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13.734 Sailing Yacht Design (MIT) 13.734 Sailing Yacht Design (MIT)

Description

This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (b This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (bSubjects

sailing design | sailing design | yacht design | yacht design | hydrostatics | hydrostatics | transverse stability | transverse stability | design spiral | design spiral | CAD | CAD | hulls | hulls | appendages | appendages | decks | decks | 2.996 | 2.996License

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See all metadata6.856J Randomized Algorithms (MIT) 6.856J Randomized Algorithms (MIT)

Description

This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimum cuts); geometric algorithms (convex hulls, linear programming in fixed or arbitrary dimension); approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms. This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimum cuts); geometric algorithms (convex hulls, linear programming in fixed or arbitrary dimension); approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.Subjects

Randomized Algorithms | Randomized Algorithms | algorithms | algorithms | efficient in time and space | efficient in time and space | randomization | randomization | computational problems | computational problems | data structures | data structures | graph algorithms | graph algorithms | optimization | optimization | geometry | geometry | Markov chains | Markov chains | sampling | sampling | estimation | estimation | geometric algorithms | geometric algorithms | parallel and distributed algorithms | parallel and distributed algorithms | parallel and ditributed algorithm | parallel and ditributed algorithm | parallel and distributed algorithm | parallel and distributed algorithm | random sampling | random sampling | random selection of witnesses | random selection of witnesses | symmetry breaking | symmetry breaking | randomized computational models | randomized computational models | hash tables | hash tables | skip lists | skip lists | minimum spanning trees | minimum spanning trees | shortest paths | shortest paths | minimum cuts | minimum cuts | convex hulls | convex hulls | linear programming | linear programming | fixed dimension | fixed dimension | arbitrary dimension | arbitrary dimension | approximate counting | approximate counting | parallel algorithms | parallel algorithms | online algorithms | online algorithms | derandomization techniques | derandomization techniques | probabilistic analysis | probabilistic analysis | computational number theory | computational number theory | simplicity | simplicity | speed | speed | design | design | basic probability theory | basic probability theory | application | application | randomized complexity classes | randomized complexity classes | game-theoretic techniques | game-theoretic techniques | Chebyshev | Chebyshev | moment inequalities | moment inequalities | limited independence | limited independence | coupon collection | coupon collection | occupancy problems | occupancy problems | tail inequalities | tail inequalities | Chernoff bound | Chernoff bound | conditional expectation | conditional expectation | probabilistic method | probabilistic method | random walks | random walks | algebraic techniques | algebraic techniques | probability amplification | probability amplification | sorting | sorting | searching | searching | combinatorial optimization | combinatorial optimization | approximation | approximation | counting problems | counting problems | distributed algorithms | distributed algorithms | 6.856 | 6.856 | 18.416 | 18.416License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.253 Convex Analysis and Optimization (MIT) 6.253 Convex Analysis and Optimization (MIT)

Description

6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject. 6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject.Subjects

affine hulls | affine hulls | recession cones | recession cones | global minima | global minima | local minima | local minima | optimal solutions | optimal solutions | hyper planes | hyper planes | minimax theory | minimax theory | polyhedral convexity | polyhedral convexity | polyhedral cones | polyhedral cones | polyhedral sets | polyhedral sets | convex analysis | convex analysis | optimization | optimization | convexity | convexity | Lagrange multipliers | Lagrange multipliers | duality | duality | continuous optimization | continuous optimization | saddle point theory | saddle point theory | linear algebra | linear algebra | real analysis | real analysis | convex sets | convex sets | convex functions | convex functions | extreme points | extreme points | subgradients | subgradients | constrained optimization | constrained optimization | directional derivatives | directional derivatives | subdifferentials | subdifferentials | conical approximations | conical approximations | Fritz John optimality | Fritz John optimality | Exact penalty functions | Exact penalty functions | conjugate duality | conjugate duality | conjugate functions | conjugate functions | Fenchel duality | Fenchel duality | exact penalty functions | exact penalty functions | dual computational methods | dual computational methodsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata2.996 Sailing Yacht Design (13.734) (MIT) 2.996 Sailing Yacht Design (13.734) (MIT)

Description

This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (but not reprod This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (but not reprodSubjects

sailing design | sailing design | yacht design | yacht design | hydrostatics | hydrostatics | transverse stability | transverse stability | design spiral | design spiral | CAD | CAD | hulls | hulls | appendages | appendages | decks | decksLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata13.734 Sailing Yacht Design (MIT)

Description

This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (bSubjects

sailing design | yacht design | hydrostatics | transverse stability | design spiral | CAD | hulls | appendages | decks | 2.996License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata2.996 Sailing Yacht Design (13.734) (MIT)

Description

This subject teaches students, having an initial interest in sailing design, how to design good yachts. Topics covered include hydrostatics, transverse stability, and the incorporation of the design spiral into one's working methods. Computer aided design (CAD) is used to design the shapes of hulls, appendages and decks, and is an important part of this course. The capstone project in this course is the Final Design Project in which each student designs a sailing yacht, complete in all major respects. The central material for this subject is the content of the book Principals of Yacht Design by Larssson and Eliasson (see further description in the syllabus). All the class lectures are based on the material in this book. The figures in the book which are shown in class (but not reprodSubjects

sailing design | yacht design | hydrostatics | transverse stability | design spiral | CAD | hulls | appendages | decksLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.253 Convex Analysis and Optimization (MIT)

Description

6.253 develops the core analytical issues of continuous optimization, duality, and saddle point theory, using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions is discussed in detail, and is the basis for an intuitive, highly visual, geometrical approach to the subject.Subjects

affine hulls | recession cones | global minima | local minima | optimal solutions | hyper planes | minimax theory | polyhedral convexity | polyhedral cones | polyhedral sets | convex analysis | optimization | convexity | Lagrange multipliers | duality | continuous optimization | saddle point theory | linear algebra | real analysis | convex sets | convex functions | extreme points | subgradients | constrained optimization | directional derivatives | subdifferentials | conical approximations | Fritz John optimality | Exact penalty functions | conjugate duality | conjugate functions | Fenchel duality | exact penalty functions | dual computational methodsLicense

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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See all metadata6.856J Randomized Algorithms (MIT)

Description

This course examines how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Topics covered include: randomized computation; data structures (hash tables, skip lists); graph algorithms (minimum spanning trees, shortest paths, minimum cuts); geometric algorithms (convex hulls, linear programming in fixed or arbitrary dimension); approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.Subjects

Randomized Algorithms | algorithms | efficient in time and space | randomization | computational problems | data structures | graph algorithms | optimization | geometry | Markov chains | sampling | estimation | geometric algorithms | parallel and distributed algorithms | parallel and ditributed algorithm | parallel and distributed algorithm | random sampling | random selection of witnesses | symmetry breaking | randomized computational models | hash tables | skip lists | minimum spanning trees | shortest paths | minimum cuts | convex hulls | linear programming | fixed dimension | arbitrary dimension | approximate counting | parallel algorithms | online algorithms | derandomization techniques | probabilistic analysis | computational number theory | simplicity | speed | design | basic probability theory | application | randomized complexity classes | game-theoretic techniques | Chebyshev | moment inequalities | limited independence | coupon collection | occupancy problems | tail inequalities | Chernoff bound | conditional expectation | probabilistic method | random walks | algebraic techniques | probability amplification | sorting | searching | combinatorial optimization | approximation | counting problems | distributed algorithms | 6.856 | 18.416License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htmSite sourced from

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