• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.291-299
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• 2016

Recently, the knowledge industry center has played a role as a facility that creates economic added value because of the high-tech companies related to the knowledge industry, information, and communication. On the other hand, support facilities that are provided in the knowledge industry center are meant to support the company in the center and improve the working conditions of laborers. On the other hand, the support policy established by the government applies to some companies, and none of the support policy is carried out in supporting facilities in the knowledge industry center. In this study, multiple analysis was performed, focusing on the support facilities in the knowledge industry center that aims to improve the working environment of laborers. This study suggests the introduction of guidelines to secure adequate area, depending on the type of supporting facilities in the Knowledge Industrial Center. The sharing of facilities, such as cultural and commercial use for Knowledge Industrial Center, corresponding to poor provision, is recommended. Because the analysis of IPA indicates that the area of commercial support facilities are higher than others and cultural facilities are more important and preferred, it is necessary to compose support facilities that consider the user's individual characteristics. Facilities impacting the working environment need to be planned carefully through a district unit plan at the initial stages of development, thus assisting the production activity of workers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.954-957
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• 2005

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence is applied for many industrial product and machine tools are the center of manufacturing devices in intelligent manufacturing system. The purpose of this paper is to present the construction of Rule Base for knowledge structure that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It constructs Rule Base of knowledge used of machine toots. The constructed Rule Base facilitates the effective operation and control of machine tools and will provide a systematic way to integrate the expert's knowledge that will apply Intelligent Machine Tools.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.27-39
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• 2014

The role of R&D center for technology commercialization can be categorized into three distinct stages: the first stage consists in developing industrial problem-solving capability; the second consists in catching up with industrialized economies developing creative imitations of imported technologies; and the third consists in acquiring advanced knowledge creation capability. Accordingly, the R&D center's organization should be aligned with this development strategy. This case study of Kazakhstan provide a managerial implication for the other developing countries. The first stage of development, which may be called the 'industrial problem solving stage,' the center will build the infrastructure in terms of both technology and human-resources. The second stage will involve building up 'knowledge capability' with a view to becoming a major industrial R&D hub in Central Eurasia. In the third stage, the center will create advanced knowledge as a 'world-class knowledge center'. In this regard, the evolution of the R&D center should be described according to the features of the center's services.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.87-93
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• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6344-6353
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• 2014

According to the changes in society, the knowledge industrial center, which is a factory related to the manufacturing industry, is now including various programs, such as information and communication knowledge. This study defined the knowledge industrial center related law into three periods: deduct layout planning type and outside space composition elements by previous research; case analysis; and suggestions of the direction of layout planning and outside space plan. As a result of the analysis, first, before 1999, the layout of the building is made mainly with a car, but depending on the form of the site, it is configured as a centered, side layout. Second, in the case of distribution, the support facility on the lower part is integrated and the factory on the higher part is distributed, so it is partly integrated and the building is unified. Third, beginning with the activation of privately owned public space in a semi-industrial district according to architecture regulations in 1999, the outside space is wider but the construction area is reduced, so the outside space composition has been changing in a similar manner to the planning methods of business facilities, such as office buildings.

• Knowledge Management Research
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• v.20 no.3
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• pp.17-38
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• 2019

Rrecently, companies have made great efforts to satisfy various needs and heightened expectations of customers, and the importance of customer center as customer contact department for customer relationship management is increasing. In the knowledge ecosystem, corporate customer centers are emerging as a new alternative to acquiring corporate competitiveness by increasing sales and increasing market share by improving marketing support activities and customer relationship management at customer contact points. As a result, the interest in the customer center has increased rapidly because it provides the opportunity to contact with the customer. In addition, in the era of the fourth industrial revolution, the customer center, which is a collection of information and communication technologies, has a big databased voice recognition technology to elaborate customer service, thereby enhancing customer satisfaction and contributing to marketing through continuous interaction with customers. Of course, we have the opportunity to transform into the frontline business intelligence front for customer knowledge. This study is a comparative case study on how the customer center of K Life Insurance that takes the lead in the customer center industry has successfully renewed and established their key information systems to improve customer services and reinforce marketing support competencies. Based on the above, this study will present factors affecting successful implementation and settlement of the customer service information systems of customer centers by independently analyzing two individual cases.

• Journal of muscle and joint health
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• v.19 no.3
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• pp.340-349
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• 2012

Purpose: This study aimed to identify the influence of knowledge and subjective health status on health promoting behavior about osteoporosis in industrial workers. Methods: The subjects were 292 industrial workers. Data were collected with structured questionnaires in July 10 to August 20, 2012. The collected data were analyzed with t-test, ANOVA, Pearson's correlation coefficients and hierarchical regression analysis by using the SPSS Win 12.0 statistics. Results: The major findings of this study were as follows; 1) The average scores of knowledge about osteoporosis, subjective health status and health promoting behavior about osteoporosis were 9.26 out of 20, 9.64 out of 14 and 39.77 out of 68. 2) There were significantly positive correlations relationship among knowledge, subjective health status and health promoting behavior. 3) The factors influencing health promoting behavior were age(${\beta}$=.069, p=.032), knowledge(${\beta}$=.026, p=.005), subjective health status(${\beta}$=.058, p<.001). Conclusion: This study suggested that we should develop preventive osteoporosis programs for industrial workers considering these results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.109-114
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• 2005

The founding purpose of Business Incubation System is to induce those businessmen who have technology and promising business ideas but are lacking fund, information, and management skill, and to speed up their business establishment and enhance the level of success by providing them with managerial knowledge, production technology, design, and equipment. While some universities made Business Incubation Center to achieve the above purpose, some other universities, especially the local ones, believed that Business Incubation Center, if managed successfully, could be an accelerator picking up the sluggish local economies. This study studied the motivators that let them move in an Incubating Center, their request for support, their level of expert utilization, and the role of head of a Center. This study found a significant level of correlation among the variables such as industrial-educational cooperation, the development of common items, utilization of professors with matching majors, utilization of research professors, and transfer of technology.

• Korean Architects
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• s.541
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• pp.48-53
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• 2014

• IE interfaces
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• v.25 no.1
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• pp.40-51
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• 2012

Today, many manufacturing companies realize that collaboration is crucial for their survival. Especially, in the perspective of quality, the importance of collaboration is emphasized because economic loss increases exponentially while defective parts go through the process in supply chain. However, the manufacturing companies are facing two main difficulties in implementing collaborative relationships with their suppliers. First, it is difficult for the suppliers to produce reliable products due to their obsolete facilities. The problem gets worse for second- or third-tire vendors. Second, the companies experience the lack of universally understandable set of terminology and effective methodologies for knowledge representation. Ontology is one of the best approaches to expressing and processing a domain knowledge. In this paper, we propose the manufacturing ontology-based quality prediction framework to represent and share the knowledge of industrial environment and to predict product quality in manufacturing processes. In addition, we develop the ontology-based quality prediction system based on the proposed framework. We carried out a series of experiments for an injection molding process at an automotive part supplier. The experimental results demonstrated that the proposed framework and system can be successfully applicable in manufacturing industry.