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This study concerns with an applicability of the management science approach to the score adjustment among the College Scholastic Aptitude Test(CSAT) optional subjects. A linear programming model is developed to minimize the sum of score distortions between optional subjects. Based on the analysis of the 377,089 CSAT(2010) applicants’ performances in social science test section, this study proposes a new approach for the score equating or linking method of the educational measurement theory. This study makes up for the weak points in the previous linear programming model. First, the model utilize the standard score which we can get. Second, the model includes a goal programming concept which minimizes the gap between the adjusting goal and the result of the adjustment. Third, the objective function of the linear programing is the weighted sum of the score distortion and the number of applicants. Fourth, the model is applied to the score adjustment problem for the whole 11 optional subjects of the social science test section. The suggested linear programming model is a generalization of the multi-tests linking problem. So, the approach is consistent with the measurement theory for the two tests and can be applied to the optional three or more tests which do not have a common anchor test or a common anchor group. The college admission decision with CSAT score can be improved by using the suggested linear programming model.
A smoothed particle hydrodynamics (SPH) method is applied for simulating two-dimensional free-surface problems. The SPH method based on the Lagrangian formulation provides realistic flow motions with violent surface deformation, fragmentation and reunification. In this study, the effect of computational parameters in SPH simulation is explored through two-dimensional dam-breaking and sloshing problem. The parameters to be considered are the speed of sound, the frequency of density re-initialization, the number of particle and smoothing length. Through a series of numerical test. detailed information was obtained about how SPH solution can be more stabilized and improved by adjusting computational parameters. Finally, some numerical simulations for various fluid flow problem were carried out based on the parameters chosen through the sensitivity study.
There are many applications which can rise to a input-output substitution model in economics and management science. Conventional analysis on input-output substitution model assumes perfect substitutability among commodities produced by alternative activities. Assumption of perfect substitutability, however, is likely to lead to "bang-bang" phenomena. In many real situations, such sensitive optimal solution behavior cannot be accepted. This paper develops an expansion path which have constant elasticity of substitution among alternative activities. Adopting the expansion path, this paper proposes an input-out substitution model with elasticity of substitution. The model well describes the real situations of decision and includes the ideal situation of perfect competition such as linear programing, so that the model is a robust and general one.