• Journal of The Korean Association of Information Education
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• v.12 no.3
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• pp.283-292
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• 2008

Computer Science Education has to be dynamically changed due to a change of information technology. This study aims to present the direction of development for computer science education according to compare a report of KEDI; Korean Educational Development Institute, twenty years ago with our latest investigation. In this research, nowadays the personal computer diffused at most home. Home is the main environment for students to use computer. Students demand new computing curricula and teaching method. The global tendency of computer science education focuses on the improvement of problem solving ability. According to our investigation, most students hope to learn the new computing skills through game-based learning. We present the unplugged teaching methods and simulation-based learning using EPL(Educational Program Langage). Of course it's important to be applied to school now. And it can be achieved just by national efforts alone.

• Journal of the Korean School Mathematics Society
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• v.15 no.4
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• pp.605-625
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• 2012

This study examined how 132 teachers of different grade levels incorporate the key competencies identified by Korea Institute for Curriculum and Evaluation into their mathematics teaching and how they perceive of its full potential of the competency-based learning and teaching in mathematics classroom. Survey and semi-structured interview methods were used to collect data for the study. It was found that in their instruction teachers emphasized competencies such as problem-solving, literacy, creativity, communication and information-processing skills in order. Inter-personal skills, self-management, citizenship, global understanding and career-development appeared to be challenging competencies for teachers to reflect in their instruction with the reasons such as no direct connections to mathematics and insufficient instruction. Findings of the study suggest that various instructional methods, development and dissemination of related curricula materials, change of evaluation method, and change teachers' perceptions may be needed for incorporating KICE's key competencies in K-12 mathematics education.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.119-132
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• 2023

In recent years, the competition for employment among college students has become more intense. It is also the time when strong personal beliefs and will to develop careers are required for successful employment through stable major study. Therefore, in this study, we tried to find out the effect on major attitude and employment efficacy according to the level of aviation safety perception, which is an important issue in the aviation industry. For analysis, survey is conducted targeting college students majoring in aviation service who are enrolled in universities in the metropolitan area and Chungcheong area. To verify the hypotheses of the study, demographic characteristics are identified based on questionnaires, reliability and validity of measurement items are verified, and structural equation model analysis is performed to verify the hypotheses. The analysis results are as follows. First, it is found that safety knowledge and safety consciousness, which are sub-factors of aviation safety perception of college students majoring in aviation service, have a positive (+) effect on subject recognition, learning process recognition, and career recognition of major recognition. Second, subject recognition, learning process recognition, and career recognition, which are sub-factors of major recognition, are found to have a positive effect on major commitment. Third, it is found that major commitment have a positive (+) effect on employment efficacy. Based on the research results, practical support plans and strategies for effective major study and successful employment are presented.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.723-730
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• 2024

In order to trace the changes in the concept and understanding of automatically generated images, this study analogously explores the creative methods of photography and cinema, which represent the existing image fields, in terms of AI-based image creation methods and 'automaticity', and discusses the understanding and possibilities of new automatic image creation. At the time of the invention of photography and cinema, the field of 'automatic creation' was established for them in comparison to traditional art genres such as painting. Recently, as AI has been applied to video production, the concept of 'automatic creation' has been expanded, and experimental creations that freely cross the boundaries of literature, art, photography, and film are active. By utilizing technologies such as machine learning and deep learning, AI automated creation allows AI to perform the creative process independently. Automated creation using AI can greatly improve efficiency, but it also risks compromising the personal and subjective nature of art. The problem stems from the fact that AI cannot completely replace human creativity.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1129-1134
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• 1989

In this paper, we propose a neural network for learning to control semi-linear dynamical systems. The network is a composite system of four three-layer backpropagation subnetworks, and is able to control inverted pendulums better than systems based on modern control theory at least in some ranges of parameters. Three of the four subnetworks in our network system process angles, velocities, and positions of a moving inverted pendulum, respectively. The outputs from those three subnetworks are input to the remaining subnetwork that makes control decisions. Each of the four subnetworks learns connection weights independently by backpropagation algorithms. Teaching signals are given by the human operator. Also, input signals are generated by the human operator, but they are converted by preprocessors to actual input data for the three subnetworks except for the network for control decisions. The whole system is implemented on both of 16 bit personal computers and 32 bit workstations. First, we briefly provide the research background and the inverted pendulum problem itself, followed by the description of our composite neural network model. Next, some results from the simulation are given, which are subsequently compared with the results from a control system based on modern control theory. Then, some discussions and conclusion follow.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.2
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• pp.166-173
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• 2004

The new way of doing education in cyber space is not limited by time or locations. The students do not need to attend classroom physically on time. Networked computers allow students to study their subjects at any time and any where. This study tries to probe the relationships among demographic variables and instructional variables with students satisfaction in the management education. Pervious studies found out that the critical success factors of cyber educations are based on the demographic and instructional variables. The results of the study demonstrate that demographic variables are not significantly related with students satisfaction. Rather instructional variables such as personal interactions with professors, job related contents and careful reduction of difficulties countered during the class proceeding are more significantly related with learning satisfaction. The result shows the newly emerged internet based education system requires in-depth collaborations and coordination among professors, system engineers, education instrument designers, and students.

• Journal of Korean Elementary Science Education
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• v.18 no.2
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• pp.1-19
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• 1999

Based on the analysis of commonalities and differences in the views of science achievement in major reform documents in the United States and Korea, an aggregated view of science achievement is presented in this paper Science achievement is conceived of in terms of science content and science process. The components of science content include: (a) concepts and theories I n physical, life, and earth and space science;(b) science, mathematics, and technology;(c) science in personal and social perspectives;(d)history and nature of science;and (e) unifying themes. The components of science process include: (a) scientific understanding;(b) scientific investigation;(c) scientific communication; and (d) scientific habits of mind. The components of science process.cut across and intersect with the components of science content. The components of science achievement overlap and are related to one another. Despite such an overlap, understanding the rot e that each component plays provides insight into its unique contributions as well as its interactions with other components. A definition of science achievement and identification of its components based on major reform documents provides a guideline for science assessment as well a s science teaching and learning.

• Korean Journal of Child Studies
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• v.25 no.6
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• pp.171-189
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• 2004

Children develop emotional intelligence during the early years of life, and according to experts, emotional intelligence(EI) is a more reliable predictor of academic achievement than IQ. However, nowadays children appear to be low on emotional well-being. This has potentially negative consequences, not only for academic achievement but also for personal relationships. The purpose of this study was to develop emotional education program for young children(EEPYC). In this study, EI is defined to carry out reasoning in regard to emotions and to use emotion for enhancement of thought. Designed to facilitate development of young children's EI. EEPYC is based on the four branch model, which is mental EI model and based on the guiding principle of Collaborative to Advance Social and Emotional Learning. The subgroups(curricular) that compose EEPYC are Emotional Perception, appraisal, and expression, Self-recognition program, Self-esteem program, Emotional Stress Regulation, Emotional problem solving & conflict resolution. EEPYC has the potential of fostering emotional intelligence. Moreover, EEPYC can promote a motivation, prosocial activity, and regulation of stress. This helps young children to develope cognition and emotion in harmonious fashion.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.2
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• pp.131-139
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• 2019

Manually reviewing electroencephalograms (EEGs) is labor-intensive and demands automated seizure detection systems. To construct an efficient and robust event detector for experimental seizures from continuous EEG monitoring, we combined spectral analysis and deep neural networks. A deep neural network was trained to discriminate periodograms of 5-sec EEG segments from annotated convulsive seizures and the pre- and post-EEG segments. To use the entire EEG for training, a second network was trained with non-seizure EEGs that were misclassified as seizures by the first network. By sequentially applying the dual deep neural networks and simple pre- and post-processing, our autodetector identified all seizure events in 4,272 h of test EEG traces, with only 6 false positive events, corresponding to 100% sensitivity and 98% positive predictive value. Moreover, with pre-processing to reduce the computational burden, scanning and classifying 8,977 h of training and test EEG datasets took only 2.28 h with a personal computer. These results demonstrate that combining a basic feature extractor with dual deep neural networks and rule-based pre- and post-processing can detect convulsive seizures with great accuracy and low computational burden, highlighting the feasibility of our automated seizure detection algorithm.