• Korea-Australia Rheology Journal
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• 제12권3_4호
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• pp.157-163
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• 2000

We develop a simple model which can describe and explain abnormal stress relaxation of ABS melt for which stress dose not exponentially decay. The relaxation behavior of ABS melt consists of two distinct relaxation modes. One is the relaxation of the matrix phase similar to the case of homopolymer melt. The other is manifested by the collection of butadiene rubber particles, named as the cluster, where the particles are connected through the interaction between grafted SAN and matrix SAN. The second mode of the relaxation is characterized by the relaxation time, which is a function of the average size and the microscopic state of the cluster. Experimental results reveal that it can be represented as the product of the average size of the clusters by a function of internal variable that represents the fraction of strained SAN chains inside the cluster.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.303-304
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• 2008

For the state estimation problem, the weighted least squares (WLS) method and the fast decoupled method are widely used at present. However, these algorithms can converge to local optimal solutions. Recently, modern heuristic optimization methods such as Particle Swarm Optimization (PSO) have been introduced to overcome the disadvantage of the classical optimization problem. However, heuristic optimization methods based on populations require a lengthy computing time to find an optimal solution. In this paper, we used PSO to search for the optimal solution of state estimation in power systems. To overcome the shortcoming of heuristic optimization methods, we proposed parallel processing of the PSO algorithm based on the PC cluster system. the proposed approach was tested with the IEEE-118 bus systems. From the simulation results, we found that the parallel PSO based on the PC cluster system can be applicable for power system state estimation.

• Journal of information and communication convergence engineering
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• 제3권2호
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• pp.84-89
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• 2005

Goal of this study is to implement 3-dimensional underwater appearance graphical display, fishery measured information display, sonar data representation and display, and 3-dimensional underwater appearance animation based on coefficient data of chaos behavior and fishing modeling of fishing gears from PC cluster system. In order to accomplish the goals of this study, it is essential to compose user interfacing and realistic description of image scenes in the towing-net fishery simulator, and techniques to describe sand cloud effects under water using particle systems are necessary. In this study, we implemented graphical representations and animations of the simulator by using OpenGL together with C routines.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.295-296
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• 2009

본 논문은 기존 PSO의 문제점으로 지적되는 Local minimum에의 고착을 해결하여 평균적인 성능을 향상시킬 수 있는 방법을 제안한다. 이를 위해 기존에는 하나의 Best Value만을 향해서 이동하는 것에서 벗어나, 각 Particle들을 Cluster로 나누고 각각의 Best Value를 중심으로 이동하며, 각 Cluster Leader들은 다른 Cluster Leader와 통신하며 순위에 따라 이동한다. 제안 방법으로 수렴속도와 Local minimum 회피에 대해 실험을 통해 비교 분석한다. 실험 결과로부터 제안 방법이 Local minimum 회피에서 성능 향상이 있음을 고찰하였다.

• 한국가시화정보학회:학술대회논문집
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• 한국가시화정보학회 2006년도 추계학술대회 논문집
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• pp.7-10
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• 2006

An experimental study has been conducted to quantitatively characterize the motion of neutrally buoyant particles in 2-dimensional Poiseuille flow through the micron-sized circular capillaries in the range of Re (Reynolds number) $\approx0.1\sim100$. $A{\mu}-PTV$ (Particle Tracking Velocimetry) system is adopted, which consists of a double-headed Nd:YAG laser, an epi-fluorescence microscope and a cooled CCD camera. Since high shear rate can be induced due to the scale effect even at low Re, it is shown that in micro scale neutrally buoyant particles in Poiseuille flow drift away from the wall and away from the center of the capillary. Consequently, particles accumulate at the equilibrium position of $0.52\sim0.64R$ with R being the radius of the capillary, which is analogous to that of tube flow in macro scale. There is a plateau in equilibrium position at small Re, while equilibrium position starts increasing at $Re\approx30$. The outermost edge of particle cluster is closer to the center of the capillary than that in previous studies due to low Re effect. The present study quantitatively presents characteristics of particle motion in circular capillaries. Furthermore, it is expected to give optimum factors for designing microfluidic systems that are to be used fur plasma separation from the blood.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (C)
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• pp.60-63
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• 2008

바이오칩을 이용하여 유전자를 분석하는데 이때 바이오 칩 분석 시스템을 이용한다. 바이오 칩은 유전자와 실험의 두 축으로 이루어져 있으며 바이오 칩 분석 시스템을 사용하여 바이오 칩에서 자료를 추출하고 필요한 정보를 얻기 위해 데이터를 분석하는 시스템이다. 데이터를 분석하는 기법 중 클러스터링을 사용하는데 유사한 유전자들을 찾아 내어 정해놓은 클러스터로 정의한다. 같은 클러스터 안에 있는 유전자들은 서로 비슷한 성질을 가지고 있기 때문에 사용자들은 이 바이오 칩 으로부터 나온 정보를 효율적이게 사용할 수 있다. 더욱 효율적으로 사용하기 위해 본 논문에서는 방대한 양의 데이터의 최적화에 효율적인 생태계 모방 알고리즘 Particle Swarm Optimization을 이용하여 데이터들을 클러스터링을 하여 분류하는 시스템을 기술하고 있다.

• Genomics & Informatics
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• 제9권2호
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• pp.89-91
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• 2011

DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3512-3528
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• 2016

A network with high mobility nodes or vehicles is vehicular ad hoc Network (VANET). For improvement in communication efficiency of VANET, many techniques have been proposed; one of these techniques is vehicular node clustering. Cluster nodes (CNs) and Cluster Heads (CHs) are elected or selected in the process of clustering. The longer the lifetime of clusters and the lesser the number of CHs attributes to efficient networking in VANETs. In this paper, a novel Clustering algorithm is proposed based on Ant Colony Optimization (ACO) for VANET named ACONET. This algorithm forms optimized clusters to offer robust communication for VANETs. For optimized clustering, parameters of transmission range, direction, speed of the nodes and load balance factor (LBF) are considered. The ACONET is compared empirically with state of the art methods, including Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) based clustering techniques. An extensive set of experiments is performed by varying the grid size of the network, the transmission range of nodes, and total number of nodes in network to evaluate the effectiveness of the algorithms in comparison. The results indicate that the ACONET has significantly outperformed the competitors.

• 한국대기환경학회지
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• 제13권1호
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• pp.51-63
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• 1997

Total suspended particulate matters in the ambient air were analyzed for eight chemical elements (Ca, Co, Cu, Fe, Mn, Pb, Si, and Zn) using an x-ray fluorescence spectrometry (XRF) at the Kyung Hee University - Suwon Campus during 1989 to 1994. To use these data as basis for source identification study, membership of each sample was selected to represent one of the well defined sample groups. The data sets consisting of 83 objects and 8 variables were initially separated into two groups, fine (d$_{p}$<3.3 ${\mu}{\textrm}{m}$) and coarse particle groups (d$_{p}$>3.3 ${\mu}{\textrm}{m}$). A hierarchical clustering method was examined to obtain possible member of homogeneous sample classes for each of the two groups by transforming raw data and by applying various distances. A disjoint principal component analysis was then used to define homogeneous sample classes after deleting outliers. Each of five homogeneous sample classes was determined for the fine and the coarse particle group, respectively. The data were properly classified via an application of logarithmic transformation and Euclidean distance concept. After determining homogeneous classes, correlation coefficients among eight chemical variables within all the homogeneous classes for calculated and meteorological variables (temperature. relative humidity, wind speed, wind direction, and precipitation) were examined as well to intensively interpret environmental factors influencing the characteristics of each class for each group. According to our analysis, we found that each class had its own distinct seasonal pattern that was affected most sensitively by wind direction.ion.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1385-1397
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• 2018

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to low prediction accuracy for wind speed. According to this situation, this paper constructs the short-time forecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate the regression relationships between the historical data and forecasting data of wind speed. In order to improve the forecast precision, historical data is clustered by cluster analysis so that the historical data whose changing trend is similar with the forecasting data can be filtered out. The filtered historical data is used as the training samples for SVR and the parameters would be optimized by particle swarm optimization (PSO). The forecasting model is tested by actual data and the forecast precision is more accurate than the industry standards. The results prove the feasibility and reliability of the model.