• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.121-123
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• 2002

The design of an air seat cushion for preventing decubitus ulcer includes many design factors such as the even distribution of interface pressure, the minimization of mean and peak interface pressure values, and the reduction of interface shear force and pressure gradient. It involves the anatomic condition of plegia's buttock as well as air pressure in air cells of cushion. As a result, a suitable design of the cushion satisfying the all requirements is a difficult problem. Therefore, an appropriate and effective numerical tool to develop an air cushion orthosis is required. The purpose of the present study was to develop an air seat cushion orthosis having optimized air cells for evenly distributed interface pressure between the buttock and cushion surface. For the purpose, an advanced finite element (FE) model for the design of air cushion was developed. Since the interface pressure and shear force behavior, as well as stress analyses were primary concern, a FE air cell model was developed and verified by the experiments. Then, the interactions of two cells were checked. Also, the human part of the developed numerical model includes every material property and geometry related to buttock and femoral parts. For construction of dimension data of buttock and femoral parts, CT scans were performed. A commercial FE program was employed for the simulation representing the seating process on the orthosis. Then, sensitive analyses were performed with varying design parameters. A set of optimal design parameters was found satisfying the design criteria of the orthosis. The results were utilized to produce a prototype of the orthosis. Experimentally, the buttock interface pressure distributions from the optimized and previous ones were compared. The new seat orthosis showed a significantly improved interface pressure characteristics compared to the most popular one in the market. The new orthosis will be used for the development of the AI(artificial intelligent) controlled seat orthosis fur prevention of decubitus ulcer fur various plegic patients and the elderly.

• Journal of Energy Engineering
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• v.28 no.4
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• pp.82-93
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• 2019

In this study, a new model is proposed to improve the problem of the decline of predict rate of heat demand on a particular date, such as a public holiday for the conventional heat demand forecasting system. The proposed model was the Four Season Mixed Heat Demand Prediction Neural Network Model, which showed an increase in the forecast rate of heat demand, especially for each type of forecast date (weekday/weekend/holiday). The proposed model was selected through the following process. A model with an even error for each type of forecast date in a particular season is selected to form the entire forecast model. To avoid shortening learning time and excessive learning, after each of the four different models that were structurally simplified were learning and a model that showed optimal prediction error was selected through various combinations. The output of the model is the hourly 24-hour heat demand at the forecast date and the total is the daily total heat demand. These forecasts enable efficient heat supply planning and allow the selection and utilization of output values according to their purpose. For daily heat demand forecasts for the proposed model, the overall MAPE improved from 5.3~6.1% for individual models to 5.2% and the forecast for holiday heat demand greatly improved from 4.9~7.9% to 2.9%. The data in this study utilized 34 months of heat demand data from a specific apartment complex provided by the Korea District Heating Corp. (January 2015 to October 2017).

• Applied Chemistry for Engineering
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• v.31 no.5
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• pp.532-538
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• 2020

In this study, emulsification process were conducted to manufacture the natural sunscreen from raw materials such as shea butter, olive emulsifier wax, and green tea extract. The emulsification was optimized by using the central composite design model-response surface methodology (CCD-RSM) where the response values were established as the mean droplet size (MDS) and emulsion stability index (ESI) after 7 days in addition to UV absorbance at 300nm. The amount of emulsifier and additives and emulsification time were established as operating variables and the optimal conditions of sunscreen emulsification were accepted as 3.70, 2.47 wt.%, and 15.42 min, respectively according to the result of CCD-RSM. On the other hand, the response values were estimated as 1173.80 nm and 99.56% for MDS and ESI, respectively, after 7 days, in addition to UV absorbance at 300 nm (2.47). The average error from actual experiments was a low level as about 3.0 ± 1.5%, which is mainly due to the fact that the optimization using CCD-RSM applied in this study was in the relatively high significant level.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.35 no.2
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• pp.79-89
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• 2009

The objective of this study was to find out the stable formulation of nano-emulsion containing high concentration of quercetin and to investigate the effect of an ethanol on the nano-emulsion prepared by POE (30) hydrogenated castor oil (HCO-30)/oil/quercetin/ethanol/water system. Nano-emulsion was prepared using emulsion inversion point (EIP) method as low-energy method plus homogenizer as high-energy method. To evaluate effect of ethanol and other components on the nano-emulsion, physical properties such as droplet size, morphology, and size distribution were determined. The optimal quercetin concentration was 0.2 % on the nano-emulsion. The droplet diameter was below 300 nm at the HCO-30 concentration below 2.00 %. Nano-emmulsion containing 4.75 % HCO-30 was the most stable and its mean droplet size was 172.40 nm. Finally, the size of nano-emulsion containing 4.00 % ethanol was 128.15 nm and size distribution was also narrow. The results showed that the breakdown process of this nano-emulsion could be attributed to Ostwald ripening. This study about effect of ethanol on the nano-emulsion showed that loading capacity of drug could be increased by using a small amount of ethanol. As prepared stable nano-emulsion, this study showed that these results could be applied to pharmaceutics, cosmetic including skin-care products, perfume and etc.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.275-285
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• 2017

National Meteorological Satellite Center(NMSC) has produced Sea Surface Temperature (SST) using Communication, Ocean, and Meteorological Satellite(COMS) data since April 2011. In this study, we have developed a new regional COMS SST algorithm optimized within the North-West Pacific Ocean area based on the Multi-Channel SST(MCSST) method and made a composite SST using polar orbit satellites as well as the COMS data. In order to retrieve the optimized SST at Northwest Pacific, we carried out a colocation process of COMS and in-situ buoy data to make coefficients of the MCSST algorithm through the new cloud masking including contaminant pixels and quality control processes of buoy data. And then, we have estimated the composite SST through the optimal interpolation method developed by National Institute of Meteorological Science(NIMS). We used four satellites SST data including COMS, NOAA-18/19(National Oceanic and Atmospheric Administration-18/19), and GCOM-W1(Global Change Observation Mission-Water 1). As a result, the root mean square error ofthe composite SST for the period of July 2012 to June 2013 was $0.95^{\circ}C$ in comparison with in-situ buoy data.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Applied Chemistry for Engineering
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• v.29 no.3
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• pp.283-288
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• 2018

As the use of environmentally friendly and non-disease natural pigments grows, various methods for extracting natural pigments have been studied. The natural color was extracted from parsley, a vegetable ingredient containing natural dyes. Target color codes of green series of natural dyes extracted as variables #50932C (L = 55.0, a = -40.0, b = 46.0) were set with the pH and temperature of extracted natural color coordinates (of the extracted), and the quantitative intensities of natural dyes were analyzed. During the colorimetric analysis predicted by the reaction surface analysis method, a color coordinate analysis was conducted under the optimal conditions of pH 8.0 and extraction temperature of $60.9^{\circ}C$. Under these conditions, predicted figures of L, a, and b were 55.0, -36.3, and 36.8, respectively, while actual experimental ones confirmed were 69.0, -35.9, and 31.4, respectively. In these results, the theory accuracy and actual error rate were confirmed to be 73.0 and 13.8%, respectively. The theoretical optimization condition of the color difference (${\Delta}E$) was at the pH of 9.2 and extraction temperature of $55.2^{\circ}C$. Under these conditions the predicted ${\Delta}E$ figure was 12.4 while the experimental one was 13.0. The difference in color analysis showed 97.5% of the theoretical accuracy and 4.5% of the actual error rate. However, the combination of color coordinates did not represent a desired target color, but rather close to the targeted color by means of an arithmetic mean. Therefore, it can be said that when the reaction surface analysis method was applied to the natural dye extraction process, the use of color coordinates as a response value can be a better method for optimizing the dye extraction process.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.5
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• pp.59-67
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• 2016

In landscape design by public institutions, although the costs and species of landscape trees stipulated by the Korean Public Procurement Service(PPS) are generally adhered to, the PPS regulations about planting trees with well-developed rootlets are almost entirely neglected. This study aimed to evaluate the performance of buried container modules, which are a new technology and product in landscape production that is able to reduce the defect rate while complying with regulations. To this end, this study measured rootlet density, rootlet development length, rootlet survival rate on excavation, and impairments of tree growth for 3 months after root pruning, and compared these variables for the container modules with those for trees that underwent root pruning in bare ground, and those that were cultivated in a container above ground. The results were as follows: First, the rootlet density was 88% for the trees in container modules, which was very high. Trees that underwent standard root pruning in bare ground had a somewhat lower density of 64%. Meanwhile, the trees that were cultivated in pots above ground died, invalidating measurement. Second, in terms of rootlet development and rootlet survival rate, the trees in container modules showed a mean length of 10.4cm, and 100% survival rate, indicating that there was no rootlet damage caused by excavation. For the trees that only underwent root pruning in bare ground, the mean length was 25.6cm and the rootlet survival rate was only half that of the trees in container modules, at 56%, demonstrating considerable damage. Rootlet development did not occur at all in the trees grown in pots. Third, the trees in container modules and those that underwent root pruning in bare ground did not show any deaths during the root pruning process, or any impairments such as stunted leaf growth. Conversely, the trees grown in pots nearly all died, and severe impairments of tree growth were observed. As shown by the results above, when we evaluated the performance of buried container modules, they showed the most outstanding performance of the three models tested in this study. The container modules prevent defects by stimulating early rooting in environments that with poor conditions for growth, or in trees that are not suited to the summer environment Therefore, it is expected that they would be an optimal means by which to enable compliance with rules such as the regulation presented by the PPS.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.1
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• pp.28-39
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• 2019

In the design process of counter measures against the beach erosion, information like the main sediment transport mode and yearly net amount of longshore and cross shore transport is of great engineering value. In this rationale, we numerically analyzed the yearly sediment budget of the Mang-Bang beach which is suffering from erosion problem. For the case of cross sediment transport, Bailard's model (1981) having its roots on the Bagnold's energy model (1963) is utilized. In doing so, longshore sediment transport rate is estimated based on the assumption that longshore transport rate is determined by the available wave energy influx toward the beach. Velocity moments required for the application of Bailard's model (1981) is deduced from numerical simulation of the nonlinear shoaling process over the Mang-Bang beach of the 71 wave conditions carefully chosen from the wave records. As a wave driver, we used the consistent frequency Boussinesq Eq. by Frelich and Guza (1984). Numerical results show that contrary to the Bailard's study (1981), Irribaren NO. has non negligible influence on the velocity moments. We also proceeds to numerically simulate the yearly sediment budget of Mang-Bang beach. Numerical results show that for ${\beta}=41.6^{\circ}$, the mean orientation of Mang-Bang beach, north-westwardly moving longshore sediment is prevailing over the south-eastwardly moving sediment, the yearly amount of which is simulated to reach its maxima at $125,000m^3/m$. And the null pint where north-westwardly moving longshore sediment is balanced by the south-eastwardly moving longshore sediment is located at ${\beta}=47^{\circ}$. For the case of cross shore sediment, the sediment is gradually moving toward the shore from the April to mid October, whereas these trends are reversed by sporadically occurring energetic wind waves at the end of October and March. We also complete the littoral drift rose of the Mang-Bang beach, which shows that even though the shore line is temporarily retreated, and as a result, the orientation of Mang-Bang beach is larger than the orientation of null pont, south-eastwardly moving longshore sediment is prevailing. In a case that the orientation of Mang-Bang beach is smaller than the orientation of null pont, north-westwardly moving longshore sediment is prevailing. And these trend imply that the Mang-Bang beach is stable one, which has the self restoring capability once exposed to erosion.