNA.

  • av Jaeson Jang
    1 430 - 1 676,-

    This book discusses the emergence of diverse functional organizations in the visual pathway which could be spontaneously and solely initiated by the random feedforward wiring of neural circuits. It demonstrates that the structure of ON and OFF retinal ganglion cell (RGC) mosaics is projected onto V1 by retino-cortical feedforward mapping to induce higher cognitive functions. This book will be beneficial for both theoretical and experimental neuroscientists, as well as for researchers using brain-inspired neural network models.

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