• Bulletin of the Korean Mathematical Society
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• v.26 no.2
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• pp.127-134
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• 1989

This paper proposes a deformation method for solving practical nonlinear programming problems. Utilizing the nonlinear parametric programming technique with Quasi-Newton method [6,7], the method solves the problem by imbedding it into a suitable one-parameter family of problems. The approach discussed in this paper was originally developed with the aim of solving a system of structural optimization problems with frequently appears in various kind of engineering design. It is assumed that we have to solve more than one structural problem of the same type. It an optimal solution of one of these problems is available, then the optimal solutions of thel other problems can be easily obtained by using this known problem and its optimal solution as the initial problem of our parametric method. The method of nonlinear programming does not generally converge to the optimal solution from an arbitrary starting point if the initial estimate is not sufficiently close to the solution. On the other hand, the deformation method described in this paper is advantageous in that it is likely to obtain the optimal solution every if the initial point is not necessarily in a small neighborhood of the solution. the Jacobian matrix of the iteration formula has the special structural features [2, 3]. Sectioon 2 describes nonlinear parametric programming problem imbeded into a one-parameter family of problems. In Section 3 the iteration formulas for one-parameter are developed. Section 4 discusses parametric approach for Quasi-Newton method and gives algorithm for finding the optimal solution.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1009-1024
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• 2018

With the increased use of LiDAR (Light Detection and Ranging) that can obtain over millions of point dataset, methodologies for efficient search and dimensionality reduction for the point cloud became a crucial technique. The existing octree-based "parametric algorithm" has proved its efficiency and contributed as a part of PCL (Point Cloud Library). However, the implementation of the algorithm on GPU (Graphics Processing Unit) is considered very difficult because of structural constraints of the octree implemented in PCL. In this paper, we present a method for the parametric algorithm on GPU environment and implement a projection of the queried points on four directions with an improved noise reduction.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.109-118
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• 2007

A parametric boundary equation is established for the principal period-2 bulb in the cubic Mandelbrot set. Using its geometry, an efficient escape-time algorithm which reduces the construction time for the period-2 bulbs in the cubic Mandelbrot set is introduced and the implementation graphic results display the fascinating fractal beauty.

• Transactions of Materials Processing
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• v.3 no.4
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• pp.468-481
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• 1994

Mathematical description of arbitrarily-shaped tool surface are introduced by parametric patch approaches along with the related contact search algorithm. In order to maintain the advantages of membrane elements and to incoporate the bending effect, a BEAM(Bending Energy Augmented Membrane) element is proposed. Computation are carried out for some complex axisymmetric multi-stage deep drawing to verify the validity and the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.1
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• pp.159-166
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• 1987

A new family of sinusoidal orthogoal trnasform is introduced. For a derivation, a parametric sinusoidal matrix whose transform might be implemented by a suitable FFT algorithm is modeled basically on the analogy of well-known sinusoidal transform such as DCT,SCT, etc., and its orthogonality condition is calculated. The parameters satisfying orthogonality condition are determined, in a sense, by particular solution after trial and error. However more than then transform matrices not yet known are obtained. It is also shown that these transforms can be computed by a DFT. of an image.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.629-632
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• 1986

Both combinatorial and parametric optimization are used in computer-aided design(CAD). The most commonly occuring parametric optimization problems in engineering design such as design of control systems, design of electric circuits are usually expressed either as differentiable or as nondifferentiable semi-infinite programming(SIP) problems. In this paper we express algorithms for a class of computer-aided design problems arising in control systems.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1128-1131
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• 1996

The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.

• Advances in Computational Design
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• v.2 no.3
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• pp.241-256
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• 2017

This paper introduces the process for Multi-objective Optimization Framework (MOF) which mediates multiple conflicting design targets. Even though the extensive researches have shown the benefits of optimization in engineering and design disciplines, most optimizations have been limited to the performance-related targets or the single-objective optimization which seek optimum solution within one design parameter. In design practice, however, designers should consider the multiple parameters whose resultant purposes are conflicting. The MOF is a BIM-integrated and simulation-based parametric workflow capable of optimizing the configuration of building components by using performance and non-performance driven measure to satisfy requirements including build programs, climate-based daylighting, occupant's experience, construction cost and etc. The MOF will generate, evaluate all different possible configurations within the predefined each parameter, present the most optimized set of solution, and then feed BIM environment to minimize data loss across software platform. This paper illustrates how Multi-objective optimization methodology can be utilized in design practice by integrating advanced simulation, optimization algorithm and BIM.

• Phonetics and Speech Sciences
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• v.1 no.3
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• pp.155-163
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• 2009

This paper introduces an automatic voice classification system for the diagnosis of individual constitution based on Sasang Constitutional Medicine (SCM) in Traditional Korean Medicine (TKM). For the developing of this algorithm, we used the voices of 473 speakers and extracted a total of 144 speech features from the speech data consisting of five sustained vowels and one sentence. The classification system, based on a rule-based algorithm that is derived from a non parametric statistical method, presents binary negative decisions. In conclusion, 55.7% of the speech data were diagnosed by this system, of which 72.8% were correct negative decisions.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.258-263
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• 2011

We study on a generalization of the two dimensional linear programming knapsack problem with the extended GUB constraint, which was presented in paper Won(2001). We identify some new parametric properties of the generalized problem and derive a solution algorithm based on the identified parametric properties. The solution algorithm has a worst case time complexity of order O($n^2logn$), where n is the total number of variables. We illustrate a numerical example.