• Journal of Radiation Industry
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• v.10 no.4
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• pp.211-217
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• 2016

We examined damages from gamma-irradiaion and determined the optimal gamma-ray dose for mutation breeding in lentil (Lens culinaris L.) bean. Four individual lines (L-C, L-2, L-8 and L-9), that have remarkable adaptability in South Korea were gamma-irradiated at doses of 50, 70, 100, 200, 300, 400, and 500 Gy. The germination rate of seed decreased as the dose increased over 50 Gy in all lines. However, $LD_{50}$ and $RD_{50}$ were different among lines. The median lethal doses($LD_{50}$) were approximately 127 (L-C), 74 (L-2), 95 (L-8), and 144 (L-9) Gy. The median reduction doses($RD_{50}$) for plant height, number of leaves, root length, and flash weight were 156, 176, 150, and 180 Gy for L-C, 253, 198, 127, and 142 Gy for L-2, 188, 175, 200, and 190 Gy for L-8, and 162, 210, 224, and 184 for L-9, respectively. The growth characteristics of the $M_1$ generation decreased as the dose increased over 70 Gy. The optimal doses of gamma irradiation for mutation breeding of lentil were determined to be 70 Gy (L-2, L-8) and 100 Gy (L-C, L-9). We performed the comet assay to observe nuclear DNA damage induced by gamma-irradiation. In comet assay, a clear difference was identified over 100 Gy treatments. With increasing doses of gamma-ray in the range of 50 to 500 Gy, the rate of head DNA was decreased significantly from 97.5% to 81.6%. Tail length was consecutively increased from $1.9{\mu}m$ to $17.4{\mu}m$. Our result provides basic information for construction of mutant pools in lentils.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.227-234
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• 2018

The smart irrigation system using ICT technology is crucial for stable production of upland crops. The objective of this study was to develop a smart irrigation system that can control soil water, depending on irrigation methods, in order to improve crop production. In surface irrigation, three irrigation methods (sprinkler irrigation (SI), surface drip irrigation (SDI), and fountain irrigation (FI)) were installed on a crop field. The soil water contents were measured at 10, 20, 30, and 40 cm depth, and an automatic irrigation system controls a valve to maintain the soil water content at 10 cm to be 30%. In subsurface drip irrigation (SSDI), the drip lines were installed at a depth of 20 cm. Controlled drainage system (CDS) was managed with two ground water level (30 cm and 60 cm). The seasonal irrigation amounts were 96.4 ton/10a (SDI), 119.5 ton/10a (FI), and 113 ton/10a (SI), respectively. Since SDI system supplied water near the root zone of plants, the water was saved by 23.9% and 17.3%, compared with FI and SI, respectively. In SSDI, the mean soil water content was 38.8%, which was 10.8% higher than the value at the control treatment. In CDS, the water contents were greatly affected by the ground water level; the water contents at the surface zone with 30 cm ground water level was 9.4% higher than the values with 60 cm ground water level. In conclusion, this smart irrigation system can reduce production costs of upland crops.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.119-133
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• 2022

One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.212-220
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• 2022

When it comes to single node leafy stem cuttings of rose (Rosa hybrida), environmental management such as air temperature, relative humidity, and light affect productivity. In order to investigate the effect of air temperature and relative humidity on the cutting success rate and rooted cuttings quality, a transparent airtight box was used to implement a closed system. We have also tried to find out the most effective photoperiod and the number of leaflets in closed system using artificial light (white LED, 104.0 µmol·m^-2·s^-1 photosynthetic photon flux density). The first experiment was conducted for a total of 6 weeks under 4 airtight period conditions. The number of roots and longest root length decreased as the airtight period increased. But there were no significant differences in the survival rate, shooting rate, and rooting rate according to airtight periods. In the second experiment the results indicated that survival and shooting rate were significantly affected by the photoperiod (0/24, 2/22, 4/20, 8/16, and 16/8 h), the number of leaflets (0, 2, and 4 leaflets) of the cuttings and their interaction. The survival rate was the highest in the 16-h day length and 4 leaflets. By considering survival rate and shooting rate with energy efficiency, the 8-h day length and 2 or 4 leaflets were judged to be the most effective.

• Korean Journal of Plant Resources
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• v.29 no.4
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• pp.495-503
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• 2016

In the present study, we investigated the plant growth characteristics and biological activity of four asparagus cultivars grown using two cultural methods and tested the possibility of domestic open field. The number of shoots, buds, roots, shoot and root fresh and dry weights, and total dry weight of the four asparagus cultivars grown in a plastic house were higher than those of the same cultivars grown in an open field. Of the cultivars grown in the open field, Jersey Giant had greater shoot number than the other cultivars. In plastic house cultivation, the number of buds in Jersey Supreme was greater than the other cultivars. The total flavonoid content of the Jersey Giant was greater than the other cultivars, but cultural method was unaffected. The total polyphenol contents in asparagus cultivars grown in the plastic house were higher than those of cultivars grown in the open field. The total polyphenol content of the Jersey Giant grown the plastic house was significantly higher than those of other cultivars. Antioxidant activity such as catalase (CAT) and peroxidase (POX) did not differ significantly with cultural methods and among the cultivars. Ascorbate peroxidase (APX) activity of asparagus cultivars grown in the open field was higher than that of cultivars grown in the greenhouse; the highest APX activity was detected in UC157. Thus, greenhouse cultivation is expected to improve plant growth characteristics and biological activities of asparagus cultivars; each cultural method should be considered when selecting a suitable cultivar for high yield and high bioactive compound content.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.44 no.3
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• pp.259-266
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• 2018

In today's society, where people look younger than their chronological age due to improvements in the quality of life, there is a gaining interest in anti-aging and how people compare to those in the same age group. We evaluated the wrinkle index, which is the most important attribute amongst skin parameters, to evaluate external age (wrinkle age). The wrinkles of the whole face were scored by divided 8 areas (forehead, glabella, nasal root, upper eyelid, lower eyelid, crow's feet, nasolabial groove and perioral skin) and analyzed the correlation between chronological age and skin parameters. 206 subjects (Korean female, n = 105 and Mongolians female, n = 101) were enrolled. Subjects were divided into four groups by ages: 20s, 30s, 40s, and 50s. Wrinkle scores of 8 areas were evaluated and developed a calculation formula based on the wrinkle scores. Skin characteristic parameters were measured about skin elasticity, pore, wrinkle, sebum secretion. There was no difference between the calculated ages and the chronological ages in Korean women. On the other hand, Mongolian looked older than chronological age by 9 years. The correlation between the facial wrinkle ages and skin physiology parameters was presented in the order of skin elasticity > pore or crow's feet > skin tone > sebum secretion in both countries. Skin elasticity represented the most related parameter with the facial wrinkle ages. This study identified the skin wrinkle patterns of Korean and Mongolian women and the wrinkle age calculation formula developed from this study can be used as a tool for calculating the facial wrinkle ages in cosmetic studies.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.6
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• pp.909-919
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• 2010

The purpose of this study was to investigate the demand and use of fresh-cut produce in school foodservice and restaurant industries. The subjects of this survey study were 200 school nutritionists and 70 cooks or managers in the restaurant industry nationwide. The data were collected by means of self-administered or e-mail questionnaires. Data analysis was completed using the SPSS window (ver. 12.0) program including frequency, $\chi^2$-test and t-test. Survey questions assessed the general characteristic of respondents, and the supply, use, and demand of fresh-cut produce in school foodservice and restaurant industries. Over 74% of the subjects have used fresh-cut produce. Most of the school foodservice (84.0%) kept fresh-cut produce for one day, while restaurant industry (28.3%) kept them up to three days. The nutritionists of school foodservice and managers of restaurant industry considered origin and date of production as the most important factor, respectively, when fresh-cut produce were being used. Fresh-cut root vegetable, such as potato and carrot was used mostly. The main reason not to use the fresh cut produce was due to the distrust of the fresh-cut produce safety in school foodservice and cost in restaurant industry. The main problem in fresh-cut produce use was the need of rewashing (29.9%) in school foodservice and irregular size (39.0%) in restaurant industry. These results indicate that the quality standard and size specification must be prepared with production guideline of safe fresh-cut produce.

• Journal of Bio-Environment Control
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• v.26 no.2
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• pp.56-63
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• 2017

This study was carried out to establish qualities of watermelon seedling (Citrullus lanatus) according to raising seedling period (RSP; 40, 45, 50, 55, 60, and 65 days) and was carried out to investigate growth characteristics after planting of the seedlings. In seedling qualities according to RSP, Plant height, stem diameter, leaf area of seedling with RSP 65 treatment were significantly increased. Fresh and dry weight in the above of corp showed a significant difference among the seedlings with RSP 40-45, RSP 50-60 and RSP 65 treatment, and that in of root were significantly higher in the seedlings with RSP 40, 45, 65 treatments than with other RSP treatments. S/R ratio was lower in the seedlings with RSP 40 and 45 treatments than with other RSP treatments. RSP affected to the leaf area and S/R ratio of seedling. After 11 weeks after planting of a various seedlings, except that height and node number of plant with 45 RSP treatment was lower than other RSP treatments, other growth characteristics were not significantly different amon RSP treatments. Leaf area, fresh weight, dry weight and S/R ratio were lowest in plant with RSP 65 treatment. Relative growth rate and net assimilation rate of planted watermelon tended to decrease and leaf area ratio was continuously increased until 9th week in the all treatments. The lighter and heavier fruit were produced in plants with RSP 40 and RSP 65 treatments (9.7 kg and 9.9 kg) and in RSP 50 and RSP 55 treatments (both 11.0kg), respectively. Fruit sugar contents was highest in fruit with RSP 45 treatment, and was lowest in RSP 50 and RSP 60 treatments. RSP showed a polynomial regression relation with the increment of fruit weight and the weight of harvested fruit. Considering the increment and weight of fruit, the most for RSP of watermelon seedling for planting were 50-55 days.