• Journal of Digital Contents Society
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• v.9 no.3
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• pp.471-481
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• 2008

Test scheduling considering power dissipation is an effective technique to reduce the testing time of complex SoCs and to enhance fault coverage under limitation of allowed maximum power dissipation. In this paper, a modeling technique of test resources and a test scheduling algorithm for efficient test procedures are proposed and confirmed. For test resources modeling, two methods are described. One is to use the maximum point and next maximum point of power dissipation in test resources, the other one is to model test resources by partitioning of them. A novel heuristic test scheduling algorithm, using the extended-tree-growing-graph for generation of maximum embedded cores usable simultaneously by using relations between test resources and cores and power-dissipation-changing-graph for power optimization, is presented and compared with conventional algorithms to verify its efficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.449-453
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• 2008

This research focused on analyzing and comparing between the results of hydraulic physical modeling and the results of numerical modeling of Grass Concrete which is newly developed in-situ block system. The physical model was built as a scale of 1:50 by Froude similitude measuring the water levels and the water velocities for before and after vegetation and the effects were analyzed after reviewing the results. In consequence, the water velocities were observed to decrease meanly 19.1%, and the water depth were determined to increase meanly 27.8% in case of the of design flood, $Q=200m^3/sec$. Moreover, the velocities were produced reduction effects of 27.2%, and the water levels were derived from addition effects of the highest 31.3% in case of the probability maximum flood(PMF), $Q=600m^3/sec$. To verifying the hydraulic physical modeling, the numerical modeling was conducted for a close examination of before and after vegetation. HEC-RAS model was for 1 dimensional numerical analysis and RMA-2 was for 2 dimensional numerical analysis. The results of the numerical simulation, under the condition of roughness coefficient calibration, shows similar results of the physical modeling. These satisfactory results show that the accomplished results of hydraulic modeling and the predicted results of numerical modeling corresponded reasonably each others.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1439-1442
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• 2010

Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.473-473
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• 2011

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily reference evapotranspiration (ETo) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it consists of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily ETo data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as ETo modeling can be generalized using GMDH-NNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1596-1599
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• 2010

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using GMDH-NNM.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.204-208
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• 2006

This study is to develop a distributed urban flood runoff model that simulates the road runoff and to test the applicability of the model by applying to Pyeongtaek city of $12.2km^2$. To generate the runoff along the runoff, agree burned DEM (Digital Elevation Model) with road networks was suggested and the proper spatial resolution of DEM was identified finer than 15 m. To test the model applicability, 32 points on the road networks were selected and the hydrographs of each point were generated. The test showed reasonable results that increase the road runoff from the high elevation roads to the low elevation roads and the road runoff considering rainwater drainage from the road also showed reasonable results.

• Journal of Korean Elementary Science Education
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• v.35 no.2
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• pp.265-276
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• 2016

In this study, modeling pedagogies were employed to re-design and teach the unit of Seasonal Changes in the $6^{th}$ grade science curriculum. The effects of the modeling-based program were investigated in both the conceptual and affective domains using an approach of mixing quantitative and qualitative techniques. The result showed that the students in the modeling-based science inquiry classroom gained a higher mean score in a conceptual achievement test than their counterparts in a traditional science classroom. The number of the conceptual resources activated to explain the causes of the seasons, as well as the types of student explanations developed through the combination of the resources activated, were greater in the modeling-based classroom. The modeling-based science inquiry was also effective in improving student attitudes toward science lessons. It was revealed, however, that the students experienced both positive and negative epistemic feelings during the modeling-based science inquiry. Implications of these findings for science education and relevant research were suggested and discussed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.839-844
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• 2008

A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.22-27
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• 2006

This paper describes the development of the stream-tube based dispersion model for modeling contaminant transport in open channels. The operator-splitting technique is employed to separate the 2D contaminant transport equation into the pure advection and pure dispersion equations. Then the total variation diminishing (TVD) schemes are combined with the second-order Lax-Wendroff and third-order QUICKEST explicit finite difference schemes respectively to solve the pure advection equation in order to prevent the occurrence of numerical oscillations. Due to various limiters owning different features, the numerical tests for 1D pure advection and 2D dispersion are conducted to evaluate the performance of different TVD schemes firstly, then the TVD schemes are applied to experimental data for simulating the 2D mixing in a straight trapezoidal channel to test the model capability. Both the numerical tests and model application show that the TVD schemes are very competent for solving the advection-dominated transport problems.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.93-100
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• 2004

Test scheduling of SoC (System-on-a-chip) is very important because it is one of the prime methods to minimize the testing time under limited power consumption of SoC. In this paper, a heuristic algorithm, in which test resources are selected for groups and arranged based on the size of product of power dissipation and test time together with total power consumption in core-based SoC is proposed. We select test resource groups which has maximum power consumption but does not exceed the constrained power consumption and make the testing time slot of resources in the test resource group to be aligned at the initial position in test space to minimize the idling test time of test resources. The efficiency of proposed algorithm is confirmed by experiment using ITC02 benchmarks.