• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.262-267
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• 2008

The focus of this paper is on devising an efficient clustering task for arbitrary color data. In order to tackle this problem, the inherent uncertainty and vagueness of color are represented by a fuzzy color model. By taking a fuzzy approach to color representation, the proposed model makes a soft decision for the vague regions between neighboring colors. A definition on a three-dimensional fuzzy color ball is introduced, and the degree of membership of color is computed by employing a distance measure between a fuzzy color and color data. With the fuzzy color model, a novel fuzzy clustering algorithm for efficient partition of color data is developed.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.298-309
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• 2004

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.2
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• pp.118-124
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• 2004

The objective of the paper is to demonstrate the noise reduction characteristics of an air-gap resonator, which is composed of an air gap and a partition sheet. By means of installing the air-gap resonator in an enclosed cavity, acoustic resonance can be effectively suppressed using a small space. In particular, it is revealed from a simple, one-dimensional model that the air-gap resonator serves as the Helmholtz resonator that generally absorbs acoustic resonance energy at its resonance frequency. As a result, the air-8ap resonator also has a resonance frequency, which can be predicted with a simple frequency equation derived in the paper. Finally, verification experiments show that the air-gap resonator can be effectively designed by predicting a reasonable gap thickness using the simple frequency-equation.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.109-121
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• 1992

In this paper, we address a layout design problem for determining a K-class-based dedicated storage layout in an automated storage retrieval system. K-class-based dedicated storage employs K zones in which lots from a class of products are stored randomly. Zones form a partition of storage locations. Our objective function is to minimize the expected single command travel time, which is expressed as a set function of space requirements for zones, average demand rates from classes, and one-way travel times from the pickup/deposit station to locations. We construct a heuristic algorithm based on analytical results and a local search method, the methodology deveolped can be used with easily-available data by warehouse planners to improve the throughput capacity of a conventional warehouse as well as an AS/RS.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1484-1486
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• 2015

그리드 기반 공간 분할 방식에서 셀 크기는 성능을 좌우하는 핵심 요소이다. 본 논문에서는 각 셀에서 충돌 검사가 일어나는 빈도에 따라 동적으로 셀의 크기를 제어하는 방식을 제안한다. 각 셀의 충돌 검사 빈도와 인접한 셀과 병합했을 때의 충돌 검사 빈도를 비교하여, 이 차이가 임의의 값보다 작을 때 셀들을 병합하여 하나의 큰 셀로 만든다. 단, 병합할 셀이 여러 개일 경우 충돌 검사 빈도가 작은 셀부터 차례로 병합한다. 이 방식을 통하여 셀의 수 및 업데이트 비용을 줄일 수 있으며 이는 공간상의 객체가 규칙적인 움직임을 보일 때 가장 효율적임을 확인했다.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.726-734
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• 2004

This paper presents a facial animation method that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically Our system creates the facial expression space from about 2400 captured facial frames. To represent the state of each expression, we use the distance matrix that represents the distance between pairs of feature points on the face. The shortest trajectories are found by dynamic programming. The space of facial expressions is multidimensional. To navigate this space, we visualize the space of expressions in 2D space by using the multidimensional scaling(MDS). But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 10 clusters from the space of 2400 facial expressions. Every tine the level increases, the system doubles the number of clusters. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. The user selects new key frames along the navigation path of the previous level. At the maximum level, the user completes key frame specification. We let animators use the system to create example animations, and evaluate the system based on the results.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1011-1020
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• 2004

A lot of work has been done to improve the I/O performance of such a system that store and manage a massive amount of data by distributing them across multiple disks and access them in parallel. Most of the previous work has focused on an efficient mapping from a grid ceil, which is determined bY the interval number of each dimension, to a disk number on the assumption that each dimension is split into disjoint intervals such that entire data space is GRID-like partitioned. However, they have ignored the effects of a GRID partitioning scheme on declustering performance. In this paper, we enhance the performance of mapping function based declustering algorithms by applying a good GRID par-titioning method. For this, we propose an estimation model to count the number of grid cells intersected by a range query and apply a GRID partitioning scheme which minimizes query result size among the possible schemes. While it is common to do binary partition for high-dimensional data, we choose less number of dimensions than needed for binary partition and split several times along that dimensions so that we can reduce the number of grid cells touched by a query. Several experimental results show that the proposed estimation model gives accuracy within 0.5% error ratio regardless of query size and dimension. We can also improve the performance of declustering algorithm based on mapping function, called Kronecker Sequence, which has been known to be the best among the mapping functions for high-dimensional data, up to 23 times by applying an efficient GRID partitioning scheme.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.532-540
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• 2019

PET microfibers with various diameters (0.5, 0.2, 0.06, and 0.01 dpf) were dyed with a dispersed dye (C.I. Disperse Blue 56) at various temperatures. The dyeing process was conducted under infinite dyebath conditions at constant temperatures. The effects of the dyeing temperature and diameter on the partition coefficient, affinity, and diffusion coefficient of disperse dyes were studied. The curve of isotherms was fitted well to Nernst-type model in a large range of initial dye concentrations. At the same temperature, the partition coefficient and affinity decreased with increasing sample diameter due to the increase in surface area. At all deniers, the partition coefficient and affinity decreased with increasing temperature because the dyeing process is an exothermic reaction. In addition, the decrease in radius of the sample gives rise to a decrease in the heat of dyeing. The fine diameter of the sample resulted in an increased surface area but decreased space between the microfibers. Consequently, decreasing the diameter of the microfibers leads to a decrease in the diffusion coefficient. At the same diameter, the diffusion coefficient increased with increasing temperature because of rapid dye movement and the large free volume of the sample inside. In addition, thermal dependence of the diffusion coefficient increased when the diameter of the sample increased.

• Journal of the Korean Mathematical Society
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• v.53 no.3
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• pp.709-723
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• 2016

Let C[0, t] denote a generalized Wiener space, the space of real-valued continuous functions on the interval [0, t] and define a random vector $Z_n:C[0,t]{\rightarrow}{\mathbb{R}}^n$ by $Zn(x)=(\int_{0}^{t_1}h(s)dx(s),{\cdots},\int_{0}^{t_n}h(s)dx(s))$, where 0 < $t_1$ < ${\cdots}$ < $t_n$ < t is a partition of [0, t] and $h{\in}L_2[0,t]$ with $h{\neq}0$ a.e. In this paper we will introduce a simple formula for a generalized conditional Wiener integral on C[0, t] with the conditioning function $Z_n$ and then evaluate the generalized analytic conditional Wiener and Feynman integrals of the cylinder function $F(x)=f(\int_{0}^{t}e(s)dx(s))$ for $x{\in}C[0,t]$, where $f{\in}L_p(\mathbb{R})(1{\leq}p{\leq}{\infty})$ and e is a unit element in $L_2[0,t]$. Finally we express the generalized analytic conditional Feynman integral of F as two kinds of limits of non-conditional generalized Wiener integrals of polygonal functions and of cylinder functions using a change of scale transformation for which a normal density is the kernel. The choice of a complete orthonormal subset of $L_2[0,t]$ used in the transformation is independent of e and the conditioning function $Z_n$ does not contain the present positions of the generalized Wiener paths.