• Korean Journal of Plant Resources
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• v.37 no.3
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• pp.270-306
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• 2024

This study investigated the diversity of 323 mung bean accessions from Korea, China, and India, along with six cultivars, using 22 agronomical traits. The standardized Shannon-Weaver index (H') for the qualitative traits ranged from 0.11 (terminal leaflet shape) to 0.98 (pubescence density of pod). Likewise, the coefficient of variation for the quantitative traits ranged from 8.76% (days to maturity (DM)) to 79.91% (lodging rate (LR)), indicating a wide genetic variance. Hypocotyl color, pod color, seed shape, and seed coat surface lust showed different distributions among Korean, Indian, and Chinese accessions. Chinese accessions had the highest average germination rate, DM, days from flowering to maturity, and one-hundred seeds weight, followed by Korean and Indian accessions, while the number of seeds per pod (SPP) displayed the opposite trend, with all except SPP showing significant variation (p < 0.05). Similarly, plant height, days to flowering, and number of pods per plant increased in the order of India > Korea > China, with LR showing the opposite trend (p < 0.05). The mung bean accessions were grouped into four major clusters using hierarchical cluster analysis supported by principal component analyses, and all of the quantitative traits showed significant variations between the clusters (p < 0.05). Generally, the mung bean accessions investigated in this study exhibited wide phenotypic trait variations, which could be beneficial for future genomics studies. Moreover, this study identified 77 accessions that outperformed the controls. Consequently, these superior accessions could provide a wide spectrum of options during the development of improved mung bean varieties.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.

• Horticultural Science & Technology
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• v.30 no.5
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• pp.557-567
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• 2012

This study was conducted to achieve basal information for the development of tomato cultivars with disease resistances through marker-assisted backcross (MAB). Ten inbred lines with TYLCV, late blight, bacterial wilt, or powdery mildew resistance and four adapted inbred lines with superior horticultural traits were collected, which can be useful as the donor parents and recurrent parents in MAB, respectively. Inbred lines collected were evaluated by molecular markers and bioassay for confirming their disease resistances. To develop DNA markers for selecting recurrent parent genome (background selection) in MAB, a total of 108 simple sequence repeat (SSR) primer sets (nine per chromosome at average) were selected from the tomato reference genetic maps posted on SOL Genomics Network. Genetic similarity and relationships among the inbred lines were assessed using a total of 303 polymorphic SSR markers. Similarity coefficient ranged from 0.33 to 0.80; the highest similarity coefficient (0.80) was found between bacterial wilt-resistant donor lines '10BA333' and '10BA424', and the lowest (0.33) between a late blight resistant-wild species L3708 (S. pimpinelliforium L.) and '10BA424'. UPGMA analysis grouped the inbred lines into three clusters based on the similarity coefficient 0.58. Most of the donor lines of the same resistance were closely related, indicating the possibility that these lines were developed using a common resistance source. Parent combinations (donor parent ${\times}$ recurrent parent) showing appropriate levels of genetic distance and SSR marker polymorphism for MAB were selected based on the dendrogram. These combinations included 'TYR1' ${\times}$ 'RPL1' for TYLCV, '10BA333' or '10BA424' ${\times}$ 'RPL2' for bacterial wilt, and 'KNU12' ${\times}$ 'AV107-4' or 'RPL2' for powdery mildew. For late blight, the wild species resistant line 'L3708' was distantly related to all recurrent parental lines, and a suitable parent combination for MAB was 'L3708' ${\times}$ 'AV107-4', which showed a similarity coefficient of 0.41 and 45 polymorphic SSR markers.

• Journal of Yeungnam Medical Science
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• v.13 no.2
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• pp.279-294
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• 1996

This study was carried out to develop a Korean language version of Zung's self-rating anxiety scale(SAS) from august, 1994 to September, 1996. The subjects consisted of 205 normal control subjects from the general population group, and 97 subjects with anxiety disorders. These 97 subjects were chosen from a group by the structured clinical interview for DSM-IV of in patients and out patients. Both normal control subjects and anxiety disorder subjects were drawn utilizing a cluster of sampling methods. In order to analyze the data on anxiety scores, Pearson's product moment correlation coefficient method was carried out, as well as reliability, factor analysis and discriminant function analysis, utilizing the SPSS/PC+ program. The results obtained were as follows: The mean average of the total anxiety scores were 32.36 + 6.35 for the normal control subjects and 50.53 + 7.67 for anxiety disorder subjects. Test-retest reliability(coefficient r=0.98, p < 0.001), and internal consistency(coefficient r=0.96, p < 0.001) were satisfactory. Factor analysis using oblique technique rotation yielded four factors. The normal control subjects scored higher concerning the symptoms such as sweating, restlessness, apprehension, insomnia and dyspnea, and lower for faintness, mental disintegration, paresthesia, dizziness and tremor. On the other hand, for the anxiety disorders, apprehension, restlessness, sweating, dyspnea and insomnia scored higher, and lower for faintness, paresthesia, nightmare, dizziness and tremor.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.227-240
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• 2011

New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.353-366
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• 2018

The purpose of this study was assessment the quality of water by using the statistical analysis technique of the Water flow and water quality from January 2012 to December 2016 at the unit basin for total pollutant load management system (TPLMS) in the Imjin River. Water flow and water quality were monitored at an average of 8 day intervals, 11 parameters were used for correlation analysis, principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). The Hierarchical CA was classified into three according to the change of space, such as natural rivers, urban rivers, point with large influence of point pollution source, it was found that the type of contamination source the similarity of water quality affected the classification of cluster. Using one-way analysis of variance (ANOVA) and post-hoc Analysis, there were statistically significant differences between mean values among the clusters. Correlation analysis showed the correlation coefficient between $COD_{Mn}$ and TOC was 0.951 (p<0.01) and the correlation was statistically significantly higher. According to the result PCA and FA, 3 principal components can explaining 72% of the total variations in water quality characteristics and main factor was EC, $BOD_5$, $COD_{Mn}$, TN, TP and TOC indirect indicators of organic matter and nutrients were influenced. This study presented the regression equation obtained by applying the factor scores to the multiple linear regression analysis and concluded that the management Indirect indicators of organic matter and nutrients is important for water quality management in the Imjin River basin.

• Journal of Mushroom
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• v.16 no.3
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• pp.203-207
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• 2018

'Daebak', a new cultivar of Grifola frondosa, was bred by mating two monokaryotic strains isolated from 'F14309' and 'GMGF44062' at the Mushroom Research Institute, Gyonggi-Do ARES in 2017. The optimum temperature for mycelial growth of 'Daebak' was $25^{\circ}C$ on PDA medium. In bottle cultivation, the culture period of 'Daebak' was 57 days, which was 2 days shorter than that of 'Cham' (control). The pinheading rate of 'Daebak' was 98.4%, which was 24.8% higher than that of 'Cham' and its CV (Coefficient of variation) was 0.6%, 5.3% lower than that of 'Cham'. Regarding the growth characteristics of 'Daebak', the diameter and thickness of the pileus were 27.7 mm and 1.73 mm, respectively, and the diameter and height of the fruiting bodies cluster were 132 mm and 87.2 mm, respectively. The pileus was thinner but the fruiting bodies cluster was larger than that of 'Cham'. Fruiting bodies weighed 139 g per 1,100 ml bottle of 'Daebak', which was 28% higher than that for 'Cham', with a CV of 2.5%, which was 6.2% lower than that of 'Cham'. The yield per 10,000 bottles (used for cultivation) of 'Daebak' was 1,376 kg, 70% higher than that of 'Cham', with a CV of 3.0% that was 11.5% lower than that of 'Cham'. With respect to physical characteristics, the strength and brittleness of the fruiting body of 'Daebak' was less than that of 'Cham'. When considering the period available for sale, the shelf life of 'Daebak' was 42 days, which was 6 days longer than that of 'Cham'.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.183-193
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• 2020

This study was conducted to evaluate the effect of environment factors on the growth of autumn season cultivation of Kimchi cabbage using the big data in terms of public open data(weather, soil information, and growth of crop, etc.). The growth data and the environment data such as temperature, daylength, and rainfall from 2010 to 2019 were collected. As a result of composing the correlation matrix, the height and leaf number showed high correlation in growing degree days(GDDs) and daylength, and the yield showed negative correlation in growing degree days and the concentration of clay. GDDs and daylength explained about 89% and 84% of variation in height, respectively. These two environmental factors also explained about 85% and 79% of variation in leaf numbers, respectively. In contrast, the coefficient of determination was low for yield when GDDs and concentration of clay was used. The outcome of regional statistical analysis indicated that relationship between yield and sum of sand and silt were high in Haenam and Jindo areas. Hierarchical cluster analysis, which was performed to verify the association of yield, GDDs, and concentration of clay, showed that Haenam and Jindo were clustered together. Although GDDs and yield vary by year and region, and there are regions with similar concentration of clays, observation data are grouped as the result. These suggests that GDDs and soil texture are expected to be related to yield. The cluster analysis results can be used for further data analysis and agricultural policy establishment.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.446-452
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• 2005

In order to examine the natural distribution variations between groups of the Stewartia koreana, the leaf form characteristics of the investigation sites were analyzed by each group. As a result, the Mt. Kumsan group showed a smaller value in leaf length, width, area, and the number of veins, but not in the petiole length and serration number. Among each character, the coefficient of variation(CV) of the characters excluding petiole length and leaf area was in a comparatively narrow range, from 11.6~17.4%. On the other hand, the CV of petiole length and leaf area between the groups was 34.9% and 28.4% respectively. The CV of these characters within the group was also extraordinary- petiole length showed 29.5~42% and leaf area showed 27.7~40.7%. Also, the simple correlation analysis between 12 leaf characteristics showed that the correlation between leaf width and leaf area was high (r=0.975). The correlations between leaf length and leaf area, between leaf length and leaf width were 0.971 and 0.969, respectively. A negative correlation between angle of leaf base and ratio of leaf length to leaf width was discovered (r= -0.843), meaning that the ratio of leaf length to leaf width decreases as angle of leaf base increases. A cluster analysis was enforced among leaf characteristics of the selected group as a standard on the similarity of quantitative, qualitative measurements. The results showed that at a 0.4 distance level, the subjects could be classified into 4 groups. Group 1 was the Mt. Jogyesan and Mt. Kayasan group, group 2 was Mt. Paegunsan, group 3 was Mt. Unmunsan and Mt. Mudungsan, and group 4 was Mt. Kumsan. At a distance level of 0.6, the subjects were classified into two groups. Group 1 was the Mt. Ktimsan group and group 2 was Mt. Mudungsan, Unmunsan, Paegunsan, Kayasan, and Cogyesan. Especially the Mt. Kumsan group had the smallest value in the leaf characteristics of leaf length, width, area, and the number of veins, showing an obvious difference from the other five groups. There were five principal components that had a meaningful eigenvalue over 1.0 among the 12 extracted components. The explanatory power of the top two main components (leaf length and width) on the total variation was 52.7%. The explanatory power was 91.3% when all 5 main components were included.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.6 s.165
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• pp.974-984
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• 2007

The purpose of this study was to find differences in evaluation criteria and to find differences in preferred images based on benefits segmented groups of jeans products consumers. Male and female Korean university students participated in the study. Quota sampling method was used to collect the data based on gender and a residential area of the respondents. Data from 492 questionnaires were used in the analysis. Factor analysis, Cronbach's alpha coefficient, cluster analysis, one-way ANOVA, and post-hoc test were conducted. As a result, respondents who seek multi-benefits considered aesthetic criteria(e.g., color, style, design, fit) and quality performance criteria(e.g., durability, ease of care, contractibility, flexibility) more importantly when evaluating and purchasing jeans products. Respondents who seek brand name considered extrinsic criteria(e.g., brand reputation, status symbol, country of origin, fashionability) more importantly than respondents who seek economic efciency. Respondents who seek multi-benefits such as attractiveness, fashion, individuality, and utility tend to prefer all the images: individual image, active image, sexual image, sophisticated image, and simple image when wearing jeans products. Respondents who seek fashion are likely to prefer individual image, and respondents who seek brand name more prefer both individual image and polished image. Mean while, respondents who seek economical efficiency less prefer sexual image and polished image.