• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1061-1065
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• 2004

The knowledge-based society of the 21st century requires effective education and learning methods in each professional field because the development of human resource determines its competence more than any other factors. It is highly desirable to develop an intelligent tutoring system, which meets ever increasing demands of education and learning. Such a system should be adaptive to each individual learner's demands as well as the continuously changing state of the learning process, thus enabling the effective education. The development of a learning environment based on learner modeling is necessary in order to be adaptive to individual learning variants. An intelligent learning environment is being developed targeting the heritage education, which is able to provide a customized and refined learning guide by storing the content of interactions between the system and the learner, analyzing the correlations in learning situations, and inferring the learning preference from the learner's learning history. This paper proposes a heritage learning system of Bulguksa temple, integrating the ontology-based learner modeling and the learning preference which considers perception styles, input and processing methods, and understanding process of information.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4593-4595
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• 2012

Introduction: Mobile learning enables users to interact with educational resources while in variable locations. Medical students in residency positions need to assimilate considerable knowledge besides their practical training and we therefore aimed to evaluate the impact of using short message service via cell phone as a learning tool in residents of Obstetrics and Gynecology in our hospital. Methods: We sent short messages including data about breast cancer to the cell phones of 25 residents of gynecology and obstetrics and asked them to study a well-designed booklet containing another set of information about the disease in the same period. The rate of learning derived from the two methods was compared by pre- and post-tests and self-satisfaction assessed by a relevant questionnaire at the end of the program. Results: The mobile learning method had a significantly better effect on learning and created more interest in the subject. Conclusion: Learning via receiving SMS can be an effective and appealing method of knowledge acquisition in higher levels of education.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.23 no.2
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• pp.163-173
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• 2010

Objectives : The purpose of this study is to survey the needs of oriental medical students about the existing teaching methods and to investigate satisfaction of student-oriented teaching & learning method on the oriental medical ophthalmology & otolaryngology class. Methods : 1. Oriental medical ophthalmology & otolaryngology were studied by student-oriented teaching method with 36 persons( 4th grade, school of Oriental medicine). 2. The satisfaction of school lesson was surveyed with questioning paper before & after applying student-oriented teaching & learning method. Results : 1. 88.9% students replied that the general teaching method is a lecture at school of oriental medicine. 2. They replied that Problem based learning(36.1%) & Team based learning(22.2%) are more effective teaching methods than lecture(19.4)%). 3. 66.6% students replied about the necessity of improvement of major subject's teaching method. Conclusions : 1. The interest & understanding degree were improved compare with other class by lecture. 2. It was positive about the interaction with professor and students(64.8%). 3. It was positive about the diagnosis and treatment of patients in the future(64.7%). 4. It was negative about the present national examination(67.6%). 5. Meditation was helpful at classwork(64.7%).

• Journal of The Korean Association For Science Education
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• v.23 no.2
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• pp.131-143
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• 2003

This study addresses the plan and methods of teaching/learning ethical aspects of science in the secondary schools, which were developed by the authors based on their 3 year research on ethical aspects of science and its teaching/learning. The general teaching/learning plan is composed of the instructional objectives of teaching/learning ethical aspect of science, its teaching/learning method and strategies, curricular content, and assessment. The article also attempted to describe a few words of care to keep in mind when apply the model and methods in the science classrooms.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.545-550
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• 2022

In Deep Learning method, it is well known that it requires large amount of data to train the deep neural network. And it also requires the labeling of each data to fully train the neural network, which means that experts should spend lots of time to provide the labeling. To alleviate the problem of time-consuming labeling process, some methods have been suggested such as weak-supervised method, one-shot learning, self-supervised, suggestive learning, and so on. In this manuscript, those methods are analyzed and its possible future direction of the research is suggested.

• Educational Technology International
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• v.19 no.2
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• pp.175-197
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• 2018

Flipped classroom (FC) has gained attention as an active learning approach. Designing effective out-of-class activities to help prepare students for in-class activities is fundamental for successful implementation of FC. This study investigated the effectiveness of Goal-Based Scenarios (GBS) for out-of-class learning in FC. Four out of twelve units in a medical humanities course for Year 2 medical students was redesigned into a FC format, where e-learning modules were designed using a GBS approach for out-of-class activities and classroom debates were implemented for in-class activities. The other eight units were delivered in a conventional classroom debate format, which included reading text materials as pre-class assignments. A formative evaluation study was conducted using questionnaires and interview methods and students' academic achievements were evaluated by comparing their pre- and post-test scores between FC and conventional units. Students had positive perceptions of the e-learning modules in GBS approach and preferred the structure of learning in the FC format. Students' pre-test scores were slightly higher in the FC units, yet their post-test scores were comparable with conventional units. This study illustrates students' perceptions that the learning was bettered structured in FC and that the out-of-class learning using the GBS approach helped them better prepared for in-class activities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.116-123
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• 2024

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.6A
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• pp.115-127
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• 2008

The Native API is a system call which can only be accessed with the authentication of the administrator. It can be used to detect a variety of malicious codes which can only be executed with the administrator's authority. Therefore, much research is being done on detection methods using the characteristics of the Native API. Most of these researches are being done by using supervised learning methods of machine learning. However, the classification standards of Anti-Virus companies do not reflect the characteristics of the Native API. As a result the population data used in the supervised learning methods are not accurate. Therefore, more research is needed on the topic of classification standards using the Native API for detection. This paper proposes a method for re-grouping malicious codes using fuzzy clustering methods with the Native API standard. The accuracy of the proposed re-grouping method uses machine learning to compare detection rates with previous classifying methods for evaluation.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.243-255
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• 2021

This study aimed to identify the effectiveness of the use of distance-evaluation tools and methods among students with learning difficulties from the teachers' point of view, to achieve this goal. A scale was built, and the psychometric characteristics were validated. It consisted, in its final form, of 17 items distributed on four axes, in addition to three open questions. It was applied to a random sample of (149) teachers of students with learning difficulties in Makkah Region. The results showed that teachers' keenness to encourage students with learning difficulties, so that they would not feel frustrated with the distance learning process. It was also evident that teachers did not use achievement portfolios in the evaluation process. In connection with the appropriate evaluation methods, the majority indicated the use of work sheets and visual evaluation methods that rely on audio and visual skills, such as presenting videos, pictures, audio and games, and applying short objective tests. Among the proposals to improve evaluation methods and tools: Individual evaluation, attention to individual treatment, obligating personal attendance of students to school, splitting the required tasks, and not increasing the skills required to be mastered. As for the obstacles that teachers face: Lack of time, difficulty in communicating with students with distance learning difficulties and problems related to the Internet such as interruption, weakness, or lack of availability.

• Wind and Structures
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• v.34 no.6
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• pp.511-523
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• 2022

Detecting the icing on wind turbine blades built-in cold regions with conventional methods is always a very laborious, expensive and very difficult task. Regarding this issue, the use of smart systems has recently come to the agenda. It is quite possible to eliminate this issue by using the deep learning method, which is one of these methods. In this study, an application has been implemented that can detect icing on wind turbine blades images with visualization techniques based on deep learning using images. Pre-trained models of Resnet-50, VGG-16, VGG-19 and Inception-V3, which are well-known deep learning approaches, are used to classify objects automatically. Grad-CAM, Grad-CAM++, and Score-CAM visualization techniques were considered depending on the deep learning methods used to predict the location of icing regions on the wind turbine blades accurately. It was clearly shown that the best visualization technique for localization is Score-CAM. Finally, visualization performance analyses in various cases which are close-up and remote photos of a wind turbine, density of icing and light were carried out using Score-CAM for Resnet-50. As a result, it is understood that these methods can detect icing occurring on the wind turbine with acceptable high accuracy.