• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.79-88
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• 2021

Scientific software requires a development process different from conventional application software due to its unique characteristics, such as expert-level deep domain knowledge requirements. In this study, we proposed a V & V development process based on RE (Reverse Engineering) and TDD (Test-Driven Development) for software development for science. We also configured a virtual scenario for the actual project, applied it, checked the procedure, and refined it. The development process of this study, suggested for the purpose of developing scientific software, will contribute to the development and application of the software that can provide high quality and high reliability. And This study is expected to serve as an opportunity for the development of scientific software and the spread of research.

• Journal of Industrial Convergence
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• v.13 no.2
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• pp.1-9
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• 2015

This Study aims to present the guidelines for the activation of the domestic GS certification market through the assessment of the characteristics of the demands of the domestic SW companies pursuing to acquire GS certification. As the results of the factor analysis of the guidelines for the activation of the domestic GS certification market, (1) strictness of the certification standards, (2) level of satisfaction on the certification services and (3) certification effects were deduced as the specific variables. This study is highly significant in that the fact that the certification market is more effectively activated when the 3 factors, namely, strictness of the certification standards, level of satisfaction on the certification services and certification effects, have been intensively reinforced although there exist countless number of specific variables including certification system, certification cost, certification expertise and certification marketing, etc. in order to activate GS certification market has been statistically verified.

• The Journal of Korean Association of Computer Education
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• v.21 no.1
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• pp.43-50
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• 2018

The 2015 Revised National Curriculum emphasizes software education to develop creative and convergent talents in preparation of the Fourth Industrial Revolution. Accordingly, it is necessary to develop competency-based training programs for informatics teachers in a rapidly changing educational environment. In this background, this study selects a framework to analyze the content of in-service training for informatics teachers through review of previous studies. By analyzing the current training programs to strengthen competencies required for informatics teachers in secondary schools, the study aims to develop implications for future in-service training programs. To this end, the study conducted a questionnaire survey of experts who participated in the development of in-service training textbooks and consulted them, then analyzed the elements of competency-based training program content and the relative importance of each competency element using the analytical hierarchy process (AHP). According to the results of the analysis, the content was relatively concentrated on the competency of "Understanding and Reconstructing the National Curriculum" required for general and informatics teachers as well, which accounted for 47% of all, or 7 hours out of the total 15 hours. In contrast, the content structure lacked the competency of highly relative importance by competency element "Establishing and Using Teaching-Learning Strategies for Informatics," which took up the highest portion of 27%. These findings will be used as basic data for understanding and reflecting the areas that fall short of the development of in-service training programs for informatics teachers.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.76-95
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• 2023

As information and communications technology-based "smart hospitals" and "digital healthcare" have become a hot topic in the healthcare field, hospital mobile apps are gaining attention; but, the utilization rate is low due to lack of publicity, unstable systems, and late updates. In this situation, systematic research is needed to increase the utilization rate of hospital mobile apps, but related research has been rare. Therefore, this study integrates the information systems success model (ISSM) from the technical perspective and the expectation-confirmation model (ECM) from the cognitive perspective to demonstrate the influence mechanism on the continuous use intention of hospital mobile apps. For this purpose, an online survey was conducted among 181 Korean adults who have used hospital mobile apps. The results of the structual equation modeling showed that most of the quality factors have significant effects on expectation confirmation, perceived usefulness, and satisfaction. Additionally, expectation confirmation significantly affects perceived usefulness and satisfaction, and both perceived usefulness and satisfaction significantly affect the continuous use intention of hospital mobile apps. This study is of importance in that it integrates the ISSM and ECM and applies them to the context of using hospital mobile apps, which are underutilized in the healthcare field, and provides practical implications for increasing the utilization rate of hospital mobile apps and operating effective and efficient services through the findings.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.49-57
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• 2020

The society we are living in has being changed to the age of the intelligent information society after passing through the knowledge-based information society in the early 21st century. In this study, we have developed the instructional model for software education based on the machine learning which is a field of artificial intelligence(AI) to enhance the core competencies of learners required in the intelligent information society. This model is focusing on enhancing the core competencies through the process of problem-solving as well as reducing the burden of learning about AI itself. The specific stages of the developed model are consisted of seven levels which are 'Problem Recognition and Analysis', 'Data Collection', 'Data Processing and Feature Extraction', 'ML Model Training and Evaluation', 'ML Programming', 'Application and Problem Solving', and 'Share and Feedback'. As a result of applying the developed model in this study, we were able to observe the positive response about learning from the students and parents. We hope that this research could suggest the future direction of not only the instructional design but also operation of software education program based on machine learning.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.3
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• pp.181-188
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• 2009

The macro tidal flat of the Gochanggun Myongsasipri, located on the southwestern coast of Korea, is studied in terms of seasonal variations of surface sediment and sedimentary environment. Surface sediments of 45 sites in the winter (February) and the summer (August) are sampled across three survey lines (15 sites in each survey line), respectively. The tidal flat of open-coast Myongsasipri is mainly composed of fine to medium sand, the distribution of which shows a coast-parallel trend. Grain-size distribution has a bi-modal trend, and grain size in the winter is coarser than that in the summer. During the winter, the upper tidal flat is dominated by medium sand, while the lower tidal flat is dominated by find sand. Such a feature is attributed to wave-dominated sedimentation in the winter. The finer grains of the summer rather than that of the winter and relationship between texture parameters suggest that tidal energy plays an important role in tidal-flat sedimentation during the summer. This study represents an environmental change from wave-dominated conditions in the winter to tide-dominated conditions in the summer as a result of the seasonal variation in the intensity of onshore-directed winds and waves in the Myongsasipri tidal flat.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.257-269
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• 2021

This study aimed to secure basic data for the development and operation of well-aging education programs by analyzing the physical, mental, and socio-economic needs of well-aging education for successful aging. The research tool was developed as a questionnaire to investigate the perception of well aging and the needs of well-aging education in terms of physical, mental, and socio-economic aspects. In February 2021, 1949 adults over the age of 19 were surveyed through an online and mobile survey by Gallup Korea. Descriptive statistics analysis, variance analysis, Borich needs analysis, and IPA analysis were conducted to analyze the needs of well-aging education. The results revealed economic power, exercise, and chronic disease management to be high in terms of the overall priority of the education needs for well-aging, and infectious disease management, independence, and social responsibility were surveyed in the order of low education needs. In terms of economic power, education needs were highest among all age groups except for the middle-age group (35-49 years old), 82.4% of all respondents, and education needs for exercise and chronic disease management were highest in the middle-age group. Therefore, it is necessary to develop well-aging education programs for each life cycle. These results are expected to be used as empirical data in establishing a platform for developing and operating educational programs for well aging.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.367-375
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• 2021

The quality of medical care can be defined as four types such as effectiveness, efficiency, adequacy, and scientific-technical quality. For the management of scientific-technical aspects, medical institutions annually disseminate the latest knowledge in the form of conservative education. However, there is an obvious limit to the fact that the latest knowledge is distributed quickly enough to the clinical site with only one-time conservative education. If intelligent information processing technologies such as big data and artificial intelligence are applied to the medical field, they can overcome the limitations of having to conduct research with only a small amount of information. In this paper, we construct databases on which the existing medicine prescription adaptations can be extended. To do this, we collect, store, manage, and analyze information related to oriental medicine at domestic and abroad Journals. We design a processing and analysis technique for oriental medicine evidence research data for the construction of a database of oriental medicine prescription extended adaption. Results can be used as a basic content of evidence-based medicine prescription information in the oriental medicine-related decision support services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.25-40
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• 2019

Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.