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-1-115.053 Optimization Methods in Management Science (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=883913
This course introduces students to the theory, algorithms, and applications of optimization. The optimization methodologies include linear programming, network optimization, integer programming, and decision trees. Applications to logistics, manufacturing, transportation, marketing, project management, and finance. Includes a team project in which students select and solve a problem in practice.Thu, 07 Aug 2014 00:01:20 GMTProf. James Orlin; Dr. Ebrahim Nasrabadi18.S997 Introduction To MATLAB Programming (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=883876
This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB® in particular.Thu, 07 Aug 2014 00:00:35 GMTYossi FarjounFlash animations in science
https://www.merlot.org/merlot/viewMaterial.htm?id=215700
Learning object repository for science teachers (biology, physics, mathematics).<br />You will find flash animations and simulations especially made by teachers for teachers.<br />The main topics are: Life sciences (transcription, replication, DNA, genetics, anatomy, organs, heart cycle, digestive tract, physiology) Earth and space sciences (astronomy, geophysics, satellisation, seismic wave,plates, continental drift, tsunami, resources and environment, water cycle) Electromagnetism (electric field, potential, magnetic field, magnet and compass, charge, Faraday’s law of induction) Optics (light, shadow, lens, geometrical optic, physical optic, laser, waves) Mechanics (motion and force, Newton’s law, gravitation, energy, nuclear )Fri, 01 Sep 2006 11:39:44 GMTCharles Sol edumediaGAUSS - A Graphic Calculator
https://www.merlot.org/merlot/viewMaterial.htm?id=85013
A free, interactive tool to graph any mathematical function. Developed with Macromedia Flash and Action Script programming language.Fri, 28 Oct 2005 07:00:00 GMTTeodoru Gugoiu La Citadelle, Ontario, CanadaMathematical Modeling in the Biosciences
https://www.merlot.org/merlot/viewMaterial.htm?id=575786
<p>The course is a mathematical and computational exploration of five diverse areas of biology: human locomotion, gene sequence analysis, signal transduction pathways involved in cancer, neurophysiology and neuroanatomy. Each biological topic is introduced by a guest speaker whose research is relevant to the given topic. We cover simple mathematical techniques to quantify such systems, and discuss how to describe the key components of a biological process mathematically. The course emphasizes the relevance of mathematical and computational tools to approaching biological questions and how to interpret mathematical results in the context of these problems. Key mathematical concepts of the course are: integration, phase- plane analysis and introductory notions from graph theory. The course is composed of both a lecture session and lab session. Prerequisites of the course are basic calculus and biology.</p>Thu, 18 Aug 2011 00:40:56 GMTKamila Larripa; Borbala Mazzag; Michael Stobb Humboldt State University; Humboldt State University; Humboldt State UniversityMatlab-based Numerical Methods in Engineering course
https://www.merlot.org/merlot/viewMaterial.htm?id=408017
<p>This web page shows links to lectures for a course on Numerical Methods in Engineering taught by the author in the Spring Semester of 2009. Click on the lecture links for class notes, Matlab scripts and functions, and assignments. Subjects covered: vectors and matrices in Matlab, graphics in Matlab, programming, numerical linear algebra, solution to equations, numerical integration, data fitting, and ordinary differential equations.</p><p> </p>Tue, 29 Sep 2009 19:41:41 GMTGilberto UrrozPopulation Modeling Applet
https://www.merlot.org/merlot/viewMaterial.htm?id=314085
<p>In this applet, the user applies Euler's Method to modeling population growth using the Malthus exponential model and the Verhulst constrained growth model. After finding the Euler solution, the user can check the solution with the Adaptive Euler Approximation or with a slope field. Also, the user can enter an exact solution obtained from separating variables (or whatever) and again check the Euler solution graphically.</p>Tue, 03 Jun 2008 14:04:20 GMTDon Kreider; Dwight Lahr Department of Mathematics, Dartmouth College; Department of Mathematics, Dartmouth College12.S990 Quantifying Uncertainty (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884089
The ability to quantify the uncertainty in our models of nature is fundamental to many inference problems in Science and Engineering. In this course, we study advanced methods to represent, sample, update and propagate uncertainty. This is a "hands on" course: Methodology will be coupled with applications. The course will include lectures, invited talks, discussions, reviews and projects and will meet once a week to discuss a method and its applications.Thu, 07 Aug 2014 00:04:59 GMTDr. Sai Ravela14.451 Dynamic Optimization Methods with Applications (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884672
This course focuses on dynamic optimization methods, both in discrete and in continuous time. We approach these problems from a dynamic programming and optimal control perspective. We also study the dynamic systems that come from the solutions to these problems. The course will illustrate how these techniques are useful in various applications, drawing on many economic examples. However, the focus will remain on gaining a general command of the tools so that they can be applied later in other classes.Thu, 07 Aug 2014 00:17:00 GMTProf. Guido Lorenzoni15.097 Prediction: Machine Learning and Statistics (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884568
Prediction is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning and statistics, and more generally, data mining. Machine learning and statistical methods are used throughout the scientific world for their use in handling the "information overload" that characterizes our current digital age. Machine learning developed from the artificial intelligence community, mainly within the last 30 years, at the same time that statistics has made major advances due to the availability of modern computing. However, parts of these two fields aim at the same goal, that is, of prediction from data. This course provides a selection of the most important topics from both of these subjects.Thu, 07 Aug 2014 00:14:44 GMTProf. Cynthia Rudin18.303 Linear Partial Differential Equations: Analysis and Numerics (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884153
This course provides students with the basic analytical and computational tools of linear partial differential equations (PDEs) for practical applications in science engineering, including heat/diffusion, wave, and Poisson equations. Analytics emphasize the viewpoint of linear algebra and the analogy with finite matrix problems. Numerics focus on finite-difference and finite-element techniques to reduce PDEs to matrix problems.Thu, 07 Aug 2014 00:06:19 GMTProf. Steven G. Johnson18.337J Parallel Computing (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=883819
This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world's fastest machines. We will make prominent use of the Julia Language software project.Wed, 06 Aug 2014 23:59:24 GMTProf. Alan Edelman18.357 Interfacial Phenomena (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=883742
This graduate-level course covers fluid systems dominated by the influence of interfacial tension. The roles of curvature pressure and Marangoni stress are elucidated in a variety of fluid systems. Particular attention is given to drops and bubbles, soap films and minimal surfaces, wetting phenomena, water-repellency, surfactants, Marangoni flows, capillary origami and contact line dynamics.Wed, 06 Aug 2014 23:58:02 GMTProf. John W. M. Bush2.092 Finite Element Analysis of Solids and Fluids I (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884352
This course introduces finite element methods for the analysis of solid, structural, fluid, field, and heat transfer problems. Steady-state, transient, and dynamic conditions are considered. Finite element methods and solution procedures for linear and nonlinear analyses are presented using largely physical arguments. The homework and a term project (for graduate students) involve use of the general purpose finite element analysis program ADINA. Applications include finite element analyses, modeling of problems, and interpretation of numerical results.Thu, 07 Aug 2014 00:10:30 GMTProf. Klaus-Jürgen Bathe2.094 Finite Element Analysis of Solids and Fluids II (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884759
This course presents finite element theory and methods for general linear and nonlinear analyses. Reliable and effective finite element procedures are discussed with their applications to the solution of general problems in solid, structural, and fluid mechanics, heat and mass transfer, and fluid-structure interactions. The governing continuum mechanics equations, conservation laws, virtual work, and variational principles are used to establish effective finite element discretizations and the stability, accuracy, and convergence are discussed. The homework and the student-selected term project using the general-purpose finite element analysis program ADINA are important parts of the course.Thu, 07 Aug 2014 00:18:38 GMTProf. Klaus-Jürgen Bathe6.042J Mathematics for Computer Science (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884148
This course covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.Thu, 07 Aug 2014 00:06:13 GMTProf. Tom Leighton; Dr. Marten van Dijk6.042J Mathematics for Computer Science (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884196
This subject offers an introduction to Discrete Mathematics oriented toward Computer Science and Engineering. The subject coverage divides roughly into thirds: Fundamental concepts of mathematics: definitions, proofs, sets, functions, relations. Discrete structures: graphs, state machines, modular arithmetic, counting. Discrete probability theory. On completion of 6.042, students will be able to explain and apply the basic methods of discrete (noncontinuous) mathematics in Computer Science. They will be able to use these methods in subsequent courses in the design and analysis of algorithms, computability theory, software engineering, and computer systems.Thu, 07 Aug 2014 00:07:08 GMTProf. Albert R. Meyer6.079 Introduction to Convex Optimization (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884236
This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software. Acknowledgements The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).Thu, 07 Aug 2014 00:07:53 GMTProf. Stephen Boyd; Prof. Pablo Parrilo6.094 Introduction to MATLAB (MIT)
https://www.merlot.org/merlot/viewMaterial.htm?id=884555
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.Thu, 07 Aug 2014 00:14:33 GMTDanilo ŠćepanovićA+Click Math Skill Self-Study Tests for Grade 1 to 12
https://www.merlot.org/merlot/viewMaterial.htm?id=504906
<p>A+Click Math Self-study Tests and Skill Assessment for Grade 1 to Grade 12. It includes more than 1000 challenging problems and answers and tons of illustrations. The practice tests adapt to student ability. This website has a graduated set of problems, starting from very simple, to quite difficult. To progress to a new level, you have to answer five consecutive questions correctly. The questions are appropriate to elementary students; almost any second grader could answer the easiest. This is a good assessment test without being insulting or frustrating.</p>Sat, 20 Nov 2010 16:52:40 GMTIgor Kokcharov AplusclickAdding apples oranges and pears
https://www.merlot.org/merlot/viewMaterial.htm?id=688991
<p>To calculate the value of apple, orange, pear from 3 purchases.</p><p>About mental arithmetic, with a pre-algebra tool introducing the Gaussian elimination.</p>Fri, 31 Aug 2012 17:00:08 GMTMaurici CarbóCogPrints: Open Access Cognitive Sciences ePrint Archive
https://www.merlot.org/merlot/viewMaterial.htm?id=1290936
<p>CogPrints (1997) is an open access, electronic archive in which authors can self-archive papers in any area of Cognitive Science: Psychology, Neuroscience, and Linguistics, including many areas of Computer Science, Philosophy, and Biology.</p>Tue, 28 Mar 2017 04:56:02 GMTSteven Harnad CogPrints/EPrints 3 at University of Southampton, UKExponential Growth Practice
https://www.merlot.org/merlot/viewMaterial.htm?id=696533
<p>This lesson assumes a background understanding of the basic parameters for an exponential function and gives students an opportunity to discover how exponential growth affects monetary stature. This gives students an opportunity to get comfortable with computations utilizing the exponential growth equation by integrating a popular culture cartoon to spark interest.</p>Sun, 30 Sep 2012 03:23:02 GMTKyle HeffelbowerFractions, Decimals, and Percents Stand Alone
https://www.merlot.org/merlot/viewMaterial.htm?id=602255
<p>This is a Stand Alone Powerpoint on Fractions, Decimals, and Percents. It is intended for fifth grader learners, after the learn about the connection between fractions, decimals, and percents. This can be used a review.</p>Sun, 27 Nov 2011 02:54:22 GMTLisa Napierala