• Journal of Yeungnam Medical Science
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• v.24 no.1
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• pp.24-40
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• 2007

Background : Accumulating evidence shows that interleukin(IL)-1 plays a critical role in inflammation and connective tissue destruction observed in both osteoarthritis and rheumatoid arthritis. IL-1 induces gene expression related to cytokines, chemokines and matrix metalloproteinases by activation of many different transcription factors. Materials and Methods : The chondrosarcoma cell line, SW1353, is known to be a valuable in vitro system for investigating catabolic gene regulation by IL-$1{\beta}$ in chondrocytic cells. To explore and analyze the changes in gene expression by IL-1 responsible for arthritis, SW1353 was treated with IL-1 for 1, 6 and 24 h and then total RNAs were purified for each time. The changes in gene expression were analyzed with 17k human cDNA microarrays and validated by semi-quantitative RT-PCR. Results : Greater than a two-fold change was observed in 1,200 genes including metallothioneins, matrix metalloproteinases, extracellular matrix proteins, antioxidant proteins, cytoskeleton proteins, cell cycle regulatory proteins, proteins for cell growth and apoptosis, signaling proteins and transcription factors. These changes appeared to be correlate with the pathophysiological changes observed in early osteoarthritis. Conclusion : cDNA microarray analysis revealed a marked variability in gene expression, and provided insight into the overall molecular changes. The result of this study provide initial information for further studies to identify therapeutic targets in osteoarthritis pathogenesis.

• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.169-206
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• 2009

This study stems from a question, "How should we understand the pattern of the Korean economy after the 1990s?" Among various analytic methods applicable, this study chooses a Structural Vector Autoregression (SVAR) with long-run restrictions, identifies diverse impacts that gave rise to the current status of the Korean economy, and differentiates relative contributions of those impacts. To that end, SVAR is applied to four economic models; Blanchard and Quah (1989)'s 2-variable model, its 3-variable extensions, and the two other New Keynesian type linear models modified from Stock and Watson (2002). Especially, the latter two models are devised to reflect the recent transitions in the determination of foreign exchange rate (from a fixed rate regime to a flexible rate one) as well as the monetary policy rule (from aggregate targeting to inflation targeting). When organizing the assumed results in the form of impulse response and forecasting error variance decomposition, two common denominators are found as follows. First, changes in the rate of economic growth are mainly attributable to the impact on productivity, and such trend has grown strong since the 2000s, which indicates that Korea's economic growth since the 2000s has been closely associated with its potential growth rate. Second, the magnitude or consistency of impact responses tends to have subsided since the 2000s. Given Korea's high dependence on trade, it is possible that low interest rates, low inflation, steady growth, and the economic emergence of China as a world player have helped secure capital and demand for export and import, which therefore might reduced the impact of each sector on overall economic status. Despite the fact that a diverse mixture of models and impacts has been used for analysis, always two common findings are observed in the result. Therefore, it can be concluded that the decreased rate of economic growth of Korea since 2000 appears to be on the same track as the decrease in Korea's potential growth rate. The contents of this paper are constructed as follows: The second section observes the recent trend of the economic development of Korea and related Korean articles, which might help in clearly defining the scope and analytic methodology of this study. The third section provides an analysis model to be used in this study, which is Structural VAR as mentioned above. Variables used, estimation equations, and identification conditions of impacts are explained. The fourth section reports estimation results derived by the previously introduced model, and the fifth section concludes.

• Management & Information Systems Review
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• v.31 no.4
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• pp.559-592
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• 2012

In spite of the transitional changes in the shoe industry in Busan area, regular academic studies on the management plan to improve the practical competitiveness of footwear industry focused in the materials, bio-dynamics, components, and designs, etc. in the engineering viewpoint are very rare. Many reports of policies were published from late 190's to 2000's but they were limited to the identification of practical situations and the measures for strategic alternatives and were not developed to be the academic studies to improve the competitiveness in terms of management control. It is intended to seek for the measures to be reviewed as the alternatives to improve the self-competitiveness of footwear companies by approaching the problems limited to such specific area in the viewpoint of management control. The core of this study is to provide the alternative plans for expansion of the industrial foundation by seeking for the measures to improve competitiveness with application of knowledge management as an alternative for improvement of not transient but sustainable industrial competitiveness, in order to help the export of shoes from Busan area which has been rapidly increased since the Korea-USA FTA and Korea-EU FTA. In such viewpoint, in the study, a questionnaire survey was performed related with the issues of Busan's footwear industry and the plan to implement knowledge management was discussed for improvement of the competitiveness of footwear industry based on the result of such questionnaire survey. As most of studies and directions have been focused in functional shoes, designs, materials, and components, etc., which are related with the properties of human dynamics, as the alternatives for improvement of the footwear industry of Busan area and did not suggest the measures to make basic changes in the management of companies, the implementation of knowledge management was emphasized in order to seek for the direction of such plan. The purpose of this study is to suggest an alternative for construction of industrial eco-system for high added value by seeking for the probability of knowledge management for conversion of footwear industry into knowledge industry. In order to accomplish the effect of increased export as the result of FTA, current management method of footwear companies is limited and the effect of FTA should be maximized by improving the competitiveness with implementation of knowledge management methods. Settlement of such knowledge management will act as the momentum to improve the competitiveness of footwear companies and, in a long-term viewpoint, will be able to maximize the improvement of knowledge industry and creation of job opportunities.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.1
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• pp.123-134
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• 2014

Identification of methods to optimize the growth of a plant community, including the capacity of the soil to further sequester carbon, is important in urban design and planning. In this study, to construct and manage an urban park to mitigate carbon emissions, soil organic carbon of varying biomass, different park construction times, and a range of vegetation types were analyzed by measuring aboveground and belowground carbon in Seoseoul Lake Park and Yangjae Citizen's Forest. The urban parks were constructed during different periods; Seoseoul Lake Park was constructed in 2009, whereas Yangjae Citizen's Forest was constructed in 1986. To identify the differences in soil organic carbon in various plant communities and soil types, above and belowground carbon were measured based on biomass, as well as the physical and chemical features of the soil. Allometric equations were used to measure biomass. Soil total organic carbon (TOC) and chemical properties such as pH, cation exchange capacity (CEC), total nitrogen (TN), and soil microbes were analyzed. The analysis results show that the biomass of the Yangjae Citizen's Forest was higher than that of the Seoseoul Lake Park, indicating that older park has higher biomass. On the other hand, TOC was lower in the Yangjae Citizen's Forest than in the Seoseoul Lake Park; air pollution and acid rain probably changed the acidity of the soil in the Yangjae Citizen's Forest. Furthermore, TOC was higher in mono-layered plantation area compared to that in multi-layered plantation area. Improving the soil texture would, in the long term, result in better vegetation growth. To improve the soil texture of an urban park, park management, including pH control by using lime fertilization, soil compaction control, and leaving litter for soil nutrition is necessary.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Journal of Nutrition and Health
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• v.54 no.3
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• pp.277-291
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• 2021

Purpose: This study was undertaken to identify the alcohol drinking status of industrial workers, their health care practice, and dietary behavior, as well as their nutrient intake. Methods: In July 2019, 220 male subjects working in the Chungnam area were enrolled in the study. Their alcohol drinking status was evaluated by applying the Alcohol Use Disorder Identification-K (AUDIT-K) system. Demographic characteristics, status of health care practice, and dietary behaviors were assessed using a self-administered questionnaire; nutrient intakes were analyzed using 24-hour recalls. Data were analyzed by applying χ²-test, ANOVA, Duncan test, and Pearson's correlation analysis with SPSS v. 25.0. Results: Workers were classified by their alcohol drinking status as 'normal' (84, 38.2%), 'problem drinker' (45, 20.5%), 'alcohol dependence I' (60, 27.3%), and 'alcohol dependence II' (31, 16.0%). The alcohol drinking status showed significant differences with age (p < 0.05), monthly income (p < 0.05), smoking status (p < 0.05), and need for weight control (p < 0.05). Moreover, increased alcohol intake resulted in significantly decreased levels of health care practice and dietary behaviors (p < 0.05, p < 0.01, respectively). The energy intake was highest in the 'alcohol dependence I' group, followed by 'alcohol dependence II', 'problem drinker', and 'normal drinker' (p < 0.05). Intakes of vitamin E, vitamin C, and niacin in the 'alcohol dependence I' group were found to be higher than the other groups (p < 0.05). A negative correlation was obtained between alcohol drinking status, health care practice, and dietary behaviors, whereas a positive correlation was determined between alcohol drinking status, energy and water intakes. Conclusion: Considering these results, we conclude the necessity to consider nutritional and alcoholic education programs for improving the quality of work life of industrial workers, based on their alcohol drinking status.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.46-54
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• 2022

Known for its effectiveness in weight loss and diabetes prevention, Gymnema sylvestre products can be found in the US, Japanese, and Indian markets. However, the recommended dosage or safety of these products has not yet been proven. Therefore, development of an analytical method for detecting the content of Gymnema sylvestre in food products is required. Accordingly, this study proposes an analysis method that can examine Gymnema sylvestre in food using LC-ESI-MS/MS and KASP (Kompetitive Allele-Specific PCR) markers. In LC-ESI-MS/MS, a simultaneous analysis method for gymnemic acid and deacylgymnemic acid was optimized using negative ionization mode, and its validation test was completed for solid and liquid samples. In addition, KASP markers were prepared by finding the specific SNP of G. sylvestre in ITS2 and matK through DNA barcodes. The two KASP markers returned positive FAM fluorescence result when combined with G. sylvestre, and this aspect was confirmed in raw G. sylvestre as well. The applicability of the method was tested on 21 different food and healthy functional products containing G. sylvestre purchased on the internet. As a result, although there was a difference in the ratios of gymnemic acid and deacylgymnemic acid in LC-ESI-MS/MS, the index component was detected in all 21 products samples. In the KASP analysis, 9 products returned positive FAM result, and the rest of the products were found to be containing G. sylvestre extract. This study is the first study to use the dual system of LC-ESI-MS/MS and KASP for the analysis of G. sylvestre. The study has confirmed that these two methods are applicable to the examine G. sylvestre content in food products.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.