• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.420-428
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• 2019

This study is the heating energy saving test of the high-bed strawberry crown heating system. The system consists of electric hot water boiler, thermal storage tank, circulation pump, crown heating pipe(white low density polyethylene, diameter 16mm) and a temperature control panel. For crown heating, the hot water pipe was installed as close as possible to the crown part after planting the seedlings and the pipe position was fixed with a horticultural fixing pin. In the local heating type, hot water at $20{\sim}23^{\circ}C$ is stored in the themal tank by using an electric hot water boiler, and crown spot is partially heated at the setting temperature of $13{\sim}15^{\circ}C$ by turning on/off the circulation pump using a temperature sensor for controlling the hot water circulation pump which was installed at the very close to crown of strawberry. The treatment of test zone consisted of space heating $4^{\circ}C$ + crown heating(treatment 1), space heating $8^{\circ}C$(control), space heating $6^{\circ}C$ + crown heating(treatment 2). And strawberries were planted in the number of 980 for each treatment. The heating energy consumption was compared between November 8, 2017 and March 30, 2018. Accumulated power consumption is converted to integrated kerosene consumption. The converted kerosene consumption is 1,320L(100%) for space $8^{\circ}C$ heating, 928L(70.3%) for space $4^{\circ}C$ + crown heating, 1,161L($88^{\circ}C$) for space $6^{\circ}C$ + crown heating). It was analyzed that space $4^{\circ}C$ + pipe heating and space $6^{\circ}C$ + crown heating save heating energy of 29.7% and 12% respectively compared to $8^{\circ}C$ space heating(control).

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.503-514
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• 2020

Climate change leads to changes in phenological response and movement of plant habitats. Korea's evergreen broad-leaved forest has widened its distribution area compared for the past 20 years, and the range of its native habitats is moving northward. We analyzed climate indices such as the warmth index, the cold index, the lowest temperature in the coldest month, and the annual average temperature, which are closely related to vegetation distribution, to predict the change in the native habitat of Lauraceae evergreen broad-leaved trees. We also analyzed the change and spatial distribution to identify the habitat climate characteristics of 8 species of Lauraceae evergreen broad-leaved trees distributed in the warm temperate zone in Korea. Moreover, we predicted the natural habitat change in the 21st century according to the climate change scenario (RCP 4.5/8.5), applying the MaxEnt species distribution model. The monthly average climate index of the 8 species of Lauraceae evergreen broad-leaved trees was 116.9±10.8℃ for the temperate index, the cold index 3.9±3.8℃, 1495.7±455.4mm for the annual precipitation, 11.7±3.5 for the humidity index, 14.4±1.1℃ for the annual average temperature, and 1.0±2.1℃ for the lowest temperature of winter. Based on the climate change scenario RCP 4.5, the distribution of the Lauraceae evergreen broad-leaved trees was analyzed to expand to islands of Jeollanam-do and Gyeongsangnam-do, adjacent areas of the west and south coasts, and Goseong, Gangwon-do on the east coast. In the case of the distribution based on the climate change scenario RCP 8.5, it was analyzed that the distribution would expand to all of Jeollanam-do and Gyeongsangnam-do, and most regions except for some parts of Jeollabuk-do, Chungcheongnam-do, Gyeongsangbuk-do, and the capital region. For the conservation of Lauraceae evergreen broad-leaved trees to prepare for climate change, it is necessary to establish standards for conservation plans such as in-situ and ex-situ conservation and analyze various physical and chemical characteristics of native habitats. Moreover, it is necessary to preemptively detect changes such as distribution, migration, and decline of Lauraceae evergreen broad-leaved trees following climate change based on phenological response data based on climate indicators and establish conservation management plans.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.531-542
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• 2021

Open-pit mines require constant monitoring as they can cause surface changes and environmental disturbances. In open-pit mines, there is little vegetation at the mining site and can be monitored using InSAR (Interferometric Synthetic Aperture Radar) coherence imageries. In this study, activities occurring in mine were analyzed by applying the recently developed InSAR coherence-based NDAI (Normalized Difference Activity Index). The March 5 Youth Mine is a North Korean mine whose development has been expanded since 2008. NDAI analysis was performed with InSAR coherence imageries obtained using Sentinel-1 SAR images taken at 12-day intervals in the March 5 Youth Mine. First, the area where the elevation decreased by about 75.24 m and increased by about 9.85 m over the 14 years from 2000 was defined as the mining site and the tailings piles. Then, the NDAI images were used for time series analysis at various time intervals. Over the entire period (2017-2019), average mining activity was relatively active at the center of the mining area. In order to find out more detailed changes in the surface activity of the mine, the time interval was reduced and the activity was observed over a 1-year period. In 2017, we analyzed changes in mining operations before and after artificial earthquakes based on seismic data and NDAI images. After the large-scale blasting that occurred on 30 April 2017, activity was detected west of the mining area. It is estimated that the size of the mining area was enlarged by two blasts on 30 September 2017. The time-averaged NDAI images used to perform detailed time-series analysis were generated over a period of 1 year and 4 months, and then composited into RGB images. Annual analysis of activity confirmed an active region in the northeast of the mining area in 2018 and found the characteristic activity of the expansion of tailings piles in 2019. Time series analysis using NDAI was able to detect random surface changes in open-pit mines that are difficult to identify with optical images. Especially in areas where in situ data is not available, remote sensing can effectively perform mining activity analysis.

• Economic and Environmental Geology
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• v.54 no.3
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• pp.399-408
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• 2021

Natural soil was artificially contaminated with heavy metals (Cd, Pb, and Zn), and the movement of earthworm was characterized in real time using the ViSSET system composed of vibration sensor and the other components. The manifestation mechanism of ecological toxicity of heavy metals was interpreted based on the accumulative frequency of earthworm movement obtained from the real-time monitoring as well as the conventional indices of earthworm behavior, such as the change in body weight before and after tests and biocumulative concentrations of each contaminant. The results showed the difference in the earthworm movement according to the species of heavy metal contaminants. In the case of Cd, the earthworm movement was decreased with increasing its concentration and then tended to be increased. The activity of earthworm was severely increased with increasing Pb concentration, but the movement of earthworm was gradually decreased with increasing Zn concentration. The body weight of earthworm was proved to be greatly decreased in the Zn-contaminated soil, but it was similarly decreased in Cd- and Pb-contaminated soils. The bioaccumulation factor (BAF) was higher in the sequence of Cd > Zn > Pb, and particularly the biocumulative concentration of Pb did not show a clear tendency according to the Pb concentrations in soil. It was speculated that Cd is accumulated as a metallothionein-bound form in the interior of earthworm for a long time. In particular, Cd has a bad influence on the earthworm through the critical effect at its higher concentrations. Pb was likely to reveal its ecotoxicity via skin irritation or injury of sensory organs rather than ingestion pathway. The ecotoxicity of Zn seemed to be manifested by damaging the cell membranes of digestive organs or inordinately activating metabolism. Based on the results of real-time monitoring of earthworm movement, the half maximal effective concentration (EC50) of Pb was estimated to be 751.2 mg/kg, and it was similar to previously-reported ones. The study confirmed that if the conventional indices of earthworm behavior are combined with the results of newly-proposed method, the mechanism of toxicity manifestation of heavy metal contaminants in soils is more clearly interpreted.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.4
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• pp.361-368
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• 2021

The objective of this study was to establish technology for removing bacteria with human- and eco-friendly material. Staphylococcus aureus as an important component for balanced equilibrium among microbiomes, was cultured under various concentrations of phosphate. Experimental observation relating to physical properties was performed in an addition of phosphate buffer. Statistically minimum value of size and hardness using atomic force microscope was observed on the matured biofilm at 5 mM concentration of phosphate. As a result of absorbance for the biofilm tagged with dye, concentration of biofilm was reduced with phophate, too. To identify whether this reduction by phosphate at the 5 mM is caused by counter ion or not, sodium chloride was treated to the biofilm under the same condition. To elucidate components of the biofilm counting analysis of the biofilm using time-of-flight secondary ion mass spectrometry was employed. The secondary ions from the biofilm revealed that alteration of physical properties is consistent to the change of extracellular polymeric substrate (EPS) for the biofilm. Viscoelastic characterization of the biofilm using a controlled shear stress rheometer, where internal change of physical properties could be detected, exhibited a static viscosity and a reduction of elastic modulus at the 5 mM concentration of phosphate. Accordingly, bacteria at the 5 mM concentration of phosphate are attributed to removing the EPS through a reduction of elastic modulus for bacteria. We suggest that the reduction of concentration of biofilm induces dispersion which assists to easily spread its dormitory. In conclusion, it is elucidated that an addition of phosphate causes removal of EPS, and that causes a function of antibiotic.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.19-32
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• 2022

The need for polar education was further emphasized, depending on the importance of the pole, which is the best place for climate change detection and prediction, and treasure trove of future technology and resources. Therefore, this study analyzed the general cognitive and affective characteristics of elementary school students' polar literacy, and in addition, analyzed the cognitive and affective characteristics according to the level of diversity about polar experience. The items developed for the study were revised through a pilot survey of 43 fifth graders. They consisted of questions about gender, polar experience, scientific literacy, polar knowledge, polar literacy skills, polar literacy beliefs, and polar literacy attitudes. The types of questions used are selectable, reliable, and Likert (4 points), for a total of 66 questions. The students who participated in the study were 323 fifth grade elementary students. The study found that students were more interested in the dramatic consequences of polar changes than the scientific causes and processes associated with it. This is confirmed through the fact that they are more interested in and familiar with polar creatures suffering from polar changes than understanding ice, which is the main feature of and the central mechanism of polar changes. Students also recognized the issue of polar climate change as a global issue other than their own. They believe that what happens in the Arctic and Antarctica will affect the whole world, but not significantly to himself and his community. The level of knowledge about polar region and the ability to analyze and infer were not significantly related to each other, and students with a higher level of diversity of experience about polar region had a better understanding of polar science and technology. In this research, it is meaningful to check the characteristics related to the students' polar region and to use it as a basic data to show the direction in which polar literacy education should proceed in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.1
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• pp.20-26
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• 2023

Fiber content in the storage roots of sweetpotato varies between different varieties. For examples, the high fiber content of certain types has a poor texture when steamed or roasted. This study was conducted to evaluate the optimal sieve mesh size for separating fibers, the chemical composition of fibers and differences in fiber content among different varieties. We found that the separated fiber content (dry weight) of mashed and steamed sweetpotato was higher after washing three times (143.3 mg/100 g) compared with that washed five times (128.4 mg/100 g). The Hogammi variety remained 85.9% of total fiber content at 10 mesh (2,000 ㎛) and 9.6% of total fiber content at 30 mesh (600 ㎛), and Jinyulmi remained 74.9 and 16.7% of total fiber content , respectively. Therefore, a 30 mesh sieve was considered the most suitable for fiber separation. Among the 10 studied cultivars, Jinhongmi showed the lowest amount of fiber (24.8 mg/100 g) and Hogammi had the highest amount (111.4 mg/100 g), which was 4.5 times larger than that of Jinhongmi. Cellulose, hemicellulose and lignin content of separated fibers showed no difference between the viscous-type Hogammi and powdery-type Jinyulmi varieties, with averages of 32.5, 22.3 and 29.6%, respectively. Correlation results using the Image J program showed a significant correlation between the distribution of the stained area and the fiber content (R = 0.74, p < 0.05). Staining distribution differed among varieties, suggesting that a simple fiber content test could be performed using the staining method on raw sweetpotato. These results provide useful information to help inform farmers on the fiber content of different sweetpotato varieties.