• Journal of Agricultural Extension & Community Development
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• v.4 no.1
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• pp.211-229
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• 1997

An environmental problem is the greatest barrier to pursuit of mankinds existence and development. The major traits of this problem are totality and complexity, therefore the finding of environmental problem's solutions is very difficult. The eco-friendly development that pursuing the ecological principles is the direction of environmental problem's solutions. Environmentally sound and sustainable development, deep ecological thought or environmentalism, the following of god's creation order and the old oriental thought are patterns and principles of eco-friendly development. Every creature has one ecological niche from the ecological principles of adoption, competition, evolution, variety, circulation, harmony and equilibrium. Ecological niche means that every creature has ecological status and duty. Therefore finding the mankinds ecological niche is important because it is desirable directions for eco-friendly development to solve environmental problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.2
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• pp.92-101
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• 2002

The Job Shop Scheduling Problem(JSSP) is concerned with schedule of m different machines and n jobs where each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. The purpose of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the large scale job shop scheduling. The proposed heuristic method is based on a Tabu Search(TS) and on a Constraint Satisfaction Technique(CST). In this paper, ILOG libraries is used to embody the job shop model, and a CST is developed for this model to generate the increased solution. Then, TS is employed to overcome the increased search time of CST on the increased problem size md to refine the next-current solution. Also, this paper presents the new way of finding neighbourhood solution using TS. On applying TS, a new way of finding neighbourhood solution is presented. Computational experiments on well known sets of MT and LA problem instances show that, in several cases, our approach yields better results than the other heuristic procedures discussed In literature.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.596-604
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• 2020

Previous studies on pipe auto-routing algorithms generally used such algorithms as A*, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A* algorithm in terms of resolution.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.92-99
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• 2024

To minimize the cumulative radiation dose, various path-finding approaches for single agent have been proposed. However, for emergence situations such as nuclear power plant accident, these methods cannot be effectively utilized for evacuating a large number of workers because no multi-agent method is valid to conduct the mission. In this study, a novel algorithm for solving the multi-agent path-finding problem is proposed using the conflict-based search approach and the objective function redefined in terms of the cumulative radiation dose. The proposed method can find multi paths that all agents arrive at the destinations with reducing the overall radiation dose. To verify the proposed method, three problems were defined. In the single-agent problem, the objective function proposed in this study reduces the cumulative dose by 82% compared with that of the shortest distance algorithm in experiment environment of this study. It was also verified in the two multi-agent problems that multi paths with minimized the overall radiation dose, in which all agents can reach the destination without collision, can be found. The method proposed in this study will contribute to establishing evacuation plans for improving the safety of workers in radiation-related facilities.

• Journal of Gifted/Talented Education
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• v.21 no.4
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• pp.1033-1053
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• 2011

In the process of establishing the principle of genetics, Mendel discovered problems based on various observations. Mendel's scientific thinking ability can be effective if this ability is embedded in gifted science education programs. The study aims to develop a science gifted education program utilizing Mendel's scientific thinking ability shown in the principles of genetics and examine students' changes in scientific thinking ability before and after the program implementation. For the program development, first, the characteristics of Mendel's scientific thinking ability in the process of establishing the principle of genetics were investigated and extracted the major elements of inquiry. Second, the science gifted education programs was developed by applying the inquiry elements from the Mendel's Law. The program was implemented with 19 students of $7^{th}$, $8^{th}$ graders who attend the science gifted education center affiliated with university during July 2011. The Mendel's scientific thinking ability was classified into induction, deduction, and integration. The elements of inquiry extracted from the Mendel's scientific thinking include making observation, puzzling observation, proposing causal questions, generating hypothesis, drawing inference, designing experiment, gathering and analyzing data, drawing conclusions, and making generalization. With applying these elements, the program was developed with four phases: $1^{st}$ - problem finding; $2^{nd}$ - hypothesis generating; $3^{rs}$ - hypothesis testing and $4^{th}$ - problem solving. After implementation, students' changes in scientific thinking ability were measured. The findings from the study are as follows: First, students' abilities of problem finding is significantly (p<.05) increased. Second, students' abilities of hypothesis generating is significantly (pp<.05) increased.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.39-46
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• 2009

Generally, Path-finding algorithms which use heuristic function may occur a problem of the increase of exploring cost in case of that there is no way determined by heuristic function or there are 2 way more which have almost same cost. In this paper, we propose an abstract graph for path-finding with dynamic information. The abstract graph is a simple graph as real road network is abstracted. The abstract graph is created by fixed-size cells and real road network. Path-finding with the abstract graph is composed of two step searching, path-finding on the abstract graph and on the real road network. We performed path-finding algorithm with the abstract graph against A* algorithm based on fixed-size cells on road network that consists of 106,254 edges. In result of evaluation of performance, cost of exploring in path-finding with the abstract graph is about 3~30% less than A* algorithm based on fixed-size cells. Quality of path in path-finding with the abstract graph is, However, about 1.5~6.6% more than A* algorithm based on fixed-size cells because edges eliminated are not candidates for path-finding.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.453-465
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• 2000

In this paper, a new method for finding the approximate solution of a second order nonlinear partial differential equation is introduced. In this method the problem is transformed to an equivalent optimization problem. them , by considering it as a distributed parameter control system the theory of measure is used for obtaining the approximate solution of the original problem.

• The Pure and Applied Mathematics
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• v.19 no.4
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• pp.363-381
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• 2012

Shortfall risk is considered by taking some exposed risks because the superhedging price is too expensive to be used in practice. Minimizing shortfall risk can be reduced to the problem of finding a randomized test ${\psi}$ in the static problem. The optimization problem can be solved via the classical Neyman-Pearson theory, and can be also explained in terms of hypothesis testing. We introduce the classical Neyman-Pearson lemma expressed in terms of mathematics and see how it is applied to shortfall risk in finance.

• Journal of applied mathematics & informatics
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• v.34 no.1_2
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• pp.95-106
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• 2016

In this paper, according to the classical LSQR algorithm forsolving least squares (LS) problem, an iterative method is proposed for finding the minimum-norm pure imaginary solution of the quaternionic least squares (QLS) problem. By means of real representation of quaternion matrix, the QLS's correspongding vector algorithm is rewrited back to the matrix-form algorthm without Kronecker product and long vectors. Finally, numerical examples are reported that show the favorable numerical properties of the method.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.636-638
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• 1997

This paper deals with the problem of finding robust controller based upon a pole assignment method for a plant with parameter perturbations. This case is not a problem of Interval polynomial family but a problem of poly topic polynomial family. As a method of stability test, we used GKT(Generalized Kharitonov Theorem) having computational advantage.