• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.3
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• pp.255-264
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• 2022

The active ingredients of Napttegi Kong(GML, Glycine max landrace), a type of native rare soybeans, were identified, and an ultrasonic extraction method was introduced as an eco-friendly extraction method. Through the component analysis of the Napttegi Kong extract, the epicatechin, which was not found in conventional soybeans, was identified. For effective extraction using ultrasonic, the main extraction conditions were optimized using the response surface analysis method. Through the Box-Behnken design process, 15 experiments were conducted with the extraction temperature, the ratio of extraction solvent/solution, and extraction time as key independent variables. A quadratic regression equation for the two dependent variables, epicatechin content and total isoflavone content, was derived, and the coefficients of determination were found to be high as R² = 0.9939 and R² = 0.9844, respectively, confirming that the correlation showed high significance. The extraction conditions satisfying the maximum expectations of these two dependent variables were predicted. to be 40.4℃ of extraction temperature, 19.3 times of extraction solvent/solution, and 91 sec of extraction time. The expected value and the actual experimental value of the epikatechin content and the total isoflavone content were similar, so it was confirmed that this experimental method is a highly reliable optimization model.

• Korean Journal of Ichthyology
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• v.19 no.1
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• pp.1-7
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• 2007

The effect of water temperature (T) and body weight (W) on the oxygen consumption of the fasted black rockfish, Sebastes schlegeli was investigated to provide empirical data for the culture management and bioenergetic growth model of this species. The mean wet body weights of two fish groups used for the present experiment were $12.9{\pm}2.7g$ ($mean{\pm}SD$) and $351.1{\pm}9.2g$. The oxygen consumption rate (OCR) was measured under three water temperature regimes (15, 20 and $25^{\circ}C$) at an interval of 5 minutes for 24 hours using a continuous flow-through respirometer. In each treatment three replicates were set up and 45 fish in small size groups and 6 fish in large size groups were used. The OCRs increased with increasing water temperature in both size groups (p<0.001). Mean OCRs at 15, 20 and $25^{\circ}C$ were 414.2, 691.5 and $843.8mg\;O_2\;kg^{-1}h^{-1}$ in small size groups, and 182.0, 250.7 and $328.2mg\;O_2\;kg^{-1}h^{-1}$ in large size groups, respectively. The OCRs decreased with increasing body weights in three water temperature groups (p<0.001). The mass effect on metabolic rate can be expressed by the power of 0.69~0.75. The data are best described by the relationship: OCR=89.12+28.79T-1.17W. $Q_{10}$ values ranged 1.90~2.79 between 15 and $20^{\circ}C$, 1.49~1.71 between 20 and $25^{\circ}C$, and 1.80~2.03 over the full temperature range, respectively. The energy loss by metabolic cost increased with increasing water temperature and decreasing body weight (p<0.001). Mean energy loss rates by oxygen consumption at 15, 20 and $25^{\circ}C$ were 282.9, 472.3 and $576.3kJ\;kg^{-1}d^{-1}$ in small size groups and 124.3, 171.3 and $224.1kJ\;kg^{-1}d^{-1}$ in large size groups, respectively.

• Journal of the Korean Geotechnical Society
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• v.39 no.5
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• pp.51-63
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• 2023

Numerical analysis was conducted to determine the effect of soil behavior by thawing and freezing of seasonal frozen soil on pile foundations. The analysis was performed using the finite element method (FEM) to simulate soil-pile interaction based on the atmosphere temperature change. Thermomechanical coupled modeling using FEM was applied with the temperature-dependent nonlinear properties of the frozen soil. The analysis model cases were applied to the MCR and HDP models to simulate the elastoplastic behavior of soil. The numerical analysis results were analyzed and compared with various conditions having different length and width sizes of the pile. The results of the numerical analysis showed t hat t he HDP model was relat ively passive, and t he aspect and magnit ude of t he bearing capacit y and displacement of the pile head were similar depending on the length and width of the pile conditions. The vertical displacement of the pile head by thawing and freezing of the ground showed a large variation in displacement for shorter length conditions. In the MCR model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0387 and 0.0277 m, respectively. In the HDP model, the vertical displacement appeared in the maximum thaw settlement and frost heaving of 0.0367 and 0.0264 m, respectively. The results of the pile bearing capacity for the two elastoplastic models showed a larger difference in the width condition than the length condition of the pile, with a maximum of about 14.7% for the width L condition, a maximum of about 5.4% for M condition, and a maximum of about 5.3% for S condition. The significance of the effect on the displacement of the pile head and the bearing capacity depended on the pile-soil contact area, and the difference depended on the presence or absence of an active layer in the soil and its thickness.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Journal of the Korean earth science society
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• v.35 no.4
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• pp.215-224
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• 2014

Data assimilation effect of mobile rawinsonde observation was evaluated using Unified Model (UM) with a Three-Dimensional Variational (3DVAR) data assimilation system during the intensive observation program of 2013 summer season (rainy season: 20 June-7 July 2013, heavy rain period: 8 July-30 July 2013). The analysis was performed by two sets of simulation experiments: (1) ConTroL experiment (CTL) with observation data provided by Korea Meteorological Administration (KMA) and (2) Observing System Experiment (OSE) including both KMA and mobile rawinsonde observation data. In the model verification during the rainy season, there were no distinctive differences for 500 hPa geopotential height, 850 hPa air temperature, and 300 hPa wind speed between CTL and OSE simulation due to data limitation (0000 and 1200 UTC only) at stationary rawinsonde stations. In contrast, precipitation verification using the hourly accumulated precipitation data of Automatic Synoptic Observation System (ASOS) showed that Equivalent Threat Score (ETS) of the OSE was improved by about 2% compared with that of the CTL. For cases having a positive effect of the OSE simulation, ETS of the OSE showed a significantly higher improvement (up to 41%) than that of the CTL. This estimation thus suggests that the use of mobile rawinsonde observation data using UM 3DVAR could be reasonable enough to assess the improvement of prediction accuracy.

• Atmosphere
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• v.15 no.2
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• pp.75-90
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• 2005

This study examines the impacts of land cover changes on the East Asia summer monsoon with the National Center for Atmospheric Research Regional Climate Model (NCAR RegCM2), coupled with Biosphere Atmosphere Transfer Scheme (BATS). To assess the goals, two types of land cover maps were used in the simulation of summer climate. One type was NCAR land cover map (CTL) and the other was current land cover map derived from satellite data (land cover: LCV). Warm and cold surface temperature biases of $1-3^{\circ}C$ occurred over central China and Mongolia in CTL. The model produced excessive precipitation over northern land area but less over southern ocean of the model domain. Changes of biophysical parameters, such as albedo, minimum stomatal resistance and roughness length, due to the land cover changes resulted in the alteration of land-atmosphere interactions. Latent heat flux and wind speed in LCV increased noticeably over central China where deciduous broad leaf trees have been replaced by mixed farm and irrigated crop. As a result, the systematic warm biases over central China were greatly reduced in LCV. Strong cooling of central China decreased pressure gradient between East Asian continent and Pacific Ocean. The decreased pressure gradient suppressed the northward transport of moisture from south China and South China Sea. These changes reduced not only the excessive precipitation over north China and Mongolia but also less precipitation over south China. However, the land cover changes increased the precipitation over the Korean Peninsula and the Japan Islands, especially in July and August.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.1
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• pp.40-49
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• 1986

Crack, craze and void are common defects which may be found in the bulk of polymeric materials such as either themoplastics or thermosets. The healing phenomena, autohesion, of these defects are known to be a intrinsic material property of various polymeric materials. However, only a few experimental and theoretical investigations on crack, void and craze healing phenomena for various polymeric materials have been reported up to date [1, 2, 3]. This may be partly due to the complications of healing processes and lacking of appropriate theoretical developments. Recently, some investigators have been urged to study the healing phenomena of various polymenic materials since the significance of the use of polymer based alloys or composites has been raised in terms of specific strength and energy saving. In the earlier published reports [1, 2, 3, 4], the crack and void healing velocity, healing toughness and some other healing mechanical and physical properties were measured experimentally and compared with predicted values by utilizing a simple model such as the reptation model under some resonable assumptions. It seems, however, that the general acceptance of the proposed modeling analyses is yet open question. The crack healing processes seem to be complicate and highly dependent on the state of virgin material in terms of mechanical and physical properties. Furthermore, it is also strongly dependent on the histories of crack, craze and void development including fracture suface morphology, the shape of void and the degree of disentanglement of fibril in the craze. The rate of crack healing may be a function of environmental factors such as healing temperature, time and pressure which gives different contact configurations between two separated surfaces. It seems to be reasonable to assume that the crack healing processes may be divided in several distinguished steps like stress relaxation with molecular chain arrangement, surface contact (wetting), inter- diffusion process and com;oete healing (to obtain the original strength). In this context, it is likely that we no longer have to accept the limitation of cumulative damage theories and fatigue life if it is probable to remove the defects such as crack, craze and void and to restore the original strength of polymers or polymer based compowites by suitable choice of healing histories and methods. In this paper, we wish to present a very simple and intuitive theoretical model for the prediction of healed fracture toughness of cracked or defective polymeric components. The central idea of this investigation, thus, may be the modeling of behavior of chain molecules under healing conditions including the effects of chain scission on the healing processes. The validity of this proposed model will be studied by making comparisons between theoretically predicted values and experimentally determined results in near future and will be reported elsewhere.

• Journal of Life Science
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• v.14 no.1
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• pp.131-140
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• 2004

T7 bacteriophage gp4 is the replicative DNA helicase that unwinds double-stranded DNA by utilizing dTTP hydrolysis energy. The quaternary structure of the active form of T7 helicase is a hexameric ring with a central channel. Single-stranded DNA passes through the central channel of the hexameric ring as the helicase translocates $5'\rightarrow3'$ along the single-stranded DNA. The DNA unwinding was measured by rapid kinetic methods and showed a lag before the single-stranded DNA started to accumulate exponentially. This behavior was analyzed by a kinetic stepping model for the unwinding process. The observed lag phase increased as predicted by the model with increasing double-stranded DNA length. Trap DNA added in the reaction had no effect on the amplitudes of double-stranded DNA unwound, indicating that the $\tau7$ helicase is a highly processive helicase. Global fitting of the kinetic data to the stepping model provided a kinetic step size of 10-11 bp/step with a rate of $3.7 s^{-1}$ per step. Both the mechanism of DNA unwinding and dTTP hydrolysis and the coupling between the two are unaffected by temperature from $4∼37^{\circ}C$. Thus, the kinetic stepping for dsDNA unwinding is an inherent property of tile replicative DNA helicase.

• Journal of Korea Water Resources Association
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• v.43 no.3
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• pp.309-323
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• 2010

As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.298-306
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• 2016

Planting date shift is one of the means of adapting to climate change in Kimchi Cabbage growers in major production areas in Korea. This study suggests a method to estimate the potential yield of Kimchi Cabbage based on daily temperature accumulation during the growth period from planting to maturity which is determined by a plant phenology model tuned to Kimchi Cabbage. The phenology model converts any changes in the thermal condition caused by the planting date shift into the heat unit accumulation during the growth period, which can be calculated from daily temperatures. The physiological maturity is estimated by applying this model to a variable development rate function depending either on growth or heading stage. The cabbage yield prediction model (Ahn et al., 2014) calculates the potential yield of summer cabbage by accumulating daily heat units for the growth period. We combined these two models and applied to the 1km resolution climate scenario (2000-2100) based on RCP8.5 for South Korea. Potential yields in the current normal year (2001-2010) and the future normal year (2011-2040, 2041-2070, and 2071-2100) were estimated for each grid cell with the planting dates of July 1, August 1, September 1, and October 1. Based on the results, we divided the whole South Korea into 810 watersheds, and devised a three - dimensional evaluation chart of the time - space - yield that enables the user to easily find the optimal planting date for a given watershed. This method is expected to be useful not only for exploring future new cultivation sites but also for developing cropping systems capable of adaptation to climate change without changing varieties in existing production areas.