• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.178-186
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• 2009

The quality control is needed to ensure the accuracy of medical information and achieved by evaluating the performance of and maintaining the system and practicing various measurements and evaluations. The Korean Institute for Accreditation of Medical Image, therefore, have held educational program for quality control of special medical equipments. The major of programs participants, however, are radiology specialists with only small number of radiological technologists from some hospitals, furthermore, the follow-up education and the share of information between participants and non-participants are insufficient in general, thus, the knowledge level of radiological technologists, regardless of their participation, is relatively low. This study carried out the questionnaire research for the 500 radiological technologists registered in Korean Society of MRI Technology, on the basis of 2008, and performed analysis for five months from May to Oct., 2008. The questionnaires were delivered by post to each radiological technologists and the response rate was 36%(n=180). The results of this revealed that the 86.7% of respondents felt the necessity of inspection on quality management, while only the 27.8% completed the educational program for manager of special medical equipment. and only the half(53.9%) had the knowledge about inspection on quality management. The completion of educational program had no correlations with sex, age, size of occupying hospital, the number of radiological technologists in occupying site and MRI laboratory, career year of general radiologist and in MRI laboratory, and the presence of biomedical engineering department in occupying hospital. The 78.0% of participants at the educational program for quality management held by the Korean Institute for Accreditation of Medical Image had the knowledge about inspection on quality management(p<.05) whereas the 43.9% of the hospitals held such program and the 54.4% of radiological technologists from those hospitals had related knowledge, which indicated that such programs held by hospitals had not effects on the knowledge level of radiological technologists. This indicates also that the contents, methods, and other conditional factors of educational programs are important for the outcome of them.

• Journal of the Korea Society of Computer and Information
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• v.6 no.4
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• pp.188-205
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• 2001

Insurer's duty of declaration is based on reciprocity of principle of the highest good, and recently it is widely recognized in the British and American insurance circles. The conception of fiduciary relationship is no longer equity or the legal theory which is only confined to the nations with Anglo-American laws. Therefore, recognizing the fiduciary relationship as the essence of insurance contract, which is more closely related to public interest than any other fields. will serve an efficient measure to seek fair and reasonable relationship with contractor, and provide legal foundation which permits contractor to bring an action for damage against violation of insurer's duty of declaration. In the future, only when the fiduciary relationship is approved as the essence of insurance contract, the business performance and quality of insurance industry is expected to increase. Therefore, to keep well this fiduciary relationship, or increase the fiduciary relationship persistency rates seems to be the bottom line in the insurance industry. In this paper, we developed a fiduciary relationship maintenance ratio based on comparison by case, which is represented with usually maintained contract months to paid months, based on each contract of the basis point. In this paper we have developed a new business model seeking the maximum profit with low cost and high efficiency, management policy of putting its priority on its substantiality, as an improvement measure to break away from the vicious circle of high cost and low efficiency, and management policy of putting its priority on its external growth(expansion of market share).

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.328-338
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• 2018

Central Asia (Uzbekistan, Kazakhstan, Kyrgyzstan) is a hot and arid continental climate, with most areas (68%) consisting of barren vegetation, desert, and meadows. The main agricultural areas for crop production include irrigated farmland, non-irrigated farmland, grassland, prairie and mountain. We are experiencing climate change with recent climate variability increasing. Agriculture is one of major economic sectors and provides a means of livings for the rural population of Central Asia, especially the poor. In the past two decades, Central Asia has experienced a high population growth rate, with Kazakhstan at 16.8%, Uzbekistan at 34.5% and Kyrgyzstan at 28.4%. As a major industry, Kazakhstan has the largest share of exports of agricultural products followed by petroleum, mineral resources, steel, and chemicals. Uzbekistan is the fifth largest cotton exporter as well as the sixth largest cotton producer in the world. Kyrgyzstan exports ores, stones, cultured pearls, and minerals. These three countries are rich in mineral resources, agricultural products, and energy resources. However, not only do they have difficulties in economic development due to the weakness of logistics and industrial infrastructure, but they also have imperceptible cooperation and investment among countries due to insufficient research and development. Through this study, we will investigate national outlook, economic indicators, major agricultural products, import and export status, and agricultural technology cooperation status, and study how Korean agricultural industry advances into these countries through SWOT analysis. Through this, we hope to contribute to the basic data of Central Asian studies and cooperation and investment in agriculture in each country. In addition, in order to increase cooperative exchange and investment in these countries, we will prepare a Central Asia logistics hub for the rapidly changing interKorean railroad era.

• Journal of Nutrition and Health
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• v.54 no.4
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• pp.398-411
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• 2021

Purpose: The objective of this study was to investigate food and nutrition information utilization practices of adults aged between 20 and 30 years to provide the basic data for developing customized content. Methods: Statistical analyses were performed using the SPSS program (ver. 24.0) for the 𝛘²-test, t-test, one-way analysis of variance, and Duncan's multiple range test. Results: Of the 570 subjects surveyed, 45.4% were men, 54.6% were women, 66.3% were in their 20s, 33.7% were in their 30s, 41.4% were single-person households, and 58.6% lived with their families. On average, 14.2% of televisions (TVs), 26.0% of personal computers (PCs), and 63.7% of smartphones were used for more than three hours per day. 30.9% of respondents searched for food and nutrition information more than once a week. 70.0% of the respondents had then applied the information in real life and 54.7% of the respondents said they would share information with others. Information retrieval rate was in the order of 'restaurant (64.8%)', 'diet (57.5%)', and 'food recipes (55.7%)'. Overall satisfaction with food and nutrition information averaged 3.33 on a five-point scale. Satisfaction score was in the order of 'enough description and easy to understand (3.43)', 'matching title and content (3.35)', and 'providing new and novel information (3.22)'. Satisfaction scores were significantly higher in the group that searched for information (p < 0.001), the group that used the retrieved information in real life (p < 0.001), and the group that conveyed this information to others (p < 0.001). Conclusion: To improve information user satisfaction, it is necessary to provide customized information that fits the characteristics of information users. For this purpose, it is necessary to continuously conduct surveys and satisfaction evaluations for each target group.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.172-191
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• 2023

This study was undertaken to strategize the mixed traffic operation of autonomous vehicles in the pilot zone. This was achieved by analyzing the changes expected when autonomous vehicles are mixed in the autonomous vehicle pilot zone. Although finding a safe and efficient traffic operation strategy is required for the pilot zone to serve as a test bed for autonomous vehicles, there is no available operation strategy based on the mixture of autonomous vehicles. In order to presents a traffic operation strategies for each period of autonomous vehicle introduction, traffic efficiency and safety analysis was performed according to the autonomous vehicle market percentage rate. Based on the analysis results, the introduction stage was divided into introductory stage, transition period, and stable period based on the autonomous vehicle market share of 30% and 70%. This study presents the following traffic operation strategies. Considering the traffic flow operation strategy, we suggest the advancement of the existing road infrastructure at the introductory stage, and operating an autonomous driving lane and the mileage system during the transition period. We also propose expanding the operation of autonomous driving lanes and easing the speed limit during the stable period. In the traffic safety strategy, we present a manual and legal system for responding to autonomous vehicle accidents in the introductory stage, an analysis of the causes of autonomous vehicle accidents and the implementation of preventive policies in the transition period, and the advancement of the autonomous system and the reinforcement of the security system during the stable period. Through the traffic operation strategy presented in this study, we foresee the possibility of preemptively responding to the changes of traffic flow and traffic safety expected due to the mixture of autonomous vehicles in the autonomous vehicle pilot zone in the future.

• Korean small business review
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• v.39 no.1
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• pp.1-39
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• 2017

The first generation of the business that had been founded in 1960~1970s faces the situation to consider the succession of the family business developed by devotion of their whole lives in the critical timing to the next generation. In the process of selecting the party of family business succession, it is required to consider a variety of succession types including smooth transfer to the other family member or the employee of the company, selling the company, or hiring external specialist. Foreign countries acknowledge the importance of the succession in the family owned company to perform multiple studies on the influential factors to the succession, distinction, and types of family business succession; and they utilize the results for the related policy development and the support of family owned business succession. However, few studies have been conducted on the succession of the domestic family owned business and majority of them are related to the types of succession. Considering its share and influential power in the domestic economy, it is necessary to develop the guideline and the policies to solve many issues on the succession of the family owned business by systemic studies. Hence, the impact of the main characteristics in the family owned business on the types of its succession was analyzed in this study focusing on five domains of Socioemtional Wealth (SEW) in view of Behavioral Agency Theory by Gomez-Mejia et al. (2007) using the data from 540 family owned small-to-medium sized businesses so as to analyze the issues on their business succession. Upon the empirical analysis results, it was confirmed that they were influenced to the selection of succession type by family succession > internal employee succession > external succession, for the variables of social contribution which were non-financial characteristics, internal employee succession > family succession > external succession for the intellectual properties, and family succession > external succession for the management participation of the family. The distinction of social contribution were influenced the most to the selection of the succession types. Financial factors, business performance, and R&D investment variables were not significantly influenced to their selection of the succession types. In case of simultaneous management, the family succession rate was high and it showed the control effect to strengthen selecting family owned business with R&D investment, social contribution, and company history variables. The behavioral agency theory used in this study was confirmed with high explanation power on the family owned business succession. The family owned business showed the tendency to maintain SEW, and non-financial factors such as accumulated know-how and social contribution based on the long term history were significantly affected to the succession in the small-to-medium sized family owned businesses, unlike general large sized listed companies. The results of this study are expected to be helpful practically for the succession of the family owned business and to suggest the guideline for the development of governmental policy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.141-158
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• 2023

From the perspective of an entrepreneur, one of the most important factors for understanding the inherent limitations of a startup, reducing the risk of failure, and succeeding is the composition of the talent, that is, the founding team. Therefore, a common concern experienced by entrepreneurs in the pre-entrepreneurship stage or the early stage of startup is the choice between independent startups and co-founding start-up. Nonetheless, in Korea, the share of independent entrepreneurship is significantly higher than that of co-founding start-up. On the other hand, focusing on the fact that many successful global innovative companies are in the form of co-founding start-up, the success factors of co-founding start-up were examined. Most of the related preceding studies are studies that identify the capabilities and characteristics of individual entrepreneurs as factors influencing the survival and success of entrepreneurship, and there is a lack of research on partnerships, that is, co-founding start-up, which are common in the field of entrepreneurship ecosystems. Therefore, this study attempted a multi-case study through in-depth interviews, collection of relevant data, analysis of contextual information, and consideration of previous studies targeting co-founders of domestic startups that succeeded in opportunistic startups. Through this, a model for deriving the phased characteristics and key success factors of co-founding start-up was proposed. As a result of the study, the key element of the preliminary start-up stage was 'opportunity', and the success factors were 'opportunity recognition through entrepreneur's experience' and 'idea development'. The key element in the early stages of start-up is "start-up team," and the success factor is "trust and complement of start-up team," and synergy is shown when "diversity and homogeneity of start-up team" are harmonized. In addition, conflicts between co-founders may occur in the early stages of start-ups, which has a large impact on the survival of start-ups. The conflict between the start-up team could be overcome through constant "mutual understanding and respect through communication" and "clear division of work and role sharing." It was confirmed that the core element of the start-up growth stage was 'resources', and 'securing excellent talent' and 'raising external funds' were important factors for success. These results are expected to overcome the limitations of start-up companies, such as limited resources, lack of experience, and risk of failure, in entrepreneurship studies, and prospective entrepreneurs preparing for a start-up in a situation where the form of co-founding start-up is attracting attention as one of the alternatives to increase the success rate. It has implications for various stakeholders in the entrepreneurial ecosystem.

• Journal of the Korean Society of Radiology
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• v.82 no.5
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• pp.1258-1273
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• 2021

Purpose The balloon-stent technique (BST) has certain strengths as an assisted technique for the treatment of complex aneurysms. After Atlas release, the BST can be executed without an exchange maneuver of the balloon to the stent-delivery catheter. The purpose of this article is to share our experience with the BST using the Scepter-Atlas combination. Materials and Methods Device inspection led us to a simple method to avoid failure in loading Atlas to the Scepter. From March 2018 to December 2019, 57 unruptured distal internal carotid artery (dICA) aneurysms were treated with coil embolization; among which, 25 aneurysms in 23 patients were treated with BST. Clinical and angiographic data were retrospectively collected and reviewed. Results The technical success rate of the Scepter-Atlas combination increased from 50% to 100% after careful inspection. BST angiographic results were comparable to the stent-assisted coil (SAC) group treated during the immediately post-embolization same period (modified Raymond-Roy classification [MRRC] 1 & 2 84% in BST, 96.3% in SAC) and during short-term follow-up (MRRC 1 & 2 95.8% in BST, 88.4% in SAC). A small number of patients showed periprocedural complications, but none had clinical consequences. Conclusion BST using the Scepter-Atlas combination can provide an effective and safe method for the treatment of dICA aneurysms. Scepters can be used as delivery catheters for Atlas.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.