• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.7
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• pp.85-93
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• 2003

Droplet vaporization at various ambient pressures is studied numerically by formulating one dimensional evaporation model in the mixture of hydrocarbon fuel and air. The ambient pressure ranged from atmospheric conditions to the supercritical conditions. The modified Soave-Redlich-Kwong state equation is used to account for the real gas effects in the high pressure condition. Non-ideal thermodynamic and transport properties at near critical and supercritical conditions are considered. Some computational results are compared with Sato's experimental data for the validation of calculations. The comparison between predictions and experiments showed quite a good agreement. The droplet lifetime increases with increasing pressure at temperature lower than the critical temperature, however, it decreases with increasing pressure at temperature higher than the critical temperature. The solubility of nitrogen can not be neglected in the high pressure and it becomes higher as the temperature and the pressure go up.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.191-200
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• 2009

This paper, which consists of two parts, dealt with the parameter tuning of the power system stabilizer for a 612[MVA] thermal power plant in KEPCO system and its validation in field test. In Part 1 of the paper, the selection of parameters such as lead-lag time constants for phase compensation, system gain was optimized by using linear & eigenvalue analyses and they were verified through the time-domain transient stability analysis. In part 2, the performance of PSS was finally verified by the generator's on-line field test. Through the comparisons of simulation results and measured data before and after tuning of the PSS, the models of generator and its controllers including AVR, Governor and PSS used in the simulation are validated and confirmed.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.778-804
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• 2017

Software today has become an inseparable part of our life. In order to achieve the ever demanding needs of customers, it has to rapidly evolve and include a number of changes. In this paper, our aim is to study the relationship of object oriented metrics with change proneness attribute of a class. Prediction models based on this study can help us in identifying change prone classes of a software. We can then focus our efforts on these change prone classes during testing to yield a better quality software. Previously, researchers have used statistical methods for predicting change prone classes. But machine learning methods are rarely used for identification of change prone classes. In our study, we evaluate and compare the performances of ten machine learning methods with the statistical method. This evaluation is based on two open source software systems developed in Java language. We also validated the developed prediction models using other software data set in the same domain (3D modelling). The performance of the predicted models was evaluated using receiver operating characteristic analysis. The results indicate that the machine learning methods are at par with the statistical method for prediction of change prone classes. Another analysis showed that the models constructed for a software can also be used to predict change prone nature of classes of another software in the same domain. This study would help developers in performing effective regression testing at low cost and effort. It will also help the developers to design an effective model that results in less change prone classes, hence better maintenance.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.11
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• pp.339-344
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• 2020

During COVID-19, education industry is organizing the concept of 'Edutech', which has evolved one step further from the existing e-Learning, by introducing various intelligent information technologues based on the core technology of the 4th industrial revolution and spreading it through diverse contents. Meanwhile, each industries are creating new industries by applying new technology to existing businesses and ask for needs of cultivating human resources who understand the existing traditional ICT technology and industrial business which can solve a newly rising problems. However, it is difficult to build contents for cultivating such human resources with the existing e-learning of transferring knowledge by one-way or some two-way commnication system which has established some interactive conversational system. Accordingly, this study conducted a research on a cooperative e-learning system that enables educators to communicate with learners in real time and allows problem-solving education based on the existing two-way communication system. As a result, frame for contents and prototype was developedp and artially applied to the actual class and conducted an efficiency analysis, which resulted in the validation of being applied to the actual class as a simulation-based cooperative content.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Research in Plant Disease
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• v.21 no.2
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• pp.67-73
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• 2015

Bacterial blossom blight of kiwifruit (Actinidia deliciosa) caused by Pseudomonas syringae pv. syringae is known to be largely affected by weather conditions during the blooming period. While there have been many studies that investigated scientific relations between weather conditions and the epidemics of bacterial blossom blight of kiwifruit, no forecasting models have been developed thus far. In this study, we collected all the relevant information on the epidemiology of the blossom blight in relation to weather variables, and developed the Pss-KBB Risk Model that is based on the Maryblyt model for the fire blight of apple and pear. Subsequent model validation was conducted using 10 years of ground truth data from kiwifruit orchards in Haenam, Korea. As a result, it was shown that the Pss-KBB Risk Model resulted in better performance in estimating the disease severity compared with other two simple models using either temperature or precipitation information only. Overall, we concluded that by utilizing the Pss-KBB Risk Model and weather forecast information, potential infection risk of the bacterial blossom blight of kiwifruit can be accurately predicted, which will eventually lead kiwifruit growers to utilize the best practices related to spraying chemicals at the most effective time.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.85-95
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• 2013

As the conventional hydraulic power steering system in the passenger vehicles is being rapidly replaced by EPS (Electric Power Steering) system, performance evaluation of the EPS system has become an important issue in the automotive industries. But the evaluation process takes significant expertise since steering conditions in the test protocols must be implemented with high accuracy. EPS HILS (Hardware-In the-Loop Simulation) system is developed together with robot steering system in this study. Main components of EPS HILS system include: C-EPS hardware, CarSim vehicle model, and road reaction force generation system powered by servo motor. The robot steering system, operated by another servo motor, was combined with EPS HILS system to substitute for steering efforts of human driver. The road reaction force generation system and the robot steering system were carefully validated by using the data obtained from vehicle tests. An on-center handling test was conducted by using EPS HILS system combined with the robot steering system. In the result of this study, robot-steered EPS HILS system developed with its high reliability and no need of skilled driver's, can be widely adopted to evaluate any performance of EPS system.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.35-41
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• 2017

This paper presents the development of a monitoring and control system for a vehicle cluster using a model-based design technique. For MBD(model-based design), MATLAB GUI(Graphic User Interface), M programs, simulink, state flow, and tool boxes are used to monitor a number of data such as warning, interrupts, and etc. connected to a real vehicle cluster. As a monitoring tool, a PC(Personal Computer) station interworks with the real vehicle cluster through the interface commands of tool boxes. Thus, unlike existing text-based designs, the MBD based vehicle cluster system provides very easy algorithm updates and addition, since it offers a number of blocks and state flow programs for each functional actions. Furthermore, the proposed MBD technique reduces the required time and cost for the development and modification of a vehicle cluster, because of verification and validation of the cluster algorithm on the monitor through a PC.

• Experimental and Molecular Medicine
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• v.50 no.11
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• pp.7.1-7.12
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• 2018

Recent findings from The Cancer Genome Atlas project have provided a comprehensive map of genomic alterations that occur in hepatocellular carcinoma (HCC), including unexpected mutations in apolipoprotein B (APOB). We aimed to determine the clinical significance of this non-oncogenetic mutation in HCC. An Apob gene signature was derived from genes that differed between control mice and mice treated with siRNA specific for Apob (1.5-fold difference; P < 0.005). Human gene expression data were collected from four independent HCC cohorts (n = 941). A prediction model was constructed using Bayesian compound covariate prediction, and the robustness of the APOB gene signature was validated in HCC cohorts. The correlation of the APOB signature with previously validated gene signatures was performed, and network analysis was conducted using ingenuity pathway analysis. APOB inactivation was associated with poor prognosis when the APOB gene signature was applied in all human HCC cohorts. Poor prognosis with APOB inactivation was consistently observed through cross-validation with previously reported gene signatures (NCIP A, HS, high-recurrence SNUR, and high RS subtypes). Knowledge-based gene network analysis using genes that differed between low-APOB and high-APOB groups in all four cohorts revealed that low-APOB activity was associated with upregulation of oncogenic and metastatic regulators, such as HGF, MTIF, ERBB2, FOXM1, and CD44, and inhibition of tumor suppressors, such as TP53 and PTEN. In conclusion, APOB inactivation is associated with poor outcome in patients with HCC, and APOB may play a role in regulating multiple genes involved in HCC development.

• Journal of agriculture & life science
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• v.44 no.5
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• pp.101-107
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• 2010

The objective of this study was to assess the statistics and associated criteria for field-scale model used to simulate nutrient concentrations in paddy field. CREAMS-PADDY, a modified version of the field-scale CREAMS model, simulates the hydrologic, sediment, and nutrient cycles in paddy fields was applied in this study. The model was calibrated and validated using data from study rice paddy fields in Republic of Korea. The calibration statistics include mean and the minimum-maximum range associated with a "temporal window" that spans a period of several days. Because nutrient concentrations in paddy filed are typically sampled infrequently (on a weekly basis, at best) and represent only an instant in time, it is not reasonable to expect any model to simulate a daily average concentration equal to an observed value on a particular day. The 5-day window and related calibration statistics were applied in this study and the applicability of this concept was tested for field-scale water quality model. As a result of calibration and validation, the ponded water nutrient concentration values showed only small changes except the fertilization period. Because of the small changes in ponded water concentration, the size of 5-day window was too small to capture the observed values. Further study is required to establish the 5-day window calibration method for field-scale water quality modeling.