• Journal of the Korean Institute of Educational Facilities
• /
• v.24 no.6
• /
• pp.11-18
• /
• 2017

Education facilities have much affect to make a good condition for the learning environment. Therefore, various approaches have been conducted to improve the physical, social and educational achievement. Especially, the physical aspect is very important to get rid of the building defect and improve the student their learning environment. For these, it needs to explain the performance and function of components and materials, which is linked with the deterioration degree. The deterioration degree is a imperative factor to make a decision whether the component would be repaired or not and to provide the repair scope of its component. In this paper, it aimed at making the deterioration degree model of roof proof under the hypothesis of which deterioration degree would be equal the repair cost at this time. Results of the study are shown that first, the $3^{rd}$ function is most proper to explain the deterioration degree model among 11 functions in view of resulted statistics. Second, the inflection of deterioration is shown at 15yr of the elementary school and 13yr of the middle and high school. This study has a limit of disclassification of the component or materials and it is, therefore, favorable to include the classification of waterproof material and work. These results would make a change from the breakdown maintenance to preventive maintenance and give a decent the learning environment for student.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.534-540
• /
• 1993

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algrithms need a special perfect position sensor or a priori information about error sources, while ours does not. To our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterative learning algorithm does not have the drawbacks of the existing iterative learning control theories. To be more specific, our algorithm learns a uncertain function inself rather than its special time-trajectory and does not request the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• East Asian mathematical journal
• /
• v.32 no.4
• /
• pp.589-608
• /
• 2016

The purpose of this study was to develop an effective Calculus Supplement Learning Program for university students who are from liberal arts and investigate how the program affects their achievement and attitude in mathematics. we analyzed their answer sheets and interview reports with qualitative methods. After adapting the program, students recognized that mathematical concepts and definitions were very important to study a college calculus. Also they picked up how to learn mathematics in college. Finally, we found that students could develop their abilities of proof, problem solving, and logical thinking through the program.

• School Mathematics
• /
• v.1 no.1
• /
• pp.109-122
• /
• 1999

In this paper we give a description of students' obstacles in their learning of geometry, especially resulted from their confusing a physical drawing with a figure, a geometrical object which a physical drawing represents. In computer-based teaching-learning environment, we could relieve such obstacles through providing students for experiences in which they must focus on elements of a figure and relations of them. But there may be potential in computer-based environment if we offer students only visual experience for validity of geometrical gacts: students' lack of understanding for need of proof and experience of cognitive obstacles which is very important for students to reflect their thinking and activities. Thus an didactical treatment must follows, which we also give an example.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.608-615
• /
• 1998

In this paper a second-order iterative learning control algorithm with feedback is proposed for the trajectory-tracking control of nonlinear dynamic systems with unidentified parameters. In contrast to other known methods, the proposed teaming control scheme utilize more than one past error history contained in the trajectories generated at prior iterations, and a feedback term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances or system parameter variations. The convergence proof of the proposed algorithm is given in detail, and the sufficient condition for the convergence of the algorithm is provided. We also discuss the convergence performance of the algorithm when the initial condition at the beginning of each iteration differs from the previous value of the initial condition. The effectiveness of the proposed algorithm is shown by computer simulation result. It is shown that, by adding a feedback term in teaming control algorithm, convergence speed, robustness to disturbances and robustness to unmatched initial conditions can be improved.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.5
• /
• pp.838-847
• /
• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.39 no.2
• /
• pp.85-94
• /
• 2002

In this paper, we show that the 2nd-order iterative learning control algorithm with CITE is more effective and has better convergence performance than the algorithm without CITE in the case of the existence of initialization errors, for the trajectory-tracking control of dynamic systems with unidentified parameters. In contrast to other known methods, the proposed learning control scheme utilize more than one past error history contained in the trajectories generated at prior iterations, and a CITE term is added in the learning control scheme for the enhancement of convergence speed and robustness to disturbances and initialization errors. And the convergence proof of the proposed algorithm in the case of the existence of initialization error is given in detail, and the effectiveness of the proposed algorithm is shown by simulation results.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.07a
• /
• pp.567-568
• /
• 2023

본 논문에서는 블록체인 기반 DID기술을 이용하여 원격교육에서 발생하는 학습데이터를 효율적으로 관리하기 위한 방법으로, 학습데이터 가중치를 고려한 DID 메타데이터관리방법을 제안하였다. 메타데이터의 식별자에 대하여 특정위치로 데이터 가중치를 검색하도록 하고 해당 가중치에 따라 처리방법을 다양화 할 수 있다. 본문에서는 블록체인의 Zero Knowledge Proof 방식 처리에 차별화를 두어 메타데이터를 처리하였으며 데이터 처리속도 및 데이터관리에 효율성높일 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.1 no.2
• /
• pp.49-55
• /
• 2000

In this paper, we show that our previously proposed second-order iterative learning control method with feedback is more effective and has better convergence performance than the second-order iterative learning control method without feedback, particularly in the case of the existence of initial condition errors. Also the convergence proof of the proposed method is given. And through the simulation result of applying the proposed method to the linear time-varying system, we show that our proposed method has enhanced robustness and stability in case of the existence of initial condition errors.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.2
• /
• pp.161-166
• /
• 2014

Using and increasing the smart devices got many changes for social environment. Especially, many researchers have studied application using smart devices for improving the learning performance in education. However, Liberal Arts of Humanities has very difficult to apply to information and communication technology cause of traditional study pattern and unit characteristic. In this paper, we suggest a method to apply the Liberal Arts of Humanities to digital broadcasting and to improve learning performance. For this study, we propose a method to making smart contents and connecting them for Liberal Arts of Humanities. And also, we propose a method for applying them to digital broadcasting in order to proof the learning performance increasing by questionary, and shows the application possibility.