• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.153-158
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• 1995

Finding shortest paths in networks is the fundamental problem in network theory and has numerous in Operations Research and related fields. The purpose of this study is to present a algorithm for solving the length of the shortest paths from a fixed node in a general network in which the arc distance can be arbitrary value. This algorithm has a worst computational bound of $n^3/4$ additions and $n^3/4$ comparisons, which is lower the worst computational bounds of other available algorithms.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.243-254
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• 2016

This study has produced a checker of the shortest path search problem with a total of 19 questions as a web-based computer evaluation based on the 'TRAFFIC' questions of PISA 2012. It is because the computer has been settled as an indispensable and significant instrument in the process of solving the problems of everyday life and as a media that is underlying in assessment. Therefore, information gifted students should be able to solve the problem using the computer and give clear enough commands to the computer so that it can perform the procedure. In addition, since it is the age that the computational thinking is affecting every sectors, it should give students new educational stimuli. The relationship between the rate of correct answers and the time took to solve the problem through the shortest route search process showed a significant correlation the variable that affected the problem solving as the difficulty of the question rises due to the increase of nodes and edges turned out to be the node than the edge. It was revealed that information gifted students went through algorithmic thinking in the process of solving the shortest route search problem. And It could be confirmed cognitive characteristics of the information gifted students such as 'ability streamlining' and 'information structure memory'.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.698-702
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• 1992

In this paper, Micro-Genetic algorithms(.mu.-GAs) is proposed on a minimum-time path planning for robot manipulator, which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can't often find the optimal values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimal values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.40-47
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• 1994

In this paper, Micro-Genetic algorithms($\mu$-GAs) is proposed on a minimum-time path planning for robot manipulator. which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can`t often find the optimaul values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimul values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.485-491
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• 1990

We propose a minimum-time path planning soheme for the robot manipulator using Hopfield neural network. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural network technique, which can allow the parallel computation, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using the PUMA 560 manipulator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1364-1371
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• 1990

We propose a time-optimal path planning scheme for the robot manipulator using Hopfield neural network. The time-optimal path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural networke technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using a PUMA 560 manipulator.

• 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.

• Korean Journal of Social Welfare
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• v.58 no.1
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• pp.59-85
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• 2006

The purpose of this study was to identify how traumatic experiences and stresses caused hopelessness and depression among low-income residents, and to delineate what social problem solving capabilities might play roles in relation to the hopelessness theory of depression. For the purpose of the study, the target group of this study was restricted to adults over 20. This study recruited 175 low-income residents(the Beneficiary of National Basic Livelihood Security Act and the Near Poor Group) in Busan, Korea and employed a self-administered survey method during February, 2004. The following are the major results of the study. First, in low-income subjects, stresses showed positive influences on hopelessness. Second, in low-income subjects, stresses and hopelessness showed positive influences on depression. Third, stress influenced depression with hopelessness as the intervening variable, but it was not statistically significant path in traumatic experiences. The hopelessness theory of depression is to test whether the individuals who have negative attributional style and experience negative life events are likely to make negative attributions for the negative events they confront. The present study, using low-income residents, found that negative life experience predict negative attributions without negative attributional style. Fourth, social problem solving capabilities buffered the relationship between stress and hopelessness. It was also significant subscales apart from Positive Problem Orientation and Negative Problem Orientation. Fifth, social problem solving capabilities buffered the relationship between hopelessness and depression. It was also significant subscales apart from Negative Problem Orientation and Impulsivity/Carelessness Style. Based on the results, practice implications by identifying what social problem solving capabilities might play roles in hopelessness theory of depression were discussed.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.607-620
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• 2002

In this paper, we consider the updating problems to reconstruct the biconnected-components and to reconstruct the weighted shortest path in response to the topology change of the network. We propose two distributed algorithms. The first algorithm solves the updating problem that reconstructs the biconnected-components after the several processors and links are added and deleted. Its bit complexity is O((n'+a+d)log n'), its message complexity is O(n'+a+d), the ideal time complexity is O(n'), and the space complexity is O(e long n+e' log n'). The second algorithm solves the updating problem that reconstructs the weighted shortest path. Its message complexity and ideal-time complexity are $O(u^2+a+n')$ respectively.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.7
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• pp.809-822
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• 1992

A mathematical approach to solving the time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in robot joint space(JS). View-time concept is used to deal with time-varying obstacles. The view-time is the period in which a time-varying obstacles. The view-time is the period in which a time-varying obstacle is viewed and approximated by an equivalent stationary obstacle. The equivalent stationary obstacle is the volume swept by the time-varying obstacle for the view-time. The swept volume is transformed into the JS obstacle that is the set of JS robot configurations causing the collision between the robot and the swept volume. In JS, the path avoiding the JS obstacle is planned, and a trajectory satisfying the constraints on robot motion planning is planned along the path. This method is applied to the collision-free motion planning of two SCARA robots, and the simulation results are given.