• The Journal of Information Systems
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• v.16 no.1
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• pp.201-230
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• 2007

Recently, the growth of e-Learning systems and its related information technology has presented a unique challenge for both schools and industry. It would make an extremely phenomenal paradigm shift in the educational method and practice. Methods of assessing the quality of e-teaming services and contents are critical issue in both practice and research. Moreover, many researchers are interested in what qualify factors more affect to the Performance of e-Learning service. Nevertheless, service quality is a construct that is difficult to define and measure. e-Learning services are composed of many factors, and they are more complicated than the traditional education services because they we performed on the distance basis and the many platforms of IT infrastructure. The purposes of our research are to classify the e-Learning service dimension and identify their factors, to develop the measurement of the factors, and finally to test empirically their relationship between the service factors and e-Learning service performance. For the development of the service factors we considered SERVQUAL model and SERVPERF model which were developed in the service marketing area. The SERVQUAL model was more fitted to the e-Learning services than the latter. From that we derived several factors that fit to our research domain, ie, tangibles, access, reliability, credibility, security, responsiveness, assurance, empathy. We combined three factors of them(reliability, credibility, security) into a factor, system stability for the semantic simplicity, and divided responsiveness factor into system operator responsiveness and teacher responsiveness as the entity based dimension classification. In the e-Learning services research, Most researcher are mentioned the quality factors of contents, so we added to two contents quality factors, ie, contents production method and richness of contents itself. We examined the relationship between the service quality factors and e-Learning performance(student satisfaction and service reuse intention). As result three quality factors(contents production method, teacher responsiveness, empathy) significantly affected student satisfaction. To the other performance variable, ie, service reuse intention, the teacher related quality factors(such as teacher responsiveness, assurance, empathy) affected only. In conclusion, even in the on-line distance teaming, the teacher's role md earnestness is as important as ever.

• Transactions of the KSME C: Technology and Education
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• v.1 no.1
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• pp.33-38
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• 2013

Offshore drilling refers to a mechanical process where a wellbore is drilled through a seabed. It is typically carried out in order to explore for and subsequently extract petroleum which lies in rock formations beneath the seabed. There are many different type of facilities from which offshore drilling operations take place. These include bottom founded drilling rigs, combined drilling and production facilities either bottom founded or floating platforms, and deepwater mobile offshore drilling units including semi-submersibles and drillships. These are capable of operating in water depths up to 3,000 m. In this paper, we introduce the drilling system, which is mounted on the offshore drilling facilities.

• Steel and Composite Structures
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• v.37 no.1
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• pp.91-98
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• 2020

Steel plate shear walls are recently used as efficient seismic lateral resisting systems. These lateral resistant structures are implemented to provide more strength, stiffness and ductility in limited space areas. In this study, the seismic behavior of the multi-story steel frames with steel plate shear walls are investigated for buildings with 4, 8, 12 and 16 stories using verified computational modeling platforms. Different number of steel moment bays with distinctive lengths are investigated to effectively determine the deflection amplification factor for low-rise and high-rise structures. Results showed that the dissipated energy in moment frames with steel plates are significantly related to the inside panel. It is shown that more than 50% of the dissipated energy under various ground motions is dissipated by the panel itself, and increasing the steel plate length leads to higher energy dissipation capability. The deflection amplification factor is studied in details for various verified parametric cases, and it is concluded that for a typical multi-story moment frame with steel plate shear walls, the amplification factor is 4.93 which is less than the recommended conservative values in the design codes. It is shown that the deflection amplification factor decreases if the height of the building increases, for which the frames with more than six stories would have less recommended deflection amplification factor. In addition, increasing the number of bays or decreasing the steel plate shear wall length leads to a reduction of the deflection amplification factor.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.159-180
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• 2022

Recently, services using metaverse in various fields are increasing, the technology is behind the metaverse is rapidly developing. Consequently, it is necessary to provide metaverse services in university libraries. Therefore, this study examined the status of using metaverse in domestic university libraries and the librarians response to it. To this end, the cases of foreign libraries and domestic university libraries were analyzed. Furthermore, an interview was conducted with nine librarians of the university library, who has running metaverse service, to collect data on the current status of the university library metaverse and perceptions of it to identify difficulties and requirements of running the service. Based on the results, it is proposing to get the differentiation of metaverse service, acquire professionals, activate education, expand the browsing feature, and select proper platforms as a way to vitalize the metaverse of domestic university libraries. It is expected that this study will help to running or planning the metaverse service of the university library.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.7-15
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• 2020

As the paradigm shifts from treatment and provider-centered healthcare to prevention and consumer-centered healthcare, the integration of ICT convergence technology is calling for an era of digital healthcare industry revival in the Fourth Industrial Revolution. It is possible to provide individual customized medical services utilizing various medical data, and it is possible to provide various medical services that transcend time and space through integration with other industries. Such digital healthcare includes health, nutrition, exercise, and patient care, while the digital healthcare industry includes healthcare and IT related to medical devices, medical information systems, and healthcare platforms that can provide personal health and medical information. Due to the social demands of the aging and the increase of chronic diseases, digital healthcare is considered as an important policy in the fourth industrial revolution in Korea. In order for the digital healthcare industry to contribute to the prolongation of human life and the improvement of quality of life, it is urgent to develop related infrastructures, legal institutions, and prepare policies. In addition, it is important to activate convergent education to foster talents who will lead the digital healthcare industry. The purpose of this study was to examine the trends of the digital healthcare industry in the era of the fourth industrial revolution and the direction of government R & D policies, and to derive directions and suggestions for future development.

• Journal of the Korea Institute of Construction Safety
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• v.2 no.1
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• pp.28-35
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• 2019

The average number of deaths in the construction industry reaches 500 per year, and in particular, it is confirmed that the type of accidents and deaths caused by disasters such as work platforms has occupied more than 60% of the total. In this study, we presented a structured and combined solution for technology, management, education, and cost that can solve systematically, politically, and external environmental factors as well as direct influence factors. In addition, we examined the safety and safety standards of domestic and international safety, and discussed implications. First, direct impact factors, organizational impact factors, policy influence factors, and external environmental impact factors were examined and classified into technical, education, and institutional dimensions. Second, in relation to the installation of the work scaffold, the standards (OSHA 1926.452), UK (The Work at Height Regulations 2005 No.735, BS5975), Japan (Labor Safety and Sanitation Regulations) and Germany (DIN 4420_4, DIN EN12810). In the case of domestic safety standards, similar to the foreign safety standards, safety measures such as materials and specifications are applied. However, details related to the installation, assembly and structure of the work platform are somewhat different from those in the United States and the United Kingdom excluding Japan. Using the results of this study, it is possible to understand the cause of the accident of foot pedestrian accident more systematically and comprehensively, and safety managers and researchers are expected to help in the accident investigation.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.115-125
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• 2016

Recently, many attentions have been paid to conducting convergence research across diverse disciplines. Along with this convergence era, an IT-based multi-disciplinary convergence project, called EDISON (EDucation-research Integrated Simulation On the Net), has been launched to support the studies of researchers engaged in several computational science and engineering (CSE) fields and to boost learning motivations of CSE students. Since 2011, we have been successfully carrying out the EDISON project. EDISON as a cyber-learning platform enables CSE researchers to share their own high-performance computing (HPC) simulation softwares developed to solve their research problems accompanying large-scale computation and I/O and users to run the softwares with little constraints on the web. Also, the EDISON platform has been utilized as lecture material by many universities in Korea. This article introduces the construction and service statistics of this EDISON platform. Specifically, we explicate several distinctions between EDISON and existing other HPC service platforms and discuss a three-layered technical architecture of the EDISON platform. We then present the up-to-date service statistics of EDISON over the past four years. Finally, we conclude this article and describe future plans.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.611-618
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• 2020

In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.33-39
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• 2022

This study aims to investigate the online class preference depending on students' gender and school level. To achieve this aim, the study conducted a survey on 4,803 elementary, middle, and high school students in 17 regions nationwide. The valid data of 4,524 were then analyzed using the Apriori algorithm to discern the associated patterns of the online class preference corresponding to their gender and school level. As a result, a total of 16 rules, including 7 from elementary school students, 4 from middle school students, and 5 from high school students were derived. To be specific, elementary school male students preferred software-based classes whereas elementary female students preferred maker-based classes. In the case of middle school, both male and female students preferred virtual experience-based classes. On the other hand, high school students had a higher preference for subject-specific lecture-based classes. The study findings can serve as empirical evidence for explaining the needs of online classes perceived by K-12 students. In addition, this study can be used as basic research to present and suggest areas of improvement for diversifying online classes. Future studies can further conduct in-depth analysis on the development of various online class activities and models, the design of online class platforms, and the female students' career motivation in the field of science and technology.