• Journal of Engineering Education Research
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• v.26 no.2
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• pp.3-22
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• 2023

The purpose of universities is diversifying, such as education and research for the transfer of knowledge and technology, and training talented people with the competencies required in industrial sites. Therefore, universities are attempting various forms of industry-academic cooperation to maintain organic relations with companies and to conduct research activities, technology sharing, technology development, technology transfer, and human resources training. In particular, in the field of engineering education, various industry-academic cooperation programs such as field training, interns, and start-up support are actively developed and operated. Accordingly, the Engineering Education Innovation Research Information Center developed an online industry-academic cooperation capstone design matching platform for engineering education to enable collaboration between universities and companies nationwide. The industry-academic cooperation matching platform was developed under the theme of capstone design. Capstone design is a project-oriented and problem-based learning method that combines the knowledge and experiences acquired by the undergraduate department and designs and produces them. The subject of the Capstone design project was to solve corporate difficulties and allow companies and universities to collaborate. This study developed an online industry-academic cooperation capstone design matching platform according to analysis, design, development, evaluation, and execution procedures. This study is meaningful in that it has developed a channel through which students and companies, who are the subjects of industry-academic cooperation, can carry out projects and communicate organically through an online matching platform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2057-2065
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• 2014

New business The e-book industry is creating a convergence of ICT and printing culture. Even so, the system changes is not great in Korea. Global market players are going to creating a membership or community-type business model to take advantage of the terminal, platform, network, but the creative content production in Korea is limited. Since the discussion is limited to such devices or network services most, we suggest the possibility of modeling a multi-faceted. And the development of technology and services platform content is also important as a strategic approach to the development of the e-book industry. Most of all, we propose the application of content, technologies and services are developed.

• Journal of Industrial Convergence
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• v.17 no.3
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• pp.39-49
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• 2019

This study, as a study on building platforms for smart campus ecosystem, took an approach that reflected the needs of various stakeholders of smart campus, and focused on functions to help them strengthen their competitiveness and advance into society by focusing on the learning of the most important university student users, college life, and social connection. First, we looked at the theories related to smart campus construction through prior research, and next, through domestic and international environmental analysis and trend analysis, we designed and presented a target model for e-portfolio focusing on core competency development and support system for Industry-Academic Cooperation, and proposed the main point for continuous smart campus development model.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.133-149
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• 2014

One of the main purposes of universities is to create new intellectual resources that will increase social values. These intellectual resources include academic research papers, lecture notes, patents, and creative ideas produced by both professors and students. However, intellectual resources in universities are often not distributed to the actual users or companies; and moreover, they are not even systematically being managed inside of the universities. Therefore, it is almost impossible for companies to access the knowledge created by university students and professors to utilize them. Thus, the current level of knowledge sharing between universities and industries are very low. This causes a great extravagant with high-quality intellectual and human resources, and it leads to quite an amount of social loss in the modern society. In the 21st century, the creative ideas are the key growth powers for many industries. Many of the globally leading companies such as Fedex, Dell, and Facebook have established their business models based on the innovative ideas created by university students in undergraduate courses. This indicates that the unconventional ideas from young generations can create new growth power for companies and immensely increase social values. Therefore, this paper suggests of a new platform for intellectual properties distribution with university-industry cooperation. The suggested platform distributes intellectual resources of universities to industries. This platform has following characteristics. First, it distributes not only the intellectual resources, but also the human resources associated with the knowledge. Second, it diversifies the types of compensation for utilizing the intellectual properties, which are beneficial for both the university students and companies. For example, it extends the conventional monetary rewards to non-monetary rewards such as influencing on the participating internship programs or job interviews. Third, it suggests of a new knowledge map based on the relationships between key words, so that the various types of intellectual properties can be searched efficiently. In order to design the system platform, we surveyed 120 potential users to obtain the system requirements. First, 50 university students and 30 professors in humanities and social sciences departments were surveyed. We sent queries on what types of intellectual resources they produce per year, how many intellectual resources they produce, if they are willing to distribute their intellectual properties to the industries, and what types of compensations they expect in returns. Secondly, 40 entrepreneurs were surveyed, who are potential consumers of the intellectual properties of universities. We sent queries on what types of intellectual resources they want, what types of compensations they are willing to provide in returns, and what are the main factors they considered to be important when searching for the intellectual properties. The implications of this survey are as follows. First, entrepreneurs are willing to utilize intellectual properties created by both professors and students. They are more interested in creative ideas in universities rather than the academic papers or educational class materials. Second, non-monetary rewards, such as participating internship program or job interview, can be the appropriate types of compensations to replace monetary rewards. The results of the survey showed that majority of the university students were willing to provide their intellectual properties without any monetary rewards to earn the industrial networks with companies. Also, the entrepreneurs were willing to provide non-monetary compensation and hoped to have networks with university students for recruiting. Thus, the non-monetary rewards are mutually beneficial for both sides. Thirdly, classifying intellectual resources of universities based on the academic areas are inappropriate for efficient searching. Also, the various types of intellectual resources cannot be categorized into one standard. This paper suggests of a new platform for the distribution of intellectual materials and human resources, with university-industry cooperation based on these survey results. The suggested platform contains the four major components such as knowledge schema, knowledge map, system interface, and GUI (Graphic User Interface), and it presents the overall system architecture.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1213-1222
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• 2021

This study is a digitalization study based on ICT technology as part of the development of innovative technologies in the new energy industry as a 2050 carbon-neutral policy. It is the development of an oneM2M-based IoT server platform that can be integrated and managed in conjunction with the external interface of each energy facility. It analyzes KEPCO's e-IoT standard specifications through the Power Research Institute's 'SPIN' and develops representative standards, LWM2M and oneM gateway platforms. OneM2M secures and analyzes the recently announced standard for Release 2 instead of the existing Release 1. In addition, the e-IoT standard oneM2M platform is developed based on R2. In addition, it selects the specifications for e-IoT gateway devices that can sufficiently implement KEPCO's e-IoT standards. In addition, a technology and system for developing a high-performance gateway device that considers future scalability were proposed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.203-223
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• 2023

Recently, the platform industry is rapidly growing in the global market, and competition is intensifying at the same time. Therefore, in order for domestic platform companies to have global competitiveness in the platform market, it is necessary to study the platform business ecosystem and success factors. However, most of the recent platform-related studies have been theoretical studies on the characteristics of platform business status analysis, platform economy, and indirect network externalities of platforms. Therefore, this study comprehensively analyzed the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzed the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. And based on these factors, an IPA analysis was conducted as a way to propose a success plan to stakeholders in the platform business ecosystem. As a result of the analysis, among the success factors collected through previous studies, manpower, capital, and challenge culture were identified as factors that are relatively well maintained in both importance and satisfaction in Silicon Valley. In the end, it can be seen that the creation of an environment and culture in which Silicon Valley can use it to challenge itself based on excellent human resources and abundant capital contributes the most to the success of Silicon Valley's platform business. On the other hand, although it is of high importance to Silicon Valley's platform corporate ecosystem, the factors that show relatively low satisfaction among stakeholders are 'learning and benchmarking among active companies' and 'strong ties and cooperation between members', and it is analyzed that interest and effort are needed to strengthen these factors in the future. Finally, the systems and policies necessary for market autonomous competition, 'business support service industry', 'name value', and 'spin-off start-up' were important factors in literature research, but the importance and satisfaction of these factors were lowered due to changes in the times and environment. This study has academic implications in that it comprehensively analyzes the success factors of Silicon Valley's business ecosystem proposed in previous studies, and at the same time analyzes the success factors extracted from stakeholders in the actual Silicon Valley platform business ecosystem. In addition, there is another academic implications that importance and satisfaction were simultaneously examined through IPA analysis based on these various extracted factors. As for academic implications, it is meaningful in that it contributed to the formation of the domestic platform ecosystem by providing the government and companies with concrete information on the success factors of the platform business ecosystem and the theoretical grounds for the growth of domestic platform businesses.

• Journal of mucopolysaccharidosis and rare diseases
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• v.4 no.1
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• pp.14-20
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• 2018

Mucopolysaccharidoses (MPSs) are a group of rare inherited metabolic disorders caused by specific lysosomal enzyme deficiencies leading to the sequential degradation of glycosaminoglycans, causing substrate accumulation in various cells and tissues and progressive multiple organ dysfunction. The rare disease medical care team at Mackay Memorial Hospital in Taiwan has been dedicated to the study of MPSs for more than 20 years. Since 1999, more than 50 academic papers focusing on MPSs have been published in international medical journals. Topics of research include the following items regarding MPSs: incidence, natural history, clinical manifestations, gene mutation characteristics, cardiac function, bone mineral density, sleep studies, pulmonary function tests, hearing assessments, percutaneous endoscopic gastrostomy, anesthetic experience, imaging analysis, special biochemical tests, laboratory diagnostics, global expert consensus conferences, prenatal diagnosis, new drug clinical trials, newborn screening, and treatment outcomes. Of these published academic research papers, more than half were cross-domain, cross-industry, and international studies with results in cooperation with experts from European, American and other Asian countries. A cross-specialty collaboration platform was established based on high-risk population screening criteria with the acronym "BECARE" (Bone and joints, Eyes, Cardiac and central nervous system, Abdomen and appearance, Respiratory system, and Ear, nose, and throat involvement). Through this platform, orthopedic surgeons, rheumatologists, ophthalmologists, cardiologists, rehabilitation physicians, gastroenterologists, otorhinolaryngologists, and medical geneticists have been educated with regards to awareness of suspected cases of MPSs patients to allow for a further confirmative diagnosis of MPSs. Because of the progressive nature of the disease, an early diagnosis and early multidisciplinary therapeutic interventions including surgery, rehabilitation programs, symptom-based treatments, hematopoietic stem cell transplantation, and enzyme replacement therapy, are very important.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.162-170
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• 2021

The Smart City Living Lab is becoming important as a local innovation platform to develop urban solutions. In January 2018, the 4th industrial innovation committee, which was a direct subordinate from the president, empathized citizens' participation and their roles within the Smart City [Urban Innovation and Future Growth Engine-Creating Smart City Strategy]. This was the starting point of the living lab. The central government and local governments have been promoting various types of living labs to encourage citizens to participate. On the other hand, due to the lack of systematic concepts and theories for practicing and structuring living labs, the practice is not performed well. This study aimed to develop systematic approaches and implementation methods of the public-led Smart City Living Lab. The Full-cycle Smart City living Lab model was designed by integrating smart city living lab work processes, as suggested in the standards of the national land plan, double design diamond framework, which is a type of innovative design methodology, and design thinking process. The entire cycle Smart City living lab model requires four components to practice the living lab, such as framework, module, process, and methodologies. In the future, this model is expected to be incorporated in the Smart City Living Lab.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.19-25
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• 2018

The growth of virtual reality(VR), which is regarded as a part of the 4th industrial revolution, is being delayed differently from the prediction. In this study, we briefly analyze these reasons from the point of view of CPND ecosystem. Virtual reality is a technology in which a user wears a device and accesses a platform through a network to use various contents. Therefore, balanced development of C-P-N-D ecosystem fields is important for successful popularization of virtual reality. In Korea, content, platforms, and devices, except for the network, are evaluated as having low competitiveness. While efforts to secure competitiveness in individual fields are important, it is also necessary to nurture network-based platforms that can utilize killer content. It should be kept in mind that simple breeding of killer content alone can not build an entire virtual reality C-P-N-D ecosystem, and the broadcast / media sector also needs to take this approach.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.