• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.103-114
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• 2012

The purpose of this research is classifying stream into different types depending on various factor from the perspective of stream corridor restoration and using it as basic data, which are used to consider efficient management and planning for the healthy stream according to the characteristic by types. In this study, 130 points of location of the Nakdong river basin which consist of various geographic factors have been chosen and hierarchical cluster analysis has been carried out in these points by using biological and physiochemical factors whose health can be considered to be predicted and evaluated. As a result of cluster analysis, there were three divided types. Type A whose biology and water quality are considered the best was the highest in forest area percentage so that it was classified into natural stream. Type B was classified into a rural region stream with a mixture of urban and agricultural region. Type C, with the most damaged water quality and biology health had the most urban region surface area and was named as urban region stream. Moreover, an overall restoration strategy according to characteristic by stream types was set. By the results of correlation analysis on factors, water quality showed a high correlation with biological properties and was affected by surrounding land usage. In evaluation of streams, it proves the need to consider not only other habitat's geographical and biological factors but also the water quality and land usage factors. There needs to be further research on stream ecosystem functionality factors and structural aspects by using a more objective and total evaluation result in selecting additional index and various other specific classification methods by stream types and its restoration strategies.

• The korean journal of orthodontics
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• v.33 no.3 s.98
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• pp.141-150
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• 2003

The purposes of this study were to classify the anteroposterior and vertical skeletal pattern of normal occlusion samples into specific types with factor and hierarchical cluster analysis, and to evaluate the range and limit of skeletal relationships that permit the establishment of normal occlusion via natural dentoalveolar compensation. Lateral cephalograms of 294 normal occlusion samples were measured, as selected from 15,836 persons through a community dental health survey who cooperated in record taking. Using a factor analysis, two factors representing anteroposterior and vertical skeletal relationships were extracted from 18 skeletal measurements. Then cluster analysis classified the skeletal patterns into nine types. The means and the standard deviations of 8 anteroposterior skeletal measurements and 10 vertical skeletal measurements were determined and comparisons of these measurements among the types were performed. The results obtained in this study showed that the range of normal occlusion included very diverse anteroposterior and vertical skeletal relationships.

• Development and Reproduction
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• v.15 no.4
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• pp.359-364
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• 2011

The seven selected primers OPA-02, OPA-04, OPA-18, OPD-07, OPD-08, OPD-15 and OPD-16 were used to generate unique shared loci to each species and shared loci by the two species. The hierarchical dendrogram indicates three main branches: cluster 1 (RORETZI 01~RORETZI 11) and cluster 2 (HILGENDORF 12~HILGENDORF 22) from two geographic populations of ascidians, Halocynthia roretzi and H. hilgendorfi. The shortest genetic distance displaying significant molecular difference was between individuals' HILGENDORF no. 14~HILGENDORF no. 19 (genetic distance =0.008). Ultimately, individual no. 02 of the RORETZI ascidian was most distantly related to HILGENDORF no. 21 (genetic distance=0.781). These results demonstrate that the H. roretzi population is genetically different from the H. hilgendorfi population. From what has been said above, the potential of PCR analysis to identify diagnostic markers for the identification of two ascidian populations has been demonstrated. Generally speaking, using a variety of decamer primers, this PCR method has been applied to identify specific markers particular to line, species and geographical population, as well as genetic diversity/polymorphism in diverse species of organisms.

• Preventive Nutrition and Food Science
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• v.21 no.4
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• pp.393-397
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• 2016

Whole grain wheat flour (WGWF) is the entire grain (bran, endosperm, and germ) milled to make flour. The WGWF of 31 Korean wheat (Triticum aestivum L.) cultivars were analyzed for the chemical compositions, and classified into groups by hierarchical cluster analysis (HCL). The average composition values showed a substantial variation among wheat varieties due to different wheat varieties. Wheat cv. Shinmichal1 (waxy wheat) had the highest ash, lipid, and total dietary fiber contents of 1.76, 3.14, and 15.49 g/100 g, respectively. Using HCL efficiently classified wheat cultivars into 7 clusters. Namhae, Sukang, Gobun, and Joeun contained higher protein values (12.88%) and dietary fiber (13.74 %). Regarding multi-trait crop breeding, the variation in chemical compositions found between the clusters might be attributed to wheat genotypes, which was an important factor in accumulating those chemicals in wheat grains. Thus, once wheat cultivars with agronomic characteristics were identified, those properties might be included in the breeding process to develop a new variety of wheat with the trait.

• Korean Journal of Adult Nursing
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• v.28 no.6
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• pp.669-679
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• 2016

Purpose: The purpose of this study was to explore the reported good service experiences from the perspective of elderly residents of long-term care facilities. Methods: Of those residents who are 65 years old or older, 14 residents whose length of stay were one month or longer and scores of the K-Mini Mental State Examination were 15 or higher were interviewed. The interview data formed the basis for the empirical statements about the reported nature of patients' experiences as residents of long-term care facilities. These data were used in concept mapping. Results: Through multidimensional scaling analysis and hierarchical cluster analysis, 62 core statements, two dimensions, and six clusters of good service experiences were derived. The two dimensions were classified as 'care centered-participation centered services' and as 'physical-emotional services.' Six cluster themes emerged as good service experiences: 'safety of care and treatment', 'responsible and supportive staff', 'comfort of living environment', 'mental well-being', and 'respect and communication'. Conclusion: The result of the study provides information about what experiences are important to older adults with cognitive impairment. The concept map can be used to develop a patient experience index for the elderly residents of long-term care facilities.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.215-231
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• 2006

Recently there are many bibliometric studies attempting to utilize Pathfinder networks(PFNets) for examining and analyzing the intellectual structure of a scholarly field. Pathfinder network scaling has many advantages over traditional multidimensional scaling, including its ability to represent local details as well as global intellectual structure. However there are some limitations in PFNets including very high time complexity. And Pathfinder network scaling cannot be combined with cluster analysis, which has been combined well with traditional multidimensional scaling method. In this paper, a new method named as Parallel Nearest Neighbor Clustering (PNNC) are proposed for complementing those weak points of PFNets. Comparing the clustering performance with traditional hierarchical agglomerative clustering methods shows that PNNC is not only a complement to PFNets but also a fast and powerful clustering method for organizing informations.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.984-994
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• 2020

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5819-5840
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• 2018

Considering the topology of hierarchical tree structure, each cluster in WSNs is faced with various attacks launched by malicious nodes, which include network eavesdropping, channel interference and data tampering. The existing intrusion detection algorithm does not take into consideration the resource constraints of cluster heads and sensor nodes. Due to application requirements, sensor nodes in WSNs are deployed with approximately uncorrelated security weights. In our study, a novel and versatile intrusion detection system (IDS) for the optimal defense strategy is primarily introduced. Given the flexibility that wireless communication provides, it is unreasonable to expect malicious nodes will demonstrate a fixed behavior over time. Instead, malicious nodes can dynamically update the attack strategy in response to the IDS in each game stage. Thus, a multi-stage intrusion detection game (MIDG) based on Bayesian rules is proposed. In order to formulate the solution of MIDG, an in-depth analysis on the Bayesian equilibrium is performed iteratively. Depending on the MIDG theoretical analysis, the optimal behaviors of rational attackers and defenders are derived and calculated accurately. The numerical experimental results validate the effectiveness and robustness of the proposed scheme.

• 한국석유지질학회:학술대회논문집
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• spring
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• pp.10-14
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• 1998

A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.581-592
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• 2015

In the GORRAM, the estimation of resource requirements for wartime equipment is based on the ELCON of the USA. The number of vulnerability groups of ELCON are 22, but unfortunately it is hard to determine how the 22 groups are classified. Thus, in this research we collected 505 types of basic items used in wartime and classified those items into new vulnerability groups using AHP and cluster analysis methods. We selected 11 variables through AHP to classify those items with cluster analysis. Next, we decided the number of vulnerability groups through hierarchical clustering and then we classified 505 types of basic items into the new vulnerability groups through K-means clustering.This paper presents new vulnerability groups of 505 types of basic items fitted to Korean weapon systems. Furthermore, our approach can be applied to a new weapon system which needs to be classified into a vulnerability group. We believe that our approach will provide practitioners in the military with a reliable and rational method for classifying wartime equipment and thus consequentially predict the exact estimation of resource requirements in wartime.