• Korean Journal of Ecology and Environment
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• v.40 no.2
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• pp.303-317
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• 2007

The fish community of small freshwater ecosystems gets easily disturbed by direct or indirect human induced disturbances during the period of urbanization. Urbanization is one of factors that generate changes in stream and influences fish fauna in developed countries. This study was conducted in Busan Metropolitan City from 2001 to 2004. In order to investigate the fish community, the city was divided into 3 parts, eastern, central and western. A total of 3,206 individuals of 46 species from 19 families were collected from 55 sites. The dominant species was Rhynchocypris oxycephalus, whereas Zacco temminckii was the subdominant species. Cluster analysis was conducted using primary freshwater fish species collected from each stream. As a result of the analysis, study sites were well differentiated into 3 parts. Two species of Z. temminckii and R. oxycephalus represented the upper part of the stream and Carassius cuvieri, Acheilognathus rhombeus, Hemiculter eigenmanni and Micropterus salmoides represented the middle and lower parts of the stream. When compared with previous studies, fish community of the eastern part of the Busan city where urbanization is in progress, showed similar patterns to the central part. At the time of the habitat restoration of fish fauna in stream, appropriate selection of fish species should be made through analysis of stream character and biogeographic distribution of fish, and long-term monitoring is also needed for sustaining the management of fish fauna.

• Korean Journal of Ecology and Environment
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• v.51 no.2
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• pp.192-203
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• 2018

Headwater streams provide various microhabitats, resulting in high diversity of macroinvertebrate community. In this study, we compared the differences of communities between two adjacent headwater streams (Jangjeon stream (GRJ; GRJ1-GRJ5) and Haanmi stream (GRH; GRH1-GRH3)) in Jungwang and Gariwang mountains, Gangwon-do and evaluated the effects of habitat condition to the macroinvertebrates community composition. In order to characterize the macroinvertebrate communities and extract influential environmental factors, we applied to Cluster analysis (CA), Indicator species analysis and Non-metric multidimensional scaling (NMDS). Total 33,613 individuals in 3 phyla, 5 classes, 13 orders, 51 families, and 114 taxa (genera or species) were collected. Gammarus sp. was dominant at the upper stream of GRJ, whereas Chironomidae spp. was abundant at GRH and the downstream of GRJ. The CA classified samples into six clusters (1-6) reflecting spatial and temporal variation of benthic macroinvertebrate communities. Benthic macroinvertebrate community composition was significantly different between two adjacent streams. Sweltsa sp. 1, Psilotreta kisoensis, Rhyacophila shikotsuensis and Serratella setigera were identified as representative indicator species for clusters 1, 2, 3 and 5, respectively. Similar to CA results, NMDS revealed the spatial and temporal differences of benthic macroinvertebrate communities, indicating the difference of community composition as well as microhabitat condition. Forest composition, proportion of boulders (>256 mm), and water velocity were main factors affecting the macroinvertebrate community composition.

• Journal of Animal Science and Technology
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• v.47 no.3
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• pp.341-354
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• 2005

For the genetic assessment of the cattle breeds including Hanwoo, eleven microsatellite markers on ten bovine autosomes were genetically characterized for 618 individuals of nineteen cattle breeds; North Eastern Asian breeds (Korean cattle, Korean Black cattle, Japanese Black cattle, Japanese Brown cattle, Yanbian cattle), Chinese yellow cattle (Luxi cattle, Nanyang cattle), European Bas taurus (Angus, Hereford, Charolais, Holstein, Limousin), African Bas taurus (N'Dama, Baoule), African Bas indicus (Kavirondo Zebu, White Fulani), Asian Bas indicus (Sahiwal, Nelore) and one Bali cattle, Bas banteng as an outbreed-reference population. Allele frequencies derived from the genotyping data were used in estimating heterozygosities, gene diversities and genetic distances. The microsatellite loci were highly polymorphic, with a total of 162 different alleles observed across all loci. Variability in allele numbers and frequencies was observed among the breeds. The average expected heterozygosity of North Eastern Asian breeds was higher than those of European and African taurines, but lower than those of Asian and African indicines. Genetic distances were estimated using Nei's DA genetic distance and the resultant DA matrix was used in the construction of the phylogenetic trees. The genetic distances between North Eastern Asian cattle breeds and Bas indicus were similar with those between European Bas taurus and Bas indicus, and African Bas taurus and Bas indicus, respectively. The clusters were clearly classified into North Eastern Asian, European and African taurines groups as well as different cluster with Chinese mainland breeds, firstly out-grouping with Bas indicus. These results suggest that Korean cattle, Hanwoo, had not been originated from a crossbred between Bas primigenius in Europe and Bas indicus in India and North Eastern Asian Bas taurus may be have separate domestication from European and African Bas taurus.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.1
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• pp.177-185
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• 2009

Cluster analysis or clustering is a kind of unsupervised learning method in which a set of data points is divided into a given number of homogeneous groups. Fuzzy clustering method, one of the most popular clustering method, allows a point to belong to all the clusters with different degrees, so produces more intuitive and natural clusters than hard clustering method does. Even more some of fuzzy clustering variants have noise-immunity. In this paper, we improved the Possibilistic Fuzzy C-Means (PFCM), which generates a membership matrix as well as a typicality matrix, using Gath-Geva (GG) method. The proposed method has a focus on the boundaries of clusters, which is different from most of the other methods having a focus on the centers of clusters. The generated membership values are suitable for the classification-type applications. As the typicality values generated from the algorithm have a similar distribution with the values of density function of Gaussian distribution, it is useful for Gaussian-type density estimation. Even more GG method can handle the clusters having different numbers of data points, which the other well-known method by Gustafson and Kessel can not. All of these points are obvious in the experimental results.

• Parasites, Hosts and Diseases
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• v.55 no.2
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• pp.149-158
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• 2017

Variant surface antigens (VSAs) encoded by pir families are considered to be the key proteins used by many Plasmodium spp. to escape the host immune system by antigenic variation. This attribute of VSAs is a critical issue in the development of a novel vaccine. In this regard, a population genetic study of vir genes from Plasmodium vivax was performed in the Republic of Korea (ROK). Eighty-five venous blood samples and 4 of the vir genes, namely vir 27, vir 21, vir 12, and vir 4, were selected for study. The number of segregating sites (S), number of haplotypes (H), haplotype diversity (Hd), DNA diversity (${\pi}$ and ${\Theta}_w$), and Tajima's D test value were conducted. Phylogenetic trees of each gene were constructed. The vir 21 (S=143, H=22, Hd=0.827) was the most genetically diverse gene, and the vir 4 (S=6, H=4, Hd=0.556) was the opposite one. Tajima's D values for vir 27 (1.08530, P>0.1), vir 12 (2.89007, P<0.01), and vir 21 (0.40782, P>0.1) were positive, and that of vir 4 (-1.32162, P>0.1) was negative. All phylogenetic trees showed 2 clades with no particular branching according to the geographical differences and cluster. This study is the first survey on the vir genes in ROK, providing information on the genetic level. The sample sequences from vir 4 showed a clear difference to the Sal-1 reference gene sequence, whereas they were very similar to those from Indian isolates.

• Asian Journal of Atmospheric Environment
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• v.11 no.2
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• pp.114-121
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• 2017

Real-time monitoring of hourly concentrations of atmospheric Radon-222 ($^{222}Rn$, radon) and some gaseous pollutants ($SO_2$, CO, $O_3$) was performed throughout 2013-2014 at Gosan station of Jeju Island, one of the cleanest regions in Korea, in order to characterize their background levels and temporal variation trend. The hourly mean concentrations of radon and three gaseous pollutants ($SO_2$, CO, $O_3$) over the study period were $2216{\pm}1100mBq/m^3$, $0.6{\pm}0.7ppb$, $211.6{\pm}102.0ppb$, and $43.0{\pm}17.0ppb$, respectively. The seasonal order of radon concentrations was as fall ($2644mBq/m^3$)$${\sim_\sim}$$winter ($2612mBq/m^3$)>spring ($2022mBq/m^3$)>summer ($1666mBq/m^3$). The concentrations of $SO_2$ and CO showed similar patterns with those of radon as high in winter and low in summer, whereas the $O_3$ concentrations had a bit different trend. Based on cluster analyses of air mass back trajectories, the air mass frequencies originating from Chinese continent, North Pacific Ocean, and the Korean Peninsula routes were 30, 18, and 52%, respectively. When the air masses were moved from Chinese continent to Jeju Island, the concentrations of radon and gaseous pollutants ($SO_2$, CO, $O_3$) were relatively high: $2584mBq/m^3$, 0.76 ppb, 225.8 ppb, and 46.4 ppb. On the other hand, when the air masses were moved from North Pacific Ocean, their concentrations were much low as $1282mBq/m^3$, 0.24 ppb, 166.1 ppb, and 32.5 ppb, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.685-691
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• 2020

In this study, an algorithm that recognizes numbers from 0 to 9 was developed using the data obtained after tracking hand movements using the echo signal of a millimeter-wave radar sensor at 77 GHz. The echo signals obtained from the radar sensor by detecting the motion of a hand gesture revealed a cluster of irregular dots due to the difference in scattering cross-sectional area. A valid center point was obtained from them by applying a K-Means algorithm using 3D coordinate values. In addition, the obtained center points were connected to produce a numeric image. The recognition rate was compared by inputting the obtained image and an image similar to human handwriting by applying the smoothing technique to a CNN (Convolutional Neural Network) model trained with MNIST (Modified National Institute of Standards and Technology database). The experiment was conducted in two ways. First, in the recognition experiments using images with and without smoothing, average recognition rates of 77.0% and 81.0% were obtained, respectively. In the experiment of the CNN model with augmentation of learning data, a recognition rate of 97.5% and 99.0% on average was obtained in the recognition experiment using the image with and without smoothing technique, respectively. This study can be applied to various non-contact recognition technologies using radar sensors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.62-71
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• 2017

This study classified cities across South Korea according to their urban characteristics, selecting representative cities for respective types, and drawing a relationship among urban characteristic elements, carbon emissions, and the energy consumption of cities. For the classification of cities, the elements of the urban characteristics were examined through a review of the related literature. Factor analysis was then carried out to select the variables from among these elements. The absolute coefficient value found in the analysis was set as a standard. A classification of cities across the country was performed using these variables, and representative cities were chosen for a comparison of the characteristics of each type. For an analysis of the relationships among the urban characteristics according to the type of city, the greenhouse gases, and the energy consumption of cities, emissions of greenhouse gases, electricity consumption, and oil consumption of the representative cities were compared and analyzed by correlation analysis. The analysis results indicated that the cause of greenhouse gas emissions and electricity consumption varies according to the elements of the characteristics of the representative cities, even when they show similar emissions and consumption.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1501-1514
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• 2008

The face shape extracted by the depth values has different appearance as the most important facial information. The face images decomposed into frequency subband are signified personal features in detail. In this paper, we develop a method for recognizing the range face images by multiple frequency domains for each depth image using the modified fuzzy c-mean algorithm. For the proposed approach, the first step tries to find the nose tip that has a protrusion shape on the face from the extracted face area. And the second step takes into consideration of the orientated frontal posture to normalize. Multiple contour line areas which have a different shape for each person are extracted by the depth threshold values from the reference point, nose tip. And then, the frequency component extracted from the wavelet subband can be adopted as feature information for the authentication problems. The third step of approach concerns the application of eigenface to reduce the dimension. And the linear discriminant analysis (LDA) method to improve the classification ability between the similar features is adapted. In the last step, the individual classifiers using the modified fuzzy c-mean method based on the K-NN to initialize the membership degree is explained for extracted coefficient at each resolution level. In the experimental results, using the depth threshold value 60 (DT60) showed the highest recognition rate among the extracted regions, and the proposed classification method achieved 98.3% recognition rate, incase of fuzzy cluster.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.23-30
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• 2006

A recommender system for E-commerce site receives information from customers about which products they are interested in, and recommends products that are likely to fit their needs. In this paper, we investigate several methods for large-scale product purchase data for the purpose of producing useful recommendations to customers. We apply the traditional data mining techniques of cluster analysis and collaborative filtering(CF), and CF with reduction of product-dimensionality by use of latent semantic indexing(LSI). If reduced product-dimensionality obtained from LSI shows a similar latent trend of customers for buying products to that based on original customer-product purchase data, we expect less computational effort for obtaining the nearest-neighbor for target customer may improve the efficiency of recommendation performance. From simulation experiments on synthetic customer-product purchase data, CF-based method with reduction of product-dimensionality presents a better performance than the traditional CF methods with respect to the recall, precision and F1 measure. In general, the recommendation quality increases as the size of the neighborhood increases. However, our simulation results shows that, after a certain point, the improvement gain diminish. Also we find, as a number of products of recommendation increases, the precision becomes worse, but the improvement gain of recall is relatively small after a certain point. We consider these informations may be useful in applying recommender system.