• Journal of the Chungcheong Mathematical Society
• /
• v.22 no.2
• /
• pp.141-148
• /
• 2009

We consider various algorithms calculating best onesided simultaneous approximations. We assume that X is a compact subset of $\mathbb{R}^{m}$ satisfying $X=\overline{intX}$, S is an n-dimensional subspace of C(X), and $\mu$ is any 'admissible' measure on X. For any l-tuple $f_1,\;{\cdots},\;f_{\ell}$ in C(X), we present various ideas for best approximation to F from S(F). The problem of best (both one and two-sided) approximation is a linear programming problem.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.269-270
• /
• 2012

• Journal of the Korean Statistical Society
• /
• v.1 no.1
• /
• pp.18-24
• /
• 1973

Study on convexity has been improved in many statistical fields, such as linear programming, stochastic inverntory problems and decision theory. In proof of main theorem in Section 3, M. Loeve already proved this theorem with the $r$-th absolute moments on page 160 in [1]. Main consideration is given to prove this theorem using convex theorems with the generalized $t$-th mean when some convex properties hold on a real linear vector space $R_N$, which satisfies all properties of finite dimensional Hilbert space. Throughout this paper $\b{x}_j, \b{y}_j$ where $j = 1,2,......,k,.....,N$, denotes the vectors on $R_N$, and $C_N$ also denotes a subspace of $R_N$.

• Communications of the Korean Mathematical Society
• /
• v.9 no.3
• /
• pp.753-765
• /
• 1994

The linearly constrained quadratic programming(QP) considered is : $$ min f(x) = c^T x + \frac{1}{2}x^T Hx $$ $$ (1) subject to A^T x \geq b,$$ where $c,x \in R^n, b \in R^m, H \in R^{n \times n)}$, symmetric, and $A \in R^{n \times n}$. If there are bounds on x, these are included in the matrix $A^T$. The Hessian matrix H may be positive definite or negative semi-difinite. For large problems H and the constraint matrix A are assumed to be sparse.

• Korean Journal of Computational Design and Engineering
• /
• v.12 no.3
• /
• pp.220-232
• /
• 2007

Current geometric modeling and analysis are commonly based on B-Rep modeling and a finite elements method respectively. Furthermore, it is difficult to represent an object whose material property is heterogeneous using the B-Rep method because the B-Rep is basically used for homogeneous models. In addition, meshes are required to analyze a property of a model when the finite elements method is applied. However, the process of generating meshes from B-Rep is cumbersome and sometimes difficult especially when the model is deformed as time goes by because the topology of deforming meshes are changed. To overcome those problems in modeling and analysis including homogeneous and heterogeneous materials, we suggest a unified modeling and analysis method based on implicit representation of the model using R-function which is suggested by Rvachev. For implicit modeling of an object a distance field is approximated and blended for a complex object. Using the implicit function mesh-free analysis is possible where meshes are not necessary. Generally mesh-free analysis requires heavy computational cost compared to a finite elements method. To improve the computing time of function evaluation, we utilize GPU programming. Finally, we give an example of a simple pipe design problem and show modeling and analysis process using our unified modeling and analysis method.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.1
• /
• pp.103-108
• /
• 2012

In this paper, the optimal design of a spring-type gravity compensation system for an articulated robot is presented. Sequential quadratic programming (SQP) is adopted to resolve various nonlinear constraints in spring design such as stress, buckling, and fatigue constraints, and to reduce computation time. In addition, continuous relaxation method is used to explain the integer-valued design variables. The simulation results show that the gravity compensation system designed by proposed method improves the performance effectively without additional weight gain in the main workspace.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.34 no.2
• /
• pp.77-90
• /
• 2009

Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

• International journal of advanced smart convergence
• /
• v.6 no.2
• /
• pp.24-33
• /
• 2017

Since 'teaching coding' or 'programming' classes for computational thinking (CT) education in K-12 are renowned around the world, a pre-service teachers' readiness for integrating CT into their teaching subjects is important due to the fact that CT is considered to be another 'R' from algoRitm for 21st century literacy, in addition to the traditional 3R (Reading, Writhing, and Arithmetic) [2] and CT roles to other disciplines. With this rationale, we designed a guided instruction based CT course for pre-service teachers. We show the effectiveness of the program with respect to the teachers' attitude toward combining CT into their teaching subjects, and mindset changes of learning computing connected with the career development of the teacher themselves. The research focused on the instructional methodology of teaching programing for non-Computer Science Education (CSE) majors who are not familiar with computer science for alleviating the cognitive load of first exposure to programming course under the CT concepts.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.22 no.4
• /
• pp.567-574
• /
• 2019

Traditional project progress method(PPM) has been used for Korean defense research and development project management for the last 20 years. However, it is difficult to intuitively understand the performance in terms of the project schedule, because the PPM does not provide the function of managing and forecasting project schedule. Therefore, this paper proposes new schedule managing and forecasting function for the PPM using earned schedule management concept. We verify the effectiveness of the proposed functions through several defense projects and prove that it is possible to reinforce the schedule management function of the PPM.

• Journal of information and communication convergence engineering
• /
• v.20 no.4
• /
• pp.265-272
• /
• 2022

The most effective method to improve information system capabilities is to enable instant access to several relational database sources and transform data with a logical structure into multiple target relational databases. There are numerous data transformation tools available; however, they typically contain fixed procedures that cannot be changed by the user, making it impossible to fulfill the near-real-time data transformation requirements. Furthermore, some tools cannot build object references or alter attribute constraints. There are various situations in which tool changes in data type cause conflicts and difficulties with data quality while transforming between the two systems. The R-programming language was extensively used throughout this study, and several different relational database structures were utilized to complete the proposed study. Experiments showed that the developed study can improve the performance of information systems by interacting with and exchanging data with various relational databases. The study addresses data quality issues, particularly the completeness and integrity dimensions of the data transformation processes.