• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.231-238
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• 2008

With the development of methodologies, there are also the researches for the concrete item selection for selecting the future emerging researches and technologies. In this paper, we use scientometrics for that purpose in the sectors of construction and transportation. In our scientometric analysis, we use Scopus database, top 1% cited papers, bibliographic coupling, cosine coefficient, and hierarchical clustering and then carry additional experts verification on our results. We try to show the detailed process of scientometric analysis and its possibility as objective methodologies to select the future emerging researches and technologies.

• Corrosion Science and Technology
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• v.20 no.2
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• pp.94-104
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• 2021

Atmospheric corrosion severity associated with aircraft parking environment was studied using metallic specimens, and temperature and humidity sensors installed at each aircraft operating base. Data were analyzed after a year of exposure. Silver was used to measure chloride deposition by integrating X-ray photoelectron spectroscopy depth profiles. Carbon steel was utilized to determine the corrosion rate by measuring the weight loss. The time of wetness was determined using temperature and humidity sensor data. Analysis of variance followed by Tukey's "honestly significant difference" test indicated that atmospheric environment inside the shelter varied significantly from that of unsheltered parking environment. The corrosion rate of unsheltered area also varies with the roof. Hierarchical clustering analysis of the measured data was used to classify air bases into groups with similar atmospheric corrosion. Bases where aircraft park at a shelter can be grouped together regardless of geographical location. Unsheltered bases located inland can also be grouped together with sheltered bases as long as the aircraft are parked under the roof. Environmental severity index was estimated using collected data and validated using the measured corrosion rate.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.153-161
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• 2018

In this paper, we propose a text-centered approach to identify the research trend of thyroid cancer in Korea. We incorporate statistical analysis, text mining and machine learning techniques with our clinical insights to find connective associations between terminologies and to discover informative clusters of literatures. The incidence of thyroid cancer in Korea increased rapidly in the 2000s, which fueled the debate regarding overdiagnosis, but recently the number of patients undergoing surgery has decreased significantly due to conscious reform efforts from various circles. We analyzed the abstracts and keywords of related research papers from DBpia. It was found that most were case reports in the 1980s, and some papers in the 1990s discussed the early detection of thyroid cancer by mass screening. While many papers focused on different diagnostic techniques and the detection of small cancers in the 2000s, many emphasized more on the quality of life of patients in the 2010s. There was an apparent change in the topics of thyroid cancer research over past decades. The results of this study would serve as a reference guide for current and future research directions.

• Corrosion Science and Technology
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• v.22 no.5
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• pp.377-386
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• 2023

Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.

• Korean Journal of Child Education & Care
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• v.17 no.1
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• pp.75-98
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• 2017

This study examined the possibility of clustering using 5-year-old children's basic learning ability and mothers' achievement expectation anxiety, and compared the impact of the children's self-regulation ability and mothers' learning involvement for each cluster. The subjects were 239 children (120 boys & 119 girls) aged 5 and attending 9 kindergartens in Seoul, Gyeonggi and Incheon, and also their mothers. The collected data were analyzed using non-hierarchical (K-means) cluster analysis and multivariate logistic regression analysis. The findings of this study were as follows. First, the mother-child pairs were classified into four clusters of 'high learning ability-high expectation anxiety', 'high learning ability-low expectation anxiety', 'low learning ability-low expectation anxiety', or 'low learning ability-high expectation anxiety'group. Second, the level of child's self-monitoring, self-control, and mother's respect and love were significantly higher in the 'high learning ability-low expectations anxiety' group than the 'low learning ability-high expectation anxiety' group. Also, pressure for academic achievement was higher in the 'high learning ability-high expectation anxiety' group than the 'low learning ability-low expectations anxiety' group. Third, child's self-monitoring, mother's pressure for academic achievement, home learning activities, and respect/love for child predicted the clustering using children's basic learning ability and mothers' achievement expectation anxiety.

• Allergy, Asthma & Immunology Research
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• v.10 no.6
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• pp.614-627
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• 2018

Purpose: Asthma is a heterogeneous disease that responds to medications to varying degrees. Cluster analyses have identified several phenotypes and variables related to fixed airway obstruction; however, few longitudinal studies of lung function have been performed on adult asthmatics. We investigated clinical, demographic, and inflammatory factors related to persistent airflow limitation based on lung function trajectories over 1 year. Methods: Serial post-bronchodilator forced expiratory volume (FEV) 1% values were obtained from 1,679 asthmatics who were followed up every 3 months for 1 year. First, a hierarchical cluster analysis was performed using Ward's method to generate a dendrogram for the optimum number of clusters using the complete post-FEV1 sets from 448 subjects. Then, a trajectory cluster analysis of serial post-FEV1 sets was performed using the k-means clustering for the longitudinal data trajectory method. Next, trajectory clustering for the serial post-FEV1 sets of a total of 1,679 asthmatics was performed after imputation of missing post-FEV1 values using regression methods. Results: Trajectories 1 and 2 were associated with normal lung function during the study period, and trajectory 3 was associated with a reversal to normal of the moderately decreased baseline FEV1 within 3 months. Trajectories 4 and 5 were associated with severe asthma with a marked reduction in baseline FEV1. However, the FEV1 associated with trajectory 4 was increased at 3 months, whereas the FEV1 associated with trajectory 5 was persistently disturbed over 1 year. Compared with trajectory 4, trajectory 5 was associated with older asthmatics with less atopy, a lower immunoglobulin E (IgE) level, sputum neutrophilia and higher dosages of oral steroids. In contrast, trajectory 4 was associated with higher sputum and blood eosinophil counts and more frequent exacerbations. Conclusions: Trajectory clustering analysis of FEV1 identified 5 distinct types, representing well-preserved to severely decreased FEV1. Persistent airflow obstruction may be related to non-atopy, a low IgE level, and older age accompanied by neutrophilic inflammation and low baseline FEV1 levels.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.83-91
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• 2024

This study utilizes association rule learning and clustering analysis to explore the co-occurrence and relationships within ecosystems, focusing on the endangered brackish-water snail Clithon retropictum, classified as Class II endangered wildlife in Korea. The goal is to analyze co-occurrence patterns between brackish-water snails and other species to better understand their roles within the ecosystem. By examining co-occurrence patterns and relationships among species in large datasets, association rule learning aids in identifying significant relationships. Meanwhile, K-means and hierarchical clustering analyses are employed to assess ecological similarities and differences among species, facilitating their classification based on ecological characteristics. The findings reveal a significant level of relationship and co-occurrence between brackish-water snails and other species. This research underscores the importance of understanding these relationships for the conservation of endangered species like C. retropictum and for developing effective ecosystem management strategies. By emphasizing the role of a data-driven approach, this study contributes to advancing our knowledge on biodiversity conservation and ecosystem health, proposing new directions for future research in ecosystem management and conservation strategies.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1121-1130
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• 2004

This paper proposes a method for line and word segmentation for machine-printed text blocks. To separate a text region into the unit of lines, it analyses the horizontal projection profile and performs a recursive projection profile cut method. In the word segmentation, between-word gaps are identified by a hierarchical clustering method after finding gaps in the text line by using a connected component analysis. In addition, a special symbol detection technique is applied to find two types of special symbols tying between words using their morphologic features. An experiment with 84 text regions from English and Korean documents shows that the proposed method achieves 99.92% accuracy of word segmentation, while a commercial OCR software named Armi 6.0 Pro$^{TM}$ has 97.58% accuracy.y.

• Advances in Traditional Medicine
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• v.6 no.4
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• pp.293-299
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• 2006

By using high-performance liquid chromatography-photodiode array detection, a simple and accurate chromatographic fingerprint method was developed for the identification of Radix Codonopsis (roots of Codonopsis) from different sources. Eighteen herbs of Codonopsis at different habitats in China, including roots from Codonopsis pilosula, Codonopsis pilosula var. modesta and Codonopsis tangshen were analyzed by the fingerprint. The amount of lobetyolin was calibrated, which was found to be more consistent in roots of Codonopsis pilosula as compared to that of Codonopsis pilosula var. modesta and Codonopsis tangshen. Having the fingerprint results, hierarchical clustering analyses were performed to classify the eighteen herbs into three groups: Codonopsis pilosula, Codonopsis pilosula var. modesta and Codonopsis tangshen. This clustering analysis agrees very well with the pharmacognostic identification result, and which could be used as a tool in the quality control of Radix Codonopsis.

• Atmosphere
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• v.19 no.2
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• pp.169-182
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• 2009

To improve the performance of climate and numerical models, concerns on the land-atmosphere schemes are steadily increased in recent years. For the realistic calculation of land-atmosphere interaction, a land surface information of high quality is strongly required. In this study, a new land cover map over the Korean peninsula was developed using MODIS (MODerate resolution Imaging Spectroradiometer) data. The seven phenological data set (maximum, minimum, amplitude, average, growing period, growing and shedding rate) derived from 15-day normalized difference vegetation index (NDVI) were used as a basic input data. The ISOData (Iterative Self-Organizing Data Analysis), a kind of unsupervised non-hierarchical clustering method, was applied to the seven phenological data set. After the clustering, assignment of land cover type to the each cluster was performed according to the phenological characteristics of each land cover defined by USGS (US. Geological Survey). Most of the Korean peninsula are occupied by deciduous broadleaf forest (46.5%), mixed forest (15.6%), and dryland crop (13%). Whereas, the dominant land cover types are very diverse in South-Korea: evergreen needleleaf forest (29.9%), mixed forest (26.6%), deciduous broadleaf forest (16.2%), irrigated crop (12.6%), and dryland crop (10.7%). The 38 in-situ observation data-base over South-Korea, Environment Geographic Information System and Google-earth are used in the validation of the new land cover map. In general, the new land cover map over the Korean peninsula seems to be better classified compared to the USGS land cover map, especially for the Savanna in the USGS land cover map.