• Journal of Species Research
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• v.13 no.1
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• pp.10-31
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• 2024

In this study, 11 strains of epilithic cyanobacteria belonging to six unrecorded species in Korea were isolated from gravel submerged in freshwater of seven collection sites in Korea. The morphological characteristics of the six species isolated in this study were consistent with the type strain of each species, and the similarity of the 16S rRNA gene sequences with the type strain of each species were 98.8-100%. In the phylogenetic tree using the 16S rRNA gene sequences, the 11 strains of these six species formed the same cluster as the strains of each species. The habitat of each previously reported species is mainly the soil surface, but all Korean strains appeared from the gravel submerged in freshwater. As a result of the morphological, ecological, and molecular analyses, these six species of cyanobacteria were identified as Geminocystis papuanica, Allocoleopsis franciscana, Ancylothrix terrestris, Klisinema persicum, Scytolyngbya timoleontis, and Shackletoniella antarctica, which were added as newly recorded species in Korea.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.1
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• pp.94-106
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• 2024

In this study, we conducted a survival analysis on battalion-level commanders(leaders), focusing on infantry battalion defensive operations using the big data of brigade-level KCTC(Korea Combat Training Center) training results. Unlike previous studies, we utilized the brigade-level KCTC training results data for the first time to conduct a survival analysis, and the research subjects were battalion-level commanders(leaders), which can affect the battle. At this time, the battle results were defined, and through cluster analysis, infantry battalions were divided into excellent, average, and insufficient units, and the difference in the survival rate of the commanders was analyzed through the Kaplan-Meier survival analysis. This provided an opportunity to objectively compare the differences between excellent and insufficient units. Subsequently, factors affecting the survival of commanders were derived using the Cox proportional hazard model, and it was possible to confirm the influencing factors from various angles by also using the survival tree model. Significance and limitations confirmed in the research process were presented as policy suggestions and future research directions.

• The Korean Journal of Mycology
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• v.28 no.1
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• pp.32-37
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• 2000

The objectives of this study was to identify genetic variations of Tricholoma matsutake (S. Ito et Imai) Sing. growing in different geographic ranges in South Korea. Mushrooms were collected during fruiting seasons from 1994 to 1997 from 11 major sites which included four sites (Bonghwa, UIjin, Goryoung, and Chungdo) in Kyongbuk Province, three sites (Changnyung, Hadong, and Hamyang) in Kyongnam Province, two sites (Yangyang and Inje) in Kangwon Province, one site (Goisan) in Choongbuk Province, and one site (Namwon) in Chonbuk Province. Two mushrooms each from three to eight shiros in each sites were collected. Genetic characteristics were analyzed by Inter-Simple Sequence Repeat Polymerase Chain Reaction (I-SSR PCR) method using six primers. With a total of 131 DNA bands identified, Nei's genetic distance and UPGMA tree were constructed. It was estimated that genetic variations between sites amounted to 12.9%, while 87.1% of total variation was explained by variations among individuals within sites. The cluster analysis indicated that the eleven major sites were clustered into four groups, group I (Yangyang, Hamyang, Inje, Hadong and UIjin), group II (Changnyung, Namwon and Chungdo), group III (Goryoung), and group IV (Bonghwa and Goisan). It is concluded that matsutake mushrooms in South Korea have a considerable degree of genetic variations between major sites.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.342-350
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• 2021

This study was conducted to investigate the effect of time of hand-thinning on vegetative growth, bitter pit incidence, fruit quality, and return bloom in 'Gamhong'/M.9 apple trees. The time of hand-thinning were 3, 5, 7 and 9 weeks after full bloom, and the primary thinning (leaving only the king fruit on cluster) and secondary thinning (adjusting crop load) were conducted at the same time. The time of hand-thinning was correlated to the vegetative growth, average fruit wight, yield, soluble solids content, bitter pit incidence, and return bloom, negatively, and to the yield of middle grade fruits (fruit weight was 250-299g and none pit on fruit surface) per tree, calcium contents of leaves, and fruit red color, positively. There was no significant effect of time of hand-thinning on fruit firmness, titratable acidity, and total incomes per tree. In conclusion, if the time of hand-thinning of 'Gamhong'/M.9 apple tree was completed at 9 weeks after full bloom, it could produce about 300g of high-quality fruit without bitter pit.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.666-676
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• 2000

For the study of morphological variation of Q. variabilis natural population in Korea, 19 populations were selected through the country in considering latitude, longitude, and geographical characters. Thirty trees were randomly selected from each population and 60 mature leaves were sampled from each tree. Four characters (leaf blade length, maximum blade width, petiole length, and vein number) were measured, and their ratios (the ratio of blade length to maximum blade width, the ratio of blade length to petiole length, the ratio of petiole length to vein number, upper 1/3 blade width to maximum blade width, and upper 1/3 blade width to lower 1/3 blade width) were calculated. 1. Analysis of variance for all leaf characters were significantly different among populations and among individuals within population. Contributions of variance among individuals within population in all the characters were higher than those among populations. Therefore, selection of plus trees may be preferable to desirable populations for breeding program of Q. variabilis. 2. Among principal component analysis for leaf characters, primary 2 principal components appeared to be major variables for leaf form of Q. variabilis because of the loading contribution of 80.5%. The first contribution component was petiole length/vein number and petiole length ; the second one was upper 1/3 blade width/maximum blade width, upper blade width/lower 1/3 blade width and vein number, respectively. 3. Latitude was positively correlated with blade length/maximum blade width and blade length/petiole length, but negatively correlated with petiole length/vein number, upper 1/3 blade width/maximum blade width, upper 1/3 blade width/lower 1/3 blade width, petiole length, and vein number. But, for longitude and altitude the former two traits and the later five traits exhibited the negative and positive correlation, respectively. 4. Cluster analysis using complete linkage method for leaf characters showed two groups to Euclidean distance 1.6. They were group I of population 1. 4, 5, and 13 and group II of population 2, 3, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, and 19. However, group II was divided again to Euclidean distance 1.3, that is a group including population 3, 7, 10, 14, 15, and 17(group II-1) and the other group comprising population 2, 6, 8, 9, 11, 12, 16, 18, and 19(group II-2). This cluster could be mainly observed due to difference among population in aspect (group I : NE, group II-1 : SE, and group II-2 : SW).

• The Korean Journal of Ecology
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• v.27 no.6 s.122
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• pp.325-333
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• 2004

Birds were censused to investigate the composition of landscape structure for bird diversity around Ulsan between May and November 2002. Associations with three main categories of habitat variables were evaluated: 1) amount and type of forest; 2) residual habitats not classified as forest or crops; 3) land-use variables. Cluster analysis of bird community shows the highest forest variables of $79.06\%$, and the others are residual habitat variables ($17.98\%$), land-use variables ($2.94\%$) in spring, and forest variables of $57.77\%$, land-use variables ($23.16\%$), residual habitat variables ($18.47\%$) in autumn, respectively. In Principal Component Analysis of a total of 196 sites, the populations are strongly correlated to Component I ($54.8\%$) based forest habitats and to Component II based on land-use. Species preferring sites were clearly separated with heterogenous forest along the first axis. In autumn, the populations are moderately correlated to Component I based land-use and to component II based forest habitats. Species preferring local habitats were also clearly separated. Fifty three species of 1,700 birds were recorded: Brown-eared Bulbul, Vinous-throated Parrotbill, Great Tit, Tree Sparrow and Black-billed Magpie accounted for over $60\%$ of the observed birds in spring and autumn. The important species were Brown-eared Bulbul, Vinous-throated Parrotbill, Great Tit and Tree Sparrow in spring and autumn. Four habitats in terms of their species richness were computed as follows: Wonhyosan has the highest an expected species number, $E[S_{59}]=19$. Moonsusan has the lowest expected species number, $E[S_{59}]=17$ in spring. In autumn, Kuenamsan has the highest expected species number, $E[S_{63}]=16$. Moonsusan has the lowest expected species number, $E[S_{63}]=12$. Pairwise similarity declined with increasing distance between recording site and recording site from Moonsusan-Wonhyosan (0.62), the same geographical regions clustered separately in a UPGMA cluster tree in spring, and in autumn from Moonsusan-ChungJoksan (0.53).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.301-311
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• 2013

This study aims to analyze characteristics, health behaviors and health management level related to private health examination recipients in one general hospital. To achieve this, we analyzed 150,501 cases of private health examination data for 11 years from 2001 to 2011 for 20,696 participants in 2011 in a Dae-Jeon general hospital health examination center. The cluster analysis for classify private health examination group is used z-score standardization of K-means clustering method. The logistic regression analysis, decision tree and neural network analysis are used to periodic/non-periodic private health examination classification model. 1,000 people were selected as a customer management business group that has high probability to be non-periodic private health examination patients in new private health examination. According to results of this study, private health examination group was categorized by new, periodic and non-periodic group. New participants in private health examination were more 30~39 years old person than other age groups and more patients suspected of having renal disease. Periodic participants in private health examination were more male participants and more patients suspected of having hyperlipidemia. Non-periodic participants in private health examination were more smoking and sitting person and more patients suspected of having anemia and diabetes mellitus. As a result of decision tree, variables related to non-periodic participants in private health examination were sex, age, residence, exercise, anemia, hyperlipidemia, diabetes mellitus, obesity and liver disease. In particular, 71.4% of non-periodic participants were female, non-anemic, non-exercise, and suspicious obesity person. To operation of customized customer management business for private health examination will contribute to efficiency in health examination center.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.68-74
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• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.407-414
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• 2013

This study was conducted to classify forest cover types using the multivariate statistical analysis in the natural forest of western Mt. Jiri. On the basis of the vegetation data by point quarter sampling, the adopted analytical methods were species-area curve (SAC), hierarchical cluster analysis (HCA), indicator species analysis (ISA), and multiple discriminant analysis (MDA). SAC selected the outlier tree species which was likely to have no influence on the classification of forest cover types, excluded from all analytical process. Based on forest vegetative information, HCA classified the study area into 2 to 10 clusters and ISA indicated that the optimal number of clusters were seven. MDA was taken to test the clusters that classified with HCA and ISA. The seven clusters were classified appropriately as overall classification success were 91.3%. The classified forest cover types were named by the ratio of the dominant species in the upper layer of each cluster. They were (1) Quercus mongolica Pure forest, (2) Mixed mesophytic forest, (3) Q. mongolica - Q. serrata forest, (4) Abies koreana - Q. mongolica forest, (5) Fraxinus mandshurica forest, (6) Q. serrata forest, and (7) Carpinus laxiflora forest.