• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.148-157
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• 2019

An optimized analytical method for sodium iron chloriphyllin in foods was established and verified by using high performance liquid chromatography with attached diode array detection. An Inertsil ODS-2 column and methanol-water (80:20 containing 1% acetate) as a mobile phase were employed. The limit of detection and quantitation of sodium iron chloriphyllin were 0.1 and 0.3 mg/kg, respectively, and the linearity of calibration curve was excellent ($R^2=0.9999$). The accuracy and precision were 93.9~104.95% and 2.0~7.7% in both inter-day and intra-day tests. Recoveries for candy and salad dressing were ranged between 93 and 104% (relative standard deviation, (RSD) 0.3~4.3%), and between 83 and 115% (RSD 1.2~2.0%), respectively. Liquid chromatography mass spectrometry was used to verify the main components of sodium iron chlorophyllin which were Fe-isochlorin e4 and Fe-chlorin e4.

• (The) Research of the performance art and culture
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• no.36
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• pp.185-221
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• 2018

This study examined the process of the formation of Deoneum, Sugungga(水宮歌), and its tendency of the change through the trace of the Pansori masters who worked in 19th century. The time that the main group of the Sugungga masters appeared in the Pansory history is estimated in early 19th century. The Sugungga masters in this time could be divided in two groups, one is the early days masters who worked in early 19th century and the other is the latter days masters who worked in middle and late 19th century. Kwon Sam-deuk(權三得), Song Heung-lok(宋興祿), Yeom Gyeo-dal(廉季達), and Shin Man-yeob(申萬葉) are the Sugungga masters who worked in early 19th century. By the records they left, I could confirm that they used the description about the dramatic characteristics in the work and Soritjo(Pansori master's tonality), like the appearance of 'Bangge(crab)' and 'Tiger', and particularly they developed which has the scene of the Rabbit's deceiving the Dragon King and Rabbit's return, 'Goandaejangja(寬大長者)', 'Gaja-Eoseoga', 'Sojinowha(笑指蘆花)', 'Apnae-Beodeuleun' and the scene of 'Rabbit's curse(the part that Rabbit curses Byeljubu)' etc. I could understand that the interest of the early days Pansori masters about Sugungga is on the characters and the latter part of the work. The separation of Dongpyeonje(東便制) and Seopyeonje(西便制) of Pansori was done in the middle and late 19th century. As the Dongpyeonje master, Song Wu-ryong(宋雨龍), Park Man-sun(朴萬順), Song Man-gab(宋萬甲), Shin Hak-jun(申鶴俊) and Yu Seong-jun(劉成俊) worked. As the Seopyeonje masters, Park Yu-jeon(朴裕全), Kim geo-bok(金巨福), Kim Su-yeong(金壽永) and Baek Gyeong-jun(白慶順) etc. sang Sugungga. The Dongpyeonje masters developed the 'Toggigibyeon(토끼奇變)' related Deoneum paying attention on the latter part of Sugungga same as the early days masters. Meanwhile it looks like that they had interest in developing the parts which belong to the middle and early parts of Sugungga like 'Toggiwhasang(토끼畵像)', 'Gogocheonbyeon(皐皐天邊)' and 'Tobyeolmundab(兎鱉問答)'. The Seopyeonje masters developed the parts belong to the early part of Sugungga, which are related to Dragon King and the courtiers in Sugung palace, like 'YongwangTansik(龍王歎息)'. And I could confirm that they developed the parts influenced by Shin Jaehyo's editorials like 'Tosahobi(兎死狐悲)' and 'Goguksancheon(故國山川)' etc. In short, I could confirm the trend that the Pansori masters in 19th century had interest in from the latter part to the early part of Sugungga. If taking a look focusing on main characters, they moved their interest in from Rabbit to the courtiers including Byeoljubu(鱉主簿) and Dragon King in Sugung palace, and it could say that, in this trend, Sori part and Deoneum were developed.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.193-200
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• 2019

The study was conducted surveying ultrasound room workers on hospital infection awareness in Daejeon and Choong-chunng region. The contamination of ultrasonic probes used in clinical trials was measured using ATP, and the results were verified after using 70% alcohol sterilization. It was measured on the group's general characteristics and the specific categories such as academic background, job type, having professional certificate and infection education. After the examination, the gel removal and method, disinfection status of the probe and variable correlation analysis were performed to analyze the recognition of the ultrasonic probe disinfection. After examination in ultrasound room, it was found that towels were used the most for cleaning, and the gel container was not replaced for more than three months. After 70% alcohol disinfection, ATP contamination was reduced from $1055.4{\pm}944.2$ to $133.5{\pm}93.2$ and the result was analyzed to be statistically significant.(${\rho}<0.01$) The found bacteria were CNS, Gram positive bacillus, and Micrococcus specs. In order to solve this problem, 70% alcohol sterilization was applied and the bacteria were not detected after the treatment. The research shows that regular training on infection control and efforts to prevent infection are necessary, and that 70% alcohol is effective in disinfect the bacteria. Therefore, the medical institution should provide active hospital infection control education to improve the awareness of hospital infection among workers and contribute to the prevention of patient infection. It is also understood that proper use of the results of this study will help prevent infection by means of ultrasonic probes.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.23-34
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• 2019

The U-Healthcare era has evolved with the development of the Internet of things (IoT) in the early stages of being connected as a society. Already, many changes such as increased well-being and the extension of human life are becoming evident across cultures. Korea entered the growing group of aging societies in 2017, and its silver industry is expected to grow rapidly by adopting the IoT of a super-connected society. In particular, the senior shift phenomenon has resulted in increased interest in the promotion of the health and well-being of the emergent silver generation which, unlike the existing silver generation, is highly active and wields great economic power. This study conducted in-depth interviews to investigate the characteristics of the new silver generation, and to develop the design for a wearable serious game that intends to boost the interest of the elderly in exercise and fitness activities according to their personalized physical training regimes as prescribed by the U-Hospital service. The usage scenario of this wearable serious game for the 'U-silver generation' is derived from social necessity. Medical professionals can utilize this technology to conduct health examinations and to monitor the rehabilitation of senior patients. The elderly can also use this tool to request checkups or to interface with their healthcare providers. The wearable serious game is further aimed at mitigating concerns about the deterioration of the physical functions of the silver generation by applying personalized exercise prescriptions. The present investigation revealed that it is necessary to merge the on / off line community activities to meet the silver generation's daily needs for connection and friendship. Further, the sustainability of the serious game must be enhanced through the inculcation of a sense of accomplishment as a player rises through the levels of the game. The proposed wearable serious game is designed specifically for the silver generation that is inexperienced in using digital devices: simple game rules are applied to a familiar interface grounded on the gourmet travels preferred by the target players to increase usability.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Food Engineering Progress
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• v.21 no.2
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• pp.158-166
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• 2017

Although Semisulcospira libertina is generally regarded as a supplement for the alleviation of alcohol hangover, little is known about its effects on cell metabolism. Therefore, this study was conducted to analyze the constituents of the extracts prepared using different extraction methods and to compare their biochemical properties. The amino acid contents were found to be much higher in acidic and enzymatic hydrolysates than hot water extracts from S. libertina. DPPH radical scavenging activities in acidic and enzymatic hydrolysates were higher than those of hot water extracts. Three types of S. libertina hydrolysate was added to HepG2 cells damaged by acetaminophen (AAP), after which the survival rate of HepG2 cell were measured. In addition, lactate dehydrogenase (LDH) activities in the culture media were evaluated. The survival rates of HepG2 cells were $77.0{\pm}4.3%$ and $81.5{\pm}1.3%$ at 3 h and 5h enzymatic hydrolysates, respectively. These cell survival rates were higher compared to those of the negative control group ($67.8{\pm}4.3%$) treated only with acetaminophen. Cellular toxicities induced by treatment with AAP were also significantly alleviated in response to treatment with the extracts of S. libertina. In addition, the activities of 2 key enzymes that metabolize ethanol, alcohol dehydrogenase and aldehyde dehydrogenase, were upregulated by 4.7- and 2.7-fold respectively in response to treatment with a 3 h enzymatic hydrolysate of S. libertina. Taken together, these results provide biochemical evidence of the method by which S. libertina exerts its biological functions, including the alleviation of alcohol hangover and the protection of liver cells against toxic insults.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.51-78
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• 2021

Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.329-341
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• 2020

As COVID-19 pandemic sweeps across the world, more than 45 million confirmed cases and over 1,000,000 deaths have occurred till now, and this situation is expected to continue for some time. In particular, more than half of the infections in European countries such as Italy and Spain occurred in nursing homes, and it is reported that over 4,000 people died in nursing homes for older adults in the United States. Therefore, the issues that need to be addressed after the COVID-19 crisis include finding a fundamental solution to group care and shifting to family-centered care. More specifically, it is expected that there will be ever more lively discussion on establishing and expanding hyper-technology based community care, that is, family-centered care integrated with ICT and other Industry 4.0 technologies. This poses a challenge of how to combine social security and social welfare with Industry 4.0 in concrete ways that go beyond the abstract suggestions made in the past. A case in point is the proposal involving smart welfare cities. Given this background, the present paper examined the concept, scope, and content of non-face-to-face care in the context of previous literature on the function and scope of the social security platform, and the concept and expandability of the smart welfare city. Implementing a smart city to realize the kind of social security and welfare that our society seeks to provide has significant bearing on the implementation of community care or aging in place. One limitation of this paper, however, is that it does not address concrete measures for implementing non-face-to-face care from the policy and legal/institutional perspectives, and further studies are needed to explore such measures in the future. It is expected that the findings of this paper will provide the future course and vision not only for the smart welfare city but also for the social security and welfare system in administrative, practical, and legislative aspects, and ultimately contribute to improving the quality of human life.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.314-320
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• 2021

With the increasing age of motherhood in recent years, attributed to late marriages due to social or environmental factors, the Down's syndrome screening test using biochemical markers has become essential for pregnant women. The process of diagnosing Down's syndrome pregnancy in the high-risk group subjects involves chromosomal analysis, which is performed on samples obtained through invasive procedures such as chorionic biopsy or amniotic fluid. Thus, to reduce unnecessary invasive tests and lower the risk to mother and fetus, it is important to identify a screening test with low risk and high Down's syndrome detection rate. Recently, as the average age of mothers has increased, numerous inspection agencies have classified high-risk mothers as women over the age of 35 years. This study evaluated a total of 36,436 pregnant women aged between 17 to 46 years, and who requested prenatal screening at an inspection agency in Yongin in 2018. Test (13,690 people) Four tests were conducted by applying the time-resolved fluoroimmunoassay method using the direct sandwich and indirect sandwich technology, and the immunoassay method using the sandwich method. We aimed to confirm the difference in positivity rate with increasing age of the subjects. We believe that in future, data obtained from this study will be very useful for the prevention and treatment of Down's syndrome risk at varied inspection institutions, and for prospective mothers.