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6.856J 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

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See all metadata12.864 Inference from Data and Models (MIT) 12.864 Inference from Data and Models (MIT)

Description

The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themeslinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc. The course is directed at making scientifically sensible deductions from the combination of observations with dynamics and kinematics represented, generically, as "models". There are two overlapping central themeslinear "inverse" methods and data "assimilation" including regression, singular value decomposition, objective mapping, non-stationary models and data, Kalman filters, adjoint methods ("assimilation") etc.standard time series analysis, including basic statistics, Fourier methods, spectra, coherence, filtering, etc.Subjects

observation | observation | kinematical models | kinematical models | dynamical models | dynamical models | basic statistics | basic statistics | linear algebra | linear algebra | inverse methods | inverse methods | singular value decompositions | singular value decompositions | control theory | control theory | sequential estimation | sequential estimation | Kalman filters | Kalman filters | smoothing algorithms | smoothing algorithms | adjoint/Pontryagin principle methods | adjoint/Pontryagin principle methods | model testing | model testing | stationary processes | stationary processes | Fourier methods | Fourier methods | z-transforms | z-transforms | sampling theorems | sampling theorems | spectra | spectra | multi-taper methods | multi-taper methods | coherences | coherences | filtering | filtering | quantitative combinations | quantitative combinations | realistic observations | realistic observations | data assimilations | data assimilations | deduction | deduction | regression | regression | objective mapping | objective mapping | time series analysis | time series analysis | inference | inferenceLicense

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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The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Subjects

Unified | Unified Engineering | aerospace | CDIO | C-D-I-O | conceive | design | implement | operate | team | team-based | discipline | materials | structures | materials and structures | computers | programming | computers and programming | fluids | fluid mechanics | thermodynamics | propulsion | signals | systems | signals and systems | systems problems | fundamentals | technical communication | graphical communication | communication | reading | research | experimentation | personal response system | prs | active learning | First law | first law of thermodynamics | thermo-mechanical | energy | energy conversion | aerospace power systems | propulsion systems | aerospace propulsion systems | heat | work | thermal efficiency | forms of energy | energy exchange | processes | heat engines | engines | steady-flow energy equation | energy flow | flows | path-dependence | path-independence | reversibility | irreversibility | state | thermodynamic state | performance | ideal cycle | simple heat engine | cycles | thermal pressures | temperatures | linear static networks | loop method | node method | linear dynamic networks | classical methods | state methods | state concepts | dynamic systems | resistive circuits | sources | voltages | currents | Thevinin | Norton | initial value problems | RLC networks | characteristic values | characteristic vectors | transfer function | ada | ada programming | programming language | software systems | programming style | computer architecture | program language evolution | classification | numerical computation | number representation systems | assembly | SimpleSIM | RISC | CISC | operating systems | single user | multitasking | multiprocessing | domain-specific classification | recursive | execution time | fluid dynamics | physical properties of a fluid | fluid flow | mach | reynolds | conservation | conservation principles | conservation of mass | conservation of momentum | conservation of energy | continuity | inviscid | steady flow | simple bodies | airfoils | wings | channels | aerodynamics | forces | moments | equilibrium | freebody diagram | free-body | free body | planar force systems | equipollent systems | equipollence | support reactions | reactions | static determinance | determinate systems | truss analysis | trusses | method of joints | method of sections | statically indeterminate | three great principles | 3 great principles | indicial notation | rotation of coordinates | coordinate rotation | stress | extensional stress | shear stress | notation | plane stress | stress equilbrium | stress transformation | mohr | mohr's circle | principal stress | principal stresses | extreme shear stress | strain | extensional strain | shear strain | strain-displacement | compatibility | strain transformation | transformation of strain | mohr's circle for strain | principal strain | extreme shear strain | uniaxial stress-strain | material properties | classes of materials | bulk material properties | origin of elastic properties | structures of materials | atomic bonding | packing of atoms | atomic packing | crystals | crystal structures | polymers | estimate of moduli | moduli | composites | composite materials | modulus limited design | material selection | materials selection | measurement of elastic properties | stress-strain | stress-strain relations | anisotropy | orthotropy | measurements | engineering notation | Hooke | Hooke's law | general hooke's law | equations of elasticity | boundary conditions | multi-disciplinary | models | engineering systems | experiments | investigations | experimental error | design evaluation | evaluation | trade studies | effects of engineering | social context | engineering drawingsLicense

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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This course begins with a comparative review of conventional and advanced multiple attribute decision making (MADM) models in engineering practice. Next, a new application of particular MADM models in reliable material selection of sensitive structural components as well as a multi-criteria Taguchi optimization method is discussed. Other specific topics include dealing with uncertainties in material properties, incommensurability in decision-makers opinions for the same design, objective ways of weighting performance indices, rank stability analysis, compensations and non-compensations. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course begins with a comparative review of conventional and advanced multiple attribute decision making (MADM) models in engineering practice. Next, a new application of particular MADM models in reliable material selection of sensitive structural components as well as a multi-criteria Taguchi optimization method is discussed. Other specific topics include dealing with uncertainties in material properties, incommensurability in decision-makers opinions for the same design, objective ways of weighting performance indices, rank stability analysis, compensations and non-compensations. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.Subjects

materials selection | materials selection | tradeoff | tradeoff | optimization | optimization | Taguchi | Taguchi | multiple attribute | multiple attribute | decision making | decision making | multiple attribute decision making | multiple attribute decision making | performance index | performance index | rank stability analysis | rank stability analysis | decision matrix | decision matrix | multi-criteria decision making | multi-criteria decision making | multiobjective optimization | multiobjective optimization | Pareto | Pareto | TOPSIS | TOPSIS | ELECTRE | ELECTRELicense

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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The basic objective of Unified Engineering is to give a solid understanding of the fundamental disciplines of aerospace engineering, as well as their interrelationships and applications. These disciplines are Materials and Structures (M); Computers and Programming (C); Fluid Mechanics (F); Thermodynamics (T); Propulsion (P); and Signals and Systems (S). In choosing to teach these subjects in a unified manner, the instructors seek to explain the common intellectual threads in these disciplines, as well as their combined application to solve engineering Systems Problems (SP). Throughout the year, the instructors emphasize the connections among the disciplines.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls filesSubjects

Unified | Unified Engineering | aerospace | CDIO | C-D-I-O | conceive | design | implement | operate | team | team-based | discipline | materials | structures | materials and structures | computers | programming | computers and programming | fluids | fluid mechanics | thermodynamics | propulsion | signals | systems | signals and systems | systems problems | fundamentals | technical communication | graphical communication | communication | reading | research | experimentation | personal response system | prs | active learning | First law | first law of thermodynamics | thermo-mechanical | energy | energy conversion | aerospace power systems | propulsion systems | aerospace propulsion systems | heat | work | thermal efficiency | forms of energy | energy exchange | processes | heat engines | engines | steady-flow energy equation | energy flow | flows | path-dependence | path-independence | reversibility | irreversibility | state | thermodynamic state | performance | ideal cycle | simple heat engine | cycles | thermal pressures | temperatures | linear static networks | loop method | node method | linear dynamic networks | classical methods | state methods | state concepts | dynamic systems | resistive circuits | sources | voltages | currents | Thevinin | Norton | initial value problems | RLC networks | characteristic values | characteristic vectors | transfer function | ada | ada programming | programming language | software systems | programming style | computer architecture | program language evolution | classification | numerical computation | number representation systems | assembly | SimpleSIM | RISC | CISC | operating systems | single user | multitasking | multiprocessing | domain-specific classification | recursive | execution time | fluid dynamics | physical properties of a fluid | fluid flow | mach | reynolds | conservation | conservation principles | conservation of mass | conservation of momentum | conservation of energy | continuity | inviscid | steady flow | simple bodies | airfoils | wings | channels | aerodynamics | forces | moments | equilibrium | freebody diagram | free-body | free body | planar force systems | equipollent systems | equipollence | support reactions | reactions | static determinance | determinate systems | truss analysis | trusses | method of joints | method of sections | statically indeterminate | three great principles | 3 great principles | indicial notation | rotation of coordinates | coordinate rotation | stress | extensional stress | shear stress | notation | plane stress | stress equilbrium | stress transformation | mohr | mohr's circle | principal stress | principal stresses | extreme shear stress | strain | extensional strain | shear strain | strain-displacement | compatibility | strain transformation | transformation of strain | mohr's circle for strain | principal strain | extreme shear strain | uniaxial stress-strain | material properties | classes of materials | bulk material properties | origin of elastic properties | structures of materials | atomic bonding | packing of atoms | atomic packing | crystals | crystal structures | polymers | estimate of moduli | moduli | composites | composite materials | modulus limited design | material selection | materials selection | measurement of elastic properties | stress-strain | stress-strain relations | anisotropy | orthotropy | measurements | engineering notation | Hooke | Hooke's law | general hooke's law | equations of elasticity | boundary conditions | multi-disciplinary | models | engineering systems | experiments | investigations | experimental error | design evaluation | evaluation | trade studies | effects of engineering | social context | engineering drawings | 16.01 | 16.02 | 16.03 | 16.04License

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See all metadata6.441 Transmission of Information (MIT) 6.441 Transmission of Information (MIT)

Description

6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include: mathematical definition and properties of information; source coding theorem, lossless compression of data, optimal lossless coding; noisy communication channels, channel coding theorem, the source-channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels. 6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include: mathematical definition and properties of information; source coding theorem, lossless compression of data, optimal lossless coding; noisy communication channels, channel coding theorem, the source-channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels.Subjects

transmission of information | transmission of information | quantitative theory of information | quantitative theory of information | efficient communication systems | efficient communication systems | mathematical definition of information | mathematical definition of information | properties of information | properties of information | source coding theorem | source coding theorem | lossless compression of data | lossless compression of data | optimal lossless coding | optimal lossless coding | noisy communication channels | noisy communication channels | channel coding theorem | channel coding theorem | the source-channel separation theorem | the source-channel separation theorem | multiple access channels | multiple access channels | broadcast channels | broadcast channels | gaussian noise | gaussian noise | time-varying channels | time-varying channels | lossless data compression | lossless data compression | telecommunications | telecommunications | data transmission | data transmissionLicense

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 metadata2.23 Hydrofoils and Propellers (13.04) (MIT) 2.23 Hydrofoils and Propellers (13.04) (MIT)

Description

This course deals with theory and design of hydrofoil sections; lifting and thickness problems for sub-cavitating sections, unsteady flow problems. It focuses on computer-aided design of low drag, cavitation free sections. The course also covers lifting line and lifting surface theory with applications to hydrofoil craft, rudder, and control surface design. Topics include propeller lifting line and lifting surface theory; computer-aided design of wake adapted propellers, unsteady propeller thrust and torque. The course is also an introduction to subjects like flow about axially symmetric bodies and low-aspect ratio lifting surfaces, and hydrodynamic performance and design of waterjets. We will also do an analysis of performance and design of wind turbine rotors in steady and stochastic win This course deals with theory and design of hydrofoil sections; lifting and thickness problems for sub-cavitating sections, unsteady flow problems. It focuses on computer-aided design of low drag, cavitation free sections. The course also covers lifting line and lifting surface theory with applications to hydrofoil craft, rudder, and control surface design. Topics include propeller lifting line and lifting surface theory; computer-aided design of wake adapted propellers, unsteady propeller thrust and torque. The course is also an introduction to subjects like flow about axially symmetric bodies and low-aspect ratio lifting surfaces, and hydrodynamic performance and design of waterjets. We will also do an analysis of performance and design of wind turbine rotors in steady and stochastic winSubjects

Theory and design of hydrofoil sections | Theory and design of hydrofoil sections | lifting and thickness problems | lifting and thickness problems | sub-cavitating sections | sub-cavitating sections | unsteady flow problems | unsteady flow problems | computer-aided design | computer-aided design | low drag | low drag | cavitation free sections | cavitation free sections | Lifting line and lifting surface theory | Lifting line and lifting surface theory | hydrofoil craft | hydrofoil craft | rudder | rudder | and control surface design | and control surface design | propeller lifting line | propeller lifting line | lifting surface theory | lifting surface theory | wake adapted propellers | wake adapted propellers | unsteady propeller thrust and torque | unsteady propeller thrust and torque | axially symmetric bodies | axially symmetric bodies | low-aspect ratio lifting surfaces | low-aspect ratio lifting surfaces | Hydrodynamic performance | Hydrodynamic performance | design of waterjets | design of waterjets | wind turbine rotors in steady and stochastic wind | wind turbine rotors in steady and stochastic wind | hydrofoil craft | rudder | and control surface design | hydrofoil craft | rudder | and control surface design | 9. low drag | cavitation free sections | 9. low drag | cavitation free sections | 5. hydrofoil craft | rudder | and control surface design | 5. hydrofoil craft | rudder | and control surface design | low drag | cavitation free sections | low drag | cavitation free sectionsLicense

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See all metadata8.08 Statistical Physics II (MIT) 8.08 Statistical Physics II (MIT)

Description

This course covers probability distributions for classical and quantum systems. Topics include: Microcanonical, canonical, and grand canonical partition-functions and associated thermodynamic potentials. Also discussed are conditions of thermodynamic equilibrium for homogenous and heterogenous systems. The course follows 8.044, Statistical Physics I, and is second in this series of undergraduate Statistical Physics courses. This course covers probability distributions for classical and quantum systems. Topics include: Microcanonical, canonical, and grand canonical partition-functions and associated thermodynamic potentials. Also discussed are conditions of thermodynamic equilibrium for homogenous and heterogenous systems. The course follows 8.044, Statistical Physics I, and is second in this series of undergraduate Statistical Physics courses.Subjects

Probability distributions | Probability distributions | quantum systems | quantum systems | Microcanonical | canonical | and grand canonical partition-functions | Microcanonical | canonical | and grand canonical partition-functions | thermodynamic potentials | thermodynamic potentials | Conditions of thermodynamic equilibrium for homogenous and heterogenous systems | Conditions of thermodynamic equilibrium for homogenous and heterogenous systems | non-interacting Bose and Fermi gases | non-interacting Bose and Fermi gases | mean field theories for real gases | mean field theories for real gases | binary mixtures | binary mixtures | magnetic systems | magnetic systems | polymer solutions | polymer solutions | phase and reaction equilibria | phase and reaction equilibria | critical phenomena | critical phenomena | Fluctuations | Fluctuations | correlation functions and susceptibilities | and Kubo formulae | correlation functions and susceptibilities | and Kubo formulae | Evolution of distribution functions: Boltzmann and Smoluchowski equations | Evolution of distribution functions: Boltzmann and Smoluchowski equationsLicense

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See all metadata8.591J Systems Biology (MIT) 8.591J Systems Biology (MIT)

Description

This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell co This course introduces the mathematical modeling techniques needed to address key questions in modern biology. An overview of modeling techniques in molecular biology and genetics, cell biology and developmental biology is covered. Key experiments that validate mathematical models are also discussed, as well as molecular, cellular, and developmental systems biology, bacterial chemotaxis, genetic oscillators, control theory and genetic networks, and gradient sensing systems. Additional specific topics include: constructing and modeling of genetic networks, lambda phage as a genetic switch, synthetic genetic switches, circadian rhythms, reaction diffusion equations, local activation and global inhibition models, center finding networks, general pattern formation models, modeling cell-cell coSubjects

molecular systems biology | molecular systems biology | constructing and modeling of genetic networks | constructing and modeling of genetic networks | control theory and genetic networks | control theory and genetic networks | ambda phage as a genetic switch | ambda phage as a genetic switch | synthetic genetic switches | synthetic genetic switches | bacterial chemotaxis | bacterial chemotaxis | genetic oscillators | genetic oscillators | circadian rhythms | circadian rhythms | cellular systems biology | cellular systems biology | reaction diffusion equations | reaction diffusion equations | local activation and global inhibition models | local activation and global inhibition models | gradient sensing systems | gradient sensing systems | center finding networks | center finding networks | developmental systems biology | developmental systems biology | general pattern formation models | general pattern formation models | modeling cell-cell communication | modeling cell-cell communication | quorum sensing | quorum sensing | models for Drosophilia development | models for Drosophilia development | 8.591 | 8.591 | 7.81 | 7.81License

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See all metadata8.022 Physics II: Electricity and Magnetism (MIT) 8.022 Physics II: Electricity and Magnetism (MIT)

Description

Course 8.022 is one of several second-term freshman physics courses offered at MIT. It is geared towards students who are looking for a thorough and challenging introduction to electricity and magnetism. Topics covered include: Electric and magnetic field and potential; introduction to special relativity; Maxwell's equations, in both differential and integral form; and properties of dielectrics and magnetic materials. In addition to the theoretical subject matter, several experiments in electricity and magnetism are performed by the students in the laboratory. Acknowledgments Prof. Sciolla would like to acknowledge the contributions of MIT Professors Scott Hughes and Peter Fisher to the development of this course. She would also like to acknowledge that these course materials include cont Course 8.022 is one of several second-term freshman physics courses offered at MIT. It is geared towards students who are looking for a thorough and challenging introduction to electricity and magnetism. Topics covered include: Electric and magnetic field and potential; introduction to special relativity; Maxwell's equations, in both differential and integral form; and properties of dielectrics and magnetic materials. In addition to the theoretical subject matter, several experiments in electricity and magnetism are performed by the students in the laboratory. Acknowledgments Prof. Sciolla would like to acknowledge the contributions of MIT Professors Scott Hughes and Peter Fisher to the development of this course. She would also like to acknowledge that these course materials include contSubjects

Electricity | Electricity | Magnetism | Magnetism | Maxwell's equations | Maxwell's equations | electrostatic potential | electrostatic potential | vector potential | vector potential | dielectrics | dielectrics | Coulomb's Law | Coulomb's Law | Electric Field | Electric Field | Electric Flux | Electric Flux | Gauss's Law | Gauss's Law | Electric Potential Gradient | Electric Potential Gradient | Poisson Equations | Poisson Equations | Laplace Equations | Laplace Equations | Curl | Curl | Conductors | Conductors | Capacitance | Capacitance | Resistance | Resistance | Kirchhoff's Rules | Kirchhoff's Rules | EMF | EMF | RC Circuits | RC Circuits | Th?venin Equivalence | Th?venin Equivalence | Magnetic Force | Magnetic Force | Magnetic Field | Magnetic Field | Ampere's Law | Ampere's Law | Special Relativity | Special Relativity | Spacetime | Spacetime | Biot-Savart Law | Biot-Savart Law | Faraday's Law | Faraday's Law | Lenz's Law | Lenz's Law | RL Circuits | RL Circuits | AC Circuits | AC Circuits | Electromagnetic Radiation | Electromagnetic Radiation | Poynting Vector | Poynting Vector | Magnetism | Maxwell's equations; | Magnetism | Maxwell's equations;License

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This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms. This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms.Subjects

Formulations | Formulations | Simplex method | Simplex method | Duality theory | Duality theory | Sensitivity analysis | Sensitivity analysis | Robust optimization | Robust optimization | Large scale optimization | Large scale optimization | Network flows | Network flows | The Ellipsoid method | The Ellipsoid method | Interior point methods | Interior point methods | Semidefinite optimization | Semidefinite optimization | Discrete optimization | Discrete optimizationLicense

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This course explores the challenges and risks faced by senior managers of construction, engineering and architecture companies in entering global markets in general, and sponsoring concessions in particular. The course includes a discussion of innovative approaches to nation building, partnering, finance, utilization of specialized delivery systems, privatization, outsourcing and concessions; opportunities created by advanced information technology; and appropriate strategies for entering attractive and rapidly expanding international fields and markets. This course explores the challenges and risks faced by senior managers of construction, engineering and architecture companies in entering global markets in general, and sponsoring concessions in particular. The course includes a discussion of innovative approaches to nation building, partnering, finance, utilization of specialized delivery systems, privatization, outsourcing and concessions; opportunities created by advanced information technology; and appropriate strategies for entering attractive and rapidly expanding international fields and markets.Subjects

management | construction | engineering | architecture | global markets | concessions | partnering | finance | privatization | outsourcing | information technology | international | globalization | greatest construction projects | Mexican road privatization | management | construction | engineering | architecture | global markets | concessions | partnering | finance | privatization | outsourcing | information technology | international | globalization | greatest construction projects | Mexican road privatization | management | management | construction | construction | engineering | engineering | architecture | architecture | global markets | global markets | concessions | concessions | partnering | partnering | finance | finance | privatization | privatization | outsourcing | outsourcing | information technology | information technology | international | international | globalization | globalization | greatest construction projects | greatest construction projects | Mexican road privatization | Mexican road privatizationLicense

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See all metadata13.04 Hydrofoils and Propellers (MIT) 13.04 Hydrofoils and Propellers (MIT)

Description

This course deals with theory and design of hydrofoil sections; lifting and thickness problems for sub-cavitating sections, unsteady flow problems. It focuses on computer-aided design of low drag, cavitation free sections. The course also covers lifting line and lifting surface theory with applications to hydrofoil craft, rudder, and control surface design. Topics include propeller lifting line and lifting surface theory; computer-aided design of wake adapted propellers, unsteady propeller thrust and torque. The course is also an introduction to subjects like flow about axially symmetric bodies and low-aspect ratio lifting surfaces, and hydrodynamic performance and design of waterjets. We will also do an analysis of performance and design of wind turbine rotors in steady and stochastic win This course deals with theory and design of hydrofoil sections; lifting and thickness problems for sub-cavitating sections, unsteady flow problems. It focuses on computer-aided design of low drag, cavitation free sections. The course also covers lifting line and lifting surface theory with applications to hydrofoil craft, rudder, and control surface design. Topics include propeller lifting line and lifting surface theory; computer-aided design of wake adapted propellers, unsteady propeller thrust and torque. The course is also an introduction to subjects like flow about axially symmetric bodies and low-aspect ratio lifting surfaces, and hydrodynamic performance and design of waterjets. We will also do an analysis of performance and design of wind turbine rotors in steady and stochastic winSubjects

Theory and design of hydrofoil sections | Theory and design of hydrofoil sections | lifting and thickness problems | lifting and thickness problems | sub-cavitating sections | sub-cavitating sections | unsteady flow problems | unsteady flow problems | computer-aided design | computer-aided design | low drag | low drag | cavitation free sections | cavitation free sections | Lifting line and lifting surface theory | Lifting line and lifting surface theory | hydrofoil craft | hydrofoil craft | rudder | rudder | and control surface design | and control surface design | propeller lifting line | propeller lifting line | lifting surface theory | lifting surface theory | wake adapted propellers | wake adapted propellers | unsteady propeller thrust and torque | unsteady propeller thrust and torque | axially symmetric bodies | axially symmetric bodies | low-aspect ratio lifting surfaces | low-aspect ratio lifting surfaces | Hydrodynamic performance | Hydrodynamic performance | design of waterjets | design of waterjets | wind turbine rotors in steady and stochastic wind | wind turbine rotors in steady and stochastic wind | hydrofoil craft | rudder | and control surface design | hydrofoil craft | rudder | and control surface design | 9. low drag | cavitation free sections | 9. low drag | cavitation free sections | 5. hydrofoil craft | rudder | and control surface design | 5. hydrofoil craft | rudder | and control surface design | low drag | cavitation free sections | low drag | cavitation free sections | 2.23 | 2.23License

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See all metadata18.03 Differential Equations (MIT) 18.03 Differential Equations (MIT)

Description

Differential Equations are the language in which the laws of nature are expressed. Understanding properties of solutions of differential equations is fundamental to much of contemporary science and engineering. Ordinary differential equations (ODE's) deal with functions of one variable, which can often be thought of as time. Topics include: Solution of first-order ODE's by analytical, graphical and numerical methods; Linear ODE's, especially second order with constant coefficients; Undetermined coefficients and variation of parameters; Sinusoidal and exponential signals: oscillations, damping, resonance; Complex numbers and exponentials; Fourier series, periodic solutions; Delta functions, convolution, and Laplace transform methods; Matrix and first order linear systems: eigenvalues and Differential Equations are the language in which the laws of nature are expressed. Understanding properties of solutions of differential equations is fundamental to much of contemporary science and engineering. Ordinary differential equations (ODE's) deal with functions of one variable, which can often be thought of as time. Topics include: Solution of first-order ODE's by analytical, graphical and numerical methods; Linear ODE's, especially second order with constant coefficients; Undetermined coefficients and variation of parameters; Sinusoidal and exponential signals: oscillations, damping, resonance; Complex numbers and exponentials; Fourier series, periodic solutions; Delta functions, convolution, and Laplace transform methods; Matrix and first order linear systems: eigenvalues andSubjects

Ordinary Differential Equations | Ordinary Differential Equations | ODE | ODE | modeling physical systems | modeling physical systems | first-order ODE's | first-order ODE's | Linear ODE's | Linear ODE's | second order ODE's | second order ODE's | second order ODE's with constant coefficients | second order ODE's with constant coefficients | Undetermined coefficients | Undetermined coefficients | variation of parameters | variation of parameters | Sinusoidal signals | Sinusoidal signals | exponential signals | exponential signals | oscillations | oscillations | damping | damping | resonance | resonance | Complex numbers and exponentials | Complex numbers and exponentials | Fourier series | Fourier series | periodic solutions | periodic solutions | Delta functions | Delta functions | convolution | convolution | Laplace transform methods | Laplace transform methods | Matrix systems | Matrix systems | first order linear systems | first order linear systems | eigenvalues and eigenvectors | eigenvalues and eigenvectors | Non-linear autonomous systems | Non-linear autonomous systems | critical point analysis | critical point analysis | phase plane diagrams | phase plane diagrams | constant coefficients | constant coefficients | complex numbers | complex numbers | exponentials | exponentials | eigenvalues | eigenvalues | eigenvectors | eigenvectorsLicense

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Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical f Most algorithms in computer vision and image analysis can be understood in terms of two important components: a representation and a modeling/estimation algorithm. The representation defines what information is important about the objects and is used to describe them. The modeling techniques extract the information from images to instantiate the representation for the particular objects present in the scene. In this seminar, we will discuss popular representations (such as contours, level sets, deformation fields) and useful methods that allow us to extract and manipulate image information, including manifold fitting, markov random fields, expectation maximization, clustering and others. For each concept -- a new representation or an estimation algorithm -- a lecture on the mathematical fSubjects

computer vision | computer vision | image analysis | image analysis | representation algorithm | representation algorithm | modeling | modeling | estimation algorithm | estimation algorithm | information | information | objects | objects | modeling techniques | modeling techniques | images | images | representations | representations | contours | contours | level sets | level sets | deformation fields | deformation fields | image information | image information | manifold fitting | manifold fitting | markov random fields | markov random fields | expectation maximization | expectation maximization | clustering | clustering | mathematical foundations | mathematical foundations | medical and biological imaging | medical and biological imagingLicense

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An introduction to the formulation, methodology, and techniques for numerical solution of engineering problems. Fundamental principles of digital computing and the implications for algorithm accuracy and stability. Error propagation and stability. The solution of systems of linear equations, including direct and iterative techniques. Roots of equations and systems of equations. Numerical interpolation, differentiation and integration. Fundamentals of finite-difference solutions to ordinary differential equations. Error and convergence analysis. Subject taught first half of term.Technical RequirementsMATLAB® software is required to run the .m files found on this course site.MATLAB® is a trademark of The MathWorks, Inc. An introduction to the formulation, methodology, and techniques for numerical solution of engineering problems. Fundamental principles of digital computing and the implications for algorithm accuracy and stability. Error propagation and stability. The solution of systems of linear equations, including direct and iterative techniques. Roots of equations and systems of equations. Numerical interpolation, differentiation and integration. Fundamentals of finite-difference solutions to ordinary differential equations. Error and convergence analysis. Subject taught first half of term.Technical RequirementsMATLAB® software is required to run the .m files found on this course site.MATLAB® is a trademark of The MathWorks, Inc.Subjects

digital computing | digital computing | algorithm accuracy | algorithm accuracy | error propagation | error propagation | linear equations | linear equations | iterative techniques | iterative techniques | roots of equations | roots of equations | systems of equations | systems of equations | numerical interpolation | numerical interpolation | differentiation | differentiation | integration | integration | finite-difference solutions | finite-difference solutions | differential equations | differential equations | 10.002J | 10.002J | 13.002 | 13.002 | 10.002 | 10.002License

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See all metadata1.561 Motion Based Design (MIT) 1.561 Motion Based Design (MIT)

Description

This course presents a rational basis for the preliminary design of motion-sensitive structures. Topics covered include: analytical and numerical techniques for establishing the optimal stiffness distribution, the role of damping in controlling motion, tuned mass dampers, base isolation systems, and active structural control. Examples illustrating the application of the motion-based design paradigm to building structures subjected to seismic excitation are discussed. This course presents a rational basis for the preliminary design of motion-sensitive structures. Topics covered include: analytical and numerical techniques for establishing the optimal stiffness distribution, the role of damping in controlling motion, tuned mass dampers, base isolation systems, and active structural control. Examples illustrating the application of the motion-based design paradigm to building structures subjected to seismic excitation are discussed.Subjects

preliminary design | preliminary design | motion-sensitive structures | motion-sensitive structures | analytical techniques | analytical techniques | numerical techniques | numerical techniques | optimal stiffness distribution | optimal stiffness distribution | damping | damping | controlling motion | controlling motion | tuned mass dampers | tuned mass dampers | base isolation systems | base isolation systems | active structural control | active structural control | building structures | building structures | wind excitation | wind excitation | seismic excitation | seismic excitation | building design | building design | numerical analysis | numerical analysis | motion control | motion control | motion-based design | motion-based design | safety | safety | serviceability | serviceability | loadings | loadings | optimal stiffness | optimal stiffness | optimal damping | optimal damping | base isolation | base isolationLicense

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6.336J is an introduction to computational techniques for the simulation of a large variety of engineering and physical systems. Applications are drawn from aerospace, mechanical, electrical, chemical and biological engineering, and materials science. Topics include: mathematical formulations; network problems; sparse direct and iterative matrix solution techniques; Newton methods for nonlinear problems; discretization methods for ordinary, time-periodic and partial differential equations, fast methods for partial differential and integral equations, techniques for dynamical system model reduction and approaches for molecular dynamics. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5211 (Introduction to Numerical Simulation). 6.336J is an introduction to computational techniques for the simulation of a large variety of engineering and physical systems. Applications are drawn from aerospace, mechanical, electrical, chemical and biological engineering, and materials science. Topics include: mathematical formulations; network problems; sparse direct and iterative matrix solution techniques; Newton methods for nonlinear problems; discretization methods for ordinary, time-periodic and partial differential equations, fast methods for partial differential and integral equations, techniques for dynamical system model reduction and approaches for molecular dynamics. This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5211 (Introduction to Numerical Simulation).Subjects

Numerical Simulation | Numerical Simulation | simulation | simulation | mathematics | mathematics | network problems | network problems | matrix solution | matrix solution | Newton method | Newton method | nonlinear problems | nonlinear problems | discretization methods | discretization methods | differential equations | differential equations | integral equations | integral equations | model-order reduction | model-order reduction | Monte Carlo | Monte Carlo | 6.336 | 6.336 | 2.096 | 2.096 | 16.910 | 16.910License

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See all metadata6.637 Optical Signals, Devices, and Systems (MIT) 6.637 Optical Signals, Devices, and Systems (MIT)

Description

6.637 covers the fundamentals of optical signals and modern optical devices and systems from a practical point of view. Its goal is to help students develop a thorough understanding of the underlying physical principles such that device and system design and performance can be predicted, analyzed, and understood. Most optical systems involve the use of one or more of the following: sources (e.g., lasers and light-emitting diodes), light modulation components (e.g., liquid-crystal light modulators), transmission media (e.g., free space or fibers), photodetectors (e.g., photodiodes, photomultiplier tubes), information storage devices (e.g., optical disk), processing systems (e.g., imaging and spatial filtering systems) and displays (LCOS microdisplays). These are the topics covered by this 6.637 covers the fundamentals of optical signals and modern optical devices and systems from a practical point of view. Its goal is to help students develop a thorough understanding of the underlying physical principles such that device and system design and performance can be predicted, analyzed, and understood. Most optical systems involve the use of one or more of the following: sources (e.g., lasers and light-emitting diodes), light modulation components (e.g., liquid-crystal light modulators), transmission media (e.g., free space or fibers), photodetectors (e.g., photodiodes, photomultiplier tubes), information storage devices (e.g., optical disk), processing systems (e.g., imaging and spatial filtering systems) and displays (LCOS microdisplays). These are the topics covered by thisSubjects

optical | optical | optical signals | optical signals | optical devices | optical devices | transmission | transmission | detection | detection | storage | storage | processing | processing | display | display | electromagnetic waves | electromagnetic waves | diffraction | diffraction | holography | holography | lasers | lasers | LEDs | LEDs | spatial light modulation | spatial light modulation | display technologies | display technologies | optical waveguides | optical waveguides | fiberoptic communication | fiberoptic communication | thermal photodetector | thermal photodetector | quantum photodetector | quantum photodetector | optical storage media | optical storage media | disks | disks | 3-D holographic material | 3-D holographic material | coherent optical processor | coherent optical processor | incoherent optical processor | incoherent optical processor | Fourier optics | Fourier optics | acousto-optics | acousto-optics | optoelectronic neural networks | optoelectronic neural networks | optical interconnection device technologies | optical interconnection device technologies | image processing | image processing | pattern recognition | pattern recognition | radar systems | radar systems | adaptive optical systems | adaptive optical systems | 6.161 | 6.161License

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See all metadata17.960 Foundations of Political Science (MIT) 17.960 Foundations of Political Science (MIT)

Description

This subject, required of all first-year PhD students in political science, introduces fundamental ideas, theories, and methods in contemporary political science through the study of a small number of major books and articles that are intrinsically good and have been influential in the field. The first semester focuses principally on issues of political theory and international relations, while the second focuses principally on American and comparative politics. Readings in the fall semester from Rawls, A Theory of Justice; Hayek, The Constitution of Liberty; Arrow Social Choice and Individual Values; Olson, The Logic of Collective Action; Waltz, Theory of International Relations; Bull, The Anarchical Society; Foucault, Discipline and Punish; Elster, Cement of Society; Keohane, After This subject, required of all first-year PhD students in political science, introduces fundamental ideas, theories, and methods in contemporary political science through the study of a small number of major books and articles that are intrinsically good and have been influential in the field. The first semester focuses principally on issues of political theory and international relations, while the second focuses principally on American and comparative politics. Readings in the fall semester from Rawls, A Theory of Justice; Hayek, The Constitution of Liberty; Arrow Social Choice and Individual Values; Olson, The Logic of Collective Action; Waltz, Theory of International Relations; Bull, The Anarchical Society; Foucault, Discipline and Punish; Elster, Cement of Society; Keohane, AfterSubjects

Political science | Political science | fundamental ideas | fundamental ideas | theories | theories | methods | methods | contemporary | contemporary | major books | major books | articles | articles | political theory | political theory | international relations | international relations | American | American | comparative politics | comparative politics | Rawls | Rawls | A Theory of Justice | A Theory of Justice | Hayek | Hayek | The Constitution of Liberty | The Constitution of Liberty | Arrow | Arrow | Social Choice and Individual Values | Social Choice and Individual Values | Olson | Olson | The Logic of Collective Action | The Logic of Collective Action | Waltz | Waltz | Theory of International Relations | Theory of International Relations | Bull | Bull | The Anarchical Society | The Anarchical Society | Foucault | Foucault | Discipline and Punish | Discipline and Punish | Elster | Elster | Cement of Society | Cement of Society | Keohane | Keohane | After Hegemony | After Hegemony | Allison | Allison | Zelikow | Zelikow | The Essence of Decision | The Essence of Decision | Doyle | Doyle | Kant | Kant | Liberal Legacies | Liberal Legacies | Foreign Affairs | Foreign AffairsLicense

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On 11 December 2009, Nottingham University's Centre for British Politics held a conference at the British Academy that drew together politicians, writers and academics to explore the interaction of British politics and fiction. In addition to the conference several video interviews were conducted with some of the speakers on the day. In this interview taken at the Fiction and British Politics Conference in London, Research Fellow - Matthew Bailey - answers a question posed by Hazel Blears. Could a West Wing-styled drama improve the standing of British politicians? Suitable for Undergraduate study and community education Dr Matthew Bailey, Research Fellow, The Centre for British Politics, The University of Nottingham Dr Matthew Bailey has published work on a variety of topics regard On 11 December 2009, Nottingham University's Centre for British Politics held a conference at the British Academy that drew together politicians, writers and academics to explore the interaction of British politics and fiction. In addition to the conference several video interviews were conducted with some of the speakers on the day. In this interview taken at the Fiction and British Politics Conference in London, Research Fellow - Matthew Bailey - answers a question posed by Hazel Blears. Could a West Wing-styled drama improve the standing of British politicians? Suitable for Undergraduate study and community education Dr Matthew Bailey, Research Fellow, The Centre for British Politics, The University of Nottingham Dr Matthew Bailey has published work on a variety of topics regardSubjects

UNow | UNow | Politics | Politics | Fiction | Fiction | Political Fiction | Political Fiction | Political Drama | Political Drama | Political Dipiction | Political Dipiction | Political Representation | Political Representation | UKOER | UKOERLicense

Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA) Except for third party materials (materials owned by someone other than The University of Nottingham) and where otherwise indicated, the copyright in the content provided in this resource is owned by The University of Nottingham and licensed under a Creative Commons Attribution-NonCommercial-ShareAlike UK 2.0 Licence (BY-NC-SA)Site sourced from

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See all metadata2.160 Identification, Estimation, and Learning (MIT)

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This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.Subjects

system identification; estimation; least squares estimation; Kalman filter; noise dynamics; system representation; function approximation theory; neural nets; radial basis functions; wavelets; volterra expansions; informative data sets; persistent excitation; asymptotic variance; central limit theorem; model structure selection; system order estimate; maximum likelihood; unbiased estimates; Cramer-Rao lower bound; Kullback-Leibler information distance; Akaike?s information criterion; experiment design; model validation. | system identification | estimation | least squares estimation | Kalman filter | noise dynamics | system representation | function approximation theory | neural nets | radial basis functions | wavelets | volterra expansions | informative data sets | persistent excitation | asymptotic variance | central limit theorem | model structure selection | system order estimate | maximum likelihood | unbiased estimates | Cramer-Rao lower bound | Kullback-Leibler information distance | Akaike?s information criterion | experiment design | model validationLicense

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 metadata17.20 Introduction to American Politics (MIT) 17.20 Introduction to American Politics (MIT)

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This course provides a substantive overview of U.S. politics and an introduction to the discipline of political science. It surveys the institutional foundations of U.S. politics as well as the activities of political elites, organizations, and ordinary citizens. It also explores the application of general political science concepts and analytic frameworks to specific episodes and phenomena in U.S. politics. This course provides a substantive overview of U.S. politics and an introduction to the discipline of political science. It surveys the institutional foundations of U.S. politics as well as the activities of political elites, organizations, and ordinary citizens. It also explores the application of general political science concepts and analytic frameworks to specific episodes and phenomena in U.S. politics.Subjects

American politics | American politics | The Constitution | The Constitution | politicians | politicians | Congress | Congress | the Presidency | the Presidency | bureaucracy | bureaucracy | judiciary | judiciary | federalism | federalism | public opinion | public opinion | political parties | political parties | partisanship | partisanship | choice | choice | campaigns | campaigns | elections | elections | policy | policy | political geography | political geography | polarization | polarization | extremism | extremism | organized interests | organized interests | economic inequality | economic inequality | race | race | immigration | immigration | multiculturalism | multiculturalismLicense

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 metadata22.101 Applied Nuclear Physics (MIT) 22.101 Applied Nuclear Physics (MIT)

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The topics covered under this course include elements of nuclear physics for engineering students, basic properties of the nucleus and nuclear radiations, quantum mechanical calculations of deuteron bound-state wave function and energy, n-p scattering cross-section, transition probability per unit time and barrier transmission probability. Also explored are binding energy and nuclear stability, interactions of charged particles, neutrons, and gamma rays with matter, radioactive decays, energetics and general cross-section behavior in nuclear reactions. The topics covered under this course include elements of nuclear physics for engineering students, basic properties of the nucleus and nuclear radiations, quantum mechanical calculations of deuteron bound-state wave function and energy, n-p scattering cross-section, transition probability per unit time and barrier transmission probability. Also explored are binding energy and nuclear stability, interactions of charged particles, neutrons, and gamma rays with matter, radioactive decays, energetics and general cross-section behavior in nuclear reactions.Subjects

Nuclear physics | Nuclear physics | Nuclear reaction | Nuclear reaction | Nucleus | Nucleus | Nuclear radiation | Nuclear radiation | Quantum mechanics | Quantum mechanics | Deuteron bound-state wave function and energy | Deuteron bound-state wave function and energy | n-p scattering cross-section | n-p scattering cross-section | Transition probability per unit time | Transition probability per unit time | Barrier transmission probability | Barrier transmission probability | Binding energy | Binding energy | Nuclear stability | Nuclear stability | Interactions of charged particles neutrons and gamma rays with matter | Interactions of charged particles neutrons and gamma rays with matter | Radioactive decay | Radioactive decay | Energetics | Energetics | nuclear physics | nuclear physics | nuclear reaction | nuclear reaction | nucleus | nucleus | nuclear radiation | nuclear radiation | quantum mechanics | quantum mechanics | deuteron bound-state wave function and energy | deuteron bound-state wave function and energy | transition probability per unit time | transition probability per unit time | barrier transmission probability | barrier transmission probability | nuclear stability | nuclear stability | Interactions of charged particles | Interactions of charged particles | neutrons | neutrons | and gamma rays with matter | and gamma rays with matter | energetics | energeticsLicense

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 metadataSP.406 Sexual and Gender Identities (MIT) SP.406 Sexual and Gender Identities (MIT)

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This course introduces scholarly debates about sexual identities, gender identities and expressions, and sexual orientation and its representation in various media. We begin with an investigation of the theoretical underpinnings of the emerging field of queer studies, from the nineteenth century to the present day. Tracing theories of and about gender, sexuality and sexual identity over time, we will examine the genealogy of "queer" as a term that has emerged to trouble and challenge static and essentialized notions of identity. The social, cultural, and political effect of "queer" has been to pose critical challenges to gay/lesbian/straight identities predicated on a sexual binary. Queer studies shifts the focus of inquiry from sexual identities to sexual practices, ma This course introduces scholarly debates about sexual identities, gender identities and expressions, and sexual orientation and its representation in various media. We begin with an investigation of the theoretical underpinnings of the emerging field of queer studies, from the nineteenth century to the present day. Tracing theories of and about gender, sexuality and sexual identity over time, we will examine the genealogy of "queer" as a term that has emerged to trouble and challenge static and essentialized notions of identity. The social, cultural, and political effect of "queer" has been to pose critical challenges to gay/lesbian/straight identities predicated on a sexual binary. Queer studies shifts the focus of inquiry from sexual identities to sexual practices, maSubjects

women | women | gender studies | gender studies | sexual identity | sexual identity | gender identities | gender identities | gender | gender | queer | queer | sexual orientation | sexual orientation | queer studies | queer studies | gay | gay | lesbian | lesbian | straight identities | straight identities | sexual practices | sexual practices | sexuality | sexuality | freud | freud | foucault | foucault | sedgwick | sedgwick | rubin | rubin | butler | butler | homosexuality | homosexuality | homosexual | homosexual | gay marriage | gay marriage | AIDs | AIDs | feminism | feminismLicense

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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