• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.575-587
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• 2004

In this paper. a new Fast Expectation-Maximization algorithm(FEM) is proposed. Firstly the K-means algorithm is modified to reduce the number of iterations for finding the initial values that are used as the initial values in EM process. Conventionally the Initial values in K-means clustering are chosen randomly. which sometimes forces the process of clustering converge to some undesired center points. Uniform partitioning method is added to the conventional K-means to extract the proper initial points for each clusters. Secondly the effect of posterior probability is emphasized such that the application of Maximum Likelihood Posterior(MLP) yields fast convergence. The proposed FEM strengthens the characteristics of conventional EM by reinforcing the speed of convergence. The superiority of FEM is demonstrated in experimental results by presenting the improvement results of EM and accelerating the speed of convergence in parameter estimation procedures.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.3
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• pp.331-339
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• 2008

The genetic structure and diversity of 15 Chinese indigenous chicken breeds was investigated using 29 microsatellite markers. The total number of birds examined was 542, on average 36 birds per breed. A total of 277 alleles (mean number 9.55 alleles per locus, ranging from 2 to 25) was observed. All populations showed high levels of heterozygosity with the lowest estimate of 0.440 for the Gushi chickens, and the highest one of 0.644 observed for Wannan Three-yellow chickens. The global heterozygote deficit across all populations (FIT) amounted to 0.180 (p<0.001). About 16% of the total genetic variability originated from differences between breeds, with all loci contributing significantly to this differentiation. An unrooted consensus tree was constructed using the Neighbour-Joining method and pair-wise distances based on marker estimated kinships. Two main groups were found. The heavy-body type populations grouped together in one cluster while the light-body type populations formed the second cluster. The STRUCTURE software was used to assess genetic clustering of these chicken breeds. Similar to the phylogenetic analysis, the heavy-body type and light-body type populations separated first. Clustering analysis provided an accurate representation of the current genetic relations among the breeds. Remarkably similar breed rankings were obtained with all methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.29-39
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• 1992

We investigate a systematic design procedure of automatic rule generation of fuzzy logic based controllers for highly nonlinear dynamic systems such as an engine dynamic modle. By "automatic rule generation" we mean autonomous clustering or collection of such meaningful transitional relations from one conditional subspace to another. During the design procedure, we also consider optimaly control strategies such as minimum squared error, near minimum time, minimum energy or combined performance critiera. Fuzzy feedback control systems designed by our method have the properties of closed-loop stability, robustness under parameter variabitions, and a certain degree of optimality. Most of all, the main advantage of the proposed approach is that reliability can be potentially increased even if a large grain of uncertainty is involved within the control system under consideration. A numerical example is shown in which we apply our strategic fuzzy controller dwsign to a highly nonlinear model of engine idling speed control.d control.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.202-212
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• 2012

Due to the deterioration of water supply network and the deficiency of raw water, the water utility of local governments have performed various projects to improve their revenue water ratio. However, it is very difficult to estimate the cost for maintaining the revenue water ratio at higher level after completing the project, because local governments have different conditions affecting the operating and maintenance cost of water supply network. The purpose of this study is to present a procedure to estimate the operating and maintenance cost required to maintain the target revenue water ratio of the water supply network. For this purpose, we estimated the cost used only for operation and maintenance of water supply network of 164 local governments with the aid of K-Mean Clustering Analysis and the data from 40 representative local governments. Then, the regression analysis was performed to find relationship between revenue water ratio and the operating and maintenance cost with two different data sets generated by two classification methods; the first method classifies the local governments by means of k-means clustering, and the other classifies the local governments according to the index standardized by the operating and maintenance cost per unit length of water mains per revenue water ratio. The results shows that the method based on the index standardized by the cost and revenue water ratio of each government produces more reliable results for finding regression equations between revenue water ratio and the operating and maintenance cost only for water supply network. The estimated regression equations for each group can be used to estimate the cost required to keep the target revenue water ratio of the local government.

• Molecular & Cellular Toxicology
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• v.2 no.2
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• pp.126-133
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• 2006

Thioacetamide (TA) is well known hepatotoxic and hepatocarcinogenic agent. TA also diminishes the contents of hepatic cytochrome P450 and inhibits the enzyme activity of the hepatic mixed function oxidases. TA metabolite, thioacetamide-s-oxide, is further transformed into a still unknown highly reactive metabolite that binds to macromolecules. In this study, we focused on TA-induced gene expression at hepatotoxic dose. Mice were exposed to two levels (5 mg/kg or 50 mg/kg i.p.) of TA, sampled at 6 or 24 h, and hepatic gene expression levels were determined to evaluate dose and time dependent changes. We evaluated hepatotoxicity by serum AST and ALT level and histopathological observation. Mean serum activities of the liver leakage enzymes, AST and ALT, were slightly increased compare to control. H & E and PAS evaluation of stained liver sections revealed TA-associated histopathological finding in mice. Centrilobular eosinophilic degeneration was observed at high dose-treated mice group. Hepatic gene expression was analyzed by QT clustering. Clustering of high dose-treated samples with TA-suggests that gene expressional changes could be associated from toxicity as measured by traditional biomarkers in this acute study.

• Journal of the Korean Electrochemical Society
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• v.14 no.1
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• pp.9-15
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• 2011

The composite membranes comprising of sulfonated polymers as matrix and ionic liquids as ion-conducting medium in replacement of water are studied to investigate the effect of annealing of the sulfonated polymers. The polymeric membranes are prepared on recast Nafion containing the ionic liquid, 1-ethyl-3-methylimidazolium tetrafluoroborate ($EMIBF_4$). The composite membranes are characterized by thermogravitational analyses, ion conductivity and small-angle X-ray scattering. The composite membranes annealed at $190^{\circ}C$ for 2 h after the fixed drying step showed better ionic conductivity, but no significant increase in thermal stability. The mean Bragg distance between the ionic clusters, which is reflected in the position of the ionomer peak (small-angle scattering maximum), is larger in the annealed composite membranes containing $EMIBF_4$ than the non-annealed ones. It might have been explained to be due to the different level of ion-clustering ability of the hydrophilic parts (i.e., sulfonic acid groups) in the non- and annealed polymer matrix. In addition, the ionic conductivity of the membranes shows higher for the annealed composite membranes containing $EMIBF_4$. It can be concluded that the annealing of the composite membranes containing ionic liquids due to an increase in ion-clustering ability is able to bring about the enhancement of ionic conductivity suitable for potential use in proton exchange membrane fuel cells (PEMFCs) at medium temperatures ($150-200^{\circ}C$) in the absence of external humidification.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2833-2850
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• 2014

This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover's distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.

• Plant Resources
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• v.4 no.3
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• pp.121-129
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• 2001

Intraspecific genetic diversity of sixteen accessions of Mogolian Alliums including fifteen species was investigated using randomly amplified polymorphic DNA (RAPD) analysis. Twenty three out of forty primers revealed scorable polymorphism. A total of 440 RAPD markers were generated on the 16 accessions of Mongolian Alliums. Among 440 RAPDs assayed, 439 were polymorphic with a mean polymorphic rate of 99.7%. Unweighted pair-group method using an arithmetic average (UPGMA) cluster analysis using RAPD data separated the 16 Allium accessions into two broad groups at similarity index 0.70. The clustering of the species was closely related with previous classification between A. altaicum and A. fistulosum. In addition, a high genetic similarity was showed between A. cepa and A. tagar.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.364-366
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• 2021

본 논문은 비전 기술을 기반으로 RHS 칼라차트를 이용하여 작물의 색채를 측정하는 특성조사기준에 관한 연구를 수행하였다. 다양한 색상을 가진 작물의 색채를 측정하기 위해 시료 채취 후 표준광원 촬영장치 광원 6500K 환경하에 촬영한 영상을 기반으로 분석 위치를 관심영역 선정 후, k-mean clustering을 활용한 세그먼테이션 방법을 통해 대표 RGB 색상을 획득한다. 획득한 RGB 색상과 RHS 칼라차트의 RGB 색상을 유클리디언 거리를 이용하여 최소화하는 RHS 칼라차트 정보를 추정하였다. 7가지 작물 시료에 대해 작물 형질 분석 전문가들이 측정한 결과와 비교 시 전체 평균 △E 5.013의 오차를 결과로 도출하였다.