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15.875 Applications of System Dynamics (MIT) 15.875 Applications of System Dynamics (MIT)

Description

15.875 is a project-based course that explores how organizations can use system dynamics to achieve important goals. In small groups, students learn modeling and consulting skills by working on a term-long project with real-life managers. A diverse set of businesses and organizations sponsor class projects, from start-ups to the Fortune 500. The course focuses on gaining practical insight from the system dynamics process, and appeals to people interested in system dynamics, consulting, or managerial policy-making. 15.875 is a project-based course that explores how organizations can use system dynamics to achieve important goals. In small groups, students learn modeling and consulting skills by working on a term-long project with real-life managers. A diverse set of businesses and organizations sponsor class projects, from start-ups to the Fortune 500. The course focuses on gaining practical insight from the system dynamics process, and appeals to people interested in system dynamics, consulting, or managerial policy-making.

Subjects

system dynamics process; modeling; business consulting; managerial policy-making; team project; standard method; process consultation; system consultation; system processes; modeling loops; analyzing loops; diffusion model; problem solving; reference modes; momentum policies; causal loop; client consultations; client consulting; molecules of structure; system dynamics models | system dynamics process; modeling; business consulting; managerial policy-making; team project; standard method; process consultation; system consultation; system processes; modeling loops; analyzing loops; diffusion model; problem solving; reference modes; momentum policies; causal loop; client consultations; client consulting; molecules of structure; system dynamics models | system dynamics process | system dynamics process | modeling | modeling | business consulting | business consulting | managerial policy-making | managerial policy-making | team project | team project | standard method | standard method | process consultation | process consultation | system consultation | system consultation | system processes | system processes | modeling loops | modeling loops | analyzing loops | analyzing loops | diffusion model | diffusion model | problem solving | problem solving | reference modes | reference modes | momentum policies | momentum policies | causal loop | causal loop | client consultations | client consultations | client consulting | client consulting | molecules of structure | molecules of structure | system dynamics models | system dynamics models

License

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2.76 Multi-Scale System Design (MIT) 2.76 Multi-Scale System Design (MIT)

Description

Multi-scale systems (MuSS) consist of components from two or more length scales (nano, micro, meso, or macro-scales). In MuSS, the engineering modeling, design principles, and fabrication processes of the components are fundamentally different. The challenge is to make these components so they are conceptually and model-wise compatible with other-scale components with which they interface. This course covers the fundamental properties of scales, design theories, modeling methods and manufacturing issues which must be addressed in these systems. Examples of MuSS include precision instruments, nanomanipulators, fiber optics, micro/nano-photonics, nanorobotics, MEMS (piezoelectric driven manipulators and optics), X-Ray telescopes and carbon nano-tube assemblies. Students master the materials Multi-scale systems (MuSS) consist of components from two or more length scales (nano, micro, meso, or macro-scales). In MuSS, the engineering modeling, design principles, and fabrication processes of the components are fundamentally different. The challenge is to make these components so they are conceptually and model-wise compatible with other-scale components with which they interface. This course covers the fundamental properties of scales, design theories, modeling methods and manufacturing issues which must be addressed in these systems. Examples of MuSS include precision instruments, nanomanipulators, fiber optics, micro/nano-photonics, nanorobotics, MEMS (piezoelectric driven manipulators and optics), X-Ray telescopes and carbon nano-tube assemblies. Students master the materials

Subjects

scale | scale | complexity | complexity | nano | micro | meso | or macro-scale | nano | micro | meso | or macro-scale | kinematics | kinematics | metrology | metrology | engineering modeling | motion | engineering modeling | motion | modeling | modeling | design | design | manufacture | manufacture | design principles | design principles | fabrication process | fabrication process | functional requirements | functional requirements | precision instruments | precision instruments | nanomanipulators | fiber optics | micro- photonics | nano-photonics | nanorobotics | MEMS | nanomanipulators | fiber optics | micro- photonics | nano-photonics | nanorobotics | MEMS | piezoelectric | transducer | actuator | sensor | piezoelectric | transducer | actuator | sensor | constraint | rigid constraint | flexible constraint | ride-flexible constraint | constraint | rigid constraint | flexible constraint | ride-flexible constraint | constaint-based design | constaint-based design | carbon nanotube | carbon nanotube | nanowire | nanowire | scanning tunneling microscope | scanning tunneling microscope | flexure | flexure | protein structure | protein structure | polymer structure | polymer structure | nanopelleting | nanopipette | nanowire | nanopelleting | nanopipette | nanowire | TMA pixel array | TMA pixel array | error modeling | error modeling | repeatability | repeatability

License

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11.942 Regional Energy-Environmental Economic Modeling (MIT) 11.942 Regional Energy-Environmental Economic Modeling (MIT)

Description

This subject is on regional energy-environmental modeling rather than on general energy-environmental policies, but the models should have some policy relevance. We will start with some discussion of green accounting issues; then, we will cover a variety of theoretical and empirical topics related to spatial energy demand and supply, energy forecasts, national and regional energy prices, and environmental implications of regional energy consumption and production. Where feasible, the topics will have a spatial dimension. This is a new seminar, so we expect students to contribute material to the set of readings and topics covered during the semester. This subject is on regional energy-environmental modeling rather than on general energy-environmental policies, but the models should have some policy relevance. We will start with some discussion of green accounting issues; then, we will cover a variety of theoretical and empirical topics related to spatial energy demand and supply, energy forecasts, national and regional energy prices, and environmental implications of regional energy consumption and production. Where feasible, the topics will have a spatial dimension. This is a new seminar, so we expect students to contribute material to the set of readings and topics covered during the semester.

Subjects

regional energy environmental modeling | regional energy environmental modeling | policies | policies | microeconomics | microeconomics | economic modeling | economic modeling | economic modeling techniques | economic modeling techniques | input-output | input-output | general equilibrium | general equilibrium | linear programming | linear programming | logit | logit | regression | regression | green accounting | green accounting | spatial energy demand | spatial energy demand | spatial energy supply | spatial energy supply | energy forecast | energy forecast | regional energy prices | regional energy prices | regional energy consumption | regional energy consumption | regional energy production | regional energy production

License

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ESD.70J Engineering Economy Module (MIT) ESD.70J Engineering Economy Module (MIT)

Description

This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 – Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools – such as Data Table and Goal Seek. It is also useful for a variety of other subjects.NoteThis MIT OpenCourseWare site is based on the materials from Professor de Neufville's ESD.70J Web site. This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 – Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools – such as Data Table and Goal Seek. It is also useful for a variety of other subjects.NoteThis MIT OpenCourseWare site is based on the materials from Professor de Neufville's ESD.70J Web site.

Subjects

excel | excel | spreadsheet | spreadsheet | modeling | modeling | dynamic modeling | dynamic modeling | analysis | analysis | data table | data table | goal seek | goal seek | sensitivity analysis | sensitivity analysis | simulation | simulation | random number generator | random number generator | counting | counting | modeling uncertainties | modeling uncertainties | random variables | random variables | statistical package | statistical package | flexibility | flexibility | contingency rules | contingency rules | excel solver | excel solver | solver | solver

License

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ESD.864 Modeling and Assessment for Policy (MIT) ESD.864 Modeling and Assessment for Policy (MIT)

Description

ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance. ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance.

Subjects

policy | policy | modeling | modeling | NASA | NASA | economics | economics | memo | memo | oil spill | oil spill | clean air | clean air | sports statistics | sports statistics | breast cancer | breast cancer | scientific assessment process | scientific assessment process | integrated assessment modeling | integrated assessment modeling | model frameworks | model frameworks | systems modeling | systems modeling | policy-analysis techniques | policy-analysis techniques | science policy | science policy | risk assessment | risk assessment | adaptive management | adaptive management

License

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ESD.70J Engineering Economy Module (MIT) ESD.70J Engineering Economy Module (MIT)

Description

This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools, such as Data Table and Goal Seek. It is also useful for a variety of other subjects. This intensive micro-subject provides the necessary skills in Microsoft® Excel spreadsheet modeling for ESD.71 Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools, such as Data Table and Goal Seek. It is also useful for a variety of other subjects.

Subjects

ESD.70 | ESD.70 | 1.145 | 1.145 | excel | excel | spreadsheet | spreadsheet | modeling | modeling | dynamic modeling | dynamic modeling | analysis | analysis | data table | data table | goal seek | goal seek | sensitivity analysis | sensitivity analysis | simulation | simulation | random number generator | random number generator | counting | counting | modeling uncertainties | modeling uncertainties | random variables | random variables | statistical package | statistical package | flexibility | flexibility | contingency rules | contingency rules | excel solver | excel solver | solver | solver

License

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15.879 Research Seminar in System Dynamics (MIT) 15.879 Research Seminar in System Dynamics (MIT)

Description

Includes audio/video content: AV special element video. Doctoral level seminar in system dynamics modeling with a focus on social, economic and technical systems. The course covers classic works in dynamic modeling from various disciplines and current research problems and papers. Participants critique theories and models, often including replication, testing, and improvement of various models. Includes audio/video content: AV special element video. Doctoral level seminar in system dynamics modeling with a focus on social, economic and technical systems. The course covers classic works in dynamic modeling from various disciplines and current research problems and papers. Participants critique theories and models, often including replication, testing, and improvement of various models.

Subjects

system dynamics | system dynamics | systems thinking | systems thinking | models | models | business dynamics | business dynamics | system dynamics modeling applied to corporate strategy | system dynamics modeling applied to corporate strategy | modeling software | modeling software | project management | project management | modeling in the real world | modeling in the real world | policy issues | policy issues | bullwhip effect | bullwhip effect

License

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15.874 System Dynamics for Business Policy (MIT) 15.874 System Dynamics for Business Policy (MIT)

Description

15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using system dynamics. 15.874 is a full semester course and 15.871 is a half semester course. The two classes meet together and cover the same material for the first half of the term. In the second half of the semester, only 15.874 continues. 15.874 and 15.871 provide an introduction to system dynamics modeling for the analysis of business policy and strategy. Students learn to visualize a business organization in terms of the structures and policies that create dynamics and regulate performance. The course uses role playing games, simulation models, and management flight simulators to develop principles for the successful management of complex strategies. Special emphasis will be placed on case studies of successful strategies using system dynamics. 15.874 is a full semester course and 15.871 is a half semester course. The two classes meet together and cover the same material for the first half of the term. In the second half of the semester, only 15.874 continues.

Subjects

system dynamics modeling applied to corporate strategy | system dynamics modeling applied to corporate strategy | simulation models | simulation models | quot; | quot; | management "flight simulators" | management "flight simulators" | high-performance organizations | high-performance organizations | growth strategy | growth strategy | management of technology | management of technology | operations | operations | project management | project management | effective use of modeling in the real world | effective use of modeling in the real world | business strategy | business strategy | system dynamics modeling | system dynamics modeling | corporate strategy | corporate strategy | case studies | case studies | business policies | business policies | visualizations | visualizations | business structures | business structures | microworlds | microworlds | role playing games | role playing games | policy design | policy design

License

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13.853 Computational Ocean Acoustics (MIT) 13.853 Computational Ocean Acoustics (MIT)

Description

This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research.

Subjects

Wave equations | Wave equations | fluid and visco-elastic media | fluid and visco-elastic media | Wave-theory formulations | Wave-theory formulations | acoustic source radiation | acoustic source radiation | seismo-acoustic propagation | seismo-acoustic propagation | stratified ocean waveguides | stratified ocean waveguides | Wavenumber Integration | Wavenumber Integration | Normal Mode | Normal Mode | propagation in plane-stratified media | propagation in plane-stratified media | Seismo-Acoustic modeling | Seismo-Acoustic modeling | Seismic interface | Seismic interface | surface waves | surface waves | stratified seabed | stratified seabed | Parabolic Equation | Parabolic Equation | Coupled Mode | Coupled Mode | range-dependent ocean waveguides | range-dependent ocean waveguides | Numerical modeling | Numerical modeling | target scattering | target scattering | reverberation clutter | reverberation clutter | Ocean ambient noise modeling | Ocean ambient noise modeling | Fluid media | Fluid media | visco-elastic media | visco-elastic media | plane-stratified media | plane-stratified media | ice covers | ice covers | 2.068 | 2.068

License

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2.068 Computational Ocean Acoustics (13.853) (MIT) 2.068 Computational Ocean Acoustics (13.853) (MIT)

Description

This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course was originally offered in Course 13 ( This course examines wave equations for fluid and visco-elastic media, wave-theory formulations of acoustic source radiation and seismo-acoustic propagation in stratified ocean waveguides, and Wavenumber Integration and Normal Mode methods for propagation in plane-stratified media. Also covered are Seismo-Acoustic modeling of seabeds and ice covers, seismic interface and surface waves in a stratified seabed, Parabolic Equation and Coupled Mode approaches to propagation in range-dependent ocean waveguides, numerical modeling of target scattering and reverberation clutter in ocean waveguides, and ocean ambient noise modeling. Students develop propagation models using all the numerical approaches relevant to state-of-the-art acoustic research. This course was originally offered in Course 13 (

Subjects

Wave equations | Wave equations | fluid and visco-elastic media | fluid and visco-elastic media | Wave-theory formulations | Wave-theory formulations | acoustic source radiation | acoustic source radiation | seismo-acoustic propagation | seismo-acoustic propagation | stratified ocean waveguides | stratified ocean waveguides | Wavenumber Integration | Wavenumber Integration | Normal Mode | Normal Mode | propagation in plane-stratified media | propagation in plane-stratified media | Seismo-Acoustic modeling | Seismo-Acoustic modeling | Seismic interface | Seismic interface | surface waves | surface waves | stratified seabed | stratified seabed | Parabolic Equation | Parabolic Equation | Coupled Mode | Coupled Mode | range-dependent ocean waveguides | range-dependent ocean waveguides | Numerical modeling | Numerical modeling | target scattering | target scattering | reverberation clutter | reverberation clutter | Ocean ambient noise modeling | Ocean ambient noise modeling | Fluid media | Fluid media | visco-elastic media | visco-elastic media | plane-stratified media | plane-stratified media | ice covers | ice covers

License

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ESD.864 Systems Modeling and Assessment for Policy (MIT) ESD.864 Systems Modeling and Assessment for Policy (MIT)

Description

This course explores how scientific information can be used to inform policy decision-making processes through the use of quantitative modeling techniques. It incorporates both hands-on analysis and practice using models as well as evaluation of the use and effectiveness of models in decision-making. The course assesses the full spectrum of model complexity from simple box model calculations to complex, global systems models. Issues addressed include scientific assessment processes; integrated assessment modeling; model frameworks; and scenarios. Examples focus on models and information used for earth system governance, with selected examples from other areas of application. This course explores how scientific information can be used to inform policy decision-making processes through the use of quantitative modeling techniques. It incorporates both hands-on analysis and practice using models as well as evaluation of the use and effectiveness of models in decision-making. The course assesses the full spectrum of model complexity from simple box model calculations to complex, global systems models. Issues addressed include scientific assessment processes; integrated assessment modeling; model frameworks; and scenarios. Examples focus on models and information used for earth system governance, with selected examples from other areas of application.

Subjects

scientific assessment process | scientific assessment process | integrated assessment modeling | integrated assessment modeling | model frameworks | model frameworks | systems modeling | systems modeling | policy-analysis techniques | policy-analysis techniques | climate change | climate change

License

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8.591J 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 co

Subjects

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 | 7.81

License

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11.433J Real Estate Economics (MIT) 11.433J Real Estate Economics (MIT)

Description

This course, offered by the MIT Center for Real Estate, focuses on developing an understanding of the macroeconomic factors that shape and influence markets for real property. We will develop the theory of land markets and locational choice. The material covered includes studies of changing economic activities, demographic trends, transportation and local government behavior as they affect real estate. This course, offered by the MIT Center for Real Estate, focuses on developing an understanding of the macroeconomic factors that shape and influence markets for real property. We will develop the theory of land markets and locational choice. The material covered includes studies of changing economic activities, demographic trends, transportation and local government behavior as they affect real estate.

Subjects

real estate; property; macroeconomic factors; supply and demand; market cycles; land markets; demographic trends; transportation; government regulation; real estate market; demographic analysis; regional growth; residential construction; new home building; commercial construction; retail stores; urban location theory; predicting demand; modeling techniques; urban economics; land use; urban growth; residential development; gentrification; zoning; property taxes; neighboorhood effects | real estate; property; macroeconomic factors; supply and demand; market cycles; land markets; demographic trends; transportation; government regulation; real estate market; demographic analysis; regional growth; residential construction; new home building; commercial construction; retail stores; urban location theory; predicting demand; modeling techniques; urban economics; land use; urban growth; residential development; gentrification; zoning; property taxes; neighboorhood effects | real estate | real estate | property | property | macroeconomic factors | macroeconomic factors | supply and demand | supply and demand | market cycles | market cycles | land markets | land markets | demographic trends | demographic trends | transportation | transportation | government regulation | government regulation | real estate market | real estate market | demographic analysis | demographic analysis | regional growth | regional growth | residential construction | residential construction | new home building | new home building | commercial construction | commercial construction | retail stores | retail stores | urban location theory | urban location theory | predicting demand | predicting demand | modeling techniques | modeling techniques | urban economics | urban economics | land use | land use | urban growth | urban growth | residential development | residential development | gentrification | gentrification | zoning | zoning | property taxes | property taxes | neighboorhood effects | neighboorhood effects

License

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6.170 Laboratory in Software Engineering (MIT) 6.170 Laboratory in Software Engineering (MIT)

Description

This course is a a core electrical engineering computer science subject at MIT. It introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include: modularity; specification; data abstraction; object modeling; design patterns; and testing. Several programming projects of varying size undertaken by students working individually and in groups. This course is a a core electrical engineering computer science subject at MIT. It introduces concepts and techniques relevant to the production of large software systems. Students are taught a programming method based on the recognition and description of useful abstractions. Topics include: modularity; specification; data abstraction; object modeling; design patterns; and testing. Several programming projects of varying size undertaken by students working individually and in groups.

Subjects

software development | modularity | specification; data abstraction; object modeling | design patterns | software development | modularity | specification; data abstraction; object modeling | design patterns | modularity | modularity | software development | software development | specification | specification | data abstraction | data abstraction | software design | software design | object modeling | object modeling | software testing | software testing | large systems | large systems

License

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ESD.83 Doctoral Seminar in Engineering Systems (MIT) ESD.83 Doctoral Seminar in Engineering Systems (MIT)

Description

ESD.83 Doctoral Seminar in Engineering Systems examines the core theory and contextual applications of the emerging field of Engineering Systems. There is a focus on doctoral–level analysis of scholarship on key concepts such as complexity, uncertainty, fragility, and robustness, as well as a critical look at the historical roots of the field and related areas such as systems engineering, systems dynamics, agent modeling, and systems simulations. Contextual applications of the course range from aerospace to technology implementation to regulatory systems to large–scale systems change. Special attention is given to the interdependence of social and technical dimensions of engineering systems. ESD.83 Doctoral Seminar in Engineering Systems examines the core theory and contextual applications of the emerging field of Engineering Systems. There is a focus on doctoral–level analysis of scholarship on key concepts such as complexity, uncertainty, fragility, and robustness, as well as a critical look at the historical roots of the field and related areas such as systems engineering, systems dynamics, agent modeling, and systems simulations. Contextual applications of the course range from aerospace to technology implementation to regulatory systems to large–scale systems change. Special attention is given to the interdependence of social and technical dimensions of engineering systems.

Subjects

engineering systems | engineering systems | complexity | complexity | uncertainty | uncertainty | fragility | fragility | robustness | robustness | systems engineering | systems engineering | systems dynamics | systems dynamics | agent modeling | agent modeling | systems simulations | systems simulations | large-scale systems change | large-scale systems change | modeling paradigms | modeling paradigms | cumulative knowledge | cumulative knowledge | empirical data generation | empirical data generation | boundary setting | boundary setting | network models | network models | policy evaluation | policy evaluation

License

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.htm

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3.20 Materials at Equilibrium (SMA 5111) (MIT) 3.20 Materials at Equilibrium (SMA 5111) (MIT)

Description

Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium). Material covered in this course includes the following topics: Laws of thermodynamics: general formulation and applications to mechanical, electromagnetic and electrochemical systems, solutions, and phase diagrams Computation of phase diagrams Statistical thermodynamics and relation between microscopic and macroscopic properties, including ensembles, gases, crystal lattices, phase transitions Applications to phase stability and properties of mixtures Computational modeling Interfaces This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5111 (Materials at Equilibrium).

Subjects

thermodynamics | thermodynamics | mechanical | mechanical | electromagnetic and electrochemical systems | electromagnetic and electrochemical systems | phase diagrams | phase diagrams | Statistical thermodynamics | Statistical thermodynamics | microscopic and macroscopic properties | microscopic and macroscopic properties | ensembles | ensembles | gases | gases | crystal lattices | crystal lattices | phase transitions | phase transitions | phase stability | phase stability | properties of mixtures | properties of mixtures | Computational modeling | Computational modeling | Interfaces | Interfaces | mechanical | electromagnetic and electrochemical systems | mechanical | electromagnetic and electrochemical systems | Computational modeling; Interfaces | Computational modeling; Interfaces | mechanical systems | mechanical systems | electromagnetic systems | electromagnetic systems | electrochemical systems | electrochemical systems | laws of thermodynamics | laws of thermodynamics | solutions | solutions | microscopic properties | microscopic properties | macroscopic properties | macroscopic properties

License

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ESD.83 Doctoral Seminar in Engineering Systems (MIT) ESD.83 Doctoral Seminar in Engineering Systems (MIT)

Description

In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development. In establishing the Engineering Systems Division, MIT has embarked on a bold experiment – bringing together diverse areas of expertise into what is designed to be a new field of study. In many respects, the full scale and scope of Engineering Systems as a field is still emerging. This seminar is simultaneously designed to codify what we presently know and to give direction for future development.

Subjects

engineering systems | engineering systems | complexity | complexity | uncertainty | uncertainty | fragility | fragility | robustness | robustness | systems engineering | systems engineering | systems dynamics | systems dynamics | agent modeling | agent modeling | systems simulations | systems simulations | large-scale systems change | large-scale systems change | modeling paradigms | modeling paradigms | cumulative knowledge | cumulative knowledge | empirical data generation | empirical data generation | boundary setting | boundary setting | network models | network models | policy evaluation | policy evaluation

License

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1.020 Ecology II: Engineering for Sustainability (MIT) 1.020 Ecology II: Engineering for Sustainability (MIT)

Description

This course covers the use of ecological and thermodynamic principles to examine interactions between humans and the natural environment. Topics include conservation and constitutive laws, box models, feedback, thermodynamic concepts, energy in natural and engineered systems, basic transport concepts, life cycle analysis and related economic methods.Topics such as renewable energy, sustainable agriculture, green buildings, and mitigation of climate change are illustrated with quantitative case studies. Case studies are team-oriented and may include numerical simulations and design exercises. Some programming experience is desirable but not a prerequisite. Instruction and practice in oral and written communication are provided. This course covers the use of ecological and thermodynamic principles to examine interactions between humans and the natural environment. Topics include conservation and constitutive laws, box models, feedback, thermodynamic concepts, energy in natural and engineered systems, basic transport concepts, life cycle analysis and related economic methods.Topics such as renewable energy, sustainable agriculture, green buildings, and mitigation of climate change are illustrated with quantitative case studies. Case studies are team-oriented and may include numerical simulations and design exercises. Some programming experience is desirable but not a prerequisite. Instruction and practice in oral and written communication are provided.

Subjects

systems | systems | conservation laws | conservation laws | constitutive laws | constitutive laws | box models | box models | mass conservation | mass conservation | perturbation methods | perturbation methods | thermodymanics | thermodymanics | heat transfer | heat transfer | enthalpy | enthalpy | entropy | entropy | multiphase systems | multiphase systems | mass and energy balances | mass and energy balances | energy supply options | energy supply options | economic value | economic value | natural resources | natural resources | multiobjective analysis | multiobjective analysis | life cycle analysis | life cycle analysis | mass and energy transport | mass and energy transport | green buildings | green buildings | transportation modeling | transportation modeling | renewable energy | renewable energy | climate modeling | climate modeling

License

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1.020 Ecology II: Engineering for Sustainability (MIT) 1.020 Ecology II: Engineering for Sustainability (MIT)

Description

This course provides a review of physical, chemical, ecological, and economic principles used to examine interactions between humans and the natural environment. Mass balance concepts are applied to ecology, chemical kinetics, hydrology, and transportation; energy balance concepts are applied to building design, ecology, and climate change; and economic and life cycle concepts are applied to resource evaluation and engineering design. Numerical models are used to integrate concepts and to assess environmental impacts of human activities. Problem sets involve development of MATLAB® models for particular engineering applications. Some experience with computer programming is helpful but not essential. This course provides a review of physical, chemical, ecological, and economic principles used to examine interactions between humans and the natural environment. Mass balance concepts are applied to ecology, chemical kinetics, hydrology, and transportation; energy balance concepts are applied to building design, ecology, and climate change; and economic and life cycle concepts are applied to resource evaluation and engineering design. Numerical models are used to integrate concepts and to assess environmental impacts of human activities. Problem sets involve development of MATLAB® models for particular engineering applications. Some experience with computer programming is helpful but not essential.

Subjects

modeling | modeling | matlab | matlab | human impact on environment | human impact on environment | economics | economics | natural resources | natural resources | assessment of model predictions | assessment of model predictions | mass balance | mass balance | energy balance | energy balance | mass transport | mass transport | energy transport | energy transport | resource economics | resource economics | life cycle analysis | life cycle analysis | chemical kinetics | chemical kinetics | population modeling | population modeling | pesticides | pesticides | nutrients | nutrients | building energy | building energy | air quality | air quality | crop irrigation | crop irrigation | groundwater | groundwater

License

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15.875 Applications of System Dynamics (MIT)

Description

15.875 is a project-based course that explores how organizations can use system dynamics to achieve important goals. In small groups, students learn modeling and consulting skills by working on a term-long project with real-life managers. A diverse set of businesses and organizations sponsor class projects, from start-ups to the Fortune 500. The course focuses on gaining practical insight from the system dynamics process, and appeals to people interested in system dynamics, consulting, or managerial policy-making.

Subjects

system dynamics process; modeling; business consulting; managerial policy-making; team project; standard method; process consultation; system consultation; system processes; modeling loops; analyzing loops; diffusion model; problem solving; reference modes; momentum policies; causal loop; client consultations; client consulting; molecules of structure; system dynamics models | system dynamics process | modeling | business consulting | managerial policy-making | team project | standard method | process consultation | system consultation | system processes | modeling loops | analyzing loops | diffusion model | problem solving | reference modes | momentum policies | causal loop | client consultations | client consulting | molecules of structure | system dynamics models

License

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1.978 From Nano to Macro: Introduction to Atomistic Modeling Techniques (MIT) 1.978 From Nano to Macro: Introduction to Atomistic Modeling Techniques (MIT)

Description

The objective of this course is to introduce large-scale atomistic modeling techniques and highlight its importance for solving problems in modern engineering sciences. We demonstrate how atomistic modeling can be used to understand how materials fail under extreme loading, involving unfolding of proteins and propagation of cracks. This course was featured in an MIT Tech Talk article. The objective of this course is to introduce large-scale atomistic modeling techniques and highlight its importance for solving problems in modern engineering sciences. We demonstrate how atomistic modeling can be used to understand how materials fail under extreme loading, involving unfolding of proteins and propagation of cracks. This course was featured in an MIT Tech Talk article.

Subjects

large-scale atomistic | large-scale atomistic | large-scale atomistic modeling techniques | large-scale atomistic modeling techniques | modern engineering sciences | modern engineering sciences | atomistic modeling | atomistic modeling | extreme loading | extreme loading | ductile and brittle materials failure | ductile and brittle materials failure | molecular dynamics | molecular dynamics | simulations | simulations | Cauchy-Born rule | Cauchy-Born rule | biomechanics | biomechanics | biomaterials | biomaterials | copper nanocrystal | copper nanocrystal | nanomechanics | nanomechanics | material mechanics | material mechanics

License

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6.891 Computational Evolutionary Biology (MIT) 6.891 Computational Evolutionary Biology (MIT)

Description

Why has it been easier to develop a vaccine to eliminate polio than to control influenza or AIDS? Has there been natural selection for a 'language gene'? Why are there no animals with wheels? When does 'maximizing fitness' lead to evolutionary extinction? How are sex and parasites related? Why don't snakes eat grass? Why don't we have eyes in the back of our heads? How does modern genomics illustrate and challenge the field? This course analyzes evolution from a computational, modeling, and engineering perspective. The course has extensive hands-on laboratory exercises in model-building and analyzing evolutionary data. Why has it been easier to develop a vaccine to eliminate polio than to control influenza or AIDS? Has there been natural selection for a 'language gene'? Why are there no animals with wheels? When does 'maximizing fitness' lead to evolutionary extinction? How are sex and parasites related? Why don't snakes eat grass? Why don't we have eyes in the back of our heads? How does modern genomics illustrate and challenge the field? This course analyzes evolution from a computational, modeling, and engineering perspective. The course has extensive hands-on laboratory exercises in model-building and analyzing evolutionary data.

Subjects

evolution from a computational | evolution from a computational | modeling | modeling | and engineering perspective | and engineering perspective | analyzing evolutionary data | analyzing evolutionary data | vaccine | vaccine | polio | polio | influenza | influenza | AIDS | AIDS | evolutionary extinction | evolutionary extinction | sex | sex | parasites | parasites | modern genomics | modern genomics | polio vaccine | polio vaccine | hands-on | hands-on | evolution from a computational | modeling | and engineering perspective | evolution from a computational | modeling | and engineering perspective

License

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6.881 Representation and Modeling for Image Analysis (MIT) 6.881 Representation and Modeling for Image Analysis (MIT)

Description

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 f

Subjects

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 imaging

License

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ESD.864 Modeling and Assessment for Policy (MIT) ESD.864 Modeling and Assessment for Policy (MIT)

Description

ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance. ESD.864 Modeling and Assessment for Policy explores how scientific information and quantitative models can be used to inform policy decision-making. Students will develop an understanding of quantitative modeling techniques and their role in the policy process through case studies and interactive activities. The course addresses issues such as analysis of scientific assessment processes, uses of integrated assessment models, public perception of quantitative information, methods for dealing with uncertainties, and design choices in building policy-relevant models. Examples used in this class focus on models and information used in earth system governance.

Subjects

scientific assessment process | scientific assessment process | integrated assessment modeling | integrated assessment modeling | model frameworks | model frameworks | systems modeling | systems modeling | policy-analysis techniques | policy-analysis techniques | science policy | science policy | risk assessment | risk assessment | adaptive management | adaptive management

License

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.htm

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13.49 Maneuvering and Control of Surface and Underwater Vehicles (MIT) 13.49 Maneuvering and Control of Surface and Underwater Vehicles (MIT)

Description

This course is about maneuvering motions of surface and underwater vehicles. Topics covered include: derivation of equations of motion, hydrodynamic coefficients, memory effects, linear and nonlinear forms of the equations of motion, control surfaces modeling and design, engine, propulsor, and transmission systems modeling and simulation during maneuvering. The course also deals with stability of motion, principles of multivariable automatic control, optimal control, Kalman filtering, and loop transfer recovery. We will also explore applications chosen from autopilots for surface vehicles; towing in open seas; and remotely operated vehicles. This course is about maneuvering motions of surface and underwater vehicles. Topics covered include: derivation of equations of motion, hydrodynamic coefficients, memory effects, linear and nonlinear forms of the equations of motion, control surfaces modeling and design, engine, propulsor, and transmission systems modeling and simulation during maneuvering. The course also deals with stability of motion, principles of multivariable automatic control, optimal control, Kalman filtering, and loop transfer recovery. We will also explore applications chosen from autopilots for surface vehicles; towing in open seas; and remotely operated vehicles.

Subjects

Maneuvering | Maneuvering | motion | motion | surface and underwater vehicles | surface and underwater vehicles | Derivation of equations of motion | Derivation of equations of motion | hydrodynamic coefficients | hydrodynamic coefficients | Memory effects | Memory effects | Linear and nonlinear forms | Linear and nonlinear forms | Control surfaces | Control surfaces | modeling and design | modeling and design | Engine | Engine | propulsor | propulsor | transmission systems modeling | transmission systems modeling | simulation | simulation | Stability of motion | Stability of motion | multivariable automatic control | multivariable automatic control | Optimal control | Optimal control | Kalman filtering | Kalman filtering | loop transfer recovery | loop transfer recovery | autopilots for surface vehicles | autopilots for surface vehicles | towing in open seas | towing in open seas | remotely operated vehicles | remotely operated vehicles | 2.154 | 2.154

License

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