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    Potential Scenario
    169

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    2012-Ogunrinde-Sunday-On some models based on second order differential equation
    This paper presents some models based on second order differential equations. Such models include interaction between different kinds of species in an environment and pricing policy for optimum inventory level of a firm.
    Potential Scenario
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    2017-Sim-EtAl-Optimal control of a coupled tanks system with model-reality differences
    In this paper, an efficient computational approach is proposed to optimize and control a coupled tanks system.
    Potential Scenario
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    1989-EY_Rodin-K_Egan-Mathematics modelling of the rate of chemical reactions
    The development of improved designs for chemical reactors as well as the prediction of optimal operating conditions in chemical production are based on an understanding of the rates at which chemical processes occur.
    Potential Scenario
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    Modeling Scenario
    405

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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.
    Modeling Scenario
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    1-079-HomeHeating-ModelingScenario
    This project concerns using Newton's Law of Cooling to model the heating of a house. In particular, if one is going away for awhile, is it more economical to leave a house at a desired temperature or reheat it upon return?
    Modeling Scenario
    305

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    1-118-SolowEconomicGrowth-ModelingScenario
    Students construct and analyze the celebrated Solow-Swan model of economic growth theory. The project is divided into three sequential parts to teach students to understand, develop, and analyze a simple nonlinear model of economic dynamics.
    Potential Scenario
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    2016-Lewnard-Townsend-Climatic and evolutionary drivers of phase shifts in the plague epidemics of colonial India
    Our analysis shows that historical datasets can yield powerful insights into the transmission dynamics of reemerging disease agents with which we have limited contemporary experience to guide quantitative modeling and inference.