• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1300-1312
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• 2019

BSTRACT In this paper, PM10 forecast model using DNN(Deep Neural Network) is developed for Seoul region. The previous Julian forecast model has been developed using weather and air quality data of Seoul region only. This model gives excellent results for accuracy and false alarm rates, but poor result for POD(Probability of Detection). To solve this problem, an WA(Wide Area) forecasting model that uses Chinese data is developed. The data is highly correlated with the emergence of high concentrations of PM10 in Korea. As a result, the WA model shows better accuracy, and POD improving of 3%(D+0), 21%(D+1), and 36%(D+2) for each forecast period compared with the Julian model.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.7
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• pp.406-412
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• 2013

A hybrid heat pump is under development with the goal of utilizing 120% of primary energy resources. A plate heat exchanger is added between the compressor and air-cooled condenser of an ordinary heat pump to heat water. For successful operation of the heat pump, it is necessary to develop a control algorithm under various operating conditions. As a virtual test bed for that purpose, a dynamic model has been developed, to simulate its dynamic behavior. It was modeled in transient one-dimensions, with varying phase lengths considered. The model was implemented in Matlab and Simulink. Simulation results were effectively applied to design a control algorithm. They also provided physical insight into how to design and operate the system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.10
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• pp.710-718
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• 2010

A numerical study was performed to predict refrigerant charge amount in a mini-channel condenser for a R410A residential air-conditioning system. Multi-channel flat tubes with 12 mini-channels of 1.17 mm average hydraulic diameter for each tube were applied to the condenser. The condenser consisted of 3 passes, and the first, second, and third pass had 44, 19, and 11 tubes, respectively. Each pass was connected by a vertical header. In this study, the condenser was divided into 410 finite volumes, and analyzed by an $\varepsilon$-NTU method. With thermophysical properties and void fraction models for each volume element, the R410A amount distribution and a total charge amount in the condenser were calculated. The predicted total charge amount was compared with the experimentally measured charge amount under a standard ARI A condition. The developed model could predict the charge amount in the mini-channel condenser within prediction errors from -23.9% to -3.0%. Air velocity distribution at the condenser face was considered as non-uniform and uniform by the simulation model, and its results showed that the air velocity distribution could significantly influence the charge amount and vapor phase distribution in the condenser.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.

• Agricultural and Biosystems Engineering
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• v.3 no.2
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• pp.65-72
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• 2002

Temperature is the most influential environment parameter which affects the quality change of agricultural products in cold storage. Therefore, it is essential to keep the uniform temperature distribution in the storage room. This study was performed to analyze the air movement and temperature distribution in the forced recirculating cold storage facility and to simulate optimum storage method of green groceries using 3-D CFD(three dimensional computational fluid dynamics) computer simulation which applied the standard $textsc{k}$-$\varepsilon$ turbulence model and FVM(finite volume method). The simulation was validated by the experimental results for onion storage and the simulation model was used to simulate the temperature and velocity distribution in the storage room with reference to the change of storage method such as location of storage, no stores, bulk storage, and pallet storage. In case of no stores, internal airflow was circulated without stagnation and consequently air movement and temperature distribution were uniform. In case of bulk storage, air movement was stagnated so much and temperature distribution of onion was not uniform. Furthermore, the inner temperature of onion roses more than the initial temperature of storage. In case of pallet storage, air movement and temperature distribution of onion were so uniform that the danger of quality change was decreased.

• Journal of the korean Society of Automotive Engineers
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• v.5 no.3
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• pp.33-44
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• 1983

This paper deals with the experimental study on the behavior of fuel (methanol) in intake manifold by using the basic apparatus which is manufactured the visible straight tube type model. In this study, the new device for liquid film thickness measurement and vaporization rate measurement are introduced to investigate the variation of liquid film thickness along the intake manifold and to observe the effect of vaporization of injected fuel. the results are summarized as follows: 1) The vaporization rate increases in proportion to decreasing of throttle valve angle and growing air fuel ratio. 2) The liquid film thickness along the intake manifold is mostly independent for the throttle valve angle in low air velocity and then affected in high air velocity, but the distribution of the liquid film thickness on circumferential position almost constant in the region of 300mm down stream from carburetor. 3) The mean liquid film thickness is 0.04 - 0.18mm in case of methanol in the region of air velocity Va = 12m/s - 55m/s and decreases with decreasing the throttle valve angle.

• Asian Journal of Atmospheric Environment
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• v.8 no.1
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• pp.25-34
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• 2014

In winter 2013, extreme air pollution by fine particulate matter ($PM_{2.5}$) in China attracted much public attention. In order to simulate the $PM_{2.5}$ pollution, the Community Multiscale Air Quality model driven by the Weather Research and Forecasting model was applied to East Asia in a period from 1 January 2013 to 5 February 2013. The model generally reproduced $PM_{2.5}$ concentration in China with emission data in the year 2006. Therefore, the extreme $PM_{2.5}$ pollution seems to be mainly attributed to meteorological (weak wind and stable) conditions rather than emission increases in the past several years. The model well simulated temporal and spatial variations in $PM_{2.5}$ concentrations in Japan as well as China, indicating that the model well captured characteristics of the $PM_{2.5}$ pollutions in both areas on the windward and leeward sides in East Asia in the study period. In addition, contribution rates of four anthropogenic emission sectors (power generation, industrial, residential and transportation) in China to $PM_{2.5}$ concentration were estimated by conducting zero-out emission sensitivity runs. Among the four sectors, the residential sector had the highest contribution to $PM_{2.5}$ concentration. Therefore, the extreme $PM_{2.5}$ pollution may be also attributed to large emissions from combustion for heating in cold regions in China.

• Journal of Radiation Protection and Research
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• v.19 no.1
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• pp.69-80
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• 1994

The TCMI(Three-Compartment Model for iodine) computer code has been developed, which is based on the three-compartment model and the respiratory model recommended in ICRP publication 54. This code is able to evaluate the thyroid burden, dose equivalent, committed dose equivalent and urinary excretion rate as time-dependent functions from the input data: working time and the radioiodine concentration in air. Using the TCMI code, the time-dependent thyroid burdens, the thyroid doses and the urinary excretion rates were calculated for three specific exposure patterns : acute, chronic and periodic. Applicability as an internal dose evaluation method has been assessed by comparing the results with some operational experiences. Simple equations and tables are provided to be used in the evaluation of the thyroid burden and the resulting doses for given I-131 concentration in air and the working time.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.5
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• pp.475-481
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• 2004

This paper presents a force model of the clean tube system, which was developed as a means of transferring air-floated wafers inside a closed tube filled with super clean air. The recovering force from the holes for floating wafers is modeled as a linear spring and thus the wafers motion is modeled as a mass-spring-damper system. The propelling forces are modeled as linear along with the wafer location. The paper also proposes a control method to emit and stop a wafer at the center of a control unit. It reveals the minimum value of the propelling force to leave from the control unit. In order to stop the wafer, it utilizes the exact time when the wafer arrives at the position to activate the propelling force. Experiments with the clean tube system built for the 12 inch wafer shows the validity of the proposed model and the algorithm.

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.70-78
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• 2020

Nitrox diving was introduced by the NOAA (National Oceanic and Atmospheric Administration) to increase the oxygen content and lower the nitrogen content in respiratory gases. The commercial diving sector specializing in underwater operations has recently introduced regulations on the use of Nitrox. Because the respiratory gas for Nitrox diving has a lower nitrogen content than the normal air, the amount of nitrogen dissolved in the body is small, which not only significantly reduces the decompression time compared to air diving, but also reduces the chance of exposure to decompression sickness. In this study, we applied the VPM (Varying Permeability Model) algorithm to virtual diving with air and Nitrox as a respiratory gas, respectively, to study the optimal Nitrox diving for the safety at the underwater works. The results showed that Nitrox diving had a longer NDL (No-Decompression Limit), a much shorter depression time. In other words, Nitrox diving in underwater works is safer from decompression sickness than commonly used air diving.