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    Potential Scenario
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    2017-Brandi-Garcia-Motivating engineering students to math classes - Practical experience teaching ODEs
    In this paper we propose an approach to teaching-learning process of mathematical concepts to engineering students with a motivational factor: a practical problem to be modeled in which students must apply concepts seen in class, in particular...
    computational toolsteachingengineering studentspractical problem
    Potential Scenario
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    2017-Alex_Honchar-Neural Networks For Solving Differential Equations
    In this post I want to show how I applied simple feed-forward NNs to different differential equations with increasing complexity: ODEs, second order ODEs, and, finally, PDEs.
    neural networksCybenko theoremdiffusion equationfluid dynamics
    Potential Scenario
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    2015-Liang-EtAl-Advanced ordinary differential equation based head modelling for Chinese marionette art preservation
    This paper addresses the heritage preservation of the marionette head carving by digitalizing the head models with a novel modelling technique using ordinary differential equations (ODEs).
    digitizationcontrolmarionetteChinese marionettehead carving
    Potential Scenario
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    2015-Just-Callender-Differential equation models of disease transmission
    The work give full analyses of standard epidemic model and then shows how to do it with differential equations and agent-based modeling. Then it compares the results.
    disease transmissionSIR modelsepidemicagent-based
    Potential Scenario
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    2015-Heiko_Enderling-Integrating experimental data to calibrate quantitative cancer models
    For quantitative cancer models to be meaningful and interpretable the number of unknown parameters must be kept minimal. We focus on a tumor hierarchy of cancer stem and progenitor non-stem cancer cells.
    cancertumorfittingagent-based
    Potential Scenario
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    2015-Dios-EtAl-How Engineers deal with Mathematics solving Differential Equations
    The students of fourth course, of the bachelor’s degree in Computer Sciences or Industrial Engineering at the University of Salamanca (Spain), they learn mathematics solving real problems with the help of the acquired interdisciplinary knowledge.
    assessmentengineering educationSimulink
    Potential Scenario
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    2015-Cano-EtAl-Bringing partial differential equations to life for students
    This work describes how to use an authoring tool, Easy Java Simulations, to build interactive simulations using FreeFem++ (Hecht F 2012 J. Numer. Math. 20 251) as a PDE solver engine.
    Java SimulationFreeFemauthoring toolsauthoring methodsphysical modellingclassroom teaching
    Potential Scenario
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    2014-Danielsen-Sørensen-Using authentic sources in teaching logistic growth
    This 12 page offering develops issues and questions about using historical materials to motivate mathematics study and develops 9 very rich exercises
    real datalogistichistorical materials
    Potential Scenario
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    2012-Rusinko-Swan-Agent-Based Fabric Modeling Using Differential Equations
    We use an agent-based modeling software, NetLogo, to simulate fabric drape by applying a modified mass spring system.
    NetLogospring massagent-baseddrapingyarnfabric
    Free Online Textbook
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    2015-Eric_Sullivan-Numerical Methods_An_Inquiry-Based_Approach_with_Python
    This is an OER effort on the part of Eric Sullivan to explore the joy of numerical methods. He has provided several versions.
    pythonnumerical analysisNumerical Methods
    Potential Scenario
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    2020-Cline_Fasteen_Francis_Sullivan_Wendt-Vision_for_Projects_Across_Mathematics_Curriculum
    We consider the use of projects in math courses as a mechanism for promoting coding, communication, and interdisciplinary application of math skills. Final projects play an important role, but we also discuss several alternate types of projects.
    modelinginterdisciplinarywritingcodingprojecttechnical writing
    Technique Narrative
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    2-001-NumericalMethodsComparisons-TechniqueNarrative
    This material teaches the basics of numerical methods for first order differential equations by following graphical and numerical approaches. We discuss the order of accuracy of the methods and compare their CPU times.
    Euler's methodimproved Euler's methodRK3 methodsRK4 methodsorder of accuracyabsolute errorCPU time
    Technique Narrative
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    1-005-NavigatingNumericalMethods-TechniqueNarrative
    This technique narrative is a discovery-based approach to learning the basics of numerical methods for first order differential equations, by following the graphical and analytical perspectives of the forward Euler method and second order Taylor...
    Euler's methodTaylor's Methodsearch and rescueCoaast Guardlost at sealongitudelatitudelimit definition
    Technique Narrative
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    1-003-IntroNumericalMethods-TechniqueNarrative
    We develop elementary approaches to numerically solving first order differential equations with Euler's Method, Improved Euler's Method and develop these geometrically to compute numeric solutions and compare them to analytic solutions.
    analytic solutionEuler's methodimproved Euler's method
    Modeling Scenario
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    175

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    1-097-SwimmingPool-ModelingScenario
    This project involves the dynamics of chlorine concentration during regular swimming pool maintenance cycles. Students will have the opportunity to use both analytic and numerical methods.
    concentrationcchlorinenumerical errorswimming poolhorineerreor
    Modeling Scenario
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    1-001d-HotelPopulationDecay-ModelingScenario
    You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel. Before you run the simulation in MATLAB, answer some questions.
    simulationlogisticexponential decayfitting
    Modeling Scenario
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    1-001a-MMDeathImmigration-Variation-ModelingScenario
    We model exponential death with m&m's as well as death with immigration.
    simulationdatam&mimmigrationdeath
    Modeling Scenario
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    3-010-EnergyInSpringMassSystem-ModlingScenario
    As a way to synthesize the effects of damping and forcing terms, this activity is meant to encourage students to explore how different forcing terms will change the total energy in a mass-spring system.
    energymass-spring systemkinetic energypotential energytotal energy
    Modeling Scenario
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    3-011-EulerBallThrowing-ModelingScenario
    If a tennis ball is thrown through the air it will hit the ground due to gravity. Using Euler's method, write a short script (Python, Matlab, R, etc.) to find the trajectory of the ball which will maximize the distance the ball lands from the...
    codingdragonVectorsEuler's methodball
    Modeling Scenario
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    6-024-DronePackageDelivery-ModelingScenario
    Students will derive a system of first order differential equations which describe the flight path of a drone delivering a package.
    VectorsTrigonometryFlightdronesparametric curveImproved Euler MethodRunge-Kutta