• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.2
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• pp.165-170
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• 1994

High quality rapeseed cultivars including Nojeokchae, Yeongsanyuchae Halla-yuchae and Tamrayuchae have been released and recommended as a zero erucic acid variety to Cheju farmers for 13 years, where is a major rapeseed production area in korea. However, rapeseeds produced in Cheju island in 1992 and 1993 contained 47.7% and 37.0% of erucic acid respectively resulting in poor quality oil being not adequate for edible oil. It was considered that the zero erucic acid varieties did not have an opportunity to be cultivated in Cheju island by farmers living in the Island. Thus, the new rapeseed varieties without erucic acid should be bred and recommended to the farmers of southern area of Korea as a multiple cropping crop just after rice harvest, and for large scale mechanized and labour-serving rapeseed culture. The change of rapeseed breeding goal would be desirable for fatty acid composition improvement of rapeseed to develop varieties adaptable to southern part of Korea, and to produce rapeseed oil directly used as an edible oil safely.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.41 no.5
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• pp.514-520
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• 1996

To clarify the proper nitrogen application level for rasing rice infant seedling under different nursery soil, Dongjinbyeo was raised at seedling box with different basal nitrogen level. The results are as follows. The higher the nitrogen level was, the lower emergence rate and the lower establishment rate. The establishment rate was less than 90%, when the nitrogen was more than 2g/box in hill soil and more than 1g/box in paddy soil. The more the nitrogen level was, the higher the seedling height in hill soil, but was higher in the order of N-2, 3, 1 and 0g /box. Leaf number wasn't significantly different between nusery soils and among nitrogen levels when seedling was raised more than 6 days. The endosperm survival rate was decreased as the increased nitrogen level, but wasn't different between the nursery soils. Amount of root was decreased as the increased nitrogen level in paddy soil, but was heavier in the order of N-1, 0, 2 and 3g /box in hill soil. Mat formation was better as the nitrogen level was decreased in all nursery soils. Considering the emergence rate, seedling charactors and mat formation, the proper nitrogen levels seemed to be 2g /box for hill soil and 1g /box for paddy soil.

• Korean Journal of Community Nutrition
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• v.28 no.1
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• pp.38-47
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• 2023

Objectives: This study examined the association between the experience of disease management education and the use of nutrition labels according to the sociodemographic characteristics and health behaviors of people diagnosed with hypertension and diabetes living in the community. Methods: Among the participants from the Community Health Survey (2018), 74,283 individuals diagnosed with hypertension or diabetes were included in the study population. According to gender, this study evaluated nutrition label use by the experience of disease management education, individual sociodemographic characteristics, and health behavior. Finally, using multiple logistic regression analysis, the association between disease management education and nutrition labels was calculated using the odds ratio (OR) and 95% confidence interval (CI). Results: Males (24.5%) experienced more disease management education than females (22.6%). In addition, younger age, higher education level, and higher equalized personal income experienced more disease management education (P < 0.001). The educational experience rate was higher in the male subjects who did not smoke or were involved in high-risk alcohol consumption (P < 0.001). In addition, the rate of disease management education experience was significantly higher for both men and women who exercised by walking (P < 0.001). The use of nutrition labels was higher in females (9.9%) than males (5.8%), and both males and females were significantly higher in young age, high education, high income, and professional and office positions (P < 0.001). The utilization rate of nutrition labels was high in non-smoking male subjects and high-risk-drinking female subjects. In addition, the utilization rate of nutrition labels was significantly higher in males and females who exercised by walking and those who experienced disease management education (P < 0.001). After adjusting for individual sociodemographic characteristics, health behavior, and disease management education, the use of nutrition labels was high among females (OR 3.19, 95% CI 2.85-3.58), high income (Q4; OR 1.62, 95% CI 1.41-1.87, Q5; OR 1.58, 95% CI 1.37-1.84) and highly educated (high school; OR 2.87, 95% CI 2.62-3.14, above college; OR 5.60, 95% CI 5.02-6.23) while it was low in the elderly (OR 0.43, 95% CI 0.40-0.47), and economically inactive (OR 0.86, 95% CI 0.76-0.96). The use of nutrition labels was high in non-smokers (OR 1.29, 95% CI 1.13-1.48), nonhigh-risk drinkers (OR 1.22, 95% CI 1.08-1.38), and subjects who exercised walking (OR 1.44, 95% CI 1.34-1.54). There was no difference in the utilization rate of nutrition labels according to obesity, and the utilization rate of nutrition labels was significantly higher in subjects who had experienced disease education (OR 1.34, 95% CI 1.24-1.44). Conclusions: Education on the use of nutrition labels, which contributes to food selection for healthy eating, might be a tool for dietary management. Moreover, the utilization rate can be a good indicator for predicting the proportion of the population practicing the guide for disease management. Improving the utilization rate of nutrition labels through disease management education can be a useful intervention for people with chronic diseases who need healthy eating habits for disease management and preventing complications, particularly those diagnosed with hypertension and diabetes.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.65-79
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• 2022

Non-face-to-face classes continue due to Covid-19. There have been e-learning classes since the past, but the difference is that the current non-face-to-face classes are blended classes that combine real-time and recording classes or combine face-to-face and non-face classes. It is also characterized by being able to self-filmed or choose various lecture platforms in a place other than a dedicated studio. The advantages of non-face-to-face classes can be learned beyond time and space, and repetitive viewing and learning speed can be adjusted. Greening classes have no time and place constraints, and real-time classes have the advantage of high communication effects with learners. Evaluating whether non-face-to-face classes provide sufficient quality compared to face-to-face classes or e-learning will be necessary if branded classes are considered for post Covid. In this paper, for the evaluation of the service quality of non-face-to-face classes, the essential attributes desired by the instructors were derived from the viewpoint of Kano quality attributes and a quality improvement plan was proposed. After expressing the degree of functions that non-face-to-face classes should have on the X-axis and the satisfaction of learners on the Y-axis, 23 quality attributes were classified into 6 quality dimensions. In addition, satisfaction coefficient, dissatisfaction coefficient, and customer satisfaction improvement index were derived. As a result, 50% of learners were satisfied with non-face-to-face classes, but the preference was slightly higher than satisfaction, suggesting the sustainability of non-face-to-face classes. In terms of the customer satisfaction improvement index, the ranking of attributes with the largest increase in satisfaction when improving class quality was as follows. Professors' quick answers to learners' questions, content that can fully explain the subject, what the professor explains easily, develop high-quality content that can be learned on mobile phones, fairness of attendance checks, and real-time classes should start on time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.spc
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• pp.30-36
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• 2022

A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1216-1221
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• 2022

Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.667-685
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• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.265-273
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• 2022

Waxy corn (Zea mays L.), which contains homozygous mutant alleles for the waxy1 (wx1) gene, is widely consumed as a snack food in Asia. This study evaluated sixteen agronomic characteristics of inbred Korean waxy corn lines to aid development of high-quality waxy corn cultivars. The plant materials studied were 177 inbred waxy corn lines developed by the National Institute of Crop Science, Rural Development Administration, Republic of Korea. For the tested lines, days to tasseling and silking averaged 77.69±2.22 days (with a range of 56-97 days), and 81.12±7.56 days (66-99 days), respectively. Plant length ranged from 88 to 237 cm (averaged 164.88±22.67 cm), ear length averaged 11.75±2.52 cm (5.0-18.5 cm), and ear width averaged 2.94±0.68 cm (1.4-4.5 cm). The number of rows on each ear of corn averaged 12.22±2.22 (7-32 rows) and the kernel number averaged 24.30±4.22 (9-37 kernels) per row. The crude protein content was 12.05±1.53% (8.90-21.80%) and total starch content was 69.27±5.74% (49.5-83.9%). Principal component analysis revealed that ear width, grain length, ear length, days to tasseling, days to silking, percentage of ear setting height, and total starch are features that allow distinction between the 177 waxy inbred corn lines. Hierarchical cluster analysis identified twelve waxy inbred lines that produce tall plants and have a short silking period. These lines may improve yield among quickly growing corn varieties.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.