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    Potential Scenario
    117

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    43

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    1991-JR_Lobry-P_Flandois-Comparison of Monod's Growth Model Parameters from the Same Data Set
    The paper obtains the parameters in Monod's Growth model using a minimization of the sum of square errors with a given data set and obtains confidence intervals
    Confidence intervalssum of square errorslinearizationgrowthModo Growth model
    Potential Scenario
    182

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    42

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    1999-Khorasheh-Ahmadi-Gerayeli-Application of Direct Search Optimization for Pharmacokinetic Parameter Estimation
    For simple pharmacokinetic compartmental models, analytical solution to the governing differential equations provide a mean to evaluate the associated rate constants. Such methods, however, can not be used used for more complex multi-compartment...
    sum of square errorsleast squarespharmacokineticslineteicscompartmental modelsdirect search
    Modeling Scenario
    364

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    272

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    1-061-PotatoCooling-ModelingScenario
    We model the cooling of a baked potato and compare it to student-collected data.
    least sum of square errorsNewton's Law of Coolingcoolingpotato
    Technique Narrative
    361

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    684

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    8-002-TrigSumRepresentation-TechniqueNarrative
    Students discover how to represent functions as sums of trigonometric functions and the value of such representations in many fields. This is an introduction to the study of Fourier Series.
    estimationTrigonometryTrigonometric Functionssum of square errorsfinite sumFourier seriesFouriere sumspectrumapproximatiopn
    Modeling Scenario
    229

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    120

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    3-015-StyrofoamBallFall-ModelingScenario
    We are given data on a falling Styrofoam ball and we seek to model this motion.
    footballresistancegravityfalling bodysum of square errorsNewton's Second Law of Motionsum of forcesstyrofoam
    Modeling Scenario
    189

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    242

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    6-019-EnablingEpidemicExploration-ModelingScenario
    We became aware of several interesting possibilities for a modeling opportunity with data and we invited you to explore the several routes to parameter estimation in a SIR model with respect to the data offered.
    Akaike Information CriterionMichaelis-Mentenepidemicsaturationgradientleast sum of square errors
    Potential Scenario
    112

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    31

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    1984-W_Brunner-D__Focht-Deterministic Three-Half-Order Kinetic Model for Microbial Degradation
    The kinetics of mineralization of carbonaceous substrates has been explained by a deterministic model which is applicable to either growth or nongrowth conditions in soil.
    kineticsnonlinear regressionsum of square errorsMonodlinearizemineralizationsubstratescarbonaceous
    Modeling Scenario
    190

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    161

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    5-080-SpaceFlightRecolonize-ModelingScenario
    This project is a combination of differential equations, multi-variable calculus, and vector calculus with use of technology to model colonization of a new planet. Students solve a system of second order differential equations to model a planet
    optimizationsum of square errorsvector calculusLagrange multipliersline integrals
    Modeling Scenario
    207

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    327

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    3-090-OneSpringMass-ModelingScenario
    We lead students through building a mathematical model for a single mass (bob)-spring system that is hanging vertically. We also lead the students, using data that they collect together with their model to approximate the value of the spring...
    undampedsum of square errorsmass springHooke's Lawoscilationleast-squares approximation
    Modeling Scenario
    346

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    338

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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
    Modeling Scenario
    328

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    680

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    1-047-Condensation-ModelingScenario
    We simulate 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. Animations are produced and data is offered for modeling with a differential...
    simulationsum of square errorscondensationbest fit
    Modeling Scenario
    570

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    307

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    5-011-ModelingIbuprofren-ModelingScenario
    We consider modeling of data from a clinical experiment administered as oral doses of 400 mg ibuprofen, an analgesic pain reliever. Concentrations of ibuprofen in the serum/plasma of the subjects were recorded after the initial ingestion of the...
    dataAICAkaike Information Criterionabsorptionsum of square errorscompartment modelibuprofendelay
    Modeling Scenario
    192

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    104

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    1-009-ICUSpread-ModelingScenario
    We offer students the opportunity to model the percentage of voluntary nonprofit hospitals in the United States with Intensive Care Units during the period of 1958-1974.
    logisticsum of square errorsIntensive Care Unithospitalspread
    Modeling Scenario
    1225

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    726

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    1-030-EyeModel-ModelingScenario
    We offer a mathematical modeling experience using differential equations to model the volume of an intraocular gas bubble used by ophthalmologists to aid the healing of a surgically repaired region of the retina.
    retinal surgeryAkaike Information CriterionSpanishsum of square errorssurgeryretionaophthalmologyeyeintraocular gas bubble
    Modeling Scenario
    182

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    138

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    4-035-ParEstSteadyState-ModelingScenario
    Students estimate parameters in a second order, linear, ordinary differential equations through analysis of the steady state solution. By applying a driver we can collect data in terms of the parameters and estimate these parameters
    driversteady statesum of square errors
    Modeling Scenario
    242

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    148

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    1-085-DrugBolus-ModelingScenario
    Given data on the concentration of a drug in the plasma of a human in mg/L at certain time intervals in hours can we determine the rate at which the drug leaves the plasma as well as the initial amount administered in a intravenous bolus of the drug?
    concentrationsum of square errorsbolusdrugrate constantadminister
    Potential Scenario
    122

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    16

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    2008-Duran-Caginalp-Parameter optimization for differential equations in asset price forecasting
    The optimization procedure is used in conjunction with daily market prices (MPs) and net asset values to determine the parameters for which the AFDE yield the best fit for the previous n days.
    financeinverse problemnumerical nonlinear optimizationasset flowfinancial market dynamicsmarket return prediction algorithm
    Potential Scenario
    167

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    49

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    2012-Augustus-Wali-Mathematical Modeling of Uganda Population Growth
    The purpose of this paper focuses on the application of logistic equation to model the population growth of Uganda using data from 1980 to 2010 (inclusive).
    population growthlogistic growthDrug and Alcohol detoxificationcarrying capacityvital coefficients
    Potential Scenario
    126

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    54

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    2018-Adeniji-EtAl-InverseProblemHolling-TannerModel
    We consider the inverse problem of parameter identification of nonlinear system of ODEs for a specific case of complete information about solution of the Holling-Tanner model for finite number of points for the finite time interval.
    goal functionabsolute error curvesinvers methodholling-Tanner model
    Potential Scenario
    109

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    35

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    2012-Nokkaew-EtAl-Estimation of Algae Growth Model Parameters by a Double Layer Genetic Algorithm
    This paper presents a double layer genetic algorithm (DLGA) to improve performance of the information-constrained parameter estimations.
    optimizationalgae growthgenetic algorithmssimulated dataconvergence of parameters