• Food Science and Preservation
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• v.18 no.6
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• pp.891-897
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• 2011

Oak barrel have been used for a long time for the aging of wine. Instead of oak barrel aging, however, roasted oak chips can be directly added in the wine before aging. In this study, Korean oak chips roasted for different time durations were used for the red wine aging, and the properties of wine aged through the addition of the roasted oak chips were characterized. No significant differences were observed in the alcohol, soluble-solid, reducing-sugar and total-acid contents based on the oak chips aging, but the total phenol content increased. The methanol, ethyl acetate, propanol, isobutanol and isoamyl alcohol contents also increased. Especially, the methanol and propanol contents increased as the roasting time was prolonged. Although the hue values were similar to one another, the intensity as well as the lightness, redness, and yellowness values were high in the wine aged with the roasted oak chips. In the sensory evaluation, the wine aged with oak chips roasted for 2 h showed the highest scores in the flavor, taste, and overall preference.

• Journal of Soil and Groundwater Environment
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• v.14 no.4
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• pp.45-53
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• 2009

This study concerned remediation of heavy metal contaminated farmland soils near abandoned mine, using stabilization method, with particular emphasis on the remediating the soils contaminated with multi-elements. In this study, stabilizing heavy metals based on 'In-situ chemical fixation' has been applied to the soil collected from an abandoned mine in Korea, using column test, with various stabilizing agents, including $FeSO_4$, $KMnO_4$, sludge (collected from coal mine drainage treatment pond), zero-valent iron (ZVI), zeolite and $CaCO_3$. Sixty five-days operation of the flow-through columns yield $FeSO_4\;+\;KMnO_4$ and zeolite are efficient on reducing As leaching from the soil. ZVI and sludge are reducing the leaching of Cu. Although $FeSO_4\;+\;KMnO_4$ seem to be efficient for most heavy metals, high pH in the initial stage of test enabled high leaching of the heavy metals, whereas fixation of the heavy metals maintain throughout the rest of the test period, with increasing pH up to around 6. Addition of some alkaline agent may inhibit the low pH during the application. The column test was also run as two set: one set incubated with deionized water for 72 hours prior to starting the test, and the other without incubation. The incubated set demonstrated better stabilizing efficiency, indicating the potential optimized operation method.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.861-870
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• 2021

In this study, fused Aerosol Optical Depth (AOD) data were produced using AOD products from the Geostationary Ocean Color Imager (GOCI) onboard Communication, Oceanography and Meteorology Satellite (COMS)satellite and the Advanced Himawari Imager (AHI) onboard Himawari-8. Since the spatial resolution and the coordinate system between the satellite sensors are different, a preprocessing was first preceded. After that, using the level 1.5 AOD dataset of AErosol RObotic NETwork (AERONET), which is ground-based observation, correlations and trends between each satellite AOD and AERONET AOD were utilized to produce more accurate satellite AOD data than the originalsatellite AODs. The fused AOD were found to be more accurate than the originalsatellite AODs. Root Mean Square Error (RMSE) and mean bias of the fused AODs were calculated to be 0.13 and 0.05, respectively. We also compared errors of the fused AODs against those of the original GOCI AOD (RMSE: 0.15, mean bias: 0.11) and the original AHI AOD (RMSE: 0.15, mean bias: 0.05). It was confirmed that the fused AODs have betterspatial coverage than the original AODsin areas where there are no observations due to the presence of cloud from a single satellite.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.393-400
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• 2021

Body weight of livestock is a crucial indicator for assessing feed requirements and nutritional status. This study was performed to estimate the body weight of Korean cattle (Hanwoo) using body volume determined from three-dimensional (3-D) image. A TOF camera with a resolution of 640×480 pixels, a frame rate of 44 fps and a field of view of 47°(H)×37°(V) was used to capture the 3-D images for Hanwoo. A grid image of the body was obtained through preprocessing such as separating the body from background and removing outliers from the obtained 3-D image. The body volume was determined by numerical integration using depth information to individual grid. The coefficient of determination for a linear regression model of body weight and body volume for calibration dataset was 0.8725. On the other hand, the coefficient of determination was 0.9083 in a multiple regression model for estimating body weight, in which the age of Hanwoo was added to the body volume as an explanatory variable. Mean absolute percentage error and root mean square error in the multiple regression model to estimate the body weight for validation dataset were 8.2% and 24.5kg, respectively. The performance of the regression model for weight estimation was improved and the effort required for estimating body weight could be reduced as the body volume of Hanwoo was used. From these results obtained, it was concluded that the body volume determined from 3-D of Hanwoo could be used as an effective variable for estimating body weight.

• Journal of the Korea Society for Simulation
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• v.30 no.3
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• pp.1-9
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• 2021

Commander and staffs on the battlefield are aware of the situation and, based on the results, they perform military activities through their military decisions. Recently, with the development of information technology, the demand for artificial intelligence to support military decisions has increased. It is essential to identify, collect, and pre-process the data set for reinforcement learning to utilize artificial intelligence. However, data on enemies lacking in terms of accuracy, timeliness, and abundance is not suitable for use as AI learning data, so a training model is needed to collect AI learning data. In this paper, a methodology for learning artificial intelligence was presented using the constructive wargame model exercise data. First, the role and scope of artificial intelligence to support the commander and staff in the military decision-making process were specified, and to train artificial intelligence according to the role, learning data was identified in the Chang-Jo 21 model exercise data and the learning results were simulated. The simulation data set was created as imaginary sample data, and the doctrine of ROK Army, which is restricted to disclosure, was utilized with US Army's doctrine that can be collected on the Internet.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1181-1194
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• 2018

This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.295-302
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• 2018

Face recognition (FR) has been widely used in various applications, such as smart surveillance systems, immigration control in airports, user authentication in smart devices, and so on. FR in well-controlled conditions has been extensively studied and is relatively mature. However, in unconstrained conditions, FR performance could degrade due to undesired characteristics of the input face image (such as irregular facial pose variations). To overcome this problem, this paper proposes a new method for determining if an input image is suitable for FR. In the proposed method, for an input face image, reconstruction error is computed by using a predefined set of reference face images. Then, suitability can be determined by comparing the reconstruction error with a threshold value. In order to reduce the effect of illumination changes on the determination of suitability, a preprocessing algorithm is applied to the input and reference face images before the reconstruction. Experimental results show that the proposed method is able to accurately discriminate non-frontal and/or incorrectly aligned face images from correctly aligned frontal face images. In addition, only 3 ms is required to process a face image of $64{\times}64$ pixels, which further demonstrates the efficiency of the proposed method.

• Analytical Science and Technology
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• v.32 no.1
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• pp.7-16
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• 2019

The objective of this study was the development of a discrimination model for the cultivational origin of paper mulberry bast fiber and Hanji using near infrared (NIR) and mid infrared (MIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA). Paper mulberry bast fiber was purchased in 10 different regions of Korea, and used to make Hanji. PLS-DA was performed using pre-treated FT-NIR and FT-MIR spectral data for paper mulberry bast fiber and Hanji. PLS-DA of paper mulberry bast fiber and Hanji samples, using FT-NIR spectral data, showed 100 % performance in cross validation and the confusion matrix (accuracy, sensitivity, and specificity). The discrimination models showed four regional groups which demonstrated clearer separation and much superior score plots in the NIR spectral data-based model than in the MIR spectral data-based model. Furthermore, the discrimination model based on the NIR spectral data of paper mulberry bast fiber had highly similar score morphology to that of the discrimination model based on the NIR spectral data of Hanji.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1383-1398
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• 2018

Sea surface wind is one of the most fundamental variables for understanding diverse marine phenomena. Although scatterometers have produced global wind field data since the early 1990's, the data has been used limitedly in oceanic applications due to it slow spatial resolution, especially at coastal regions. Synthetic Aperture Radar (SAR) is capable to produce high resolution wind field data. KOMPSAT-5 is the first Korean satellite equipped with X-band SAR instrument and is able to retrieve the sea surface wind. This study presents the validation results of sea surface wind derived from the KOMPSAT-5 backscattering coefficient data for the first time. We collected 18 KOMPSAT-5 ES mode data to produce a matchup database collocated with buoy stations. In order to calculate the accurate wind speed, we preprocessed the SAR data, including land masking, speckle noise reduction, and ship detection, and converted the in-situ wind to 10-m neutral wind as reference wind data using Liu-Katsaros-Businger (LKB) model. The sea surface winds based on XMOD2 show root-mean-square errors of about $2.41-2.74m\;s^{-1}$ depending on backscattering coefficient conversion equations. In-depth analyses on the wind speed errors derived from KOMPSAT-5 backscattering coefficient data reveal the existence of diverse potential error factors such as image quality related to range ambiguity, discrete and discontinuous distribution of incidence angle, change in marine atmospheric environment, impacts on atmospheric gravity waves, ocean wave spectrum, and internal wave.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.157-179
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• 2019

The Seoul's 2030 Youth-Housing has been regarded as the only option to procure rental housing sites in downtown Seoul. But its supply did not catch up with the initial expectation, and the criticism that it may disrupt the current zoning system of the city has persisted. Consequently, the 2030 Youth-Housing policy has undergone amendments for six times within the last three years, and the significant changes in its guideline also have been made within the last one year. The study, in this context, tries to figure out the tendencies of those changes made in the guidelines so far by analyzing the aspects of the parcels allowable for Youth-Housing as well as the areas allowable for up-zoning. In the process, the propositional logic is to be adopted to draw the scope of the buildable areas for Youth-Housing. For this, the study refines the raw GIS data, inputs the values for each proposition, and proceeds the logical operation to judge every parcel of the city to discern whether it is eligible for a buildable site and/or for up-zoning for Youth-Housing. It is seen that: 1) the buildable sites rather evenly distribute around the peripheral subway-station areas while more concentrating on the quasi-residential and commercial areas; and 2) the areas eligible for up-zoning have the tendency to concentrate more on quasi-residential areas than others.