• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1517-1527
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• 2020

This study is about the UV protection effect and water resistance of a multiple emulsion (W/O/W) sunblock cream applied with emotional engineering and reports an actual industrial case. Multiple emulsion system of sunblock cream has the characteristics of changing to a W/O type that is soft and moist when applied, and has excellent water resistance after absorption. Multiple emulsion cream is a highly functional sunblock cream that has both moisture and water resistance. It is a stable milky white cream with a viscosity of 36,000 cps. The organic sunscreen used for the sunscreen was ethylhexylmethoxycinnamate and bisethylhexyloxyphenolmethoxyphenyltriazine. Hexagonal zinc oxide and titanium dioxide that block both UVB and UVA were used. As a result of measuring the UV protection effect by the in-vitro method, the UV protection effect (SPF) is 78.9 for multiple emulsion cream, 76.7 for W/O cream, and 71.3 for O/W cream. It was found that the blocking effect was different. This obtained the highest effect value in the multiple emulsion. As a clinical (in-vivo) result of the UV protection effect, the SPF value representing the UV protection effect of the sunblock cream developed with a multiple emulsion system was 85.7, and the PA-value that blocks the UVA area was 26.5, and ++++. It was found that it has a corresponding high blocking effect. As a result of the water resistance test, the W/O/W formulation had a high waterproofing resistance of 93.8% even after 4 hours, W/O had 75.4%, and O/W had a low water resistance of 25.3%. In the results of the HUT test, it was found in the order of multiple emulsion sun block cream > hydrophilic cream > lipophilic cream. Based on the research results of this multiple emulsion, it is expected to be highly active as a sunblock cream dedicated to outdoor activities by improving the feeling of use, UV protection index, and water resistance. Therefore, in this study, a multiple emulsion system of sunblock cream is developed and has a characteristic that changes to a W/O type that has a soft and moist feeling when applied, and has excellent water resistance after absorption.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• Journal of Nutrition and Health
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• v.54 no.6
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• pp.644-663
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• 2021

Purpose: This study was conducted to evaluate the safety of iodine intake based on ingestion levels and urinary iodine excretion of women of childbearing age (15-45 years old) using data from the 2013-2015 Korea National Health and Nutrition Examination Survey. Methods: Iodine intake was calculated using the 24 hours dietary recall method and urinary iodine excretion. The iodine nutrition database for the analysis of dietary iodine intake was constructed using the food composition database of the Rural Development Administration (RDA), the Korean Nutrition Society (KNS), the Ministries of Food and Drug Safety, China and, Japan. The World Health Organization (WHO) evaluation criteria and hazard quotient (HQ) calculated using biomonitoring equivalents (BE) were applied to evaluate the safety of the iodine intake. Results: Of the study subjects, 15.22% had a urinary iodine concentration level of less than 100 ㎍/L, which was diagnosed as deficient, and 48.16% had an excessive iodine concentration of over 300 ㎍/L. Urinary iodine concentration was 878.71 ㎍/L, iodine/creatinine was 589.00 ㎍/g, and iodine/creatinine was significantly higher at the age of 30-45 years. The dietary iodine intake was 273.47 ㎍/day, and the iodine intake calculated from the urinary iodine excretion was 1,198.10 ㎍/day. Foods with a high contribution to iodine intake were vegetables, seafood, seaweed and processed foods. The HQ was 1.665 when the urinary iodine content was > 1,000 ㎍/L. Conclusion: The results of this study implicate that the urinary iodine concentration, rather than the dietary iodine intake, is more appropriate to evaluate the iodine status under the current situation that a comprehensive iodine database for Koreans has not been established.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.155-173
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• 2022

Purpose: This study was undertaken to update the Nutrition Quotient for Elderly (NQ-E), which reflects dietary quality and behavior among Korean older adults. Methods: The first 29 items of the measurable food behavior checklist were obtained from a previous NQ-E checklist, recent literature reviews, and national nutrition policies and recommendations. One-hundred subjects (50 men and 50 women) aged ≥ 65 years living in the Seoul Metropolitan Area, including Gyeonggi Province, completed a pilot survey from March to April 2021. Based on the results of the pilot study, we conducted factor analysis and frequency analysis to determine whether the items of the survey were properly organized and whether the distribution of answers for each evaluation item was properly distributed. As a result, we reduced the number of items on the food behavior checklist and used 23 items for the national survey. Nationwide, 1,000 subjects (472 men and 528 women) aged > 65 years, completed the checklist survey, which was applied using a face-to-face survey method from May to August 2021. The construct validity of the NQ-E 2021 was assessed using confirmatory factor analysis, LISREL. Results: Seventeen food behavior checklist items were selected for the final NQ-E 2021. Checklist items addressed three factors: balance (8 items), moderation (2 items), and practice (7 items). Standardized path coefficients were used as the weights of items to determine nutrition quotients. NQ-E and three-factor scores were calculated according to the weights of questionnaire items. Conclusion: The updated NQ-E 2021 produced by structural equation modelling provides a suitable tool for assessing the dietary quality and behavior of Korean older adults.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1627-1642
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• 2021

This study aims to evaluate physical fitness according to the bone age of youth, and ultimately provide basic data for balanced development of youth through physical fitness standard indicators according to the bone age. A total of 730 youth aged 11 to 13 years in bone age and 11 to 13 years in chronological age were selected as subjects; and after taking X-ray films to calculate the bone age, they were evaluated by using the TW3 method. A total of 2 components in physique, which were stature and weight, were measured using a stadiometer(Hanebio, Korea, 2021) and Inbody 270(Biospace, Korea, 2019). A total of 7 components in physical fitness were measured as well, which included muscular strength (Hand Grip Strength), balance (Bass Stick Test), agility (Plate Tapping), power (Standing Long Jump), flexibility (Sit&Reach), muscular endurance (Sit-Up), and cardiovascular endurance (Shuttle Run). Descriptive statistics and independent t-test were conducted for data processing using the SPSS PC/Program(Version 26.0), and it was considered significant at the level of p< .05. The results of this study may be summarized as follow. First, the result of comparing the bone age and the chronological age of 11 to 13 years old in physical fitness, males showed significant difference in muscular strength, power, muscular endurance, and cardiovasular endurance. In females, muscular strength, balance, agility, power, flexibility, muscular endurance, and cardiovascular endurance showed significant difference. Second, physical fitness standard indicators were presented for each gender and age (11-13 years old) of youth according to the bone age; and based on this, physical fitness standard indicators, which are basic data for physical fitness evaluation according to the bone age of youth, were presented.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.111-129
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• 2022

Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.343-355
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• 2022

This study investigated the consumption tendency and awareness of paprika in order to expand and promote the consumption of Capsicum annuum L. The research investigated the relationship of preference and loyalty based on emotional response of paprika according to the semantic differential scale. The survey was conducted from January to February 2022 using a random sampling method targeting 155 general people, and a total of 142 questionnaires were analyzed excluding 13 wrong answers. The nine items on the awareness of paprika showed to be consisted of three factors such as 'Food taste', 'Usability', and 'Economics' by factor analysis. Regarding to the awareness of paprika the positive answer that 'I think paprika is good for health' among the nine questions was the highest at 92.3%. In the preference aspect of shape, blocky type had the highest preference for the shape of paprika, followed by mini and conical types in order of preference (p < 0.001). As for color preference, yellow paprika was the most preferred, followed by orange, red, and green, showing statistical significance. The emotional response of paprika by paprika image showed a statistically significant difference in the four colors. The words such as 'bright', 'clean', and 'spirited' appeared as representative emotional vocabulary for paprika. Multiple regression analysis was performed to examine the effect of paprika on the three factors of awareness, preference, and loyalty due to the quality of life. As a result, the higher the paprika preference and quality of life, and the higher the taste and availability factors, the higher the paprika awareness and loyalty. As the variable that has the most influence on the loyalty of the survey respondents, preference was found to have the highest explanatory power at 43%. From these results, it was judged as a very important factor in the survey on the shape and color preference of paprika. Therefore, the recent increase in awareness that paprika is good for health is thought to act as a positive factor in revitalizing the domestic market and increasing consumption of paprika in the future. Also, among the three types of paprika, the yellow blunt type showed the highest preference. Therefore, in order to produce and promote this type of paprika, it is also important to increase the cultivation to suit the purchasing propensity of consumers.