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    Potential Scenario
    158

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    1992-John_Mathews-Bounded population growth-a curve fitting lesson
    The purpose of this article is to present two methods for fitting the logistic curve to data supplied by the U. S. census bureau.
    datalogisticlinearizationfitting
    Potential Scenario
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    2018-Dyjuan_Tatro-The_Mathematics_of_Cancer-Fitting_Gompertz_Equation_to_Tumor_Growth
    Fitting the Gompertz Model to long term breast cancer study data, this project ascertains gompertzian parameters that can be used to predicts tumor growth as a function of time.
    tumorgrowthGompertzfittingparameter
    Modeling Scenario
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    416

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    1-102-CancerTumor-ModelingScenario
    This module guides students in the use of differential equation models to predict cancer growth and optimize treatment outcomes. Several classical models for cancer growth are studied, including exponential, power law, Bertalanffy, logistic, and...
    optimizationlogisticpredictiondata fittingpower lawGompertzcancer growtheponentialBertalanaffy
    Modeling Scenario
    401

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    1-102C-CancerGrowth-ModelingScenario
    This module guides students in the use of differential equation models to predict cancer growth and study treatment outcomes. Several classical models for cancer growth are presented including exponential, power law, Bertalanffy, logistic, and...
    optimizationcancerlogisticexponentialpredictiontumorgrowthdata fittingpower lawBertanffyGompertz
    Potential Scenario
    184

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    49

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    2012-Transtrum-Qiu-Optimal experiment selection for parameter estimation in biological differential equation models
    We explore the question to what extent parameters can be efficiently estimated by appropriate experimental selection.
    experimental designsystems biologyAssociation & Data Fittingreaction ratesdecay rates
    Potential Scenario
    170

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    91

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    2018-Akman-EtAl-Parameter Estimation in Ordinary Differential Equations Modeling via Particle Swarm Optimization
    We demonstrate Particle Swarm Optimization efficacy by showing that it outstrips evolutionary computing methods previously used to analyze an epidemic model.
    epidemicParticle Swarm Optimizationoptimize parameters
    Potential Scenario
    247

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    80

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    2017-Floyd_Ballard-Dice Activities for DE Models
    This document includes descriptions of four activities that are appropriate for a calculus or differential equations class, all using dice to motivate a differential equation model for a real-world scenario.
    simulationcurve fittingcdicecollect dataclass activitiesanalyze dataclass activity
    Potential Scenario
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    45

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    2010-Singh-Mishra-athematical modeling approach to study growth rate of grassroots technological innovations
    In this paper we have proposed a simple mathematical model by using ordinary differential equation to know the spread rate of technological innovations in rural India.
    logisticexponentialsigmoidtechnological innovationsasymptoticspread of innovation
    Technique Narrative
    432

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    2-005-LinearizeItAll-TechniqueNarrative
    Linear approximations are often used to simplify nonlinear ordinary differential equations (ODEs) for ease in analysis. The resulting linear approximation produces an ODE where closed form solutions may be obtained.
    computationerrorTorricelli's Lawdata fittinglinear approximation
    Modeling Scenario
    372

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    222

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    1-005C-OilSlick-ModelingScenario
    We describe a modeling activity for Calculus I students in which modeling with difference and differential equations is appropriate.
    Problem Solvingoil slickspreadfittinglineassumptions
    Modeling Scenario
    259

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    227

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    1-054-GrowthInFarmland-ModelingScenario
    An enriching project developing a model from data with missing temporal information is described. Students fit functions to the data that leads to the creation of a differential equations model, which they then are required to analyze in multiple...
    fittingfarmfarmland
    Modeling Scenario
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    459

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    1-011A-Kinetics-ModelingScenario
    We help students see the connection between college level chemistry course work and their differential equations coursework. We do this through modeling kinetics, or rates of chemical reaction.
    kineticsLaw of Mass Actionfittingorder of reactionchemical reaction
    Modeling Scenario
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    153

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    1-001s-StochasticMDeathImmigration-ModelingScenario
    We develop a mathematical model of a death and immigration process using m&ms as a stochastic process with the help of probability generating functions (pgf). We start with 50 m&ms in a bag.
    simulationdatalogisticimmigrationstochasticdeathfitting
    Modeling Scenario
    367

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    162

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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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    1-011-Kinetics-ModelingScenario
    We make the connection between chemistry course and differential equations coursework. We do this through modeling kinetics, or rates of chemical reaction. We study zeroth, first, and second order reactions.
    kineticschemistryLaw of Mass Actionchemical kineticsorder of reactionchemical reaction
    Modeling Scenario
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    259

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    6-029-TumorGrowth-ModelingScenario
    This modeling scenario guides a student familiar with single ordinary differential equation (ODE) models towards the development of a more complex system of two ODEs for describing the evolution of tumor growth over time.
    Pop_Growth Pilotlogisticcomparmenttumorsynthetic datasum of squares error
    Modeling Scenario
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    126

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    1-084-GoingViral-ModelingScenario
    Students employ randomization in order to create a simulation of the spread of a viral disease in a population (the classroom). Students then use qualitative analysis of the expected behavior of the virus to devise a logistic differential equation.
    simulationlogisticrandomfittingpartial fractions
    Modeling Scenario
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    1-046-GoingViral-ModelingScenario
    Students participate in a simulation of the spread of a viral disease in the classroom and model the process with a logistic differential equation. The simulation uses random numbers and the entire class participates.
    simulationmathematical modeldatalogisticrandom number generatorfittingrandom process