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18.465 Topics in Statistics: Statistical Learning Theory (MIT) 18.465 Topics in Statistics: Statistical Learning Theory (MIT)

Description

The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory. The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.

Subjects

machine learning algorithms | machine learning algorithms | boosting | boosting | support | support | support vector machines | support vector machines | neural networks | neural networks | Vapnik- Chervonenkis theory | Vapnik- Chervonenkis theory | concentration inequalities in product spaces | concentration inequalities in product spaces | empirical process theory | empirical process theory

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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1.223J Transportation Policy, Strategy, and Management (MIT) 1.223J Transportation Policy, Strategy, and Management (MIT)

Description

This class surveys the current concepts, theories, and issues in strategic management of transportation organizations. It provides transportation logistics and engineering systems students with an overview of the operating context, leadership challenges, strategies, and management tools that are used in today's public and private transportation organizations. The following concepts, tools, and issues are presented in both public and private sector cases: alternative models of decision-making, strategic planning (e.g., use of SWOT analysis and scenario development), stakeholder valuation and analysis, government-based regulation and cooperation within the transportation enterprise, disaster communications, systems safety, change management, and the impact of globalization. This class surveys the current concepts, theories, and issues in strategic management of transportation organizations. It provides transportation logistics and engineering systems students with an overview of the operating context, leadership challenges, strategies, and management tools that are used in today's public and private transportation organizations. The following concepts, tools, and issues are presented in both public and private sector cases: alternative models of decision-making, strategic planning (e.g., use of SWOT analysis and scenario development), stakeholder valuation and analysis, government-based regulation and cooperation within the transportation enterprise, disaster communications, systems safety, change management, and the impact of globalization.

Subjects

public transportation systems; pollution; infrastructure; government regulation; public policy; strategic planning management; labor relations; maintenance planning; administration; financing; marketing policy; fare policy; management information; decision support systems; transit industry; service provision; private sector; alternative models of decision-making; strategic planning; stakeholder valuation and analysis; government-based regulation and cooperation; transportation enterprise; disaster communications; systems safety; change management; and the impact of globalization; | public transportation systems; pollution; infrastructure; government regulation; public policy; strategic planning management; labor relations; maintenance planning; administration; financing; marketing policy; fare policy; management information; decision support systems; transit industry; service provision; private sector; alternative models of decision-making; strategic planning; stakeholder valuation and analysis; government-based regulation and cooperation; transportation enterprise; disaster communications; systems safety; change management; and the impact of globalization; | public transportation systems | public transportation systems | pollution | pollution | infrastructure | infrastructure | government regulation | government regulation | public policy | public policy | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector | alternative models of decision-making | alternative models of decision-making | strategic planning | strategic planning | stakeholder valuation and analysis | stakeholder valuation and analysis | government-based regulation and cooperation | government-based regulation and cooperation | transportation enterprise | transportation enterprise | disaster communications | disaster communications | systems safety | systems safety | change management | change management | and the impact of globalization | and the impact of globalization | the impact of globalization | the impact of globalization | 1.223 | 1.223 | ESD.203 | ESD.203

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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18.465 Topics in Statistics: Statistical Learning Theory (MIT) 18.465 Topics in Statistics: Statistical Learning Theory (MIT)

Description

The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory. The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.

Subjects

machine learning algorithms | machine learning algorithms | boosting | boosting | support | support | support vector machines | support vector machines | neural networks | neural networks | Vapnik- Chervonenkis theory | Vapnik- Chervonenkis theory | concentration inequalities in product spaces | concentration inequalities in product spaces | empirical process theory | empirical process theory

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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1.223J Transportation Policy, Strategy, and Management (MIT) 1.223J Transportation Policy, Strategy, and Management (MIT)

Description

This class surveys the current concepts, theories, and issues in strategic management of transportation organizations. It provides transportation logistics and engineering systems students with an overview of the operating context, leadership challenges, strategies, and management tools that are used in today's public and private transportation organizations. The following concepts, tools, and issues are presented in both public and private sector cases: alternative models of decision-making, strategic planning (e.g., use of SWOT analysis and scenario development), stakeholder valuation and analysis, government-based regulation and cooperation within the transportation enterprise, disaster communications, systems safety, change management, and the impact of globalization. This class surveys the current concepts, theories, and issues in strategic management of transportation organizations. It provides transportation logistics and engineering systems students with an overview of the operating context, leadership challenges, strategies, and management tools that are used in today's public and private transportation organizations. The following concepts, tools, and issues are presented in both public and private sector cases: alternative models of decision-making, strategic planning (e.g., use of SWOT analysis and scenario development), stakeholder valuation and analysis, government-based regulation and cooperation within the transportation enterprise, disaster communications, systems safety, change management, and the impact of globalization.

Subjects

public transportation systems; pollution; infrastructure; government regulation; public policy; strategic planning management; labor relations; maintenance planning; administration; financing; marketing policy; fare policy; management information; decision support systems; transit industry; service provision; private sector; alternative models of decision-making; strategic planning; stakeholder valuation and analysis; government-based regulation and cooperation; transportation enterprise; disaster communications; systems safety; change management; and the impact of globalization; | public transportation systems; pollution; infrastructure; government regulation; public policy; strategic planning management; labor relations; maintenance planning; administration; financing; marketing policy; fare policy; management information; decision support systems; transit industry; service provision; private sector; alternative models of decision-making; strategic planning; stakeholder valuation and analysis; government-based regulation and cooperation; transportation enterprise; disaster communications; systems safety; change management; and the impact of globalization; | public transportation systems | public transportation systems | pollution | pollution | infrastructure | infrastructure | government regulation | government regulation | public policy | public policy | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector | alternative models of decision-making | alternative models of decision-making | strategic planning | strategic planning | stakeholder valuation and analysis | stakeholder valuation and analysis | government-based regulation and cooperation | government-based regulation and cooperation | transportation enterprise | transportation enterprise | disaster communications | disaster communications | systems safety | systems safety | change management | change management | and the impact of globalization | and the impact of globalization | the impact of globalization | the impact of globalization | 1.223 | 1.223 | ESD.203 | ESD.203

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 https://ocw.mit.edu/terms/index.htm

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Supporting People with Down Syndrome (M-Learning)

Description

This short course covers the key points from the full Down Syndrome e-learning course, including aspects such as communication, health problems and independence. It can be used on most browser-enabled mobile devices.

Subjects

care | circle of support | circles of support | disability | down syndrome | downs | downs syndrome | support | time bank | HEALTH CARE / MEDICINE / HEALTH and SAFETY | P

License

Attribution-Noncommercial-No Derivative Works 2.0 UK: England & Wales Attribution-Noncommercial-No Derivative Works 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-nd/2.0/uk/ http://creativecommons.org/licenses/by-nc-nd/2.0/uk/

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Open for Business (O4B) - Supporting students: a learning resource for new lecturers

Description

Welcome to this OER which aims to support new lecturers in HE improve their practice in managing students' learning. These resources have been created in alignment with the UK Professional Standards Framework and can be used toward professional recognition against that Framework

Subjects

supporting students | sol:010611:01ofb | student support | module/unit lead | inclusion | learning environments | new lecturers | academic support | assessment | teaching portfolio | ukoer | ukpsf | omac | hea | jisc | open for business | o4b | solent | southampton solent university | Education | X000

License

Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales Attribution-Noncommercial-Share Alike 2.0 UK: England & Wales http://creativecommons.org/licenses/by-nc-sa/2.0/uk/ http://creativecommons.org/licenses/by-nc-sa/2.0/uk/

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HST.184 Health Information Systems to Improve Quality of Care in Resource-Poor Settings (MIT) HST.184 Health Information Systems to Improve Quality of Care in Resource-Poor Settings (MIT)

Description

This course is a collaborative offering of Sana, Partners in Health, and the Institute for Healthcare Improvement (IHI). The goal of this course is the development of innovations in information systems for developing countries that will (1) translate into improvement in health outcomes, (2) strengthen the existing organizational infrastructure, and (3) create a collaborative ecosystem to maximize the value of these innovations. The course will be taught by guest speakers who are internationally recognized experts in the field and who, with their operational experiences, will outline the challenges they faced and detail how these were addressed. This course is a collaborative offering of Sana, Partners in Health, and the Institute for Healthcare Improvement (IHI). The goal of this course is the development of innovations in information systems for developing countries that will (1) translate into improvement in health outcomes, (2) strengthen the existing organizational infrastructure, and (3) create a collaborative ecosystem to maximize the value of these innovations. The course will be taught by guest speakers who are internationally recognized experts in the field and who, with their operational experiences, will outline the challenges they faced and detail how these were addressed.

Subjects

health informatics | health informatics | clinical decision support | clinical decision support | health care management | health care management | public health | public health | international development | international development | developing country | developing country

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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16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

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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HST.921 Information Technology in the Health Care System of the Future (MIT) HST.921 Information Technology in the Health Care System of the Future (MIT)

Description

This course will show how information technologies (IT) shape and redefine the health care marketplace. Students will learn how IT enhances medical care through: 1) improved economies of scale, 2) greater technical efficiencies in the delivery of care, 3) advanced tools for patient education and self-care, 4) network-integrated decision support tools for clinicians, and 5) opportunities for e-health delivery over the internet. Students will work in interdisciplinary teams to design an innovative solution to a current or future health care problem. Students' proposed solutions will draw upon understanding of tools and principles acquired and will be presented as an application design during the final days of the course. Adjunct Faculty Mirena Bagur Sherri Dorfman Paul Heinzelman Gary H This course will show how information technologies (IT) shape and redefine the health care marketplace. Students will learn how IT enhances medical care through: 1) improved economies of scale, 2) greater technical efficiencies in the delivery of care, 3) advanced tools for patient education and self-care, 4) network-integrated decision support tools for clinicians, and 5) opportunities for e-health delivery over the internet. Students will work in interdisciplinary teams to design an innovative solution to a current or future health care problem. Students' proposed solutions will draw upon understanding of tools and principles acquired and will be presented as an application design during the final days of the course. Adjunct Faculty Mirena Bagur Sherri Dorfman Paul Heinzelman Gary H

Subjects

information technology | information technology | health care system | health care system | economy of scale | economy of scale | technical efficiency | technical efficiency | patient education | patient education | self-care | self-care | network integration | network integration | decision support tool | decision support tool | internet | internet | web | web | disease managment | disease managment | health economics | health economics | clinical effectiveness | clinical effectiveness | trials design | trials design | software | software

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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20.453J Biomedical Information Technology (BE.453J) (MIT) 20.453J Biomedical Information Technology (BE.453J) (MIT)

Description

The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java®, Lisp, Perl, Python, etc.). A major term project is The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java®, Lisp, Perl, Python, etc.). A major term project is

Subjects

imaging | imaging | medical imaging | medical imaging | metadata | metadata | medical record | medical record | DICOM | DICOM | computer architecture | computer architecture | client-server architecture | client-server architecture | SEM | SEM | TEM | TEM | OME | OME | RDF | RDF | semantic web | semantic web | BioHaystack | BioHaystack | database | database | schema | schema | ExperiBase | ExperiBase | genomics | genomics | proteomics | proteomics | bioinformatics | bioinformatics | clinical decision support | clinical decision support | microarray | microarray | gel electrophoresis | gel electrophoresis | diagnosis | diagnosis | 20.453 | 20.453 | 2.771 | 2.771 | HST.958 | HST.958

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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6.867 Machine Learning (MIT) 6.867 Machine Learning (MIT)

Description

6.867 is an introductory course on machine learning which provides an overview of many techniques and algorithms in machine learning, beginning with topics such as simple perceptrons and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course gives the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how and why they work. The underlying theme in the course is statistical inference as this provides the foundation for most of the methods covered.  6.867 is an introductory course on machine learning which provides an overview of many techniques and algorithms in machine learning, beginning with topics such as simple perceptrons and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course gives the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how and why they work. The underlying theme in the course is statistical inference as this provides the foundation for most of the methods covered. 

Subjects

machine learning | machine learning | perceptrons | perceptrons | boosting | boosting | support vector machines | support vector machines | Markov | Markov | hidden Markov models | hidden Markov models | HMM | HMM | Bayesian networks | Bayesian networks | statistical inference | statistical inference | regression | regression | clustering | clustering | bias | bias | variance | variance | regularization | regularization | Generalized Linear Models | Generalized Linear Models | neural networks | neural networks | Support Vector Machine | Support Vector Machine | SVM | SVM | mixture models | mixture models | kernel density estimation | kernel density estimation | gradient descent | gradient descent | quadratic programming | quadratic programming | EM algorithm | EM algorithm | orward-backward algorithm | orward-backward algorithm | junction tree algorithm | junction tree algorithm | Gibbs sampling | Gibbs sampling

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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HST.921 Information Technology in the Health Care System of the Future (MIT) HST.921 Information Technology in the Health Care System of the Future (MIT)

Description

The healthcare system in the US has been in the midst of a rapid transition in response to changing trends and patterns of care. The growing emphasis on evidence-based medical practice, continuous quality improvement, clinical and cost-effectiveness, and risk management have led to a sea change in medical practice that has been stressful for clinicians, patients, and administrators. As care becomes more tightly managed, it becomes a challenge for clinicians, administrators, and patients to balance time, money, resources, and clinical outcomes. Can emerging technologies help solve these complex problems? How has the demise of the dot.com industry effected these trends and slowed the proliferation of potential solutions?This innovative, trans-faculty course will teach the student how informa The healthcare system in the US has been in the midst of a rapid transition in response to changing trends and patterns of care. The growing emphasis on evidence-based medical practice, continuous quality improvement, clinical and cost-effectiveness, and risk management have led to a sea change in medical practice that has been stressful for clinicians, patients, and administrators. As care becomes more tightly managed, it becomes a challenge for clinicians, administrators, and patients to balance time, money, resources, and clinical outcomes. Can emerging technologies help solve these complex problems? How has the demise of the dot.com industry effected these trends and slowed the proliferation of potential solutions?This innovative, trans-faculty course will teach the student how informa

Subjects

information technology | information technology | health care system | health care system | economy of scale | economy of scale | technical efficiency | technical efficiency | patient education | patient education | self-care | self-care | network integration | network integration | decision support tool | decision support tool | internet | internet | web | web | disease managment | disease managment | health economics | health economics | clinical effectiveness | clinical effectiveness | trials design | trials design | software | software

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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1.259J Transit Management (MIT) 1.259J Transit Management (MIT)

Description

This course discusses management methods of relevance to public transportation systems. Topics include: Strategic Planning Management, Labor Relations, Maintenance Planning and Administration, Financing, Marketing and Fare Policy, and Management Information and Decision Support Systems. The course shows how these general management tasks are dealt with in the transit industry and presents alternative strategies. It also identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation. This course discusses management methods of relevance to public transportation systems. Topics include: Strategic Planning Management, Labor Relations, Maintenance Planning and Administration, Financing, Marketing and Fare Policy, and Management Information and Decision Support Systems. The course shows how these general management tasks are dealt with in the transit industry and presents alternative strategies. It also identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation.

Subjects

public transportation systems | public transportation systems | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector | 1.259 | 1.259 | 11.542 | 11.542 | ESD.227 | ESD.227

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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IV (MIT) IV (MIT)

Description

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 files 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 files

Subjects

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

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16.410 Principles of Autonomy and Decision Making (MIT) 16.410 Principles of Autonomy and Decision Making (MIT)

Description

This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information This course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information

Subjects

autonomy | autonomy | decision | decision | decision-making | decision-making | reasoning | reasoning | optimization | optimization | autonomous | autonomous | autonomous systems | autonomous systems | decision support | decision support | algorithms | algorithms | artificial intelligence | artificial intelligence | a.i. | a.i. | operations | operations | operations research | operations research | logic | logic | deduction | deduction | heuristic search | heuristic search | constraint-based search | constraint-based search | model-based reasoning | model-based reasoning | planning | planning | execution | execution | uncertainty | uncertainty | machine learning | machine learning | linear programming | linear programming | dynamic programming | dynamic programming | integer programming | integer programming | network optimization | network optimization | decision analysis | decision analysis | decision theoretic planning | decision theoretic planning | Markov decision process | Markov decision process | scheme | scheme | propositional logic | propositional logic | constraints | constraints | Markov processes | Markov processes | computational performance | computational performance | satisfaction | satisfaction | learning algorithms | learning algorithms | system state | system state | state | state | search treees | search treees | plan spaces | plan spaces | model theory | model theory | decision trees | decision trees | function approximators | function approximators | optimization algorithms | optimization algorithms | limitations | limitations | tradeoffs | tradeoffs | search and reasoning | search and reasoning | game tree search | game tree search | local stochastic search | local stochastic search | stochastic | stochastic | genetic algorithms | genetic algorithms | constraint satisfaction | constraint satisfaction | propositional inference | propositional inference | rule-based systems | rule-based systems | rule-based | rule-based | model-based diagnosis | model-based diagnosis | neural nets | neural nets | reinforcement learning | reinforcement learning | web-based | web-based | search trees | search trees

License

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BE.453J Biomedical Information Technology (MIT) BE.453J Biomedical Information Technology (MIT)

Description

The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java®, Lisp, Perl, Python, etc.). A major term project is The objective of this subject is to teach the design of contemporary information systems for biological and medical data. These data are growing at a prodigious rate, and new information systems are required. This subject will cover examples from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures will be covered. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (C, C++, Java®, Lisp, Perl, Python, etc.). A major term project is

Subjects

imaging | imaging | medical imaging | medical imaging | metadata | metadata | medical record | medical record | DICOM | DICOM | computer architecture | computer architecture | client-server architecture | client-server architecture | SEM | SEM | TEM | TEM | OME | OME | RDF | RDF | semantic web | semantic web | BioHaystack | BioHaystack | database | database | schema | schema | ExperiBase | ExperiBase | genomics | genomics | proteomics | proteomics | bioinformatics | bioinformatics | clinical decision support | clinical decision support | microarray | microarray | gel electrophoresis | gel electrophoresis | diagnosis | diagnosis | 2.771J | 2.771J | 2.771 | 2.771 | HST.958J | HST.958J | HST.958 | HST.958

License

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1.050 Solid Mechanics (MIT) 1.050 Solid Mechanics (MIT)

Description

This course introduces students to the fundamental principles and methods of structural mechanics. Topics covered include: static equilibrium, force resultants, support conditions, analysis of determinate planar structures (beams, trusses, frames), stresses and strains in structural elements, states of stress (shear, bending, torsion), statically indeterminate systems, displacements and deformations, introduction to matrix methods, elastic stability, and approximate methods. Design exercises are used to encourage creative student initiative and systems thinking.Technical RequirementsJava® Virtual Machine software (automatically installed in most major web browsers) is required to run the .class files found on this course site. Java® plug-in software is required to run the This course introduces students to the fundamental principles and methods of structural mechanics. Topics covered include: static equilibrium, force resultants, support conditions, analysis of determinate planar structures (beams, trusses, frames), stresses and strains in structural elements, states of stress (shear, bending, torsion), statically indeterminate systems, displacements and deformations, introduction to matrix methods, elastic stability, and approximate methods. Design exercises are used to encourage creative student initiative and systems thinking.Technical RequirementsJava® Virtual Machine software (automatically installed in most major web browsers) is required to run the .class files found on this course site. Java® plug-in software is required to run the

Subjects

elastic stability | elastic stability | matrix methods | matrix methods | statically indeterminate systems | statically indeterminate systems | torsion | torsion | bending | bending | shearing | shearing | strains in structural elements | strains in structural elements | stress | stress | beams | beams | frames | frames | determinate planar structures | determinate planar structures | support conditions | support conditions | static equilibrium | static equilibrium

License

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11.437 Financing Economic Development (MIT) 11.437 Financing Economic Development (MIT)

Description

This course focuses on financing tools and program models to support local economic development. It includes an overview of private capital markets and financing sources to understand capital market imperfections that constrain economic development; business accounting; financial statement analysis; federal economic development programs; and public finance tools. Program models covered include revolving loan funds, guarantee programs, venture capital funds, bank holding companies, community development loan funds and credit unions, micro enterprise funds, and the use of the Community Reinvestment Act to leverage bank financing.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls files found on this course site. Free Microsoft® Excel This course focuses on financing tools and program models to support local economic development. It includes an overview of private capital markets and financing sources to understand capital market imperfections that constrain economic development; business accounting; financial statement analysis; federal economic development programs; and public finance tools. Program models covered include revolving loan funds, guarantee programs, venture capital funds, bank holding companies, community development loan funds and credit unions, micro enterprise funds, and the use of the Community Reinvestment Act to leverage bank financing.Technical RequirementsMicrosoft® Excel software is recommended for viewing the .xls files found on this course site. Free Microsoft® Excel

Subjects

financing tools | financing tools | program models to support local economic development | program models to support local economic development | private capital markets | private capital markets | financing sources | financing sources | capital market imperfections | capital market imperfections | economic development | economic development | business accounting | business accounting | financial statement analysis | financial statement analysis | federal economic development programs | federal economic development programs | public finance tools | public finance tools | funds | funds | guarantee programs | guarantee programs | venture capital funds | venture capital funds | bank holding companies | bank holding companies | community development loan funds | community development loan funds | credit unions | credit unions | micro enterprise funds | micro enterprise funds | use of the Community Reinvestment Act to leverage bank financing | use of the Community Reinvestment Act to leverage bank financing | Community Reinvestment Act | Community Reinvestment Act | bank financing | bank financing | program management | program management

License

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1.259J Transit Management (MIT) 1.259J Transit Management (MIT)

Description

1.259J discusses management methods of relevance to public transportation systems. Topics include: strategic planning management; labor relations; maintenance planning and administration; financing; marketing and fare policy; and management information and decision support systems. The course focuses on how these general management tasks are addressed in the transit industry and presents alternative strategies. It identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation. 1.259J discusses management methods of relevance to public transportation systems. Topics include: strategic planning management; labor relations; maintenance planning and administration; financing; marketing and fare policy; and management information and decision support systems. The course focuses on how these general management tasks are addressed in the transit industry and presents alternative strategies. It identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation.

Subjects

public transportation systems | public transportation systems | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector | management methods | management methods | urban public transportation systems | urban public transportation systems | maintenance administration | maintenance administration | public transport service organizations | public transport service organizations | privatization | privatization | deregulation | deregulation | performance assessment | performance assessment | budgeting | budgeting | pricing | pricing | budgets | budgets | workforce planning | workforce planning | workforce management | workforce management | 1.259 | 1.259 | 11.542 | 11.542 | ESD.227 | ESD.227

License

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HST.921 Information Technology in the Health Care System of the Future (MIT) HST.921 Information Technology in the Health Care System of the Future (MIT)

Description

Includes audio/video content: AV faculty introductions. This innovative, trans-faculty subject teaches how information technologies (IT) are reshaping and redefining the health care marketplace through improved economies of scale, greater technical efficiencies in the delivery of care to patients, advanced tools for patient education and self-care, network integrated decision support tools for clinicians, and the emergence of e-commerce in health care. Student tutorials provide an opportunity for interactive discussion. Interdisciplinary project teams comprised of Harvard and MIT graduate students in medicine, business, law, education, engineering, computer science, public health, and government collaborate to design innovative IT applications. Projects are presented during the final class Includes audio/video content: AV faculty introductions. This innovative, trans-faculty subject teaches how information technologies (IT) are reshaping and redefining the health care marketplace through improved economies of scale, greater technical efficiencies in the delivery of care to patients, advanced tools for patient education and self-care, network integrated decision support tools for clinicians, and the emergence of e-commerce in health care. Student tutorials provide an opportunity for interactive discussion. Interdisciplinary project teams comprised of Harvard and MIT graduate students in medicine, business, law, education, engineering, computer science, public health, and government collaborate to design innovative IT applications. Projects are presented during the final class

Subjects

health care | health care | health care policy | health care policy | patient behavior | patient behavior | information management | information management | medical informatics | medical informatics | medical records | medical records | health record | health record | online medicine | online medicine | PHR | PHR | EHR | EHR | patient privacy | patient privacy | entrepreneurship | entrepreneurship | start-up | start-up | innovation | innovation | cybermedicine | cybermedicine | telemedicine | telemedicine | non-profit | non-profit | pharmaceutical | pharmaceutical | insurance | insurance | hospital | hospital | doctor | doctor | patient | patient | medicine | medicine | social networking | social networking | economies of scale | economies of scale | patient education | patient education | self-care | self-care | network integration | network integration | decision support tools | decision support tools | disease managment | disease managment | health economics | health economics | clinical effectiveness | clinical effectiveness | medical software | medical software | mobile applications | mobile applications | intellectual property | intellectual property

License

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IV (MIT) IV (MIT)

Description

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

License

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1.050 Solid Mechanics (MIT) 1.050 Solid Mechanics (MIT)

Description

Includes audio/video content: AV faculty introductions. 1.050 is a sophomore-level engineering mechanics course, commonly labelled "Statics and Strength of Materials" or "Solid Mechanics I." This course introduces students to the fundamental principles and methods of structural mechanics. Topics covered include: static equilibrium, force resultants, support conditions, analysis of determinate planar structures (beams, trusses, frames), stresses and strains in structural elements, states of stress (shear, bending, torsion), statically indeterminate systems, displacements and deformations, introduction to matrix methods, elastic stability, and approximate methods. Design exercises are used to encourage creative student initiative and systems thinking. Includes audio/video content: AV faculty introductions. 1.050 is a sophomore-level engineering mechanics course, commonly labelled "Statics and Strength of Materials" or "Solid Mechanics I." This course introduces students to the fundamental principles and methods of structural mechanics. Topics covered include: static equilibrium, force resultants, support conditions, analysis of determinate planar structures (beams, trusses, frames), stresses and strains in structural elements, states of stress (shear, bending, torsion), statically indeterminate systems, displacements and deformations, introduction to matrix methods, elastic stability, and approximate methods. Design exercises are used to encourage creative student initiative and systems thinking.

Subjects

solid mechanics | solid mechanics | engineering design | engineering design | open ended exercises | open ended exercises | matrix analysis of structures | matrix analysis of structures | structural mechanics | structural mechanics | static equilibrium | static equilibrium | force resultants | force resultants | support conditions | support conditions | determinate planar structures | determinate planar structures | beams | beams | trusses | trusses | frames | frames | stress | stress | strain | strain | shear | shear | bending | bending | torsion | torsion | matrix methods | matrix methods | elastic stability | elastic stability | design exercises | design exercises | interactive exercises | interactive exercises | systems thinking | systems thinking

License

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1.259J Transit Management (MIT) 1.259J Transit Management (MIT)

Description

This course discusses management methods of relevance to public transportation systems. Topics include strategic planning management, labor relations, maintenance planning and administration, financing, marketing and fare policy, and management information and decision support systems. The course shows how these general management tasks are dealt with in the transit industry and presents alternative strategies. It also identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation. This course discusses management methods of relevance to public transportation systems. Topics include strategic planning management, labor relations, maintenance planning and administration, financing, marketing and fare policy, and management information and decision support systems. The course shows how these general management tasks are dealt with in the transit industry and presents alternative strategies. It also identifies alternative arrangements for service provision, including different ways of involving the private sector in public transportation.

Subjects

1.259 | 1.259 | 11.542 | 11.542 | ESD.227 | ESD.227 | public transportation systems | public transportation systems | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector

License

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1.253J Transportation Policy and Environmental Limits (MIT) 1.253J Transportation Policy and Environmental Limits (MIT)

Description

Through a combination of lectures, cases, and class discussions this subject examines the economic and political conflict between transportation and the environment. It investigates the role of government regulation, green business and transportation policy as facilitators of economic development and environmental sustainability. It analyzes a variety of international policy problems including government-business relations; the role of interest groups, non-governmental organizations, and the public and media in the regulation of the automobile; sustainable development; global warming; the politics of risk and siting of transport facilities; environmental justice; equity; and transportation and public health in the urban metropolis. It provides students with an opportunity to apply transpor Through a combination of lectures, cases, and class discussions this subject examines the economic and political conflict between transportation and the environment. It investigates the role of government regulation, green business and transportation policy as facilitators of economic development and environmental sustainability. It analyzes a variety of international policy problems including government-business relations; the role of interest groups, non-governmental organizations, and the public and media in the regulation of the automobile; sustainable development; global warming; the politics of risk and siting of transport facilities; environmental justice; equity; and transportation and public health in the urban metropolis. It provides students with an opportunity to apply transpor

Subjects

public transportation systems | public transportation systems | pollution | pollution | infrastructure | infrastructure | government regulation | government regulation | public policy | public policy | strategic planning management | strategic planning management | labor relations | labor relations | maintenance planning | maintenance planning | administration | administration | financing | financing | marketing policy | marketing policy | fare policy | fare policy | management information | management information | decision support systems | decision support systems | transit industry | transit industry | service provision | service provision | private sector | private sector | 1.253 | 1.253 | 11.543 | 11.543 | ESD.222 | ESD.222

License

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1.364 Advanced Geotechnical Engineering (MIT) 1.364 Advanced Geotechnical Engineering (MIT)

Description

1.364 examines site characterization and geotechnical aspects of the design and construction of foundation systems. Topics include: site investigation (with emphasis on in situ testing), shallow (footings and raftings) and deep (piles and caissons) foundations, excavation support systems, groundwater control, slope stability, soil improvement (compaction, soil reinforcement, etc.), and construction monitoring. This course is a core requirement for the Geotechnical Master of Engineering program at MIT. 1.364 examines site characterization and geotechnical aspects of the design and construction of foundation systems. Topics include: site investigation (with emphasis on in situ testing), shallow (footings and raftings) and deep (piles and caissons) foundations, excavation support systems, groundwater control, slope stability, soil improvement (compaction, soil reinforcement, etc.), and construction monitoring. This course is a core requirement for the Geotechnical Master of Engineering program at MIT.

Subjects

geotechnical engineering | geotechnical engineering | soil | soil | soil mechanics | soil mechanics | foundations | foundations | earth retaining structures | earth retaining structures | site investigation | site investigation | ultimate limit | ultimate limit | serviceability limit | serviceability limit | soil improvement | soil improvement | gravity walls | gravity walls | composite construction | composite construction | reinforced earth | reinforced earth | structural support | structural support | excavations | excavations | bracing | bracing | tieback anchors | tieback anchors | tiebacks | tiebacks | safety factors | safety factors | boreholes | boreholes | soil sampling | soil sampling | stratigraphy | stratigraphy | SPT | SPT | FV | FV | PCPT | PCPT | spread foundation design | spread foundation design | in situ tests | in situ tests | bearing capacity | bearing capacity | strength parameters | strength parameters | allowable settlements | allowable settlements | sand | sand | clay | clay | soil-structure interaction | soil-structure interaction | pile types | pile types | pile selection | pile selection | pile behavior | pile behavior | pile capacity | pile capacity | pile driving | pile driving | pile load tests | pile load tests | slope stability | slope stability | cantilevers | cantilevers | propper walls | propper walls | braced excavations | braced excavations | reinforced soil | reinforced soil | soil nailing | soil nailing | geosynthetic reinforcement | geosynthetic reinforcement

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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