Titlebook: A First Course in Engineering Drawing; K. Rathnam Textbook 2018 Springer Nature Singapore Pte Ltd. 2018 Engineering drawing textbook.Dimen

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書目名稱A First Course in Engineering Drawing讀者反饋學科排名

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Introduction,en enormen Erkenntnisgewinn erlebten, hat sich die – vor allem deutschsprachige – Kriminologie von diesen Wissenschaften in einem Befreiungsakt bewusst abgesondert. In der ersten H?lfte dieses Jahrhunderts bis in die 1950er Jahre war Kriminologie vor allem Kriminalbiologie. Dann fand die konsequente

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Geometrical Construction,experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book provides a guide for readers seeking to understand the evolution patterns for the microstrucur

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Scales,mon ancestor (LUCA) has been normally considered as the ancestor of cellular organisms that originated the three domains of life: Bacteria, Archaea and Eukarya. Recent studies about the nature of LUCA indicate that this first organism should present hundreds of genes and a complex metabolism. Trying

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Curves Used in Engineering Practice,l colleagues have been kind enough to suggest that this book not only has a contribution to make to ecological economics, but also has relevance to economics general. Thus our OUf distinction distinction between between genotypic genotypic and phenotypic evolution may be used to characterise not onl

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Projections of Lines,mell and perfumes have been used since the earliest times of recorded history (Stoddart 1986). Fragrances have been used for at least 5000 years and all traditional scents are found in modern perfumes. The purpose of using perfumes seems to be to enhance a person’s sexual attractiveness, which is ap

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Sections of Solids,earch trends.Presents concepts to promote and facilitate effThis book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural ne