• Korean Journal of Microbiology
• /
• v.32 no.2
• /
• pp.155-162
• /
• 1994

Cells of Acinetobacter sp. strain JC1 DSM 3803, an aerobic monoxide-oxidizing bacterium, growing on glucose exhibited high catalase activity at the mid-exponential growth phase. The enzyme activity decreased gradually after then until the early stationary phase, increased again at the mid-stationary phase, and then decreased again thereafter. Cells growing on glucose was found to contain three kinds of catalses. Cat1, Cat2 and Cat3. The activities of Cat1 and Cat3 did change significantly during growth, but that of Cat2 exhibited significant variation. Cat3 was found to present only in cells growing on glucose, but not in cells growing on carbon monoxide of methanol. The activities of call and Cat3 in cell-free extracts were stable upon treatment with ethanol and chloroform, but decreased to some extent when the enzymewere treated with 2mM $H_2O_2$ and/or 3-amino-1,2,4-triazole (AT). Cat2 was found to be extremely sensitive to the ethanol-chloroform and $H_2O_2$ treatments, but was insensitive to the AT treatment. Cat1 exhibited enzyme activity after incubation for 1 min at 80$^{\circ}C$. Cat2 and Cat3 did not show enzyme activity after incubation for 1 min at 60$^{\circ}C$ and 70$^{\circ}C$, respectively. Cat2 was found to have peroxidase activity. Cat3 was purified to homogenity in seven steps. The molecular weight of the native enzyme was estimated to be 150,000. Sodium dodecyl sulfate-gel electrophoresis revealed two identical subunits of molecular weight 65,000. The enzyme was found to show two $K_m$ values of 39 mM and 58mM. The optimal pH for the enzyme activity was 7.0, but the activities at pH 6.0, 8.0, and 9.0, were found to be comparable to that at the optimal pH. The optimal temperature for the enzyme activity was found to be 40$^{\circ}C$. The enzyme also exhibited strong activity at 20$^{\circ}C$, 30$^{\circ}C$, and 50$^{\circ}C$. The purified enzyme was not affected by the ethanol-chloroform treatment. The enzyme, howerver, showed less than 10% of the original activity when it was treated with 12 mN AT, 0.1 mM $NaN_3$ of 1mM KCN.

• Journal of Nutrition and Health
• /
• v.51 no.1
• /
• pp.87-102
• /
• 2018

Purpose: The purpose of this study was to develop a valid instrument for measuring the dietary quality and behaviors of Korean elderly. Methods: The development of the Nutrition Quotient for Elderly (NQ-E) was conducted in three steps: item generation, item reduction, and validation. The 41 items of the NQ-E checklist were derived from a systematic literature review, expert in-depth interviews, statistical analyses of the fifth Korean National Health and Nutrition Examination Survey data, and national nutrition policies and recommendations. Pearson's correlation was used to determine the level of agreement between the questionnaires and nutrient intake level, and 24 items were selected for a nationwide survey. A total of 1,000 nationwide elderly subjects completed the checklist questionnaire. The construct validity of the NQ-E was assessed using confirmatory factor analysis, LISREL. Results: The nineteen checklist items were used as final items for NQ-E. Checklist items were composed of four-factors: food behavior (6 items), balance (4 items), diversity (6 items), and moderation (3 items). The standardized path coefficients were used as the weights of the items. The NQ-E and four-factor scores were calculated according to the obtained weights of the questionnaire items. Conclusion: NQ-E would be a useful tool for assessing the food behavior and dietary quality of the elderly.

• (The)Study of the Eastern Classic
• /
• no.66
• /
• pp.303-330
• /
• 2017

The purpose of this article is figuring out the modern understanding of SimChong Jeon's narrative and its storytelling strategy in the movie (2014). In the movie, there are three steps which are based on the temporal flow of narrative. shows the web-like structure of desire especially by focusing on the male character Sim Hakkyu. The relationship among characters in is gradually broken because of the desire. Moreover, the desire pushes Sim Chong who is Sim Hakkyu's daughter into the sacrifice. This part seems similar with the narrative of SimChong-Jeon which has been transmitted since 18~19 century in Choson dynasty. However, also tells a different story which describes the progress of Sim Hakkyu's seeking the real relationship filled with love. This difference is able to make people read with the 'stroytelling' point of view. All the lack or problem in is closely related to the desire of Sim Hakkyu. His narrative is something different from the typical story of SimChong-Jeon. A new narrative of Sim Hakkyu is not Sim Chong centered story but rather the anti of it. 'The other narrative' in seems social practice of storytelling in order to break down the preconception of SimChong-jeon called 'cannon'. This is the storytelling strategy of and it suggests the another way of creating new narrative which is based on the classical cannon.

• Korean Journal of Remote Sensing
• /
• v.14 no.2
• /
• pp.175-195
• /
• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• Journal of Christian Education in Korea
• /
• v.67
• /
• pp.11-44
• /
• 2021

In the early 21st century, the global COVID-19 pandemic, which has arisen during the development of the technological science of the Fourth Industrial Revolution, has been a great challenge in all fields including politics, economy, industry, education and religion in Korean society. To prevent the spread of the COVID-19 epidemic, the Korean government announced 'social distancing guidelines,' focused on the 'prohibition of three conditions'(crowd, closeness, airtight) for safety reasons. These quarantine guidelines made it more difficult for Korean churches and Sunday schools to operate. In general, looking at the statistical data of the major denominations of the Korean Church in the second half of the 20th century, shows that the Church has entered a period of stagnant or declining growth. Data also show that the number of students attending Sunday School is decreasing. The researcher identified four causes of the crisis faced by the Korean church and Korean Sunday school entering the 21st century. These trends are influenced by the tendencies of postmodernism, the deconstruction of modern universalism, the certainty and objectivity of knowledge, and the grand narrative and worldview of diffusion. Moreover, it is a phenomenon in which the young population decreases in contrast to the increasing elderly population in the age of population cliff in Korean society. Sunday Schools are also facing a crisis, as the youth population, who will become the future heroes of the Korean church, is declining. Finally, constraints of Church and Sunday school education activities are due to COVID-19 Pandemic. As analysis shows the loss of the Church's educational vision and a decrease in the passion for education. Accordingly, the researcher suggests four new strategies for the next generation of Korean Sunday schools, whose ranges from 200 members or less; this range covers the majority of Sunday School program run by churches in Korea. First, in the age of postmodernism, a time of uncertainty and relativism, Christian Societies requires teachers who are certain of absolute Christian truth and faith. Second, in an era of declining population cliffs for younger generations, a shift to a home-friendly Sunday school paradigm is needed. Third, during the COVID-19 pandemic, educational activities must appropriately utilize face-to-face and non-face-to-face communication. Finally, even in difficult times, Korean Sunday school should nevertheless remember the Lord's great commandment(Matthew 28:18-20) and restore the vision and passion of education to announce and teach the gospel. The researcher hopes that this study will provide small, positive steps in rebuilding Korean Sunday school educational activities for future generations in difficult times.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.13 no.6
• /
• pp.49-62
• /
• 2018

The purpose of this study is to develop an assessment index for the selection of promising start-ups, which will enhance the efficiency of program that support start-ups. In order to develop assessment models for selecting start-ups, three major research steps were conducted. First, this study attempted to theoretically redefine the assessment index from the perspective of the Balanced Scorecard (BSC) through a literature review. Second, major assessment index were derived using Delphi technique for experts in start-up areas. Third, weights were derived by applying AHP technique to calculate the importance of each index. The results of this study are summarized as follows. First, this study attempted to apply the assessment model for selecting start-ups from the Balanced Scorecard (BSC) view through the previous study review. Second, the final major questions were derived with sufficient opinions collected and structured survey of leading start-up experts in areas related to research subjects and elicited the most representative questions. Third, the results of applying the weights of the main selected assessment index, commercialization viewpoint is the most priority, followed by market view, technology development viewpoint, and organizational capability viewpoint. In the middle section, th ability to make products in the commercialization viewpoint, market competitiveness in the market, product discrimination capacity in the technology development perspective, and the ability of the entrepreneur in the organizational capacity perspective were important. Overall important items were found to be in the order of the capabilities of entrepreneurs, market competitiveness, product fire capability, and product discrimination. The importance of small items was highest priority for comparative excellence of competing products, and the degree of marketability, capacity of entrepreneurship, ability to raise capital, desire for entrepreneurship, and passion were shown. The results of this study presented a conceptual alternative to the preceding study on the development of existing selection assessment indexes. And it provides meaningful and important implications as an attempt to develop more sophisticated indicators by overcoming the limitations of empirical research on only some of the evaluation metrics.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.43-61
• /
• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.75-94
• /
• 2021

The low birth rate and shortened military service period are causing concerns about selecting excellent military officers. The Republic of Korea entered a low birth rate society in 1984 and an aged society in 2018 respectively, and is expected to be in a super-aged society in 2025. In addition, the troop-oriented military is changed as a state-of-the-art weapons-oriented military, and the reduction of the military service period was implemented in 2018 to ease the burden of military service for young people and play a role in the society early. Some observe that the application rate for military officers is falling due to a decrease of manpower resources and a preference for shortened mandatory military service over military officers. This requires further consideration of the policy of securing excellent military officers. Most of the related studies have used social scientists' methodologies, but this study applies the methodology of text mining suitable for large-scale documents analysis. This study extracts words of discriminative characteristics from the Republic of Korea Air Force Non-Commissioned Officer Applicant cover letters and analyzes the polarity of pass and fail. It consists of three steps in total. First, the application is divided into general and technical fields, and the words characterized in the cover letter are ordered according to the difference in the frequency ratio of each field. The greater the difference in the proportion of each application field, the field character is defined as 'more discriminative'. Based on this, we extract the top 50 words representing discriminative characteristics in general fields and the top 50 words representing discriminative characteristics in technology fields. Second, the number of appropriate topics in the overall cover letter is calculated through the LDA. It uses perplexity score and coherence score. Based on the appropriate number of topics, we then use LDA to generate topic and probability, and estimate which topic words of discriminative characteristic belong to. Subsequently, the keyword indicators of questions used to set the labeling candidate index, and the most appropriate index indicator is set as the label for the topic when considering the topic-specific word distribution. Third, using L-LDA, which sets the cover letter and label as pass and fail, we generate topics and probabilities for each field of pass and fail labels. Furthermore, we extract only words of discriminative characteristics that give labeled topics among generated topics and probabilities by pass and fail labels. Next, we extract the difference between the probability on the pass label and the probability on the fail label by word of the labeled discriminative characteristic. A positive figure can be seen as having the polarity of pass, and a negative figure can be seen as having the polarity of fail. This study is the first research to reflect the characteristics of cover letters of Republic of Korea Air Force non-commissioned officer applicants, not in the private sector. Moreover, these methodologies can apply text mining techniques for multiple documents, rather survey or interview methods, to reduce analysis time and increase reliability for the entire population. For this reason, the methodology proposed in the study is also applicable to other forms of multiple documents in the field of military personnel. This study shows that L-LDA is more suitable than LDA to extract discriminative characteristics of Republic of Korea Air Force Noncommissioned cover letters. Furthermore, this study proposes a methodology that uses a combination of LDA and L-LDA. Therefore, through the analysis of the results of the acquisition of non-commissioned Republic of Korea Air Force officers, we would like to provide information available for acquisition and promotional policies and propose a methodology available for research in the field of military manpower acquisition.

• Journal of Intelligence and Information Systems
• /
• v.27 no.3
• /
• pp.199-230
• /
• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• 한국노년학
• /
• v.40 no.4
• /
• pp.707-727
• /
• 2020

This study aims to empirically analyze the role that perception of the probability of lonely death among the elderly people living alone plays in the relationship between perceived social support and preference for institutional care based on Andersen's expanded Behavioral Model (2002). The subjects (n=676) of this study were the elderly people living alone, extracted from the "2018 Seoul Aging Survey." With "perceived social support" as an independent variable, "preference for institutional care" as a dependent variable, and "perception of the probability of lonely death" as a mediator variable, we conducted a Binary Logistic Regression to follow the three steps of analyzing mediation effect, as suggested by Baron and Kenny (1986). The results showed that perceived social support has a negative effect on the preference for institutional care and perception of the probability of lonely death among the elderly people living alone; at the same time, perception of the probability of lonely death was found to have a positive effect on their preference for institutional care. Lastly, perception of the probability of lonely death was found to partially mediate the effect of perceived social support among the elderly people living alone in terms of their preference for institutional care. Based on these findings, the practical implications of this study can be summarized as follows. First, various programs and support should be provided to the elderly people living alone in order to enhance the level of perceived social support, a factor that has been confirmed to increase preference for institutional care among the elderly people living alone. Second, as the perception of the probability of lonely death was confirmed to be a psychosocial factor of the preference for institutional care, we need to promote education and support for older people living alone to prepare them for lonely death. These efforts are expected to form a foundations for implementing a community-based integrated care system, "Aging in Place," which is the policy direction required for older people care.