• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.49.3-49
• /
• 2001

In 1994 Adelman´s pioneer work demonstrated that deoxyribonucleic acid (DNA) could be used as a medium for computation to solve mathematical problems. He described the use of DNA based computational approach to solve the Hamiltonian Path Problem (HPP). Since then a number of combinatorial problems have been analyzed by DNA computation approaches including, for example: Maximum Independent Set (MIS), Maximal Clique and Satisfaction (SAT) Problems. In the present paper we propose a method of solving another classic combinatorial optimization problem - the eraph Coloring Problem (GCP), using specifically designed circular DNA plasmids as a computation tool. The task of the analysis is to color the graph so that no two nodes ...

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.635-642
• /
• 1989

We formulated the multi-robot trajectory problem into a series of NLP problem, each of which is that of finding the optimal tip positions of the robots for the next time step. The NLP problem is composed of an objective function and three constraints, namely: a) Joint position limits, b) Joint velocity limits, and c) Collision-avoidance constraints. By solving a series of NLP problem, optimally coordinated trajectories can be determined without requiring any prior path information. This is a novel departure from the previous approach in which either all paths or at least one path is assumed to be given. Practical application of the developed method is for optimal synthesis of multiple robot trajectories in off-line. To test the validity and effectiveness of the method, numerical examples are illustrated.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.8
• /
• pp.122-129
• /
• 1997

In this paper, we propose a Hopfield model for solving the part-matching in case that is the number of parts and positions are changed. The goal of this paper is to minimize part-connection in pairs and total path of part-connections. Therefore, this kind of problem is referred to as a combinatiorial optimization problem. First of all, we review the theoretical basis for Hopfield model and present two optimal algorithms of part-matching. The first algorithm is Traveling Salesman Problem(TSP) which improved the original and the second algorithm is Wdighted Matching Problem (WMP). Finally, we show demonstration through com- puter simulation and analyze the stability and feasibility of the generated solutions for the proposed con- nection methods. Therefore, we prove that the second algorithm is better than the first algorithm.

• International Journal of Computer Science & Network Security
• /
• v.24 no.1
• /
• pp.45-51
• /
• 2024

The subject of navigation has drawn a large interest in the last few years. The navigation within a city is to find the path between two points, source location and destination location. In many cities, solving the routing problem is very essential as to find the route between different locations (starting location (source) and an ending location (destination)) in a fast and efficient way. This paper considers streets with diagonal streets. Such streets pose a problem in determining the directions of the route to be followed. The paper presents a solution for the path planning using the reconfigurable mesh (R-Mesh). R-Mesh is a parallel platform that has very fast solutions to many problems and can be deployed in moving vehicles and moving robots. This paper presents a solution that is very fast in computing the routes.

• Computers and Concrete
• /
• v.12 no.3
• /
• pp.261-283
• /
• 2013

This paper aims to contribute to the three-dimensional generalization of numerical prediction of crack propagation through the formulation of finite elements with embedded discontinuities. The analysis of crack propagation in two-dimensional problems yields lines of discontinuity that can be tracked in a relatively simple way through the sequential construction of straight line segments oriented according to the direction of failure within each finite element in the solid. In three-dimensional analysis, the construction of the discontinuity path is more complex because it requires the creation of plane surfaces within each element, which must be continuous between the elements. In the method proposed by Chaves (2003) the crack is determined by solving a problem analogous to the heat conduction problem, established from local failure orientations, based on the stress state of the mechanical problem. To minimize the computational effort, in this paper a new strategy is proposed whereby the analysis for tracking the discontinuity path is restricted to the domain formed by some elements near the crack surface that develops along the loading process. The proposed methodology is validated by performing three-dimensional analyses of basic problems of experimental fractures and comparing their results with those reported in the literature.

• Journal of Korean Society of Transportation
• /
• v.17 no.2
• /
• pp.163-178
• /
• 1999

Conventional shortest path searching a1gorithms are based on the partial searching method such as Dijsktra, Moore etc. The a1gorithms are effective to find a shortest path in mini-modal condition of a network. On the other hand, in multi-modal case they do not find a shortest path or calculate a shortest cost without network expansion. To copy with the problem, called Searching Area Problem (SAP), a global searching method is developed in this paper with Genetic Algorithm. From the results of two examples, we found that the a1gorithm is useful to solving SAP without network expansion.

• Journal of the Korea Convergence Society
• /
• v.9 no.12
• /
• pp.495-507
• /
• 2018

This study was done to develop and validate a path model for the causal relationship of nursing information literacy competency and problem solving, self-direct learning, and clinical performance ability of nursing students. Subject were 208 nursing students in the fourth grade of nursing school. Data were collected from June 4 to June 18, 2018. The nursing information literacy competency of nursing students showed direct effects on problem solving ability (${\gamma}=.70$, p<.001) and direct effects on self-directed learning ability (${\gamma}=.53$, p<.001). Nursing information literacy competency showed direct (${\gamma}=.31$, p<.001) and indirect effects (${\gamma}=.31$, p=.007) on clinical performance ability. These variables explained for 46.2% of clinical performance ability. Therefore, it is recommended to develop an education program that can enhance the nursing information literacy competency for improving the problem solving, self-directed learning, and clinical performance ability of nursing students.

• Journal of Practical Engineering Education
• /
• v.12 no.2
• /
• pp.275-291
• /
• 2020

This study aims to identify the structural relationship between mastery-approach goal orientation, instructor support, problem solving, collaborative skills, and course satisfaction among students who participated in project-based learning. To achieve the purpose of this research, researchers have conducted surveys between June and December in 2019. A total of 283 cases were selected for analysis. According to the study, mastery-approach goal orientation and instructor support have positive effects on problem solving and course satisfaction. Instructor support has positive effects on collaboration skills, and problem solving has positive effects on collaboration skills and course satisfaction. Also, the mediating effect of problem solving in the relationship among mastery-approach goal orientation, instructor support, collaboration skills, and course satisfaction was found to be statistically significant. However, the path between mastery-approach goal orientation and collaboration skills was not statistically significant. Based on these findings, academic and practical implications were suggested.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2325-2330
• /
• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.4
• /
• pp.843-859
• /
• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.