• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.175-182
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• 2018

Knowledge of the optimum cultivation period for Chinese cabbage would help growers especially in spring in Korea. Growth and yield of Chinese cabbage in a temperature gradient chamber was evaluated for the growing periods of 64 days from three set of transplanting dates including March 6, March 20, and April 3 in 2017. Air temperature in the chamber was elevated step-by-step, by $2^{\circ}C$ above the ambient temperature. This increment was divided into three phases; i.e. low (ambient+$2^{\circ}C$, A), medium (ambient+$4^{\circ}C$, B), and high temperature (ambient+$6^{\circ}C$, C). The fresh weight of Chinese cabbage was greater under B and C conditions in the first period and A in the second period, which indicated that GDDs affected the fresh weight considerably. However, leaf growth (number, area, length, and width) did not differ by GDDs. Bolting appeared under A condition in the first period, which was caused by low temperature in the early growth stage. Soft rot was developed under C condition in the second period and all temperature conditions in the third period, which resulted from high temperature in the late stage. Fresh weight increased when GDDs ranged from 587 to 729. However, it decreased when GDDs > 729. The maximum expected yield (16.3 MT/10a) was attained for the growing period of 64 days from transplanting date during which GDDs reached 601. The GDDs for optimum cultivation ranged from 478-724 under which the yield was about 95% (15.5 MT/10a) of maximum fresh weight. Such an optimum condition for GDDs was validated at five main cultivation regions including Jindo, Haenam, Naju, Seosan, and Pyeongtaek in Korea. In these regions, GDDs ranged from 619-719. This suggested that the optimum GDDs for Chinese cabbage cultivation would range from 478-724, which would give the useful information to expect the cultivation periods for ensuring maximum yield.

• Journal of the Korean earth science society
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• v.36 no.3
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• pp.199-209
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• 2015

The Atlantic meridional overturning circulation (AMOC), driven by high density water sinking around Greenland serves as a global climate regulator, because it transports heat and materials in the climate system. We analyzed the mechanism of AMOC on a decadal time scale simulated with the HadGEM2-AO model. The lead-lag regression analysis with AMOC index shows that the decadal variability of the thermohaline circulation in the Atlantic Ocean can be considered as a self-sustained variability. This means that the long-term change of AMOC is related to the instability which is originated from the phase difference between the meridional temperature gradient and the ocean circulation. When the overturning circulation becomes stronger, the heat moves northward and decreases the horizontal temperature-dominated density gradients. Subsequently, this leads to weakening of the circulation, which in turn generates the anomalous cooling at high latitudes and, thereby strengthening the AMOC. In this mechanism, the density anomalies at high latitudes are controlled by the thermal advection from low latitudes, meaning that the variation of the AMOC is thermally driven and not salinity driven.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.227-238
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• 2006

Line density index(LDI) was developed to quantify a densely isothermal line rate as standard index in the ocean environment. Theoretical background on the LDI development process restricting index range 0 to 100 was described. And validation test was done for the LDI application condition that total line length is not greater than 1/10 of unit area. NOAA SST(Sea Surface Temperature) data were used for the experimental application of LDI in the South Sea of Korea. Using GIS, $0.1^{\circ}C$ isothermal lines were linearized as vector data form SST raster data, and unit area were built as polygon data. For the LDI calculation, spatial overlapping(line in polygon) was implemented. To analyze the effect of unit area size for the LDI distribution, two cases of unit area size were designed and descriptive statistics was calculated including performing normality test. The results showed no change of LDI's essential characteristics such as mean and normality except for the range of value, variance and standard deviation. Accordingly, it was found that complex structure of thermal front and even smaller scale of front width than unit area size could influence on the LDI distribution. Also, correlation analysis performed between LDI and difference of temperature(${\Delta}T^{\circ}C$), and horizontal thermal gradient(${\Delta}T^{\circ}C/km$) on the front was obtained from linear regression model. This obtained value was compared with the results from previous researches. Newly developed LDI can be used to compare the thermal front regions changing spatio-temporally in the ocean environment using absolute index value. It is considered to be significant to analyze the relationship between thermal front and marine environment or front and marine organisms in a quantitative approach described in this study.

• Journal of the Korean Chemical Society
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• v.58 no.6
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• pp.575-579
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• 2014

Development of liposomes has been actively studied for effective delivery of drug at tumor site. However, despite their preferential accumulation at tumor site, the therapeutic efficacy of such liposomal drug has been limited because of low drug release. Therefore, we developed a temperature-sensitive liposome (TSL), which can be made to maximize release of drug by external stimulation such as ultrasound. Doxorubicin (DOX) as a model drug was encapsulated into TSL by a pH gradient method. The particle size of the TSL was $142.0{\pm}6.24nm$. Surface charge was $-10.55{\pm}1.12mV$. Release of drug from TSLs was up to 80% within 15 min at over $42^{\circ}C$ measured by fluorescence intensity. Cytotoxicity of released DOX from TSLs with ultrasound was highly increased compared to TSLs without ultrasound. Taken together, we demonstrate that temperature sensitive drug release from TSLs with ultrasound, which may be useful for cancer therapy to increase drug concentration at tumor site by external stimulation.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• The Journal of the Acoustical Society of Korea
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• v.32 no.1
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• pp.1-13
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• 2013

Salinity does not generally affect sound speed because it shows very small variations in the ocean. However, low salinity water appears in the Western Sea of Jeju Island every summer so that sound speed and sound propagation can change near sea surface. We calculated Sound Speed Profile (SSP) using vertical profiles of temperature and salinity, which were averaged over years of normal salinity and low salinity (<28 psu) from 30 years (1980~2009) at 3 sites of Korea Oceanographic Data Center (KODC). As a result, sound speed variation by low salinity alone was -5.36 m/s at sea surface and -1.35 m/s at 10m depth for low salinity environments. Gradient of SSP was positive down to 5 m depth due to decrease of sound speed near surface, leading formation of haline channel. Simulation of acoustic propagation using a ray model (Bellhop) confirmed the haline channel. Haline channel has formed 4 times while hydrostatic channel controlled by only pressure has formed 9 times for 30 years. The haline channel showed larger critical angles of rays than hydrostatic channel. Haline channel was also formed at some sites among 20 measurement sites in low salinity water mass which appeared on August $1^{st}$ 2010.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.4
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• pp.289-296
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• 2009

The appearance and variation of cold water area and its expansion mechanism of tidal front in the south western coast of Korea in summer were studied on the basis of oceanographic data(1966-1995), satellite images from NOAA and SeaWiFs and numerical model. Cold water appearance in southwestern field of Jindo was due to the vertical mixing by strong tidal current. Tidal front where horizontal gradient of water temperature was more than $0.3^{\circ}C$/km parallels to contours of H/$U^3$ parameter 2.0~2.5 and the outer boundary of cold water region corresponds with contours of the parameter 2.5~3.0 in the southwestern sea of Korea during the period between neap and spring tides. The position replacement of tidal front formed in the study ares varies in a range of 25~75km and cold water region extends about 90km. These suggest that the magnitude of variation of frontal position and cold water area was proportionate to the tidal current during lunar tidal cycle. Moreover, it was estimated that the southwestward expansion of cold water region was derived from the southwestward tide-induced residual currents with speed more than 10cm/s.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.663-671
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• 2006

This study was performed for exploring the spatial distribution pattern of Pinus densiflora and Quercus spp. in Korea. Firstly, the spatial distribution map of Pinus densiflora and Quercus spp. was prepared in grid of $100m{\times}100m$ at national level, using digital forest type map and actual vegetation map. And thematic maps for topography, climate, and soil were also prepared in the raster form of $100m{\times}100m$. Through GIS based spatial analysis of the digital distribution map of Pinus densiflora and Quercus spp. and thematic maps, the spatial characteristics of Pinus densiflora and Quercus spp. distribution was explored in relation to the environmental factors such as topography, climate, and soil. And the occurrence frequency models of Pinus densiflora and Quercus spp. were derived. Pinus densiflora occurs more often than Quercus spp. at low elevation, low slope gradient, and high temperature areas. In addition, Pinus densiflora is mainly distributed at shallow and well-drained loamy soil from igneous rocks. In contrast, Quercus spp. is more common at shallow and well-drained loamy soil from metamorphic rocks. As a result, the prediction model for the spatial distribution of Pinus densiflora and Quercus spp. by topographical variables has proven successful with high statistical significance. The result of this study can contribute to rational management of Pinus densiflora and Quercus spp. stand in Korea, considering environmental factors such as topography, climate, and soil.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.445-454
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• 2022

Ice accretion on the aircraft components, such as wings, fuselage, and empennage, can occur when the aircraft encounters a cloud zone with high humidity and low temperature. The prevention of ice accretion is important because it causes a decrease in the aerodynamic performance and flight stability, thus leading to fatal safety problems. In this study, a shape design optimization of a multi-element airfoil is performed to minimize the amount of ice accretion on the high-lift device including leading-edge slat, main element, and trailing-edge flap. The design optimization framework proposed in this paper consists of four major parts: air flow, droplet impingement and ice accretion simulations and gradient-free optimization algorithm. Reynolds-averaged Navier-Stokes (RANS) simulation is used to predict the aerodynamic performance and flow field around the multi-element airfoil at the angle of attack 8°. Droplet impingement and ice accretion simulations are conducted using the multi-physics computational analysis tool. The objective function is to minimize the total mass of ice accretion and the design variables are the deflection angle, gap, and overhang of the flap and slat. Kriging surrogate model is used to construct the response surface, providing rapid approximations of time-consuming function evaluation, and genetic algorithm is employed to find the optimal solution. As a result of optimization, the total mass of ice accretion on the optimized multielement airfoil is reduced by about 8% compared to the baseline configuration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.239-249
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• 2020

Rice flour varieties have been developed to replace wheat, and consumption of rice flour has been encouraged. damage related to pre-harvest sprouting was occurring due to a weather disaster during the ripening period. Thus, it is necessary to develop pre-harvest sprouting rate prediction system to minimize damage for pre-harvest sprouting. Rice cultivation experiments from 20 17 to 20 19 were conducted with three rice flour varieties at six regions in Gangwon-do, Chungcheongbuk-do, and Gyeongsangbuk-do. Survey components were the heading date and pre-harvest sprouting at the harvest date. The weather data were collected daily mean temperature, relative humidity, and rainfall using Automated Synoptic Observing System (ASOS) with the same region name. Gradient Boosting Machine (GBM) which is a machine learning model, was used to predict the pre-harvest sprouting rate, and the training input variables were mean temperature, relative humidity, and total rainfall. Also, the experiment for the period from days after the heading date (DAH) to the subsequent period (DA2H) was conducted to establish the period related to pre-harvest sprouting. The data were divided into training-set and vali-set for calibration of period related to pre-harvest sprouting, and test-set for validation. The result for training-set and vali-set showed the highest score for a period of 22 DAH and 24 DA2H. The result for test-set tended to overpredict pre-harvest sprouting rate on a section smaller than 3.0 %. However, the result showed a high prediction performance (R2=0.76). Therefore, it is expected that the pre-harvest sprouting rate could be able to easily predict with weather components for a specific period using machine learning.