• Journal of Distribution Science
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• v.13 no.6
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• pp.105-118
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• 2015

Purpose - Currently, strengthening small and medium-sized enterprises (SME) in terms of competitiveness is a key economic issue. However, the problem is that many SMEs lack the internal competence required to cope with a rapidly changing market structure. Such problems can act as an obstacle to economic development, yet most SMEs in Korea are dealing with this problem today. A company's source of competitive advantage is changing from quantity to quality, facility to knowledge, and hardwork to creativity. Under such circumstances, a company should place learning and sharing of knowledge and continuously creating new knowledge as its priority. This study aims to identify the effect of a chief executive officer's (CEO) compassion and forgiveness - positive factors in organizational emotion - on learning organization activities and organizational performance, through a theoretical comparison. Research design, data, and methodology - For this study, SMEs based in Daejeon and Chungcheong area were selected. To secure credibility of the data, the subjects were selected among those who have been working at the business for six months or longer. The survey was conducted for 30 days from March 5, 2015 to April 5, 2015. Both offline and online surveys were conducted. Fifty companies were chosen and 700 questionnaires were distributed, with 506 used for analysis. Fifty subject companies (25 from Daejeon, 10 from Chungnam, 10 from Chungbuk, and five from Sejong) were selected and the objective, target, and survey content were explained to a manager at each company either face-to-face or on the phone. Of the total of 700 questionnaires distributed via mail or e-mail, 78.6% or 550 copies were returned. Excluding 44 insufficient questionnaires, the remainder, 506 questionnaires, were used for analysis. Results - This study analyzed how the CEO's compassion and forgiveness affects learning organization activities and organizational performance. First, compassion of the CEO at the SMEs directly affected the learning organization activities and indirectly affected the organizational performance. Second, forgiveness of the CEO at the SMEs did not affect the learning organization activities and organizational performance directly or indirectly. Conclusions - The study conclusions are as follows. First, CEO compassionate behavior at the SMEs was a significant variable that directly and indirectly affected learning organization activities and organizational performance. Therefore, the CEO of an SME can create a positive organizational atmosphere through compassionate behaviors in the organization. Second, the forgiving behavior of the CEO did not have direct or indirect effects on learning organization activities and organizational performance. However, the reason for a CEO to continue his or her forgiving behavior is because it strengthens employee resilience, commitment, and self-efficacy to protect the organization from negative influences such as layoffs, risks, and wrongdoings. The action of forgiveness does not have direct or indirect effects. However, the CEO shall continue such behavior to strengthen members' physiological resilience, commitment, and self - effectiveness, and to protect the organization from risks including layoff and external negative factors.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.161-171
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• 2009

In this paper, we propose an automatic method for setting data constraints of a data cleansing service, which is for managing the quality of data exchanged between composite services based on SOA(Service-Oriented Architecture) and enables to minimize human intervention during the process. Because it is impossible to deal with all kinds of real-world data, we focus on business data (i.e. costumer order, order processing) which are frequently used in services such as CRM(Customer Relationship Management) and ERP(Enterprise Resource Planning). We first generate an extended-element vector by extending semantics of data exchanged between composite services and then build a rule-based system for setting data constraints automatically using the decision tree learning algorithm. We applied this rule-based system into the data cleansing service and showed the automation rate over 41% by learning data from multiple registered services in the field of business.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.123-131
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• 2015

Recently the development of ICT has a big impact on education field, and diffusion of smart devices has brought new education paradigm. Since people has an opportunity to use various contents anytime and communicate in an interactive way, the method of learning has changing. In 2011, Korean government has established the smart education promotion plan to be a first mover in the paradigm shift from e-learning to smart learning. Especially, government aimed to improve the quality of learning materials and method in public schools, and also to decrease the high expenditure on private education. However, the achievement of smart education policy has not emerged yet, and the refinement of smart learning policy and strategy is essential at this moment. Therefore, the purpose of this study is to propose the successful strategies for smart learning in public education. First, this study explores the status of public education and smart learning environment in Korea. Then, it derives the key success factors through SWOT(Strength, Weakness, Opportunity, Threat) analysis, and suggests strategic priorities through AHP(Analytic Hierarchy Priority) method. The interview and survey were conducted with total 20 teachers, who works in public schools. As a results, focusing on weakness-threat(WT) strategy is the most prior goal for public education, to activate the smart learning. As sub-factors, promoting the education programs for teachers($W_2$), which is still a weakness, appeared as the most important factor to be improved. The second sub-factor with high priority was an efficient optimizing the capability of new learning method($S_4$), which is a strength of systematic public education environment. The third sub-factor with high priority was the extension of limited government support($T_4$), which could be a threat to other public schools with no financial support. In other words, the results implicate that government institution factors should be considered with high priority to make invisible achievement in smart learning. This study is significant as an initial approach with strategic perspective for public education. While the limitation of this study is that survey and interview were conducted with only teachers. Accordingly, the future study needs to be analyzed in effectiveness and feasibility, by considering perspectives from field experts and policy makers.

• Journal of Internet Computing and Services
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• v.13 no.6
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• pp.41-53
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• 2012

Open educational resources(OER) enable the spread of mutual information exchange and provide advantages to both their users and institutions, such as reducing costs, improving content quality, and establishing relationships. The recent research on OER was about their connection to formal education, copyright trends, and corporate e-learning. There have been very few studies, however, on the utilization of OER and on the problems related to their practical use. Thus, this study was conducted for the purposes of analyzing the status of OER usage in education-related institutions and of providing suggestions for institution operation based on the analysis results, to promote the use of OER. A survey was conducted among more than 200 institutions in Asia, and the survey results showed that 'images and visual materials' are the most commonly used materials in Asia, and that the factors barring OER usage in the said region are 'lack of awareness', 'lack of skills', 'the absence of a reward system', and poor cooperation in participation. To promote OER usage, each institution should provide training courses about awareness, utilization skills, and copyrights. There is also a need to provide support for the establishment of reward systems and environments for OER usage. Finally, more active participation is required for inter-agency cooperation in OER sharing.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Knowledge Management Research
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• v.10 no.3
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• pp.51-80
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• 2009

The purpose of this study is to empirically analyze the impact that occurs when Korean organizations make practical use of various information technology tools and systems in the knowledge management process, such as sharing, learning and creating knowledge. Such a process is usually made through online and offline knowledge management activities. This paper also verifies how the externalization of tacit knowledge, and the internalization of explicit knowledge via the Internet and offline socialization activities have altered the mechanisms of knowledge transfers inside organizations. For the research, a survey was conducted on the satisfaction and usability levels of information technology, and the impact of IT usage on the results of knowledge management activities and knowledge transfers. 622 Korean organizations were surveyed, including major listed firms and public organizations. The results were examined as an online/offline integration process using SECI's Model proposed by Nonaka (1994, 1995). The analysis shows that information technology satisfaction and the usage of information technology help accelerate the pace of the knowledge flow and amplify the volume of the knowledge transfer by boosting the externalization and internalization processes-also known as knowledge management activities. However. there is no distinct correlation between information technology and socialization, an offline knowledge transferal activity. In particular, the quality of knowledge-an end result of knowledge transfer-does not improve merely by the externalization of online knowledge and instead requires the internalization of knowledge processes. Above all, the research reveals that offline socialization processes vastly contribute to the improvement of knowledge quality. This paper suggests that in order to ensure a transfer of quality knowledge, an organization or a company should focus on the use of information technology rather than the satisfaction level of information technology, and that knowledge transfers via the Internet has limitations in creating high quality of knowledge. For an organization to ensure the transfer of high-quality knowledge, the organization should not entirely hinge the transfer of knowledge online, as it is essential to have an offline method-a form of socialization such as a 'community of practice.'

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.493-503
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• 2011

The Korea Ministry of Education, Science and Technology (MEST) determines admission quota of cyber universities. MEST's decision is made based on each university's physical and administrative capacity for handling admission numbers. However, the unique characteristics of cyber universities (e.g., online teaching and learning environments) are not considered in MEST's current decision process. MEST also lacks specifics in their policies that are required to ensure university's autonomous control for admission number as well as learners' rights and quality assurance. This study intended to improve decision making process on admission quota of cyber universities so as to increase quality assurance of education. The alternative admission quota decision frameworks have been formulated based on (a) the analysis of the current practices of cyber universities, (b) focus group interviews, and (c) recommendations of the expert.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.76-83
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• 2023

Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.

• Journal of Family Resource Management and Policy Review
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• v.8 no.1
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• pp.47-60
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• 2004

Recognizing a tremendous increase in the Internet users and popularity of E-learning through the Internet, this study attempted to analyze interactive financial education web sites for children. Using meta search engines and major search engines, interactive financial education web sites identified based on the three criteria and analyzed in terms of the appropriateness for specific age groups, the coverage of contents related to the basic knowledge for financial literacy, and the interactive activities. The results showed that financial education web sites for children were needed to be improved in terms of both quantity and quality. The study also provides a guideline how to search for an appropriate financial education web sites for children when parents want teach about money to their children.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.79-80
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• 2011

국방기술 및 무기체계의 도입은 다양한 형태의 정보원을 바탕으로 다각정인 분석을 해야 하며, 국가 경제 및 정치적인 사항 등 많은 요소의 영향을 받는다. 또한 한 번 도입된 체계는 짧게는 5년에서 길게는 10년 혹은 15년에 이르기 까지 아주 오랜 기간동안 도입되어야 하기 때문에 개발 단계에서 이를 전력화 하고 유지 보수하는 단계에 이르기 까지 일괄적이면서도 미래 선도 기술에 대한 예측이 가능하도록 서비스가 되어야 한다. 아울러 해를 거듭할 수록 최첨단 군사기술이 등장하고 있기 때문에 다양한 학습 콘텐츠를 제공하기 위해서는 시맨틱 검색에 기반한 다양한 국방 기술 정보를 제공하는 시맨틱 검색 환경을 제공해야 한다. 본 고에서는 이에 따른 시맨틱 검색 및 복합지식 기반 이러닝 환경의 프로토타입을 제시한다.