• Electrical & Electronic Materials
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• v.11 no.11
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• pp.1-8
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• 1998

This paper presents an arificial neuro-fuzzy technique based prtial discharge (PD) pattern classifier to power system application. This may require a complicated analysis method employ -ing an experts system due to very complex progressing discharge form under exter-nal stress. After referring briefly to the developments of artificical neural network based PD measurements, the paper outlines how the introduction of new emerging technology has resulted in the design of a number of PD diagnostic systems for practical applicaton of residual lifetime prediction. The appropriate PD data base structure and selection of learning data size of PD pattern based on fractal dimentsional and 3-D PD-normalization, extraction of relevant characteristic fea-ture of PD recognition are discussed. Some practical aspects encountered with unknown stress in the neuro-fuzzy techniques based real time PD recognition are also addressed.

• Smart Media Journal
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• v.12 no.9
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• pp.89-94
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• 2023

Recommender systems provide users with the most favorable items by analyzing explicit or implicit feedback of users on items. Recently, as the size of deep-learning-based models employed in recommender systems has increased, many studies have focused on reducing inference time while maintaining high recommendation accuracy. As one of them, a study on recommender systems with a knowledge distillation (KD) technique is actively conducted. By KD, a small-sized model (i.e., student) is trained through knowledge extracted from a large-sized model (i.e., teacher), and then the trained student is used as a recommendation model. Existing studies on KD for recommender systems have been mainly performed only for implicit feedback settings. Thus, in this paper, we try to investigate the performance and accuracy when applied to explicit feedback settings. To this end, we leveraged a total of five state-of-the-art KD methods and three real-world datasets for recommender systems.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.365-373
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• 2005

Ubiquitous learning environment needs various new model of e-learning as web based education system has been proposed. The demand for the customized courseware which is required from the learners is increased. the needs of the efficient and automated education agents in the web-based instruction are recognized. But many education systems that had been studied recently did not service fluently the courses which learners had been wanting and could not provide the way for the learners to study the learning weakness which is observed in the continuous feedback of the course. In this paper we propose a multi-agent system for course scheduling of learner-oriented using weakness analysis algorithm via personalized ubiquitous environment factors. First proposed system analyze learner's result of evaluation and calculates learning accomplishment. From this accomplishment the multi-agent schedules the suitable course for the learner. The learner achieves an active and complete learning from the repeated and suitable course.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.6-20
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• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.876-883
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• 2009

Learning Diagnosis & Prescription Service(LDPS) in Cyber Home Learning System is a educational service which provides customized learning contents based on student's academic level and individualized counseling and comments after diagnosing learner's study habits beyond the past e-Learning systems which offer the same contents to different students. For a national point of view, it is a crucial project in public education to achieve the goals of the next-generation e-Learning service by making a lot efforts both in time and money. However, those efforts has been made, not in terms of providing a better quality of service and a better user experience in a effective and enjoyable way, but in terms of developing the technology-driven system. Therefore, in this study, two types of usability evaluations has been conducted in order to enhance a user experience on the LDPS. One is the expert reviews by utilizing the usability evaluation tools (heuristics) which was focused on educational contexts developed by Suh Young-suhk(2007). The other is the user testing with students who have done think-aloud during the evaluation, remembering their retrospective experience with LDPS, and the interview with teachers & service operators were conducted. As the implications on the research, this is an effort to provide an user-friendly educational system for the students nationwide.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.577-583
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• 2012

Objective: This paper describes the process and results related to the development of gesture recognition-based natural user interface(NUI) for vehicle maintenance e-Training system. Background: E-Training refers to education training that acquires and improves the necessary capabilities to perform tasks by using information and communication technology(simulation, 3D virtual reality, and augmented reality), device(PC, tablet, smartphone, and HMD), and environment(wired/wireless internet and cloud computing). Method: Palm movement from depth camera is used as a pointing device, where finger movement is extracted by using OpenCV library as a selection protocol. Results: The proposed NUI allows trainees to control objects, such as cars and engines, on a large screen through gesture recognition. In addition, it includes the learning environment to understand the procedure of either assemble or disassemble certain parts. Conclusion: Future works are related to the implementation of gesture recognition technology for a multiple number of trainees. Application: The results of this interface can be applied not only in e-Training system, but also in other systems, such as digital signage, tangible game, controlling 3D contents, etc.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.132-138
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• 2022

Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.457-463
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• 2015

This paper presents the need for the concept of collective intelligence based system for the timely learning and incorrect notes show the utilization and satisfaction. The old wrong answer note system is characterized by the provision of uniform right answer explanations for the questions whose answers were wrong by checking whether the evaluation items were answered right or wrong. The characteristic requires a lot of improvements in terms of wrong answer analysis and feedback since it cannot properly receive feedback on the items that a learner got right by luck in spite of poor understanding of them and on the errors in the selection process of wrong answers by individual learners. The SERO wrong answer note was designed to propose new ways to identify and capture such "score errors" and compensate for the practical weaknesses of learners. The Stability Emergency Risk Opportunity (SERO) wrong answer note is based on a method of categorizing and analyzing evaluation items answered by the examinee into four types (S, E, R and O type), and commentary correct as well as incorrect answers by presenting a variety of commentary notes using the collective intelligence of the study show that satisfaction is high.

• Journal of The Korean Association For Science Education
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• v.34 no.8
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• pp.703-718
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• 2014

This study sought to investigate learning progressions for astronomical systems which synthesized the motion and structure of Earth, Earth-Moon system, solar system, and the universe. For this purpose we developed ordered multiple-choice items, applied them to elementary and middle school students, and provided validity evidence based on the consequence of assessment for interpretation of learning progressions. The study was conducted according to construct modeling approach. The results showed that the OMCs were appropriate for investigating learning progressions on astronomical systems, i.e., based on item fit analysis, students' responses to items were consistent with the measurement of Rasch model. Wright map analysis also represented that the assessment items were very effective in examining students' hypothetical pathways of development of understanding astronomical systems. At the lower anchor of the learning progression, while students perceived the change of location and direction of celestial bodies with only two-dimensional earth-based view, they failed to connect the locations of celestial bodies with Earth-Moon system model, and they could recognized simple patterns of planets in the solar system and milky way. At the intermediate levels, students interpreted celestial motion using the model of Earth rotation and revolution, Earth-Moon system, and solar system with space-based view, and they could also relate the elements of astronomical structures with the models. At the upper anchor, students showed the perspective change between space-based view and earth-based view, and applied it to celestial motion of astronomical systems, and they understood the correlation among sub-elements of astronomical systems and applied it to the system model.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.100-107
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• 2013

As the eBook market grows fast recently, various eBook viewer solutions such as hardware viewers and software readers came out to the market. We can, however, hardly find mobile eBook interfaces for the reading disabled people who have difficulties in reading for their visual impairment or learning disabilities, or dyslexia. An eBook viewer interfaces for the reading disabled people should be carefully and distinctively designed because the reading disabled people cannot use normal versions of eBook viewer. In this paper, we suggest a eBook viewer interface model to make the reading disabled people read eBooks easily. Depending on the type of the reading disabled people: the full blind, the almost blind, the just learning disabled, our model provides an adaptive interface to make them read eBooks effectively. In addition, unlike the existing simple audio books, we also support annotation systems to make the reading disabled people interact with eBook viewer. To show the effectiveness of our model, we implemented an eBook viewer prototype on an android-based mobile device. We are sure that our model and implementation can make the reading disabled people, who is 10% of all the domestic people, read eBooks effectively.