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Description

This course develops logical, empirically based arguments using statistical techniques and analytic methods. It covers elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation. Emphasis is placed on the use and limitations of analytical techniques in planning practice. This course is required for and restricted to first-year Master in City Planning students. This course develops logical, empirically based arguments using statistical techniques and analytic methods. It covers elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation. Emphasis is placed on the use and limitations of analytical techniques in planning practice. This course is required for and restricted to first-year Master in City Planning students.Subjects

statistics | statistics | statistical methods | statistical methods | quantitative research | quantitative research | argument | argument | measurement | measurement | research design | research design | frequency distribution | frequency distribution | histogram | histogram | stemplot | stemplot | boxplot | boxplot | dispersion | dispersion | probability | probability | normal distribution | normal distribution | binomial distribution | binomial distribution | sampling | sampling | confidence interval | confidence interval | significance | significance | correlation | correlation | regression | regressionLicense

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

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See all metadata6.094 Introduction to MATLAB (MIT) 6.094 Introduction to MATLAB (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with students doing sample MATLAB problems in real time. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. Acknowledgements The 6.094 course materials were developed by Danilo Šćepanović, Sourav R. Dey, Ankit Patel, and Patrick Ho. This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with students doing sample MATLAB problems in real time. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. Acknowledgements The 6.094 course materials were developed by Danilo Šćepanović, Sourav R. Dey, Ankit Patel, and Patrick Ho.Subjects

introduction to MATLAB | introduction to MATLAB | scripts | scripts | making variables | making variables | manipulating variables | manipulating variables | functions | functions | flow control | flow control | line plots | line plots | surface plots | surface plots | vectorization | vectorization | linear algebra | linear algebra | optimization | optimization | differential equations | differential equations | data structures | data structures | debugging | debugging | animation | animation | symbolic math | symbolic math | Simulink | Simulink | file input/output | file input/output | graphical user interfaces | graphical user interfacesLicense

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

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This course develops the fundamentals of feedback control using linear transfer function system models. Topics covered include analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and use of z-plane design. Students will complete an extended design case study. Students taking the graduate version (2.140) will attend the recitation sessions and complete additional assignments. This course develops the fundamentals of feedback control using linear transfer function system models. Topics covered include analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and use of z-plane design. Students will complete an extended design case study. Students taking the graduate version (2.140) will attend the recitation sessions and complete additional assignments.Subjects

feedback loops | feedback loops | control systems | control systems | compensation | compensation | Bode plots | Bode plots | Nyquist plots | Nyquist plots | state space | state space | frequency domain | frequency domain | time domain | time domain | transfer functions | transfer functions | Laplace transform | Laplace transform | root locus | root locus | op-amps | op-amps | gears | gears | motors | motors | actuators | actuators | nonlinear systems | nonlinear systems | stability theory | stability theory | dynamic feedback | dynamic feedback | mechanical engineering problem archive | mechanical engineering problem archiveLicense

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

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This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments. This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments.Subjects

feedback loops | feedback loops | compensation | compensation | Bode plots | Bode plots | Nyquist plots | Nyquist plots | state space | state space | frequency domain | frequency domain | time domain | time domain | transfer functions | transfer functions | Laplace transform | Laplace transform | root locus | root locus | op-amps | op-amps | gears | gears | motors | motors | actuators | actuators | nonlinear systems | nonlinear systems | stability theory | stability theory | control systems | control systems | dynamic feedback | dynamic feedback | mechanical engineering problem archive | mechanical engineering problem archiveLicense

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

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See all metadata2.004 Dynamics and Control II (MIT) 2.004 Dynamics and Control II (MIT)

Description

Upon successful completion of this course, students will be able to: Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains Make quantitative estimates of model parameters from experimental measurements Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods Obtain the frequency-domain response of linear systems to sinusoidal inputs Compensate the transient response of dynamic systems using feedback techniques Design, implement and test an active control system to achieve a desired performance measure Mastery of these topics will be assessed via homework, quizzes/exams, and lab assig Upon successful completion of this course, students will be able to: Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains Make quantitative estimates of model parameters from experimental measurements Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods Obtain the frequency-domain response of linear systems to sinusoidal inputs Compensate the transient response of dynamic systems using feedback techniques Design, implement and test an active control system to achieve a desired performance measure Mastery of these topics will be assessed via homework, quizzes/exams, and lab assigSubjects

Laplace transform | Laplace transform | transform function | transform function | electrical and mechanical systems | electrical and mechanical systems | pole-zero diagram | pole-zero diagram | linearization | linearization | block diagrams | block diagrams | feedback control systems | feedback control systems | stability | stability | root-locus plot | root-locus plot | compensation | compensation | Bode plot | Bode plot | state space representation | state space representation | minimum time | minimum timeLicense

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

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See all metadata2.004 Systems, Modeling, and Control II (MIT) 2.004 Systems, Modeling, and Control II (MIT)

Description

Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments. Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments.Subjects

Laplace transform | Laplace transform | transform function | transform function | electrical and mechanical systems | electrical and mechanical systems | pole-zero diagram | pole-zero diagram | linearization | linearization | block diagrams | block diagrams | feedback control systems | feedback control systems | stability | stability | root-locus plot | root-locus plot | compensation | compensation | Bode plot | Bode plot | state space representation | state space representation | minimum time | minimum timeLicense

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

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See all metadata16.31 Feedback Control Systems (MIT) 16.31 Feedback Control Systems (MIT)

Description

This course covers the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, the student should be able to design controllers using state-space methods and evaluate whether these controllers are robust. This course covers the fundamentals of control design and analysis using state-space methods. This includes both the practical and theoretical aspects of the topic. By the end of the course, the student should be able to design controllers using state-space methods and evaluate whether these controllers are robust.Subjects

linear system response | linear system response | aircraft control | aircraft control | frequency response methods | frequency response methods | Nyquist stability theorem | Nyquist stability theorem | bode plots | bode plots | state-space systems | state-space systems | full-state feedback control | full-state feedback control | open-loop estimators | open-loop estimators | closed-loop estimators | closed-loop estimators | robustness analysis | robustness analysis | small gain theorem | small gain theoremLicense

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

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See all metadata6.094 Introduction to MATLAB (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with students doing sample MATLAB problems in real time. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. Acknowledgements The 6.094 course materials were developed by Danilo ??epanovi?, Sourav R. Dey, Ankit Patel, and Patrick Ho.Subjects

introduction to MATLAB | scripts | making variables | manipulating variables | functions | flow control | line plots | surface plots | vectorization | linear algebra | optimization | differential equations | data structures | debugging | animation | symbolic math | Simulink | file input/output | graphical user interfacesLicense

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

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See all metadata16.06 Principles of Automatic Control (MIT) 16.06 Principles of Automatic Control (MIT)

Description

This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods. This course introduces the design of feedback control systems as applied to a variety of air and spacecraft systems. Topics include the properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability, the Root locus method, Nyquist criterion, frequency-domain design, and state space methods.Subjects

classical control systems | classical control systems | feedback control systems | feedback control systems | bode plots | bode plots | time-domain and frequency-domain performance measures | time-domain and frequency-domain performance measures | stability | stability | root locus method | root locus method | nyquist criterion | nyquist criterion | frequency-domain design | frequency-domain design | state space methods | state space methodsLicense

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

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This course focuses on the design of control systems. Topics covered include: frequency domain and state space techniques; control law design using Nyquist diagrams and Bode plots; state feedback, state estimation, and the design of dynamic control laws; and elementary analysis of nonlinearities and their impact on control design. There is extensive use of computer-aided control design tools. Applications to various aerospace systems, including navigation, guidance, and control of vehicles, are also discussed. This course focuses on the design of control systems. Topics covered include: frequency domain and state space techniques; control law design using Nyquist diagrams and Bode plots; state feedback, state estimation, and the design of dynamic control laws; and elementary analysis of nonlinearities and their impact on control design. There is extensive use of computer-aided control design tools. Applications to various aerospace systems, including navigation, guidance, and control of vehicles, are also discussed.Subjects

estimation of aerospace systems | estimation of aerospace systems | control of aerospace systems | control of aerospace systems | control systems | control systems | frequency domain | frequency domain | state space | state space | control law design | control law design | Nyquist diagram | Nyquist diagram | Bode plot | Bode plot | state feedback | state feedback | state estimation | state estimation | dynamic control | dynamic control | nonlinearities | nonlinearities | nonlinearity | nonlinearity | control design | control design | computer-aided control design | computer-aided control design | feedback control system | feedback control systemLicense

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

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See all metadata2.004 Dynamics and Control II (MIT)

Description

Upon successful completion of this course, students will be able to: Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domains Make quantitative estimates of model parameters from experimental measurements Obtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methods Obtain the frequency-domain response of linear systems to sinusoidal inputs Compensate the transient response of dynamic systems using feedback techniques Design, implement and test an active control system to achieve a desired performance measure Mastery of these topics will be assessed via homework, quizzes/exams, and lab assigSubjects

Laplace transform | transform function | electrical and mechanical systems | pole-zero diagram | linearization | block diagrams | feedback control systems | stability | root-locus plot | compensation | Bode plot | state space representation | minimum timeLicense

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

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See all metadata2.004 Systems, Modeling, and Control II (MIT)

Description

Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments.Subjects

Laplace transform | transform function | electrical and mechanical systems | pole-zero diagram | linearization | block diagrams | feedback control systems | stability | root-locus plot | compensation | Bode plot | state space representation | minimum timeLicense

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

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Subjects

germany | wwi | worldwari | worldwarone | greatwar | cartoons | worldwar1 | worldwar19141918 | thedallasmorningnews | mexicanplot | plotwithvilla | prussiaduchyLicense

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This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor C This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor CSubjects

energetics | energetics | visualization | visualization | graph | graph | plot | plot | chart | chart | materials science | materials science | DMSE | DMSE | structure | structure | symmetry | symmetry | mechanics | mechanics | physicss | physicss | solids and soft materials | solids and soft materials | linear algebra | linear algebra | orthonormal basis | orthonormal basis | eigenvalue | eigenvalue | eigenvector | eigenvector | quadratic form | quadratic form | tensor operation | tensor operation | symmetry operation | symmetry operation | calculus | calculus | complex analysis | complex analysis | differential equations | differential equations | ODE | ODE | solution | solution | vector | vector | matrix | matrix | determinant | determinant | theory of distributions | theory of distributions | fourier analysis | fourier analysis | random walk | random walk | Mathematica | Mathematica | simulation | simulationLicense

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

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Interpreting data: graphs and charts 1Subjects

stem and leaf plots | ukoer | lfwoer | learning from woerk | uopcpdrm | continuous professional development | cpd | work-based learning | wbl | box and whisker plots | Social studies | L000License

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/Site sourced from

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See all metadata6.0002 Introduction to Computational Thinking and Data Science (MIT)

Description

6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.Subjects

Python 3.5 | Python | machine learning | knapsack problem | greedy algorithm | optimization | weights | models | computational thinking | data science | dynamic programming | recursion | exponential time | stochastic | random | probability | independent variables | dependent variables | monte carlo simulation | simulation | population sampling | law of large numbers | variance | confidence interval | empirical rule | standard deviation | central limit theorem | bias | error distribution | sampling | error bars | numpy | scipy | matplotlib | pylab | python | plotting | graphing | supervised learning | computer modelling | signal-to-noise | feature vectors | classification model | regression model | classification | classifier | nearest neighbors | feature scaling | decision trees | entropy | training data | clustering | cluster analysis | unsupervised learning | objective function | dendogram | statistical fallacy | systematic errors | correlation and causation | misleading statistics | GIGO | axis truncating | extrapolation | data enhancement | Texas Sharpshooter FallacyLicense

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

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See all metadataTermodinámica Química II Termodinámica Química II

Description

Desarrollar y aplicar recursos de la termodinámica a cuestiones de interés tecnológico en general. Aplicar la termodinámica a la resolución de cuestiones de termoquímica. Aplicar la termodinámica al análisis del equilibrio químico. Aplicar la termodinámica a la teoría de las disoluciones. Aplicar la termodinámica a los sistemas ternarios. Aplicar la termodinámica a los equilibrios iónicos y las pilas galvánicas. Desarrollar y aplicar recursos de la termodinámica a cuestiones de interés tecnológico en general. Aplicar la termodinámica a la resolución de cuestiones de termoquímica. Aplicar la termodinámica al análisis del equilibrio químico. Aplicar la termodinámica a la teoría de las disoluciones. Aplicar la termodinámica a los sistemas ternarios. Aplicar la termodinámica a los equilibrios iónicos y las pilas galvánicas.Subjects

sistemas abiertos | sistemas abiertos | Explotación de Minas | Explotación de Minas | equilibrio químico | equilibrio químico | diagramas termodinámicos | diagramas termodinámicos | sistemas ternarios | sistemas ternarios | disoluciones | disoluciones | electroquímica | electroquímica | procesos electroquímicos | procesos electroquímicos | Termodinámica química | Termodinámica química | estabilidad del equilibrio | estabilidad del equilibrioLicense

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See all metadataTermodinámica Química I Termodinámica Química I

Description

Aplicar los conceptos y principios básicos de la termodinámica a cuestiones de interés tecnológico en general. Aplicar la termodinámica a la resolución de cuestiones de termoquímica. Aplicar la termodinámica al análisis del equilibrio en general. Aplicar la termodinámica a los equilibrios heterogéneos y, en particular, a los cuerpos puros y los sistemas binarios. Aplicar los conceptos y principios básicos de la termodinámica a cuestiones de interés tecnológico en general. Aplicar la termodinámica a la resolución de cuestiones de termoquímica. Aplicar la termodinámica al análisis del equilibrio en general. Aplicar la termodinámica a los equilibrios heterogéneos y, en particular, a los cuerpos puros y los sistemas binarios.Subjects

termoquímica | termoquímica | equilibrio y espontaneidad | equilibrio y espontaneidad | Explotación de Minas | Explotación de Minas | equilibrios heterogéneos | equilibrios heterogéneos | Termodinámica química | Termodinámica química | diagramas de fases | diagramas de fases | principios de la termodinámica | principios de la termodinámicaLicense

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Aplicar la mecánica estadística a la determinación de propiedades termodinámicas. Realizar el estudio de las interfases y los sistemas dispersos y sus aplicaciones. Desarrollar y aplicar los conceptos y recursos de la cinética química. Realizar el estudio de los fenómenos electrolíticos y aplicarlos a procesos industriales y de corrosión. Aplicar la mecánica estadística a la determinación de propiedades termodinámicas. Realizar el estudio de las interfases y los sistemas dispersos y sus aplicaciones. Desarrollar y aplicar los conceptos y recursos de la cinética química. Realizar el estudio de los fenómenos electrolíticos y aplicarlos a procesos industriales y de corrosión.Subjects

fenómenos electroquímicos y corrosión | fenómenos electroquímicos y corrosión | cinética química | cinética química | química de superficies | química de superficies | química física | química física | Explotación de Minas | Explotación de Minas | reacciones explosivas | reacciones explosivas | isotermas de adsorción | isotermas de adsorción | sistemas dispersos | sistemas dispersos | adsorción | adsorción | catálisis | catálisis | termodinámica estadística | termodinámica estadística | interfases | interfasesLicense

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See all metadata6.094 Introduction to MATLAB® (MIT) 6.094 Introduction to MATLAB® (MIT)

Description

This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month. This course provides an aggressively gentle introduction to MATLAB®. It is designed to give students fluency in MATLAB, including popular toolboxes. The course consists of interactive lectures with a computer running MATLAB for each student. Problem-based MATLAB assignments are given which require significant time on MATLAB. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.Subjects

matlab | matlab | simulink | simulink | matlab programming | matlab programming | variables | variables | plotting | plotting | scripts | scripts | functions | functions | flow control | flow control | linear algebra | linear algebra | polynomials | polynomials | optimization | optimization | differential equations | differential equations | ode | ode | probability | probability | statistics | statistics | data structures | data structures | images | images | animation | animation | debugging | debugging | symbolic math | symbolic math | toolboxes | toolboxes | scope | scope | function block | function block | nervous system | nervous systemLicense

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See all metadataStatistical Methods for Planners I (MIT) Statistical Methods for Planners I (MIT)

Description

This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice. This course develops logical, empirically based arguments using statistical techniques and analytic methods. Elementary statistics, probability, and other types of quantitative reasoning useful for description, estimation, comparison, and explanation are covered. Emphasis is on the use and limitations of analytical techniques in planning practice.Subjects

statistics | statistics | statistical methods | statistical methods | quantitative reasoning | quantitative reasoning | variability | variability | numeracy | numeracy | measurement | measurement | stata | stata | logic | logic | probability | probability | inferential statistics | inferential statistics | regression | regression | census | census | bivariate | bivariate | multivariate | multivariate | normal curve | normal curve | research design | research design | decision tree | decision tree | utility | utility | planning | planning | distribution | distribution | city planning | city planning | scatterplot | scatterplotLicense

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

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See all metadata21M.734 Lighting Design for the Theatre (MIT) 21M.734 Lighting Design for the Theatre (MIT)

Description

This class explores the artistry of Lighting Design. Students gain an overall technical working knowledge of the tools of the trade, and learn how, and where to apply them to a final design. However essential technical expertise is, the class stresses the artistic, conceptual, collaborative side of the craft. The class format is a "hands on" approach, with a good portion of class time spent in a theatre. This class explores the artistry of Lighting Design. Students gain an overall technical working knowledge of the tools of the trade, and learn how, and where to apply them to a final design. However essential technical expertise is, the class stresses the artistic, conceptual, collaborative side of the craft. The class format is a "hands on" approach, with a good portion of class time spent in a theatre.Subjects

Lighting | Lighting | Design | Design | Theatre | Theatre | Stagecraft | Stagecraft | Technical | Technical | Stage | Stage | Production | Production | Theater | Theater | theatrical lighting design | theatrical lighting design | Boston theater | Boston theater | theater architecture | theater architecture | written script analysis | written script analysis | plot | plot | paperwork | paperwork | theoretical design | theoretical design | spatial adaptation | spatial adaptation | artistry | artistry | storyboards | storyboardsLicense

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See all metadata2.14 Analysis and Design of Feedback Control Systems (MIT)

Description

This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments.Subjects

feedback loops | compensation | Bode plots | Nyquist plots | state space | frequency domain | time domain | transfer functions | Laplace transform | root locus | op-amps | gears | motors | actuators | nonlinear systems | stability theory | control systems | dynamic feedback | mechanical engineering problem archiveLicense

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

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See all metadata21W.755 Writing and Reading Short Stories (MIT) 21W.755 Writing and Reading Short Stories (MIT)

Description

This class will focus on the craft of the short story, which we will explore through reading great short stories, writers speaking about writing, writing exercises and conducting workshops on original stories. This class will focus on the craft of the short story, which we will explore through reading great short stories, writers speaking about writing, writing exercises and conducting workshops on original stories.Subjects

short story | short story | voice | voice | point of view | point of view | character | character | place | place | plot | plot | pace | pace | conflict | conflict | want | want | obstacle | obstacle | writer's block | writer's block | workshop | workshop | incident | incident | description | description | publishing | publishing | revelation | revelation | reader | reader | writer | writer | free writing | free writing | rewrite | rewriteLicense

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

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See all metadata21W.755 Writing and Reading Short Stories (MIT) 21W.755 Writing and Reading Short Stories (MIT)

Description

This course is an introduction to the short story. Students will write stories and short descriptive sketches. Students will read great short stories and participate in class discussions of students' writing and the assigned stories in their historical and social contexts. This course is an introduction to the short story. Students will write stories and short descriptive sketches. Students will read great short stories and participate in class discussions of students' writing and the assigned stories in their historical and social contexts.Subjects

short story | short story | creative writing | creative writing | voice | voice | point of view | point of view | character | character | place | place | plot | plot | pace | pace | conflict | conflict | obstacle | obstacle | writer's block | writer's block | workshop | workshop | incident | incident | description | description | publishing | publishing | revelation | revelation | reader | reader | writer | writer | free writing | free writing | rewrite | rewriteLicense

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

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