The Science and Engineering of Materials Enhanced (SI) (7版)

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The Science and Engineering of Materials Enhanced 7/E (SI Edition) 作(編/譯)者 : ASKELAND & WRIGHT 出版年份 : 2022 ISBN : 9780357447888 書號 : MX0538 幾色 : 4 規格 : 平裝 發行公司 : CENGAGE 英文書名中譯 : 材料科學 版次 : 7E 頁數 : 896 內容簡介 Table of Contents: 1. Introduction to Materials Science and Engineering. 2. Atomic Structure. 3. Atomic and Ionic Arrangements. 4. Imperfections in the Atomic and Ionic Arrangements. 5. Atom and Ion Movements in Materials 6. Mechanical Properties: Part One. 7. Mechanical Properties: Part Two. 8. Strain Hardening and Annealing. 9. Principles of Solidification. 10. Solid Solutions and Phase Equilibrium. 11. Dispersion Strengthening and Eutectic Phase Diagrams. 12. Dispersion Strengthening by Phase Transformations and Heat Treatment. 13. Heat Treatment of Steels and Cast Irons. 14. Nonferrous Alloys. 15. Ceramics. 16. Polymers. 17. Composites: Teamwork and Synergy in Materials. 18. Construction Materials. 19. Electronic Materials. 20. Magnetic Materials. 21. Photonic Materials 22. Thermal Properties of Materials. 23. Corrosion and Wear. Appendix A: Selected Physical Properties of Materials. Appendix B: The Atomic and Ionic Radii of Selected Elements.

Engineering of Mind An Introduction to The Science of Intelligent Systems

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Presenting a reference model architecture for the design of intelligent systems Engineering of Mind presents the foundations for a computational theory of intelligence. It discusses the main streams of investigation that will eventually converge in a scientific theory of mind and proposes an avenue of research that might best lead to the development of truly intelligent systems. This book presents a model of the brain as a hierarchy of massive parallel computational modules and data structures interconnected by information pathways. Using this as the basic model on which intelligent systems should be based, the authors propose a reference model architecture that accommodates concepts from artificial intelligence, control theory, image understanding, signal processing, and decision theory. Algorithms, procedures, and data embedded within this architecture would enable the analysis of situations, the formulation of plans, the choice of behaviors, and the computation of uncertainties. The computational power to implement the model can be achieved in practical systems in the foreseeable future through hierarchical and parallel distribution of computational tasks. The authors' reference model architecture is expressed in terms of the Real-time Control System (RCS) that has been developed primarily at the National Institute of Standards and Technology. Suitable for engineers, computer scientists, researchers, and students, Engineering of Mind blends current theory and practice to achieve a coherent model for the design of intelligent systems.