• Spatial Information Research
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• v.20 no.4
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• pp.17-27
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• 2012

This study was performed to evaluate the spatial distribution of heavy metals using principal component analysis and Ordinary Kriging technique in the Gangwon Mine site. In the soils from the sub soil, the contents of Zn and Ni in the PC1 were gradually dispersed from south to north direction, while the components of Cd and Hg in the PC2 showed an increase significantly from middle-south area in the Gangwon Mine site. According to the cluster analysis, pollutant metals of As and Cu were presented a strong spatial autocorrelation structure in cluster D. The concentration of As was 0.83mg/kg and shown to increase from the south to north direction. The spatial distribution maps of the soil components using geostatistical method might be important in future soil remediation studies and help decision-makers assess the potential health risk affects of the abandoned mining sites.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.219-227
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• 2014

Ethernet, ATM, and CAN are wide-utilized communication protocols for information transfer by internet. Many researches about Network Time-delay have been based on network modeling. But almost of them have not shown an optimal solution in various communication environments. So, asynchronous sample system modeling based internet is needed to be robust in various network environments. Also as closed loop system in internet has a different operational characteristics and noise characteristics comparing with conventional control system, new robust control method is needed in instruments which demand to be safe and precise for internet environments. In order to achieve the safe and precise real-time control in remote plant, this paper is aimed to analysis the transfer characteristics and time-delay of control system in cluster web server.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1A
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• pp.31-37
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• 2012

The phase distribution in concrete materials strongly affects its material properties. It is important to identify the spatial distribution of void in concrete because the void in concrete materials affects mechanical behavior and permeability significantly. Therefore, a proper method to describe the void distribution of a material is needed. In this research, CT(computed tomography) is used to examine and to quantify the void distribution of porous concrete specimens. 3D concrete digital specimens are created by subsequent stacking of 2D cross-sectional images from CT. Then, probability distribution functions such as two-point correlation, lineal-path and two-point cluster functions are used for void distribution characterization. It is confirmed that probability distribution functions obtained from CT images are effective in characterizing void distributions including the anisotropy and percolation.

• Journal of Society of Preventive Korean Medicine
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• v.17 no.3
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• pp.177-185
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• 2013

Objective : Eucommiae Cortex is bark of Eucommia ulmoides Oliver, a deciduous tree native to China. Today, teas or herbal drugs made from E. ulmoides leaves are widely consumed as a healthy food especially in Eastern Asia including Japan, China and Korea. This study was aimed to verify the extraction efficiency of bioactive compounds from Eucommiae Cortex depending on characteristics of decoction water. Method : Six types of decoction water with various origin were prepared and the contents of minerals in water were analyzed by ICP-AES and ICP-MS. The contents of extracted bioactive compounds were analyzed by HPLC and the relationship between mineral contents and extracted bioactive compounds in the decoction water were analysed by multiple factor analysis. The decoction waters could be classified in three groups by hierarchical cluster analysis. Result : Extracted amounts of compounds in Eucommiae Cortex showed a positive relationship with Na, Si, K concentration in decoction water, while a negative relationship with Ca, Mg concentration. Conclusion : The study proved that the minerals in water influenced the extraction efficiency of bioactive compounds from Eucommiae Cortex.

• Journal of Forest and Environmental Science
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• v.28 no.4
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• pp.199-204
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• 2012

This study was conducted to estimate climax index by eco-morphology for major 36 tree and sub-tree species in natural deciduous forests so as to interpret seral position of each species in the forest community. Fourteen eco-morphological characters which were considered to be associated with successional gradient in the forest were selected for the study. Four levels per character for each species were given on a standardized scale of increasing climax, and the index was computed by the proportion of the sum of total scores, expressed by percent values. With calculated mean value of 54.8 for all indices, Carpinus cordata had the highest index value of 90.5, and Populus davidiana recorded the lowest of 13.2. The most climax group, greater than 70 of the index, contained only 8 species, intermediate group, between 41 to 70 of the index, had 23 species, and the most pioneer group, less than 40 of the index comprised 5 species. The result has noticed that the large number of species would take advantage of most diverse resource and niche in the intermediate stage of the sere in the forest. By cluster analysis all 36 species were subjected to be classified into several species groups which had common similar eco-morphological characteristics. The indices were additionally plotted on the two dimensional graph to recognize the positions related to the light absorption factor and reproduction factor. The climax index of tree and sub-tree species developed by this study could be applied to understand the present status of successional stage on the basis of species composition by the method of summing up the indices. And comparison of forest successional stage among various forest communities could be done by summing up the climax indices of composed species in each community. However, this kind of applied methodology should be limited to the forest of similar species composition and site condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1398-1417
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• 2013

A method is proposed to reduce excess resources from a virtual machine(VM) while avoiding subsequent migrations for a computer cluster that provides cloud service. The proposed scheme cuts down on the resources of a VM based on the probability that migration may occur after a reduction. First, it finds a VM that can be scaled down by analyzing the history of the resource usage. Then, the migration probability is calculated as a function of the VM resource usage trend and the trend error. Finally, the amount of resources needed to eliminate from an underutilized VM is determined such that the migration probability after the resource reduction is less than or equal to an acceptable migration probability. The acceptable migration probability, to be set by the cloud service provider, is a criterion to assign a weight to the resource reduction either to prevent VM migrations or to enhance VM utilization. The results of simulation show that the proposed scheme lowers migration frequency by 31.6~60.8% depending on the consistency of resource demand while losing VM utilization by 9.1~21.5% compared to other known approaches, such as the static and the prediction-based methods. It is also verified that the proposed scheme extends the elapsed time before the first occurrence of migration after resource reduction 1.1~2.3-fold. In addition, changes in migration frequency and VM utilization are analyzed with varying acceptable migration probabilities and the consistency of resource demand patterns. It is expected that the analysis results can help service providers choose a right value of the acceptable migration probability under various environments having different migration costs and operational costs.

• Journal of Korean Clinical Nursing Research
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• v.18 no.3
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• pp.354-367
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• 2012

Purpose: This study was done to verify validity and reliability of a neonatal patient classification system (NeoPCS-1). Methods: An expert group of 8 nurse managers and 40 nurses from 8 Neonatal Intensive Care Units in Korea, verified content validity of the measurement using item level content validity index (I-CVI). The participants were nurses caring for 469 neonates. Data were collected from November 11 to December 14, 2011 and analyzed using descriptive statistics, ANOVA, intraclass correlation coefficient, and K-cluster analysis with PASW 18.0 program. Results: Nursing domains and activities included 8 items with 91 activities. I-CVI was above .80 in all areas. Interrater reliability was significant between two raters (r=.95, p<.001). Classification scores for participants according to patient types and nurses' intuition were significantly higher for the following patients; gestational age (${\leq}29$ weeks), body weight (<1,000 gm), and transfer from hospital. Six groups were classified using cluster analysis method based on nursing needs. Patient classification scores were significantly different for the groups. Conclusion: These results show adequate validity and reliability for the NeoPCS-1 based on nursing needs. Study is needed to refine the measurement and develop index scores to estimate number of nurses needed for adequate neonatal care.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.113-124
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• 2015

Unlike structured data which are gathered and saved in a predefined structure, unstructured text data which are mostly written in natural language have larger applications recently due to the emergence of web 2.0. Text mining is one of the most important big data analysis techniques that extracts meaningful information in the text because it has not only increased in the amount of text data but also human being's emotion is expressed directly. In this study, we used R program, an open source software for statistical analysis, and studied algorithm implementation to conduct analyses (such as Frequency Analysis, Cluster Analysis, Word Cloud, Social Network Analysis). Especially, to focus on our research scope, we used keyword extract method based on a Data Dictionary. By applying in real cases, we could find that R is very useful as a statistical analysis software working on variety of OS and with other languages interface.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.10
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• pp.947-952
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• 2006

It has been confirmed that the inner defect of insulator and the perfect diagnosis for aging are closely related to safe electric power transmission system and that the detection of accident and diagnosis technique turn out to be very important issues. But perfect diagnosis is difficult because discharge pattern is irregular. Thus, we investigated discharge pattern using the new distribution statistical models with cross-inked polyethylene(XLPE) specimens. Voltage was applied to power frequency by step method, and calibration of discharge was set to 50 pC. After the voltage was applied, it measured the discharge occurring during 10s. We investigated discharge pattern using the K-means analysis and Weibull function. We also investigated variation of centroid and shape parameter due to variation of voltage. As a result of analyzing K-means, it was confirmed that cluster including many object numbers was formed by the presence of void. And result of Weibull distribution, it was confirmed that shape parameter of discharge varied from 1.28 to 1.62 in no void specimens, and that shape parameter of discharge number varied from 1.28 to 1.62. In the void, shape parameter of discharge varied from 5.66 to 6.43, and shape parameter of discharge number varied from 5.05 to 5.08.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.1
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• pp.35-50
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• 2004

This study evaluated the applicability of the static hierarchic clustering model to clustering query results in OPAC. Two clustering methods(Between Average Linkage(BAL) and Complete Linkage(CL)) and two similarity coefficients(Dice and Jaccard) were tested on the query results retrieved from 16 title-based keyword searchings. The precision of optimal dusters was improved more than 100% compared with title-word searching. There was no difference between similarity coefficients but clustering methods in optimal cluster effectiveness. CL method is better in precision ratio but BAL is better in recall ratio at the optimal top-level and bottom-level clusters. However the differences are not significant except higher recall ratio of BAL at the top-level duster. Small number of clusters and long chain of hierarchy for optimal cluster resulted from BAL could not be desirable and efficient.