• Journal of Korea Society of Industrial Information Systems
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• v.21 no.3
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• pp.13-19
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• 2016

Spark, an in-memory big-data processing framework is popular to use for real-time processing workload. Spark can store all intermediate data in the cluster memory so that Spark can minimize I/O access. However, when the resident memory of workload is larger that the physical memory amount of the cluster, the total performance can drop dramatically. In this paper, we analyse the factors of bottleneck on PageRank Application that needs many memory through experiment, and cluster the Spark with Tachyon File System for using memory to solve the factor of bottleneck and then we improve the performance about 18%.

• Journal of Distribution Science
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• v.19 no.12
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• pp.33-43
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• 2021

Purpose: This paper aims to determine features of the relationship between human development, tourism and national brand. Research design, data and methodology: ranking indicators, cluster analysis, K means method, correlation analysis. Results: The analysis covers data for 95 countries for 2019. The number of countries is justified by the availability of comparable data for calculations. A direct relationship between the indicators for the entire sample has been revealed in the result of the correlation analysis. However, this relationship has not been confirmed for the groups of countries that were formed through the cluster analysis. Spearman Rank Order and Kendall Tau Correlations have been calculated for the five obtained clusters. In two of the five clusters, the relationship between the indicators has not been found. A strong negative link between all the indicators has been detected in the cluster with average index values. A strong positive link between TTCI and BSI has been revealed in the group of countries with the best index values. A strong positive link between TTCI and HDI has been found in the group of countries with the worst index values. Conclusions: The analysis demonstrates that there is a relationship between BSI, TTCI and HDI, and while this link is observed for the sample as a whole, it is not homogeneous for groups of countries.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.1
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• pp.83-96
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• 2004

Purpose: The purpose of this research is, by investigating organizational characteristics, types of nursing organizational culture and team effectiveness in ICU, to ascertain the type of nursing organizational culture and the organizational characteristic that can improve the team effectiveness. Method: The research targeted 427 nurses from 33 ICUs of 14 general hospitals which have more than 250 beds and the data were gathered by using self-report questionnaires from April 10, 2003 to April 24, 2003. For this research, the following tools were used; the tool for measuring organizational characteristics and organizational cultures and the tool for measuring team effectiveness. Result: The most significant nursing organizational characteristic in ICU is the centralization. The organizational culture in ICU is generally rank-oriented culture. There was a significant difference (p<.01) in four types of organizational cultures; relation-oriented, innovation-oriented, rank-oriented and task-oriented. Verifying influence power of organizational cultures upon team effectiveness of ICU, relation-oriented culture had 49.2% of an influence upon team effectiveness, innovation- oriented and relation-oriented culture had 60.4% of an influence, and rank-oriented, innovation-oriented and relation-oriented culture had 61.2% of an influence. The organizational culture profiles according to the types of nursing organizational cultures in 33 ICUs were found by a cluster analysis. They were classified into five culture profiles; strong balance culture profile, weak balance culture profile, innovation-oriented and task-oriened culture profile, strong relation culture profile and strong rank culture profile(p<0.5). According to me organizational culture profiles, a significant difference of team effectivenesses(coworker satisfaction, team performance perception, team satisfaction and team commitment) was found(p<.01). The strong balance culture profile had the best team effectivenesses. Conclusion: For nursing culture management, a nursing administrator should identify the relevant nursing organizational culture at first by utilizing an innovative team-leader. After identifying the organizational culture, the administrator should make strategic plans and practices that can distinguish good organizational cultures to be expanded from ones to be sublated so that a strong balance culture can be developed.

• Journal of KIISE
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• v.45 no.1
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• pp.61-68
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• 2018

The identification of genes that contribute to the prediction of prognosis in patients with cancer is one of the challenges in providing appropriate therapies. To find the prognostic genes, several classification models using gene expression data have been proposed. However, the prediction accuracy of cancer prognosis is limited due to the heterogeneity of cancer. In this paper, we integrate microarray data with biological network data using a modified PageRank algorithm to identify prognostic genes. We also predict the prognosis of patients with 6 cancer types (including breast carcinoma) using the K-Nearest Neighbor algorithm. Before we apply the modified PageRank, we separate samples by K-Means clustering to address the heterogeneity of cancer. The proposed algorithm showed better performance than traditional algorithms for prognosis. We were also able to identify cluster-specific biological processes using GO enrichment analysis.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.84-84
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• 2019

본 연구는 전국 임의의 산양삼 재배지를 선정하여 재배지 내의 토양 특성 및 토양세균군집을 분석하고, 토양 특성, 세균군집 및 산양삼 생육특성 간의 상관관계를 구명하기 위하여 수행되었다. 토양 이화학성 분석은 농촌진흥청의 종합분석실 매뉴얼에 따라 분석하였고, 토양세균군집 분석은 pyrosequencing analysis (Illumina platform)를 이용하였다. 토양세균군집과 생육특성 간의 상관관계는 Spearman's rank correlation을 이용하여 분석하였다. 전국 8개 산양삼 재배지로부터 분리한 토양세균군집은 2개의 cluster로 군집화를 이루는 것을 확인하였다. 모든 토양 샘플에서 Proteobacteria와 Alphaproteobacteria가 각각 평균 상대적 빈도수가 35.4%, 24.4%로 우점종으로 나타났다. 나타났다. 두 개의 cluster 간 토양세균군집의 상대적 빈도수를 비교 분석한 결과, 먼저 Proteobacteria (p = 0.03), Actinobacteria (p = 0.02), Ahlpaproteobacteria (p = 0.029), Betaproteobacteria (p = 0.021)는 cluster 1에서 cluster 2에 비해 상대적 빈도수가 유의적으로 높았고, Fimicutes (p = 0.004), Cyanobacteria (p = 0.004), Acidobacteriia (p = 0.041), Ktedonobacteria (p = 0.019), Gammaproteobacteria (p = 0.034), Bacilli (p = 0.009)은 cluster 2에서 유의적으로 상대적 빈도수가 높은 것으로 나타났다. 토양세균군집 cluster 간 산양삼의 생육특성을 비교 분석한 결과, cluster 2 재배지에서 수집한 산양삼 시료의 지하부 생중량은 cluster 1 재배지에서 수집한 산양삼 시료에 비해 cluster 2에서 유의적 (p = 0.04)으로 높았다. 산양삼 생육특성과 토양세균군집 간의 상관관계를 분석한 결과, 산양삼의 생육은 토양 pH가 낮고 Acidobacteria의 상대적 빈도수가 높은 토양에서 증가하였으며, Acidobacteriia와 Koribacteraceae의 상대적 빈도수는 산양삼의 생육과 유의적인 정의 상관관계를 보이는 것으로 나타났다. 본 연구 결과는 토양미생물군집과 산양삼 생육 간의 상관관계를 구명하는 중요한 자료가 될 것으로 생각되고, 나아가 산양삼 재배적지를 선정하는데 있어 보다 명확한 정보를 제공할 수 있을 것으로 사료된다.

• Korean Journal of Environmental Biology
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• v.37 no.3
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• pp.380-388
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• 2019

The studies regarding soil bacterial community and correlation analysis of wild-simulated ginseng cultivation area are insufficient. The purpose of this study was to investigate the correlation between soil bacterial community and growth characteristics of wild-simulated ginseng for selection of suitable cultivation area. The bacterial community was investigated by high throughput sequencing technique (Illumina platform). The correlation coefficient between soil bacterial community and growth characteristics were analyzed using Spearman's rank correlation. The soil bacterial community from soil samples of 8 different wild-simulated ginseng cultivated area exhibited two distinct clusters, cluster 1 and cluster 2. The relative abundance of Proteobacteria (35.4%) and Alphaproteobacteria(24.4%) was observed to be highest in all soil samples. The lower soil pH and higher abundance of Acidobacteria resulted in increased growth of wild-simulated ginseng. Additionally, abundance of Acidobacteriia (class) and Koribacteraceae (family) demonstrated significant positive correlation with fresh weight of wild-simulated ginseng. The results of this study clearly state the correlation between growth characteristic and soil bacterial community of wild-simulated ginseng cultivation area, thereby offering effective insight into selection of suitable cultivation area of wild-simulated ginseng.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.52-62
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• 2013

Design Hourly Factor(DHF) is defined as the ratio of design hourly volume(DHV) to Average Annual Daily Traffic(AADT). Generally DHV used the 30th rank hourly volume. But this case DHV is affected by holiday volumes so the road is at risk for overdesigning. Computing K factor is available for counting 8,760 hour traffic volume, but it is impossible except permanent traffic counts. This study applied three method to make DHF, using 30th rank hourly volume to make DHF(method 1), using peak hour volume to make DHF(method 2). Another way to make DHF, rank hourly volumes ordered descending connect a curve smoothly to find the point which changes drastic(method 3). That point is design hour, thus design hourly factor is able to be computed. In addition road classified 3 type for national highway using factor analysis and cluster analysis, so we can analyze the characteristic of DHF by road type. DHF which was used method 1 is the largest at any other method. There is no difference in DHF by road type at method 2. This result shows for this reason because peak hour is hard to describe the characteristic of hourly volume change. DHF which was used method 3 is similar to HCM except recreation road but 118th rank hourly volume is appropriate.

• Journal of Information Science Theory and Practice
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• v.6 no.3
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• pp.45-60
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• 2018

Research performance evaluation in Korean universities follows strict guidelines that specify scoring systems for publication venue categories and formulas for co-authorship credit allocation. To find out how the standards differ across universities and how they differ from bibliometric research evaluation measures, this study analyzed 25 standards from major Korean universities and rankings produced by applying standards and bibliometric measures such as publication and citation counts, normalized impact score, and h-index to the publication data of 195 tenure-track professors of library and information science departments in 35 Korean universities. The study also introduced a novel impact score normalization method to refine the methodology from prior studies. The results showed the university standards to be mostly similar to one another but quite different from citation-driven measures, which suggests the standards are not quite successful in quantifying the quality of research as originally intended.

• Journal of Plant Biology
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• v.25 no.1
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• pp.9-19
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• 1982

A thin-layer chromatographic study was made of the chloroform-soluble and flavonoid fractions from the fruit peels of 16 species, 2 varieties and 5 formas of the Citrus plants cultivated in Je Ju Island for their interspecific relatinships. In addition, 3 hybrids and 9 native plants were also studied for their taxonomic position. Three phenograms were developed from these chromatographic data after cluster analysis via the unweighted paired group method using rithmatic average by Sneath and Sokal. These plants were grouped into 5 alliences based on the phenogram obtained from the chloroform-soluble fracitons, which were nearly identical to the subgenus rank by Tanaka, and rutinoside and neohesperidoside groups by Horowitz. Those from the flavonoid and methanol-soluble fractions were not able to evaluate the morphological classification except for a few cases.