• Journal of Digital Convergence
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• v.19 no.12
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• pp.331-337
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• 2021

The adaptation of smartfarm technology that converges ICT is increasing productivity and competitiveness in the agriculture. Technologies have been developed that enable environmental monitoring through various sensors and automatic control of the cultivation environment, and researches are underway to advance smartfarm technology using data generated from smartfarms. In this paper, an environmental control method to reduce the energy consumption of a smartfarm by using the environment and control data of the smartfarm is proposed. It was confirmed that energy consumption could be reduced compared to an independent environmental control method by creating an environmental prediction model using accumulated environmental data and selecting a control method to minimize energy consumption in a given situation by considering multiple environmental factors. In the future, research is needed to obtain higher energy efficiency through the advancement of the predictive model and the improvement of the complex control algorithms.

• Journal of The Korean Association of Information Education
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• v.23 no.3
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• pp.273-282
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• 2019

In this study, we have look through the national progress of computer science education in South Korea and analyzed the main subjects and contents of each period. We suggests the ways to evolve the current computer science education in terms of class hours for computer science education, hierarchical instructions, and the limitation of current national curriculum. In South Korea, it has been leaded the computer science education in the world since the it was promoted in earnest since 1995. Based on the recently revised national curriculum, South Korean government are taking efforts to nurture a leader through computer science education in terms of the students' future skills. However, it should be promoted to strengthen the ability of not only problem-solving ability through programming education, but also balanced computing and digital literacy through enhancing the ICT skills. In order to improve the curriculum of computer science education in elementary school of South Korea, a sufficient class hours of computer science education should be secured first.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.207-223
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• 2019

This study aims to explore the casual relation between construction company employees' Self-Leadership and two variables: Organization Citizenship Behaviour and Organizational Trust through Psychology Empowerment. To explain in details, this study examines how the independent variable, Self Leadership, with its behavior-focused, natural reward and constructive thought pattern strategies, affects the dependent variable, Organization Citizenship Behavior and Organizational Trust through the intervening variable, Psychology Empowerment. A survey was conducted on current employees of construction companies in metropolitan areas to empirically examine the research model. The result of study hypothesis on Self-Leadership is as follows; first, Self-Leadership showed a positive effect on Psychology Empowerment, Organization Citizenship Behaviour and Organizational Trust. Second, Psychology Empowerment showed a positive effect on Organization Citizenship Behaviour. Third, Psychology Empowerment showed a positive effect on Organizational Trust. The capacity of individuals is critical when it comes to competitiveness of construction companies. When employees willingly participate in building trust within the company, the work place will become more and more constructive; based on trust, efficiency will increase because people from different processes can work together and performance will also improve even when project managers are absent because others could help their role instead, thus driving more efficient human resource management to the company. To conclude, a company's vision can be spread wide and far when their employees engage themselves in Learning Organization with Self Leadership. They will also be satisfied with their work through improving interpersonal relationship at work.

• Journal of Information Technology Applications and Management
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• v.25 no.3
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• pp.43-54
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• 2018

In recent years, international cooperation has become important not only at the humanitarian level but also at the socio-economic level. As a result, major foreign countries are increasing capital-intensive international cooperation. In this environment, Korea needs to look for differentiated international cooperation plans centered on sustainable talent cultivation and move away from capital-based international cooperation. In this study, we analyzed the case of HRD (Human Resource Development) center in Cambodia as an international cooperation model between industry-academia-college for training software (SW) workforce. The HRD Center in Cambodia is an educational institution that fosters SW talent and can be viewed as an international cooperation model that can influence the ICT industry in Cambodia as an educational platform. In fact, 190 people who have been hired so far have entered various fields. 97% of graduates have been satisfied with HRD center and 90% of them are willing to recommend the center. In particular, as highlighted in the case study, the HRD Center has had a positive effect on not only cultivating self-initiated learning-based SW talent, but also formulating positive image of Korea and Korean companies thereby facilitating entry into the global market. The HRD Center in Cambodia has developed a virtuous cycle of fostering human resources, providing education, advancing industry and building a cooperative network. Korea has transformed into a platform for international cooperation and human resource development and education by providing active support and aid. This case study will be utilized as a new model of international cooperation with SW expert training platform for Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.655-661
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• 2020

This study examined community-centered informatization education support measures for empowerment of women with disabilities based on gender perspective.First, the 'Digital Information Gap Survey' conducted by the Ministry of Science and ICT used the 2018 'Digital Information Gap Survey' to find out the current status of the digital information gap between male and female handicapped people. The law on information education support for women with disabilities is presented.Lastly, based on the current status of informatization education support available to women with disabilities, centered on local communities, such as establishing a comprehensive women's disability support center, visiting education considering disability types, developing and supporting customized informatization education considering learning ability, and discovering community resources related to informatization. In this paper, we propose a plan to support informatization education for women with disabilities based on capacity building.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.942-948
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• 2020

In this paper, we propose a clustered algorithm that possible more efficient user distinction within clustering using context-aware attribute information. In typically, the data provided to classify interrelationships within cluster information in the process of clustering data will be as a degrade factor if new or newly processing information is treated as contaminated information in comparative information. In this paper, we have developed a clustering algorithm that can extract user's recognition information to solve this problem in using K-means algorithm. The proposed algorithm analyzes the user's clustering attributed parameters from user clusters using accumulated information and clustering according to their attributes. The results of the simulation with the proposed algorithm showed that the user management system was more adaptable in terms of classifying and maintaining multiple users in clusters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.208-219
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• 2021

In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.75-82
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• 2021

Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.

• Journal of Engineering Education Research
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• v.25 no.6
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• pp.93-102
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• 2022

Due to COVID-19, all activities in society are emphasized non-face-to-face, and the educational environment is changing without exception. Looking at the results of the survey after conducting non-face-to-face education, there was a lot of rejection of non-face-to-face practical education. The biggest reason was that instructors were not familiar with the non-face-to-face education method, and feedback was not smooth during or after education. In particular, software practice education was not easy to share the software development environment, but communication and feedback on class contents and tasks were important. In particular, if face-to-face and non-face-to-face are alternately variable, it is not easy for practical education to be consistently connected. Even if non-face-to-face hands-on education is changed to face-to-face hands-on education, we will present a plan to use a data sharing system such as question-and-answer, assignment, practice content, and board content so that it can proceed smoothly. This study presents an efficient software education process that can provide learners with a software integrated practice environment based on a shared server, question-and-answer between instructors and learners, and share feedback on tasks. For the verification of the presented process, the effectiveness was confirmed through the survey results by applying the face-to-face/non-face-to-face education process to 220 trainees for 30 months in software education classes such as A university hands-on education, B company new employees, and ICT education courses.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.968-975
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• 2023

Purpose: We would like to confirm that the false positive rate of flames/smoke is high when detecting fires. Propose a method and dataset to recognize and classify fire situations to reduce the false detection rate. Method: Using the video as learning data, the characteristics of the fire situation were extracted and applied to the classification model. For evaluation, the model performance of Yolov8 and Slowfast were compared and analyzed using the fire dataset conducted by the National Information Society Agency (NIA). Result: YOLO's detection performance varies sensitively depending on the influence of the background, and it was unable to properly detect fires even when the fire scale was too large or too small. Since SlowFast learns the time axis of the video, we confirmed that detects fire excellently even in situations where the shape of an atypical object cannot be clearly inferred because the surrounding area is blurry or bright. Conclusion: It was confirmed that the fire detection rate was more appropriate when using a video-based artificial intelligence detection model rather than using image data.