• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.65-75
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• 2005

Measurement of network traffic have shown that the self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting the long-range correlation structure in a self-similar traffic for the congestion control. We have advanced the framework of the multiple time scale congestion control and showed its effectiveness at enhancing performance for the rate-based feedback control. Our contribution is threefold. First, we define a modular extension of the TCP-a function called with a simple interface-that applies to various flavours of the TCP-e.g., Tahoe, Reno, Vegas and show that it significantly improves performance. Second, we show that a multiple time scale TCP endows the underlying feedback control with proactivity by bridging the uncertainty gap associated with reactive controls which is exacerbated by the high delay-bandwidth product in broadband wide area networks. Third, we investigate the influence of the three traffic control dimensions-tracking ability, connection duration, and fairness-on performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.75-80
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• 2008

Measurement of network traffic have shown that the self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting the long-range correlation structure in a self-similar traffic for the congestion control. We have advanced the framework of the multiple time scale congestion control and showed its effectiveness at enhancing performance for the rate-based feedback control. Our contribution is threefold. First, we define a modular extension of the TCP-a function called with a simple interface-that applies to various flavours of the TCP-e.g., Tahoe, Reno, Vegas and show that it significantly improves performance. Second, we show that a multiple time scale TCP endows the underlying feedback control with proactivity by bridging the uncertainty gap associated with reactive controls which is exacerbated by the high delay-bandwidth product in broadband wide area networks. Third, we investigate the influence of the three traffic control dimensions-tracking ability, connection duration, and fairness-on performance.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• The Korean Journal of Emergency Medical Services
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• v.23 no.2
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• pp.61-73
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• 2019

Purpose: This study aimed to introduce active learning methods, including flipped, case-based, and team-based learning in an electrocardiography (ECG) course and to investigate outcomes and satisfaction with these methods. Methods: To identify the learning effect of active learning, pre-and post-academic self-efficacy was compared between the experimental and control groups. In the experimental group, pre-and post-knowledge and clinical performance regarding ECG were also assessed. In addition, class satisfaction was investigated after application of active learning methods in the experimental group. Data were collected from 84 paramedic students and analyzed using SPSS 22.0 (IBM, Armonk, NY, USA). Results: The experimental group showed significant improvement in post-academic self-efficacy and knowledge. The experimental group also showed high clinical performance (9.83 out of 10 in ECG checking ability and 9.63 out of 10 in ECG reading ability). The mean satisfaction score was 4.23 out of 5 (responses based on a Likert scale) in the experimental group. Conclusion: Active learning in an ECG course was found to be highly effective and satisfactory. Furthermore, paramedic students can enhance their accountability and judgement with team-based learning through free engagement in discussion.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1848-1849
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• 2006

The new robust controller design method is proposed for the flight control systems with model uncertainties. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the "explosion of complexity" problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.1
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• pp.33-42
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• 2002

Recently, various experiments to apply reinforcement learning method to the self-learning intelligent control of continuous dynamic system have been reported in the machine learning related research community. The reports have produced mixed results of some successes and some failures, and show that the success of reinforcement learning method in application to the intelligent control of continuous control systems depends on the ability to combine proper function approximation method with temporal difference methods such as Q-learning and value iteration. One of the difficulties in using function approximation method in connection with temporal difference method is the absence of guarantee for the convergence of the algorithm. This paper provides a proof of convergence of a particular function approximation method based on \"barycentric interpolator\" which is known to be computationally more efficient than multilinear interpolation .

• The Mathematical Education
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• v.52 no.4
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• pp.531-547
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• 2013

The purpose of the study is to examine how effects of activities using Google SketchUp on students' spatial ability and 3D geometric thinking in measuring the volume of solid figures. By comparing the results from pre- and post-tests between the experimental group and control group, we found that activities using Google SketchUp help students improve their spatial ability in the spatial orientation and visualization. In addition, more than half students in the experimental group moved from level 4 up to level 7 in thinking process of measuring the volume in terms of Battista(2004)'s levels. This study suggests that the instruction with Google SketchUp can help to improve students' spatial ability and 3D geometric thinking in the regular class in middle school. In addition, SketchUp can be an advanced technological tool to support students' self-directed learning, which create an efficient educational environment and a great opportunity to learn geometry in an effective manner.

• Journal of Digital Contents Society
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• v.11 no.3
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• pp.349-356
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• 2010

This study was to develop improving vocational basic skill program and content which are basic of instruction-learning ability for the vocational education substantiality. To pursue this goal, 'self-development capability' among vocational basic skills was developed through the research methodology and procedure. The interpersonal relation capability was selected as one of vocational basic skill areas when it was more effective by e-learning contents through literature review, expert conference etc. The self-development capability can be self-control and development under performing business tasks. In this study, self-development capability was programmed a interpersonal scheme, a cooperative capability, a leadership capability, a conflict management, negotiation capability, and a customer service capability. Especially this program was developed as a form of e-Learning contents focusing on improving problem solving under real case using multimedia strategies such as movies, simulation, game.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.297-302
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• 2004

In the information-oriented society, the paradigm of education has changed from the existing traditional teaching-centered education to the learning-centered education. In the Web-based Learning System which an learning-centered educational environment using the internet, students should have responsibility of their learning as taking more opportunities to participate their learning positively, to control their process of learning and to evaluate their learning by themselves to improve self-directed loaming ability. In this paper, the Web-based Learning System with a Self-Study Plan to lead students to select own purposes and methods of the study and write a self_evaluation is developed. The Self-Study Plan is a guide to lead the process, an order to have an individualized study and a report to evaluate own study. In addition, the suggested System is designed through object-oriented method using the extension mechanism of UML to archive the improvement of reuse and maintenance.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.247-254
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• 2021

The purpose of this study is to investigate the effects of action learning on the satisfaction of majors by cultivating task-solving ability through self-reflection in the form of team learning for a certain period of time in the form of team learning by using action learning for students taking convergence curriculum in universities. The subjects of the study were 40 students from the Department of Sports Rehabilitation, a convergence of the Department of Sports and Health Management and the Department of Physical Therapy located in Jeollanam-do. This was conducted to confirm the difference in the effect of satisfaction. Comparison of changes in groups of experimental groups with action learning teaching methods showed significant differences in self-directed learning skills, problem-solving skills, and major satisfaction(p<.001)(p<.05). A significant difference in self-directed learning ability, problem-solving ability, and major satisfaction was also shown in the comparison of changes in control groups that applied traditional teaching methods(p<.05). Comparison of changes between groups showed significant differences in self-directed learning skills, problem-solving skills and major satisfaction(p<.05). Applying the action learning teaching method to the level of students in the convergence course will improve self-directed learning skills, problem-solving skills, and major satisfaction, and further research will be needed to expand the target and add variables to combine qualitative research.