• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.154-160
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• 2018

This thesis aims to develop PBL (Problem-Based-Learning) problems. Its goal is for some groups of students to creative their own problems and to confirm the effectiveness of PBL as they apply it to AI (Artificial Intelligence) in engineering schools. Modern industrial society needs competent people who have abilities in cooperative learning, self-controlled learning, united knowledge application, and creative problem-solving. Universities need to offer their students the opportunity to improve their problem-solving and cooperative learning abilities in order to train the competent people that society demands. PBL activity is an appropriate learning method for the accomplishment of these goals. The study subjects are 37 sophomore students in H University who are studying 'AI'. Five PBL problems were submitted to the class over a period of 15 weeks. The students wrote and submitted a reflective journal after they finished each PBL activity. In addition, they filled out a class evaluation form to assess the performances of each member when the $5^{th}$ PBL problem activity was accomplished. The study shows that the students experienced the effectiveness of PBL in many fields, such as the comprehension of the studied contents (86.48%), comprehension of cooperative learning (94.59%), authentic experience (75.67%), problem-solving skills (89.18%), presentation skills (97.29%), creativity improvement (81.08%), knowledge acquisition ability (86.48%), communication ability (97.29%), united knowledge application (78.37%), self-directed study ability (86.48%) and confidence (97.29%). Through these methods, the students were able to realize that PBL learning activities play an important role in their learning. These methods prepare and enhance their ability to think creatively, work systematically and speak confidently as they learn to become competitive engineers equipped with the knowledge and skills that modern industrial society demands.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.6
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• pp.838-851
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• 2015

This study explores the level of designer brands' market oriented attitude through a conceptual framework of market orientation. Designer brands have rapidly increased in the Korean fashion market with a competitive environment that pushes designers to improve market oriented attitudes and strategy. Designers working for 20 brands that the government designated as 'promising creative designer brands' were invited for in-depth interviews, 19 designers from 18 brands participated in this study. The generation of market intelligence that composes market orientation meant that the designers were confirmed to collecting different types of information according to information sources. They showed interest in collecting information on the exploration of design trends from overseas designers as well as operational and managerial information from domestic designers. Fashion-related stakeholders mainly collected feedback on design concepts from the press and public institutions. They collected customer feedback from buyers; however, appropriate feedback was inadequate. Designers generally appeared to place less value on the collection of customer responses and opinions; however, two groups of designers showed customer-oriented attitudes according to accumulated experience. The market-oriented attitude of top designers had an important role in designer brands; consequently, top designers should be properly trained to improve market-oriented attitudes to increase market performance.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.39-50
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• 2015

Genetic algorithm (GA) and particle swarm optimization (PSO) are two excellent approaches to multimodal optimization problems. However, slow convergence or premature convergence readily occurs because of inappropriate and inflexible evolution. In this paper, a novel optimization algorithm with a flexible grid optimization (FGO) is suggested to provide adaptive trade-off between exploration and exploitation according to the specific objective function. Meanwhile, a uniform agents array with adaptive scale is distributed on the gird to speed up the calculation. In addition, a dominance centroid and a fitness center are proposed to efficiently determine the potential guides when the population size varies dynamically. Two types of subregion division strategies are designed to enhance evolutionary diversity and convergence, respectively. By examining the performance on four benchmark functions, FGO is found to be competitive with or even superior to several other popular algorithms in terms of both effectiveness and efficiency, tending to reach the global optimum earlier. Moreover, FGO is evaluated by applying it to a parameter decision in a least squares support vector machine (LS-SVM) to verify its practical competence.

• IE interfaces
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• v.21 no.2
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• pp.229-236
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• 2008

Recently, ubiquitous computing paradigm considers as a tool for making innovation and competitive strength in manufacturing industry like other industries. Particularly, the location-based service that enables us to trace real-time logistics make effective management of schedules for inventory control, facilities and equipments, jobs planning, and facilitate the processes of information management and intelligence, which relate with ERP and SCM in organizations. Our study tries to build the location-based system for products of semiconductors in manufacturing place and suggests the good conditions and effective tracking procedures for positions of products. Our study show that the system is good for the saving of time in tracking products, however, it has to be improved in terms of accuracy. The study verifies the application of RFID technology in manufacturing industry and suggests the improvement of photograph process through RFID. In addition, our research introduces the future operation of FAB in semiconductors' processes that relate with real-time automation and RFID in manufacturing company.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.117-134
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• 2008

The outpaced growth of online channel sales over the traditional retail sales is a result from superior shopping convenience that online stores offer to their customers. One major source of online shopping convenience is a personalized store that reduces customer's shopping time. Personalization of an online store is accomplished by using various in-store shopping behavior data that the Internet and Web Technology provides. Brick-and-mortar retailers have not been able to make this type of data available for their stores until now. However, RFID technology has now opened a new possibility to personalization of traditional retail stores. In this paper, we propose BRIMPS (BRIck-and-Mortar Personalization System) as a system that brick-and-mortar retailers may use to personalize their business and become more competitive against online retailers.

• Journal of the Society of Disaster Information
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• v.2 no.1
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• pp.3-18
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• 2006

Recently the demand for civil bodyguards and security guards shows rapid growth by the social development and improve the quality of life. However the supply and training system have some limitations in spite of the high demand guard-secretary. The main role of secretaries has been to accompany superiors in order to maintain their dignity or trait. But the secretaries are required to play additional roles of safety managers such as a security manager, a protocol manager, an intelligence manager and a protective driver in order to overcome the domestic and the international safety environment and to elevate the quality of service as a competitive work. So, the purpose of this article is to analyse current situation of civil body and security guard training industry and to seek an educational model. For it, the following questions will be examined. First, Do the professional training organizations meet social demand for the body and security guards? Second, What kind of training has to be provide for the body and security guards? and what the qualifications of the trainers? Then, what are the differences in training courses between private organizations and universities? Is there differences in the job placement among the trainers of private organizations and universities? etc.. In summary to meet the social demand common curriculum for the body and security guard will be drawn from the analyses of diverse training organizations with different training courses in contents, training periods, educational value, and social aim.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.29-43
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• 2009

The advancement of emerging technologies can create more national value, and this motivates many nations to invest their resources in the emerging technologies. However, due to limited financial and human resources, even a wealthy nation cannot afford to randomly invest its resource in all profitable technologies. Therefore, cautious appraisal and prioritization of the competitive technologies should be conducted first, and then concentrated investment should be done for only the selected technologies. In this study, we propose a quantitative criterion for prioritizing the targeted electronic device technologies. The prioritization scheme devised in this study consists of a growth layer, a profitability layer, a vitality layer, and an influence layer. The proposed model forecasts the most promising technologies by applying the revised version of the Analytic Hierarchy Process (AHP). We performed empirical experiments on 12 emerging electronic device technologies to analyze the practical applicability of our study. The experimental data was obtained from 70 experts in high-tech industry as a part of the 2004 Prioritization and Selection project that was carried out in South Korea. As a result, the proposed scheme was able to present the most promising areas for investment in the field of electronic device technology.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.115-131
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• 1998

Customer service process is one of the most important processes in today's competitive business environment. Among the various activities of customer service process, equipment malfunction diagnosis activity should be performed fast and accurately. When a customer calls the service center and reports the observed symptoms, he/she describes them in layman's terms. Therefore, the customer-reported symptoms have not been considered helpful information for service representatives. However, in order to perform diagnosis activity fast and accurately, we need to make use of the customer-reported symptoms actively. In this research, we developed three systems called R-EMD (Rule-based Equipment Malfunction Diagnostic system), C-EMD (Case-based Equipment Malfunction Diagnostic system) and R&C-EMD (Rule & Case-based Equipment Malfunction Diagnostic system), each of which diagnoses equipment malfunctions using the customer-reported symptoms. R&C-EMD is a hybrid system that utilizes both rule-based and case-based technologies. The diagnosis rules used in R&C-EMD and R-EMD were not acquired from service manuals or interviews with service representatives. Rater, we extracted them directly from the past diagnosis cases based on symptoms' frequencies. By this way, we were able to overcome the knowledge acquisition bottleneck. Using the real 100 malfunction diagnosis cases, we evaluated the performances of R&C-EMC, R-EMD and C-EMD in terms of speed and accuracy. In diagnosis time, R&C-EMD took longer than R-EMD and shorter than C-EMD. However, R&C-EMC was the best in accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12B
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• pp.1091-1099
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• 2003

Korea National Intelligence Service has been issued on K4 Firewall Certificates, and these K4 Firewalls has b een installing all Korean public organizer. I would evaluate the performance tests between the before setting and the after setting of Packet Filtering, NAT, Proxy, and Authentication services on functions of Solaris K4 Firewall System. Also I had been created by performance test between existing 32 bit and latest 64 bit K4 Firewall System on Solaris Operating System, So that the result of improved more two times passed rate on 64bit than 32bit on Solaris K4 Firewall System, At finally, I would conclude that the change direction will be useful for research and development on K4 Firewall System and Korean Firewall System which is a very competitive system in the world.