• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.266-279
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• 2021

This study applied the e-PBL (e-Project-based learning) method for "Urban Forest Management" courses in the Department of Forest Science at S University to progress in university forest education. e-PBL effectively motivates self-directed learning, problem-solving, communication skills, and learners' responsibility by enabling them to choose, design, and perform their projects. Due to the COVID-19 pandemic in 2020, learners were encouraged to use online media to carry out projects and submit presentations for the campus forest. Learners' educational effects were subsequently investigated through a five-point Likert scale. This study discovered a positive effect on learners' motivation and interest (4.17) through e-PBL. Learners responded that e-PBL also helped their understanding regarding the subject (4.17). In addition, this study provided evidence that the e-PBL method was helpful in problem-solving (4.25), communication (4.33), and decision-making skills (4.21). According to learners' responses, there are positive indications that learners were satisfied with e-PBL. Learners responded that interactions and communications with team members could improve their understanding of the subject. Hence, there is scope for improving an efficient and successful e-PBL model suitable for university forest education by providing more efficient instructional time management, e-PBL method guidelines, and institutional support.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2529-2551
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• 2022

Visual servoing (VS) based on the Kalman filter (KF) algorithm, as in the case of KF-based image-based visual servoing (IBVS) systems, suffers from three problems in uncalibrated environments: the perturbation noises of the robot system, error of noise statistics, and slow convergence. To solve these three problems, we use an IBVS based on KF, African vultures optimization algorithm enhanced extreme learning machine (AVOA-ELM), and fuzzy logic (FL) in this paper. Firstly, KF online estimation of the Jacobian matrix. We propose an AVOA-ELM error compensation model to compensate for the sub-optimal estimation of the KF to solve the problems of disturbance noises and noise statistics error. Next, an FL controller is designed for gain adaptation. This approach addresses the problem of the slow convergence of the IBVS system with the KF. Then, we propose a visual servoing scheme combining FL and KF-AVOA-ELM (FL-KF-AVOA-ELM). Finally, we verify the algorithm on the 6-DOF robotic manipulator PUMA 560. Compared with the existing methods, our algorithm can solve the three problems mentioned above without camera parameters, robot kinematics model, and target depth information. We also compared the proposed method with other KF-based IBVS methods under different disturbance noise environments. And the proposed method achieves the best results under the three evaluation metrics.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.316-321
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• 2017

We analyze the online Hangul handwriting recognition problem (HHR) and present solutions based on recurrent neural networks. The solutions are organized according to the three kinds of sequence labeling problem - sequence classifications, segment classification, and temporal classification, with additional consideration of the structural constitution of Hangul characters. We present a stacked gated recurrent unit (GRU) based model as the natural HHR solution in the sequence classification level. The proposed model shows 86.2% accuracy for recognizing 2350 Hangul characters and 98.2% accuracy for recognizing the six types of Hangul characters. We show that the type recognizing model successfully follows the type change as strokes are sequentially written. These results show the potential for RNN models to learn high-level structural information from sequential data.

• Smart Media Journal
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• v.10 no.1
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• pp.116-123
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• 2021

Due to the rapid growth of the online fashion market and the resulting expansion of online choices, there is a problem that the seller cannot directly respond to a large number of consumers individually, although consumers are increasingly demanding for more personalized recommendation services. Images are being tagged as a way to meet consumer's personalization needs, but when people tagging, tagging is very subjective for each person, and artificial intelligence tagging has very limited words and does not meet the needs of users. To solve this problem, we designed an algorithm that recognizes the shape, attribute, and emotional information of the product included in the image with AI, and codes this information to represent all the information that the image has with a combination of codes. Through this algorithm, it became possible by acquiring a variety of information possessed by the image in real time, such as the sensibility of the fashion image and the TPO information expressed by the fashion image, which was not possible until now. Based on this information, it is possible to go beyond the stage of analyzing the tastes of consumers and make hyper-personalized clothing recommendations that combine the tastes of consumers with information about trends and TPOs.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.309-316
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• 2022

This study is a study on the YouTube e-learning advanced service plan in the non-face-to-face era. The trends in education change were examined through literature research and prior research, and improvement measures were suggested through online surveys and in-depth interviews. As for the research method, the first online survey was conducted based on the Honeycomb model and the Likert 5-point scale targeting 90 MZ generation who have experience learning on YouTube for a total of 14 days from October 15 to 28, 2021. A second in-depth interview was conducted with 6 people who answered that the frequency of learning through YouTube is high. As a result of the experiment, users thought that there was an improvement point according to the purpose of learning, and they were able to derive elements that felt a problem in common. In addition, I proposed a new YouTube learning platform through additional questions. Through this study, it is expected that YouTube e-learning service reference materials can be used to respond to the post-non-face-to-face era.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.601-605
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• 2009

Recently, photo sharing and publishing based Social Network Sites(SNSs) are increasingly attracting the attention of academic and industry researches. Millions of users have integrated these sites into their daily practices to communicate with online people. In this paper, we propose an efficient face annotation and retrieval system under SNS. Since the system needs to deal with a huge database which consists of an increasing users and images, both effectiveness and efficiency are required, In order to deal with this problem, we propose a face annotation classifier which adopts an online learning and social decomposition approach. The proposed method is shown to have comparable accuracy and better efficiency than that of the widely used Support Vector Machine. Consequently, the proposed framework can reduce the user's tedious efforts to annotate face images and provides a fast response to millions of users.

• 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 Information Technology Services
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• v.20 no.6
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• pp.107-123
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• 2021

Recently, there have been a number of researchers in the field of education who are actively exploring the educational applications of Blockchain technology, even though it is still in its infancy. Some researchers have been investigating its application in educational administration to issue academic credentials' or maintain student records with distributed ledger, which is the basis of Blockchain technology. Whereas, others have been examining its application in redesigning learning systems that are being used in various contexts, including online learning and lifelong education. In that vein, this paper aims to discuss a liberal arts education system which will be supported by Blockchain-based 'smart contracts'. At present, active efforts are being made to innovate liberal arts education in Korea, centered around government-funded university innovation projects and there have been reports of great achievements. However, if the Blockchain technology is applied to innovating the liberal arts education, we will innovate not only the liberal arts education but also university education as a whole. In this paper, there are suggestions on how to build a learner-centered educational environment where a liberal arts education system is supported by Blockchain-based smart contracts. First of all, the current innovation in liberal arts education and its limitations are discussed, followed by ways in which Blockchain-based smart contracts can reframe the liberal arts education system. Last but not least, the paper addresses implications of the Blockchain technology applications in liberal arts education, along with their future prospects.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.213-221
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• 2021

With the advent of the 4th industrial revolution, the need for artificial intelligence education has increased. The online learning environment caused by COVID-19 made it possible to use variety of artificial intelligence platforms. In this study, an aritificial intelligence class plan was developed and proposed to achieve the goal of artificial intelligence education using an AI platform. The AI platform used is AI for Oceans, With the theme of creating a program for the environment, designed a 6-hour project class using Novel Engineering-based on STEAM model. Students experience AI for Oceans enough time and learn supervised learning by experience. Based on understanding of supervised learning, students design their own programs for the environment using Entry's AI blocks. In this study, for AI convergence education, this lesson was developed and presented with the goal of acquiring the creative problem solving ability and integrated thinking ability by using the principles of artificial intelligence to solve problems.