• Journal of Life Science
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• v.34 no.7
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• pp.493-499
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• 2024

Antimicrobial peptides are antimicrobial substances inherent in animals and plants, with strong antibacterial activity even in small amounts and with various other functions such as antiviral and antioxidant actions. Plants can be grown with just water and sunlight, allowing for their mass production at low costs. However, transforming a chloroplast into one that produces antimicrobial peptides, rather than growing plants, increases the amount of protein expression and minimizes contamination of the ecosystem because gene transfer by pollen does not occur. In that context, using transgenic plant chloroplasts to produce recombinant proteins increases protein degradation and reduces the solubility of proteins. To solve this problem, we fused SUMO, a fusion protein, with a recombinant protein. We also used a 6xHis tag to purify the fusion protein. The antimicrobial peptide stomoxyn is an antibacterial substance found in stable flies. Stomoxyn has an α-helix structure and is amphiphilic, which allows it to dissolve bacterial cell membranes. In this study, we constructed a transformation vector to express stomoxyn in both plant chloroplasts and Escherichia coli and used this vector to confirm the expression of stomoxyn in E. coli. The expression of the protein was then confirmed in E. coli using a transformation vector. The expressed stomoxyn was purified by nickel column and SUMOase treatment, and its antibacterial activity was confirmed using an agar diffusion assay. The EGFP gene was used to ensure that the transformed vector was inserted into the chloroplast.

• Information Systems Review
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• v.18 no.4
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• pp.69-88
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• 2016

Nowadays, organizations have adopted Smart Work to efficiently manage tasks, such as electronic document approval, customer management, and site inspection, without spatial-temporal constraints. Smartphones, which are commonly used in Smart Work, enable individuals to perform their jobs anytime and anywhere, thus blurring the boundary between work and non-work. To solve the problem of blurred work/non-work boundaries, a construct of self-control and affective factors needs to be considered because business style is changed from command to autonomy in the Smart Work context. Moreover, employees can convey their emotions easily over smartphones. Recent marketing studies have analyzed consumers' behavior based on the combination of cognitive, affective, and behavioral components, and researchers of information systems are also interested in these factors. However, previous research has some limitations, such as not classifying factors into cognitive, affective, and behavioral as well as not covering all three factors. Therefore, we explore the roles of cognitive, affective, and behavioral components in emotional exhaustion and education performance, and conduct a survey on undergraduate and graduate students, who are the major users of smartphones. Findings show that when individuals improve their cognitive capability (self-control) and usage experience (smartphone communication and internet usage), they can decrease emotional exhaustion and increase education performance. In the role of affective capability, increasing education performance is partially accepted. These results imply that organizations should not focus on controlling the usage of smartphones but on promoting appropriate smartphone usage.

• Journal of Korean Home Economics Education Association
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• v.22 no.4
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• pp.109-138
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• 2010

This study examined how practical reasoning process is reflected in the 2007 revised home economics textbook of the 7th grade that is being used in schools since 2010. For a textbook analysis of the components of practical reasoning process, 12 published textbooks were all analyzed, and analysis areas were decided by reconstructing the textbook system into introduction, body contents, learning activities, evaluation. Analysis criteria were extracted from the previous literatures. Practical reasoning process was classified into Valued Ends, Context and Background, Alternatives and Means, on sequence, and Action and Reflection. As a result of analyzing categories and problems that practical reasoning process is reflected in the textbook, firstly, here was a category, which Valued Ends was absent in the practical reasoning process. In the relevant category, general problem solving progress and practical reasoning process could not be differentiated, and activity was developed with 'strategies for solution' as objective. Second, there was a category that the practical reasoning process was reflected in body contents. In this category, knowledge, concept, principle, and theory were insufficiently dealt with. Third, there was a category that reflected components of practical reasoning process but was covered with general problem solving process. Fourth, there was a category that described theme of sub-unit and body contents from the different curriculum perspectives. A curriculum perspective works as the foundation of preparing class contents or consistency of methods when developing lessons. Therefore, confusion might occur when a teacher plans a class with this kind of textbook. Fifth, a category that suggested partial components of practical reasoning process was shown the most and this category is difficult to maximize effects of practical reasoning process.

• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.1-14
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• 2004

When two objects are tying in the same visual direction there occurs abrupt depth change between two objects, which is against the assumption of the computational model for stereopsis on the surfaces in a natural scene. For this reason, this stimulus configuration is popularly used in the studies for the effectiveness of the constraints employed in the computational model. Contrary to the results from two nails (or objects) tying in the same visual direction, the two different surfaces from random-dot stereogram (RDS) in the same situation can be seen simultaneously in the different depth. The seemingly contradictory results between two situations my reflect the different strategies imposed by binocular mechanism for each situation during binocular matching process. Otherwise, the surfaces tying in the same visual direction is not equivalent situation to two objects tying in the same visual direction with regards to matching process. In order to examine above possibilities, the stereoscopic depth of the surface was measured after manipulating the visual direction of the surface elements. The visual direction of each dot pair from different surfaces in RDS (in Experiment 1) or the visual direction of line (hawing rectangle with regard to that of the vertical line (in Experiment 2) was manipulated. The stereoscopic depth of the surface was found to be varied depending on visual direction of the surface elements in both RDS and line hawing stimulus. Similar to the results from two nails situation depth of the surface was greatly reduced when each surface element was tying in the same visual direction as that of the other surface element or the other object. These results suggest that binocular mechanism imposes no different strategy in resolving correspondence problem in both two objects and two surfaces situation. And the results were discussed in the context of usefulness of the constraints employed in the computational model for stereopsis.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of The Korean Association For Science Education
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• v.37 no.5
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• pp.825-833
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• 2017

The Korean Ministry of Education has emphasized human resource development with creative and convergent ability for future science and technology development. Korean STEAM Education aims to enhance students' interest and their understanding of science and technology as well as to develop students' creative problem-solving skills. Through STEAM R&E project, students experience self-directed research in order to solve the problem in the context of everyday life. In this study, we aim to find out whether the creative leader competency of high school students changed after they experienced the STEAM R&E project. The creative leader competency consisted of three domains: cognitive, affective, and societal domain. We measured the creative leader competency using the questionnaire scales. The questionnaire was administered to 612 high school students who participated in the 2016 STEAM R&E project. Pre- and post- test scores were collected, and we analyzed it. We compared the mean difference between pre- and post- test scores as well as the mean differences among science high school, gifted school, science core school, and general high school. From the result, we found that all student' creative leader competency improved after participating in the STEAM R&E project in all three domains. The result also showed that students' test scores of science high school and gifted school showed no significant mean differences, while student's scores of both science core school and general high school improved significantly. From the results, we concluded that STEAM R&E activities could be an effective tool in cultivating creative leader competency, especially for general high school students and science core school students. We also suggested that further researches are needed to find how we could enhance students' creative leader competency.

• Cartoon and Animation Studies
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• s.36
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• pp.437-467
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• 2014

This study is intended to reveal reading comic books helps improve creativity. Though the long-lasting negative recognition towards comic books has positively changed these days, we need a ground upon which the social recognition needs improvement in that children's comic books have been used as a learning tool. Its introduction points out that there has been shortage of empirical researches on comic book reading, and as one of the empirical research methods, presents a method of comparative analysis on comic book reading, school study, and creativity tests via survey. The theoretical background in the 2nd chapter, first, puts emphasis on the significance of the creativity theory among all the other theories related to creativity, which focuses on problem-solving capacity. Second, it theoretically reviews the meaning which 'fun' and 'interest' have in development of creativity in the context of developmental process of the modern educational theories. Third, it empathizes that traits of reading comic books start off with 'fun' and 'interest', that awareness of reality gets expanded via the process of characters making their way through a strange world with empathy and absorption, and that comic book reading has to do with creativity. Fourth, it presents a model questionnaire with which to study relationship between comic books and creativity in an empirical way. The analysis on the survey outcome in the 3rd chapter shows, first, that smart students read many comic books, not to mention that studying helps improve creativity, which indicates above all, comic book reading and improvement of creativity are not negatively related, but are mutually complementary. Second, that creativity enhanced by reading comic books is higher than that enhanced by studying, which may mean comic book reading is more effective than studying in developing creativity. It has drawn a conclusion based upon these results, that reading comic books bears positive efficacy on both studying and developing creativity. Standing on this conclusion, it proposes it necessary to develop methods by grades of educating how to read comic books and to provide a recommended list of comic books to read.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.167-185
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• 2019

As most G-20 countries expect medical spending to grow rapidly over the next few decades, the burden of healthcare costs continues to grow globally due to an increase in the elderly population and chronic illnesses, and the ongoing quality improvement of health care services. However, under the rapidly changing technological environment of healthcare and IT convergence, the problem may become even bigger if not properly recognized and not properly prepared. In the context of the paradigm shift and the increasing problem of the medical field, complex responses in technical, institutional and business aspects are urgently needed. The key is to derive a business model that is appropriate for businesses that integrate IT in the medical field. With the arrival of the era of the 4th industrial revolution, new technologies such as Internet of Things have been applied to eHealthcare, and the need for new business models has emerged.In the e-healthcare of the Internet era, it became a traditional firm-based business model. However, due to the characteristics of dynamics and complexity of things Internet in the Internet of things, A business ecosystem-based approach is needed. In this paper, we present and analyze the major success factors of the ecosystem based on the 3 - layer structure of the e - healthcare business ecosystem as a result of research on e - healthcare business ecosystem based on emerging technology such as Internet of things. The three-layer business ecosystem was defined as (1) Infrastructure Layer, (2) Character Layer, and (3) Stakeholder Layer. As the key success factors for the eHealthCare business ecosystem, the following four factors are suggested: (1) introduction of the iHealthcare concept, (2) expansion of the business ecosystem, (3) business ecosystem change process innovation, and (4) business ecosystem leadership innovation.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.6 no.1
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• pp.56-64
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• 1995

Family is a primary unit of the major socialization processing for children. Parents among the family members are one of the most important figures from whom the child and adolescent acquire a wide variety of behavior patterns, attitudes, values and norms. An organization of family members product family structural functioning. Abnormal family structure is one of the most important reference models in the learning of antisocial patterns of behavior. Therefore incest and child sexual abuse including spouse abuse, elderly abuse, and neglect occurs in the abnormal family structural setting. In particular, incest, a specific form of sexual abuse, was once thought to be a phenomenon of great rarity, but our clinical experiences, especially over the past decade, have made us aware that incest and child sexual abuse is not rare case and on the increasing trend. Therefore, the aim of this study was to determine the family problem and dynamics of incest family, and character pattern of post-incest adolescent victim in Korea. A total of 1,838 adolescents from middle and high school(1,237) and juvenile correctional institute(601) were studied, sampled from Korean student population and adolescent delinquent population confined in juvenile correctional institutes, using proportional stratified random sampling method. The subjects' ages ranged from 12 to 21 years. Data were collected through questionnaire survey. Data analysis was done by IBM PC of Behavior Science Center at the Korea university, using SAS program. Statistical methods employed were Chi-square, principal component analysis and t-test etc. The results of this study were as follows ; 1) Of 1,071 subjects, 40(3.7%) reported incest experiences(sibling incest : 1.6% ; another type of incest : 2.1%) in their family setting. 2) The character pattern of post-incest adolescent victim was more socially maladjusted, immature, impulsive, rigid, anxious and dependent than non-incest adolescent. Also they showed some problem in academic performance and their assertiveness. 3) The other family members of incest family revealed more psychological and behavioral problem such as depression, alcoholism, psychotic disorder and criminal act than the non-incest family, even though there is no evidence of the context between them. 4) The family dynamics of incest family tended to be dysfunctional trend, as compared with non-incest family. It showed that the psychological instability of family member, parental rejection toward their children, coldness and indifference among family member and marital discordance between the parents had significant correlation with incest.