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    Potential Scenario
    189

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    75

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    1996-D_Erdman-MM_Morelock-A Study of Kinetics
    This paper introduces new and old features of the SAS System for the estimation and simulation of systems of first-order differential equations with emphasis on examples in kinetics.
    simulationkineticsparameter estimationEnzymesubstratesavingscompartmentstomachbloodginseng
    Modeling Scenario
    257

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    270

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    1-002-Tossing-ModelingScenario
    We offer students simulation experience or data from a simulation and ask them to model the simulation using several approaches, to include exponential decay fit, difference equation, and differential equation.
    Modeling and simulationexponentialdecaydice
    Modeling Scenario
    238

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    343

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    1-062-BacteriaGrowth-ModelingScenario
    We offer students a simulation experience or data from a simulation and ask them to model the simulation using several approaches: exponential growth fit, difference equation, differential equation, and parameter estimation using EXCEL spreadsheet.
    bacteriaexponentialgrowth
    Potential Scenario
    1249

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    47

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    2000-Erdman-Morelock-A Study of Kinetics The Estimation and Simulation of Systems of First-Order Differential Equations
    This paper introduces new and old features of the SAS System for the estimation and simulation of systems of first-order differential equations with emphasis on examples in kinetics.
    kineticsSAScompartmentpharmacokinetics
    Modeling Scenario
    370

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    242

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    1-101-ClassMMDeathImmigration-ModelingScenario
    We offer students an opportunity to generate unique data for their team on a death and immigration model using m&m's and then pass on the data to another student team for analysis with a model they built. The key is to recover the parameters.
    simulationimmigrationdata collectiondeath
    Modeling Scenario
    233

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    185

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    1-125-DiceyPopulation-ModelingScenario
    We offer students an opportunity to generate data for their team on a death and immigration model using 12 and 20 sided dice and then pass on the data to another student team for analysis with a model they built. The key is to recover the...
    simulationimmigrationdeathdice
    Modeling Scenario
    238

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    504

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    3-076-CircuitBuilding-ModelingScenario
    In this project students will establish a mathematical model for an electric circuit as a second-order ordinary differential equation with constant coefficients.
    simulationexperimentMultisimcircuitinductancecapacitorKirchhoff's Voltage Lawresistor
    Article or Presentation
    302

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    942

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    2020-TeachingModule-SpreadOfCommonColdSimulation
    This simulation is meant to introduce the idea of a differential equation model and investigate the impact of heightened hygiene and decreased interactions on the spread of an infectious disease. The focus of this simulation is on the common cold.
    simulationmoduleinfectious diseasediseasespreadTeaching Modulespread of disease
    Modeling Scenario
    405

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    507

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    1-047a-CondensationOptimization-ModelingScenario
    We seek to optimize a condensation process which is modeled by a simulation using the random motion of 200 particles in a 50 by 50 square in which a particle bounces off the two vertical and top walls and condenses on the bottom wall.
    simulationdataoptimizationenergycondensationbest fitcostsum of scquare errors
    Potential Scenario
    226

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    108

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    2016-Lofgren-EtAl-Equations of the End Teaching Mathematical Modeling Using the Zombie Apocalypse
    In this article, we explore several uses of zombie epidemics to make mathematical modeling and infectious disease epidemiology more accessible to public health professionals, students, and the general public.
    simulationinfectious diseasediseaseepidemicZombieWhite Zed
    Modeling Scenario
    267

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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
    Article or Presentation
    236

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    71

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    2009-Brian_Winkel-Population_modelling_with_MandMs
    Several activities in which population dynamics can be modeled by tossing M&M’s® candy are presented.
    simulationparameter estimationimmigrationdeathdifference equation
    Modeling Scenario
    413

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    485

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    1-001-MM-DeathAndImmigration-ModelingScenario
    We conduct a simulation of death and immigration, using a small set of "individuals", m&m candies or any two sided object (coin, chips), in which upon tossing a set of individuals we cause some to die and others then to immigrate. Modeling ensues!
    simulationimmigrationdeathSpanishdatsWinkelBrian Winkel
    Potential Scenario
    256

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    67

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    2018-Van_Kinh Nguyen-Esteban_Hernandez-Vargas-Parameter estimation in mathematical models of viral infections using R
    Mathematical modeling has played a central role to understand mechanisms in different viral infectious diseases. In this approach, biological-based hypotheses are expressed via mathematical relations and then tested based on empirical data.
    simulationdiseasevirusviral infection
    Potential Scenario
    122

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    52

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    2007-Exben_Friis-Jensen-Modeling and Simulation of Glucose-Insulin Metabolism
    In this thesis one of the models of diabetes, Bergman’s minimal model is described trough derivation and simulations.
    Metabolisminsulin resistanceglucosePID controllerintolerance
    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
    Potential Scenario
    170

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    60

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    2019-Hu-Treinen-One-step_method_for_modelling_longitudinal_data_with_differential_equations
    This study proposes a new approach to estimate the parameters in differential equation models used to describe non-linear trajectories of longitudinal data.
    simulationparameter estimationshoppingfittingbehaviour
    Article or Presentation
    191

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    57

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    2011-Brian_Winkel-Sourcing_for_parameter_estimation_and_study_of_logistic_differential_equation
    We present two simulation activities for students to generate real data and several data sources for the purpose of estimating parameters in the logistic differential equation model.
    dataparameter estimationparameterlogistic equationsource
    Modeling Scenario
    229

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    116

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    6-045-CholeraTranmission-ModelingScenario
    During the project described here, the students will learn how to solve and address a practical problem such as cholera transmission using various mathematical tools.
    infectious diseasecholeraendemicdisease-freetransmission ratewaterborne pathogen
    Potential Scenario
    203

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    73

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    2017-D_Goulet-Modeling, Simulating, and Parameter Fitting of Biochemical Kinetic Experiments
    In many chemical and biological applications, systems of differential equations containing unknown parameters are used to explain empirical observations and experimental data. The differential equations are typically nonlinear.
    optimizationBiochemistrysensitivity analysischromatographymass actioncluster analysisconservation lawsdimerizationestrogen receptor protein