• 한국기계연구소 소보
• /
• s.20
• /
• pp.33-39
• /
• 1990

In the existing robot programming methods, off-line method because important role of programming because of improvement of hardware and softeare of PC. The purpose of this study is to develop practical robot programming system for polishing task using PC. In the first place, we have investigated the existing robot programming systems, and derived the requirement of this programming system from the existing systems. And we have decied the structure of this system. After that, we have developed this system. Using Windows software, this programming system has man/machine interface function. Therefore users can use easily and quickly.

• The Journal of Korean Association of Computer Education
• /
• v.19 no.2
• /
• pp.1-10
• /
• 2016

This study is for developing a programming education course to improve pre-service teachers' pedagogical content knowledge(PCK) of programming education. A 40-hour training course was designed with App Inventor, a block-based mobile programming environment, and with problem-based learning method and project-based learning method. After the curriculum was adopted to 12 undergraduate students, the effect of education was tested with a programming PCK questionnaire. As a result, after a 20-hour problem-based learning class, overall score and teaching method score were enhanced significantly. After another 20-hour project-based learning class, content knowledge, teaching method, and curriculum score were improved.

• Journal of Practical Engineering Education
• /
• v.9 no.2
• /
• pp.139-148
• /
• 2017

As the connection between objects and computers becomes easier, learning using physical computing is presented as a good alternative to solve the problems raised in programming education for beginners. In this paper, we propose a training method that can be applied to basic programming courses for beginners. To do this, we will proceed with a basic programming lecture based on the physical computing method. Currently, physical computing courses focus on various input sensor connection methods and output device control. However, the content of programming education using physical computing materials is lacking. In this paper, we proposed and tested a teaching method that is used in programming education by using low cost materials used in physical computing.

• The Journal of Korean Association of Computer Education
• /
• v.13 no.3
• /
• pp.13-23
• /
• 2010

The revised 7th education course of information implies that students use variety of information devices to solve the common problems and it also includes the programming education for improving problem-solving abilities. Not only improving problem-solving abilities but also developing thinking skill is expected in programming education. However, traditional programming education is teacher-oriented and focused on language syntax. Accordingly, students have heavy cognitive load and it decrease students' interest of programming. Therefore, in this paper, a instructional method of programming using educational robot is proposed to improve interest of elementary students in concretive operation stage for effectiveness of programming education. Additionally, results of experiments show that proposed robot programming instructional method can be applied in elementary education.

• 전기의세계
• /
• v.30 no.6
• /
• pp.375-385
• /
• 1981

New algorithms are derived for nonlinear programming problems which are characterized by their large variables and equality and inequality constraints. The algorithms are based upon the introduction of the Dependent-Variable-Elimination method, Independent-Variable-Reduction method, Optimally-Ordered-Triangular-Factorization method, Equality-Inequality-Sequential-Satisfaction method, etc. For a case study problem relating to the optimal determination of load flow in a 10-bus, 13-line sample power system, several approaches are undertaken, such as SUMT, Lagrange's Multiplier method, sequential applications of linear and quadratic programming method. For applying the linear programming method, the conventional simplex algorithm is modified to the large-system-oriented one by the introduction of the Two-Phase method and Variable-Upper-Bounding method, thus resulting in remarkable savings in memory requirements and computing time. The case study shows the validity and effectivity of the algorithms presented herein.

• Journal of applied mathematics & informatics
• /
• v.17 no.1_2_3
• /
• pp.121-144
• /
• 2005

In this paper, we propose unconstrained and constrained posynomial Geometric Programming (GP) problem with negative or positive integral degree of difficulty. Conventional GP approach has been modified to solve some special type of GP problems. In specific case, when the degree of difficulty is negative, the normality and the orthogonality conditions of the dual program give a system of linear equations. No general solution vector exists for this system of linear equations. But an approximate solution can be determined by the least square and also max-min method. Here, modified form of geometric programming method has been demonstrated and for that purpose necessary theorems have been derived. Finally, these are illustrated by numerical examples and applications.

• Journal of the military operations research society of Korea
• /
• v.2 no.1
• /
• pp.111-125
• /
• 1976

This paper is to explore technological forecasting methodologies and their application to military R&D programming. Among a number of forecasting methodologies, eight frequently used methods are explained. They are; Delphi method, analogy, growth curve, trend extrapolation, analytical model, breakthrough, normative method, and combined method. Due to the characteristic situation of a developing country, the application of technological forecasting to the Korean military R&D programming is limited. Therefore, only two forecasting methods such as Delphi and normative method are utilized in the development of a decision model for the military R&D programming. The model consists of a dynamic programming using decision tree model, which optimizes the total cost to equip a certain military item under a given range of risk during a given period. Some pitfalls in forecasting methodologies and of the model are discussed.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.15 no.1
• /
• pp.73-82
• /
• 1990

This paper describes two algorithms to Nonlinear programming problems with equality constraints and with equality and inequality constraints. The first method treats nonlinear programming problems with equality constraints. Utilizing the nonlinear programming problems with equality constraints. Utilizing the nonlinear parametric programming technique, the method solves the problem by imbedding it into a suitable one-parameter family of problems. The second method is to solve a nonlinear programming problem with equality and inequality constraints, by minimizing a square sum of nonlinear functions which is derived from the Kuhn-Tucker condition.

• Journal of applied mathematics & informatics
• /
• v.27 no.3_4
• /
• pp.567-579
• /
• 2009

Recently, Peng et al. proposed a primal-dual interior-point method with new search direction and self-regular proximity for LP. This new large-update method has the currently best theoretical performance with polynomial complexity of O($n^{\frac{q+1}{2q}}\;{\log}\;{\frac{n}{\varepsilon}}$). In this paper we use this search direction to propose a primal-dual interior-point method for convex quadratic programming (QP). We overcome the difficulty in analyzing the complexity of the primal-dual interior-point methods for convex quadratic programming, and obtain the same polynomial complexity of O($n^{\frac{q+1}{2q}}\;{\log}\;{\frac{n}{\varepsilon}}$) for convex quadratic programming.

• East Asian mathematical journal
• /
• v.28 no.3
• /
• pp.293-303
• /
• 2012

Sequential quadratic programming (SQP) has been one of the most important methods for solving nonlinear constrained optimization problems. Recently, filter method, proposed by Fletcher and Leyffer, has been extensively applied for its promising numerical results. In this paper, we present and study an active set SQP-filter algorithm for inequality constrained optimization. The active set technique reduces the size of quadratic programming (QP) subproblem. While by the filter method, there is no penalty parameter estimate. Moreover, Maratos effect can be overcome by filter technique. Global convergence property of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.