• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.271-280
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• 2018

Recently, big data has been growing rapidly due to the development of IT technology. Especially in the medical field, big data is utilized to provide services such as patient-customized medical care, disease management and disease prediction. In Korea, 'National Health Alarm Service' is provided by National Health Insurance Corporation. However, the prediction model has a problem of short-term prediction within 3 days and unreliability of social data used in prediction model. In order to solve these problems, this paper proposes a disease prediction model using medicine prescription data generated from actual patients. This model predicts the total number of patients and the risk of disease in each region and uses the ARIMA model for long-term predictions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.45-54
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• 2012

In order to predict trailing edge noise from a flat plate more effectively and accurately, the prediction algorithm based on semi-analytic model for point pressure spectrum is proposed. The semi-analytic model consists of empirical models for point pressure spectra and theoretical model to determine the boundary layer characteristics needed for the empirical models. The proposed methods are applied to predict the trailing edge noise of the flat plate located in the mean flow of speed 38 m/s, for which the measured data are available. In present study, six empirical models for point pressure spectra are utilized for the predictions of trailing edge noise and their prediction results are compared to the measured data. Through the analysis of these comparisons, it is revealed that the present method based on non-frozen formula using Efimtsov model and Smol'yakov-Tkachenko model can provide more accurate and efficient predictions of trailing edge noise.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.5
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• pp.526-534
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• 2004

A new second-moment closure model for turbulent heat fluxes is proposed on the basis of the elliptic equation. The new model satisfies the near-wall balance between viscous diffusion, viscous dissipation and temperature-pressure gradient correlation, and also has the characteristics of approaching its respective conventional high Reynolds number model far away from the wall. The predictions of turbulent heat transfer in a channel flow have been carried out with constant wall heat flux and constant wall temperature difference boundary conditions respectively. The velocity field variables are supplied from the DNS data and the differential equations only fur the mean temperature and the scalar flux are solved by the present calculations. The present model is tested by direct comparisons with the DNS to validate the performance of the model predictions. The prediction results show that the behavior of the turbulent heat fluxes in the whole region is well captured by the present model.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.89-96
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• 2016

The mechanism for laminar dust flame propagation can only be elucidated from a comprehensive mathematical model which incorporates conduction and radiation, as well as the chemical kinetics of particle devolatilization and gas phase and char reaction. The mathematical model for a flat, laminar, premixed coal-air flame is applied to the atmospheric coal-air mixtures studied by Smoot and co-workers, and comparisons are made with their measurements and predictions. Here the principal parameter for comparison is the laminar burning velocity. The studies of Smoot and co-workers are first reviewed and compared with those predicted by the present model. The effects of inlet temperature and devolatilization rate constants on the burning velocities are studied with the present model, and compared with their measurements and predictions. Their measured burning velocities are approximately predicted with the present model at relatively high coal concentrations, with a somewhat increased inlet temperature. From the comparisons, their model might over-estimate particle temperature and rates of devolatilization. This would enable coal-air mixtures to be burned without any form of preheat and would tend to increase their computed values of burning velocity.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.6
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• pp.524-534
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• 2012

In order to predict trailing edge noise from a flat plate more effectively and accurately, the prediction algorithm based on semi-analytic model for point pressure spectrum is proposed. The semi-analytic model consists of empirical models for point pressure spectra and theoretical model to determine the boundary layer characteristics needed for the empirical models. The proposed methods are applied to predict the trailing edge noise of the flat plate located in the mean flow of speed 38 m/s, for which the measured data are available. In present study, six empirical models for point pressure spectra are utilized for the predictions of trailing edge noise and their prediction results are compared to the measured data. Through the analysis of these comparisons, it is revealed that the present method based on non-frozen formula using Efimtsov model and Smol'yakov-Tkachenko model can provide more accurate and efficient predictions of trailing edge noise.

• Particle and aerosol research
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• v.20 no.3
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• pp.103-114
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• 2024

Liquid-spray cleaning has recently been considered an eco-friendly cleaning method in the semiconductor industry because it efficiently cleans contaminated wafers without using any chemicals, relying instead on direct momentum transfer through dropwise impaction. Previous researches are mainly divided into two groups, such as modelling studies predicting the cleaning effect of single-droplet impact and experimental works for measuring particle removal efficiency (PRE) that essentially accompanies multiple droplet impacts. Here, we developed a Monte Carlo model to connect the single-droplet based model to the ensemble effect of multiple droplet impacts in real cleaning experiments, and thereby predict the PREs from the impaction conditions of droplets and the diameters of target particles. Additionally, we developed a two-fluid supersonic nozzle system, capable of spraying 10-60 ㎛ droplets under control of impact velocity, with aims to validate the model predictions of PREs for 15-130 nm contaminant particles on a Si wafer. We confirmed that the model predictions are in agreement with the experimental data within 7% and the cleaning time needs to be controlled for ensuring the efficient removal of particles.

• Tribology and Lubricants
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• v.31 no.6
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• pp.294-301
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• 2015

In this paper, we predict the rotordynamic force coefficients of tilting pad journal bearings (TPJBs) with rocker-back pivots, and we compare the predictions to recently published predictions and test data. The present TPJB model considers the rocker-back pivot stiffness calculated based on the Hertzian contact-stress theory, which is nonlinear with the application of a force . For the five-pad TPJB in load-between-pad and load-on-pad configurations, the predictions show the pressure- and film-thickness distributions, the deflection and stiffness of the individual pivots, and bearing stiffness and damping coefficients. The minimum film thickness and peak pressure occur at the bottom pad on which the applied load is directed. Because of the preload, the pres- sure is positive even at the upper pad in the opposite direction to the applied load. The pivot deflection and stiff- ness are maximum at the bottom pad that receives the heaviest pressure load. The predicted stiffness coefficients increase as the static load and rotor speed increase, while the damping coefficients decrease as the rotor speed increases, but increase as the static load increases. In general, the predicted stiffness coefficients agree well with the test data. The predicted damping coefficients overestimate the test data, particularly for large static loads. In general, the current predictive model considering the pivot stiffness improves the accuracy of the rotordynamic performance compared to previously reported models.

• Journal of Soil and Groundwater Environment
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• v.21 no.4
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• pp.30-41
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• 2016

The amount of groundwater related data is drastically increasing domestically from various sources since 2000. To justify the more expansive continuation of the data acquisition and to derive valuable implications from the data, continued employments of sophisticated and state-of-the-arts statistical tools in the analyses and predictions are important issue. In the present study, we employed a well established machine learning technique of Gaussian Process Regression (GPR) model in the trend analyses of groundwater level for the long-term change. The major benefit of GPR model is that the model provide not only the future predictions but also the associated uncertainty. In the study, the long-term predictions of groundwater level from the stations of National Groundwater Monitoring Network located within Han River Basin were exemplified as prediction cases based on the GPR model. In addition, a few types of groundwater change patterns were delineated (i.e., increasing, decreasing, and no trend) on the basis of the statistics acquired from GPR analyses. From the study, it was found that the majority of the monitoring stations has decreasing trend while small portion shows increasing or no trend. To further analyze the causes of the trend, the corresponding precipitation data were jointly analyzed by the same method (i.e., GPR). Based on the analyses, the major cause of decreasing trend of groundwater level is attributed to reduction of precipitation rate whereas a few of the stations show weak relationship between the pattern of groundwater level changes and precipitation.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.233-241
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• 1987

Difficulties are encountered when the behavior of complex systems (i.e., fuel failure probability) that have unreliable deterministic models is predicted. For more realistic prediction of the behavior of complex systems with limited observational data, the present study was undertaken to devise an approach of combining predictions from the deterministic model and actual observational data. Predictions by this method of combining are inferred to be of higher reliability than separate predictions made by either model taken independently. A systematic method of hierarchical pattern discovery based on the method developed in the SPEAR was used for systematic search of weighting factors and pattern boundaries for the present method. A sample calculation was performed for prediction of CANDU fuel failures that had occurred due to power ramp during refuelling process. It was demonstrated by this sample calculation that there exists a region of feature space in which fuel failure probability from the PROFIT model nearly agree with that from observational data.

• Tribology and Lubricants
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• v.40 no.1
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• pp.28-37
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• 2024

This paper presents the development of a squeeze film damper (SFD) test rig and experimental identification of the effects of clearance, damper length, journal eccentricity ratio, excitation amplitude, oil supply pressure, and oil flow rate on the damping coefficients of a test SFD with open ends and a central groove. Test data are compared with predictions from a simple model developed for short SFDs with open ends and a central groove. The test results show a significant decrease in the damping coefficient with increasing clearance and a dramatic increase with damper length, which are in good agreement with the simple model predictions. According to the simple model, the damping coefficient is inversely proportional to the cube of the clearance and directly proportional to the cube of the length. An increase in the journal eccentricity ratio results in a dramatic increase in the damping coefficient by as much as 15 times that of the concentric case, particularly at low excitation frequencies. By contrast, the measured damping coefficient remains almost constant with changes in the excitation amplitude and supply pressure, which are not major factors in the damper design. In general, the test data agree well with the simple model predictions, excluding cases that show increases in the SFD length and journal eccentricity, which indicate significant dependency on the excitation frequency.