• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.123-133
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• 2020

Four LEDs (blue, green, red, and white light) were tested to identify the most attractive wave length to utilize as the forecasting tools for the B. tabaci in glass houses. Attractiveness was evaluated by the total number of the B. tabaci attached to a yellow sticky trap. In the condition of no host plant supplement, the attraction efficacy was ordered from high to low as blue light (107.3±2.5), white light (83.0±12.1), red light (58±21.8), and green light (39.7±8.1). In the supplement of the host plant, the attraction was observed in the order of blue light (52±17.4), red light (38.7±5.8), green light (12.7±1.5), and white light (11.7±5.0). In both experimental conditions, blue light showed the highest attraction. In terms of the host plant effect to LED attraction, it varied following as white light (85.9%), green light (68.1%), blue light (51.6%), and red light (33.3%). This result suggests that red light is the least affected by the host plant. In the evaluation of the relative control efficacy, it was determined following as red light (66.7%), blue light (48.5%), green light (31.9%) and white light (14.1%) (F_3,8 = 14.7, P = 0.001). Taken together, blue light had a very high initial attraction, and red light was revealed low attraction effect by the supplement of the host plant. In field demonstration experiments, a high attractive efficacy was not observed due to low-temperature conditions, but similar higher attractive efficacy was observed in blue and red lights compared to the control. The commercialization of LEDs using red and blue in the future is expected to provide important information regarding B. tabaci population density forecast in glass house.

• Journal of Life Science
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• v.32 no.7
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• pp.510-522
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• 2022

In this study, to biosynthesize PHA with properties more similar to polypropylene, a Bacillus sp. EMK-5020 strain that biosynthesized poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) was isolated from soil. Bacillus sp. EMK-5020 strain biosynthesized PHBV containing 1.3% 3-hydroxyvalerate (3HV) using reducing sugar contained in Makgeolli lees enzymatic hydrolysate (MLEH) as a single carbon source. As the amount of propionic acid, which was added as a second carbon source, increased, the content of 3HV also increased. PHBV containing up to 48.6% of 3HV was synthesized when 1.0 g/l of propionic acid was added. Based on these results, the strain was cultured for 72 hr in a 3 l fermenter using reducing sugar in MLEH (20 g/l) and propionic acid (1 g/l) as the main and secondary carbon sources, respectively. As a result, 6.4 g/l DCW and 50 wt% of PHBV (MLEH-PHBV) containing 8.9% 3HV were biosynthesized. Through gel permeation chromatography and thermogravimetric analysis, it was confirmed that the average molecular weight and the decomposition temperature of MLEH-PHBV were 152 kDa and 273℃, respectively. In conclusion, the Bacillus sp. EMK-5020 strain could biosynthesize PHBV containing various 3HV fractions when MLEH and propionic acid were used as carbon sources, and PHBV-MLEH containing 8.9% 3HV was confirmed to have higher thermal stability than standard PHBV (8% 3HV).

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.2
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• pp.61-72
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• 2022

The present study was conducted to examine the effect of soybean silage as a crude protein supplement for corn silage in the diet of Hanwoo steers. The first experiment was conducted to evaluate the effect of replacing corn silage with soybean silage at different levels on rumen fermentation characteristics in vitro. Commercially-purchased corn silage was replaced with 0, 4, 8, or 12% of soybean silage. Half gram of the substrate was added to 50 mL of buffer and rumen fluid from Hanwoo cows, and then incubated at 39℃ for 0, 3, 6, 12, 24, and 48 h. At 24 h, the pH of the control (corn silage only) was lower (p<0.05) than that of soybean-supplemented silages, and the pH numerically increased along with increasing proportions of soybean silage. Other rumen parameters, including gas production, ammonia nitrogen, and total volatile fatty acids, were variable. However, they tended to increase with increasing proportions of soybean silage. In the second experiment, 60 Hanwoo steers were allocated to one of three dietary treatments, namely, CON (concentrate with Italian ryegrass), CS (concentrate with corn silage), CS4% (concentrate with corn silage and 4% of soybean silage). Animals were offered experimental diets for 110 days during the growing period and then finished with typified beef diets that were commercially available to evaluate the effect of soybean silage on animal performance and meat quality. With the soybean silage, the weight gain and feed efficiency of the animal were more significant than those of the other treatments during the growing period (p<0.05). However, the dietary treatments had little effect on meat quality except for meat color. In conclusion, corn silage mixed with soybean silage even at a lower level provided a greater ruminal environment and animal performances, particularly with increased carcass weight and feed efficiency during growing period.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1285-1300
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• 2022

Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Korean Home Economics Education Association
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• v.34 no.3
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• pp.133-148
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• 2022

This study aims to explore the status and motives for using avatars and digital fashion items in the metaverse and to examine consumers' purchase satisfaction and future purchase intentions. We intend to provide implications for the development of avatars and fashion items, and the direction of the fashion industry and clothing education. For this purpose, the purchasing status, consumer motives for using avatars and digital fashion items, purchase satisfaction, and future purchase intentions were investigated, through a survey with 149 consumers aged 19 years or older, with the experience of using avatars. The results are as follows. First, the percentage of avatar ownership was high among women aged between 19 and 29, and those with low or high incomes. The younger group was more likely to make mobile phone purchases than the older group, and the older group was more likely to use credit cards. Even those respondents who owned avatars did not purchase frequently or spent a lot on items. On the other hand, in the case of fashion item purchases, the group spending more than 8,000 won was aged between 19 and 29, and the frequency and amount of purchases increased as income increase. Second, among the motives for using avatars and fashion items, the pursuit of pleasure had the greatest influence, and men paid more attention to self-expression through avatars than women. Third, the motive for vicarious satisfaction influenced purchase satisfaction, and the factors that influenced future purchase intention were vicarious satisfaction and stress relief. The results of this study suggests that avatars and fashion items should be developed considering factors that can relieve stress for all age groups, create a sense of unity among metaverse users, and provide satisfaction in a virtual world that is different from reality. In addition, education on how to use fashion items and consumption attitudes in education related to clothing life will be required.

• Journal of the Korean Orthopaedic Association
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• v.56 no.1
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• pp.42-50
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• 2021

Purpose: Periprosthetic fractures of a tumor prosthesis are rare but have difficulties in achieving sound fixation because of the poor bone quality, which increases the risk of loosening or re-fracture, even after bone union. A cortical strut onlay allograft was adopted for peri-prosthetic fractures after hip arthroplasty into the periprosthetic fracture of a tumor prosthesis, assuming that it would assist in firm fixation, shorten the time to union, and increase the bone stock, thereby, lower the chance of loosening and re-fracture. Materials and Methods: This study reviewed 27 patients (30 cases) of periprosthetic fracture of tumor prosthesis. Sixteen cases (allograft group) had augmentation with an onlay allograft, while 14 cases (conventional group) had internal fixation or conservative treatment. The following were assessed; mode of periprosthetic fracture, difference in the time to union between a strut cortical onlay allograft and without it, and survival of prosthesis, complication, and functional outcome between the two groups. Results: According to the unified classification system (UCS), 21 cases were type B (70.0%; B1, 14; B2, 1; B3, 6) and 9 cases were type C. The five-, 10-year survival of the 30 reconstructions by Kaplan-Meier plot was 84.5%±4.18% and 42.2%±7.83%, respectively. The average time to bone union of the entire cohort was 5.1 months (range, 2.0-11.2 months). The allograft group (3.5 months) showed a shorter period for union than the conventional group (7.2 months) (p<0.0001). All four cases of major complications occurred in the conventional group. Two cases with loosening and anterior angulation were treated with a change of prosthesis, and another with infection underwent amputation. The remaining case with loosening had conservative management. At the final follow-up, the average Musculosketal Tumor Society score of the allograft group (26.1) was better than that of the conventional group (20.9). Conclusion: Bone union in periprosthetic fractures of a tumor prosthesis can be achieved, but the minimization of complications is important. An onlay allograft facilitates firm fixation and increases the bone stock with a shortened time to union. This simple method can minimize the risk of loosening, joint contracture, and re-fracture.

• Journal of the Korean Orthopaedic Association
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• v.56 no.3
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• pp.234-244
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• 2021

Purpose: To date, studies of firearm and explosive injuries in the Korean military have been limited compared to its importance. To overcome this, this study examined the characteristics of musculoskeletal damages in soldiers who have suffered firearm and explosive injuries over the past four years. Materials and Methods: From January 2015 to July 2019, military forces who had suffered musculoskeletal injuries from firearms or explosive substances were included. The medical records and radiographs were reviewed retrospectively, and telephone surveys about Short Musculoskeletal Functional Assessment (SMFA) for this group were conducted. To compare the functional outcomes, statistical analysis was performed using a t-test for the types of weapons, and ANOVA for others. Results: Of the 61 patients treated for firearms and explosives injuries, 30 patients (49.2%) were included after undergoing orthopedic treatment due to musculoskeletal injury. The average age at injury was 26.4 years old (21-52 years old). The number of officers and soldiers was similar. Eleven were injured by gunshot and 19 by an explosive device. Sixteen were treated in the Armed Forces Capital Hospital and 10 at private hospitals. More than half of the 16 patients (53.3%) with a fracture had multiple fractures. The most common injury site was the hand (33.3%), followed by the lower leg (30.0%). There were 14 patients (46.7%) with Gustilo-Anderson classification 3B or higher who required a soft tissue reconstruction. Fifteen patients agreed to join the SMFA survey for the functional outcomes. Between officers and soldiers, officers had better scores in the Bother Index compared to soldiers (p=0.0045). Patients treated in the Armed Forces Capital Hospital had better scores in both the Dysfunction and Bother Index compared to private hospitals (p=0.0008, p=0.0149). Conclusion: This is the first study to analyze of weapons injuries in the Korean military. As a result of the study, the orthopedic burden was high in the treating patients with military weapon injuries. In addition, it is necessary to build a military trauma registry, including firearm and explosive injuries, for trauma treatment evaluation and development of military trauma system.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.