• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.79-88
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• 2004

Since computer integrated technology was introduced to the field of education, it has offered an expanding range of interactive possibilities which are remarkably powerful and helpful for the learners, especially constructing the cyber learning environments. Interactivity, the critical element in cyber learning, is categorized into three dimensions: student-to-contents, student-to-student and student-to-instructors. Six surrogate variables are introduced, and two quantitative model are developed for evaluating the degree of interactivity. The first model, which is called Data Envelopment Analysis model, is a linear programming based technique for measuring the relative performance of organizational units where the presence of multiple inputs and outputs makes comparison difficult. DEA model allows each unit to adopt a set of weight that shows it in the most favorable light in comparison to the other unit. The Second model employes the weighted average of standardized input variables for evaluation. Actual data have been collected from the Cyber IT university and these two models are applied for comparison. The analysis shows that the results from these two models are very much similar to each other, and are highly correlated to the level of class satisfaction.

• Atmosphere
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• v.26 no.1
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.1-10
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• 2022

Recently, as the offshore structures are operated in the deep-sea oil fields, interest in the analysis of relative wave elevation around platforms is increased. In this study, it is examined how the analysis results differ depending on the characteristics of the wave probe when interpreting the relative wave elevation in the model test. First, by conducting the wave probe comparison experiment in the two-dimensional wave tank, it is confirmed how the measured values differ according to the type of wave probe for the same physical phenomenon. Two types of wave probe are selected, the resistance type and the capacitance type, and the causes of the difference in measured values is studied. After that, the model test of the semi-submersible platform is conducted to investigate the relative wave elevation. Relative wave elevation is measured with the wave probes used in the wave probe comparison experiment and analyzed to estimate the asymmetric factor and the extreme upwell. The results between the two types of wave probes are compared, and qualitative study for the cause of the difference is conducted by photographing the physical phenomenon using a high-speed camera. Through the above study, it is confirmed that the capacitance type wave probe shows a larger measured value than the resistance type under the breaking-wave condition, and the same results are obtained for the asymmetric factor and the extreme upwell. These results is thought to be due to the difference in the measurement principle between wave probes, which is whether or not they measured water bubbles. This implies that the model test should be conducted using appropriate wave probes by considering the physical phenomenon to be analyzed.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.45-50
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• 2002

Use of a phenomenological model, developed far prediction of catalytic deactivation, is demonstrated in comparing harshness of different driving cycles that are currently used to rapidly age catalytic converters on engine test benches. The model shows that seemingly equivalent driving cycles cause the catalytic converters to reach significantly different levels of deactivation. The comparison of the model prediction with the limited vehicle data seems encouraging despite the simplicity of the model at the current stage of its infancy.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.370-375
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• 1998

The objectives of this study are to evaluate the applicability of SCS TR-20 model for small ungauged watershed, to show the behavior of the model with variation of topography in watershed, and to evaluate the storage effect of paddy field for flood flow. For this purpose, simulated data from the model were compared with the observed flood data at two sites (HS#3, HS#4) in Balan watershed. From the comparison between simulated and observed data, it was found that the model is applicable to this watershed.

• Journal of applied mathematics & informatics
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• v.6 no.2
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• pp.599-609
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• 1999

Neural networks are explored as an alternative to a regres-sion model for prediction of the number of daily household vehicular trips. This study focuses on contrasting a neural network model with a regression model in term of variable selection as well as the appli-cation of these models for prediction of extreme observations, The differences in the models regarding data transformation variable selec-tion and multicollinearity are considered. The results indicate that the neural network model is a viable alternative to the regression model for addressing both messy data problems and limitation in variable structure specification.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.65-75
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• 1989

A general software reliability model is developed, which includes the Jelinski-Moranda model, the Goel-Okumoto model, the Shanthikumar model and the Ross model as special cases. In each of above models estimators of the software failure rate and the number of remaining errors are presented and compared in terms of the expected absolute error loss and the expected squared error loss by a Monte Carlo simulation.

• Journal of Korean Society of Transportation
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• v.10 no.1
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• pp.5-20
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• 1992

Even though the types of ramp facilities in Korea are not various like other countries operations in these sections are very important because ramp merging and /or diverging flow affects freeway overall sections. In this study existing methodologies especially the gap acceptance model and the regression model in USHCM are evaluated with our field data. By gap acceptance model the merging capacity is founded 2.360 pcph which is increased by 7% than the capacity of freeway basic section. And in comparison of actual lane 1 volume to the estimation volume by HCM model the model slightly overestimates the actual volue.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.160-162
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• 2016

A compact model of tunnel field effect transistor (TFET) has been developed. The model includes a surface potentia calculation module and a band-to-band-tunneling current module. Model comparison with TCAD shows that the mode calculates TFET surface potential and drain current accurately.

• Journal of Korean Elementary Science Education
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• v.27 no.1
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• pp.60-74
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• 2008

The purpose of this study was to examine the effects of a brain-based science teaching and learning model on the science related attitudes, scientific inquiry skills and science knowledge of the 2nd graders in Intelligent Life course. For this study, 117 elementary students from four classes of the 2nd grade in Seoul were selected. In the comparison group, traditional instruction was implemented and in the experimental group, instruction according to brain-based science teaching and learning model was implemented for four weeks. The results of this study were as follows : There were little differences between the comparison and experimental groups in terms of the science related attitudes except for the sub-domains of interest and curiosity. And brain-based science teaching and learning model programs improved a few scientific inquiry skills, especially observation and classification. In addition, the experimental groups showed a positive effect on science knowledge. In conclusion, brain-based science teaching and learning model programs were more effective in improvement of the science related attitudes, scientific inquiry skills and science knowledge of elementary students.