• The Mathematical Education
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• v.60 no.3
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• pp.341-362
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• 2021

The purpose of this study is to explore the qualitative characteristics of pre-service teachers' motivation while they are participating in group activities for developing mathematical essay assessment problem and revising it. For this purpose, we analyzed individual factors about group learning activities as well as contextual factors about practical competency (in developing and revising mathematical essay assessment problem through collecting data of student responses to the problem). As results of data analyses, autonomy, among individual factors regarding group learning activities, was one of the main characteristics in attainment value, utility value, and intrinsic value, whereas task, authority, and grouping, among contextual factors regarding practical competency, appeared to have a positive impact on task value. These results suggest how to think of specific ideas and articulate them in designing a curriculum to develop student-evaluation expertise for pre-service teachers.

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.1-7
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• 2008

The primary aim of the paper is to solve an unstable axisymmetric initial value problem of wave propagation when given initial data that is deteriorated by noise such as measurement error. To overcome the instability of the problem, Tikhonov's regularization, known as a non-iterative numerical regularization method, is introduced to solve the problem. The L-curvecriterion is introduced to find the optimal regularization parameter for the solution. It is confirmed that fairly stable solutions are realized and that they are accurate when compared to the exact solution.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.157-162
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• 2010

The cart-pole balancing problem is a pseudo-standard benchmark problem from the field of control methods including genetic algorithms, artificial neural networks, and reinforcement learning. In this paper, we propose a novel approach by using online reinforcement learning(OREL) to solve this cart-pole balancing problem. The objective is to analyze the learning method of the OREL learning system in the cart-pole balancing problem. Through experiment, we can see that approximate faster the optimal value-function than Q-learning.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.174-178
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• 1997

In this paper,we consider a LQG problem subject to the stochastic multirate system. By restating the problem as a periodic LQG problem, it is pointed out that the lack of measurements and control inputs in some time instants makes the problem singular. A method of transforming the problem into a nonsingular one enables us to obtain the solution,however which gives a resulting value of the LQG cost and the setimation error dynamic different with those of the original system. As a consequence, we present a optimal value of the original cost and the estimation error covariance of the original system,which are expressed by periodic Lyapunov equation respectively. The evaluation resulte can be exploited in comparing the control system performances and specifying the sampling rates.

• Korean Journal of Mathematics
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• v.20 no.4
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• pp.507-515
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• 2012

We investigate the number of the solutions for the elliptic boundary value problem. We obtain a theorem which shows the existence of six weak solutions for the elliptic problem with jumping nonlinearity crossing three eigenvalues. We get this result by using the geometric mapping defined on the finite dimensional subspace. We use the contraction mapping principle to reduce the problem on the infinite dimensional space to that on the finite dimensional subspace. We construct a three dimensional subspace with three axis spanned by three eigenvalues and a mapping from the finite dimensional subspace to the one dimensional subspace.

• Korean Journal of Mathematics
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• v.18 no.3
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• pp.323-334
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• 2010

We give a theorem for the existence of at least three solutions for the fourth order elliptic boundary value problem with the square growth variable coefficient nonlinear term. We use the variational reduction method and the critical point theory for the associated functional on the finite dimensional subspace to prove our main result. We investigate the shape of the graph of the associated functional on the finite dimensional subspace, (P.S.) condition and the behavior of the associated functional in the neighborhood of the origin on the finite dimensional reduction subspace.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.75-86
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• 2008

A remarshalling is one of the operational strategies considered importantly at a port container terminal for the fast ship operations and heighten efficiency of slacking yard. The remarshalling rearranges the containers scattered at a yard block in order to reduce the transfer time and the rehandling time of container handling equipments. This Paper deals with the rearrangement problem, which decides to where containers are transported considering time value of each operations. We propose the mixed integer programming model minimizing the weighted total operation cost. This model is a NP-hard problem. Therefore we develope the heuristic algorithm for rearrangement problem to real world adaption. We compare the heuristic algorithm with the optimum model in terms of the computation times and total cost. For the sensitivity analysis of configuration of storage and cost weight, a variety of scenarios are experimented.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.3
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• pp.47-56
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• 1999

제한된 출력 즉 오차 측정된 출력 값만을 사용하여 원하는 목표치에 도달하도록 하는 제어 문제를 푸는데 많은 연구가 진행되어 왔다. 종종 그러한 제어기를 설계할 때 해를 구하기 어려운 Non Linear Two Point Boundary Value Problem에 직면하게 된다. 특히 Reduced order 추정자 알고리즘은 백색 잡음에 의하여 영향을 받은 선형 시스템의 측정된 상태 뿐 만 아니라 보조 상태를 추정하기 위하여 개발되었다. 추정자를 설계할 때 상태는 무편향성이고 추정자의 편차는 추정자 및 추정상태와 공통되는 상태에 대한 모든 출력의 subspace에 수직이 된다. 특히 reduced order에서의 필터 성능은 full order에서의 필터 성능에 대해 suboptimal 이지만 상응한 Riccati equation을 푸는데 계산시간이 줄고 memory사용이 적은 이점이 있다. 본 논문에서는 Kronecker algebra와 선택행렬을 이용하여 Non Linear Two Point Boundary Value Problem을 Linear Two Point Boundary Value Problem으로 변환시켜 부수적으로 수반되는 대수적인 Riccati equation을 유도함으로써 문제를 쉽게 해결하는데 있다.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.153-160
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• 2020

This research aims to provide empirical basic data for the development of local communities through the establishment of efficient strategies for the formation of positive relations between the club and the region through the Creation of Shared Value (CSV) activities. We come up with the results of this study to show that CSV, social problem orientation, and core competency utilization affect the team trust of local community, and that CSV, long-term orientation, social problem orientation and core competency utilization affect community identification. The research should enhance the value of professional sports teams that promote their own path to self-sustaining as a single independent business area, and identify their trust through CSV activities for co-prosperity with their local communities, and thus their relationship with the community. Therefore, various strategies and efforts will ultimately increase the team trust and community identity of local residents in professional volleyball teams, while at the same time gaining positive effects on professional volleyball teams.

• Journal of IKEEE
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• v.23 no.4
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• pp.1150-1156
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• 2019

This paper explores a model-free value-based approach for solving survival gridworld problem. Survival gridworld problem opens up a challenge involving taking risks to gain better rewards. Classic value-based approach in model-free reinforcement learning assumes minimal risk decisions. The proposed method involves a hybrid on-policy and off-policy updates to experience roll-outs using a modified Q-based update equation that introduces a parametric linear rectifier and motivational discount. The significance of this approach is it allows model-free training of agents that take into account risk factors and motivated exploration to gain better path decisions. Experimentations suggest that the proposed method achieved better exploration and path selection resulting to higher episode scores than classic off-policy and on-policy Q-based updates.