• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.714-723
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• 2020

This study was conducted to investigate the community stability and similarity of benthic macroinvertebrates in the Giran stream between August and September 2018, and compare results to those reported by Lee (2004). As relates to the total number of species in each taxon in 2018, 45 species were additionally discovered compared to the 2003 study; the number of EPT taxa increased by 14 species and OCH taxa increased by 18 species. The diversity and richness indexes increased while the dominance index tended to decrease. According to analysis of functional feeding groups, 11 more Gathering-collector species were found, making it the highest functional feeding group with 24 species. According to analysis of functional habitat groups, 15 more clinger species were found than in the past, making it the highest functional habitat group with 41 species. A community stability comparison showed that species belonging to 'Stability Group I' had the highest stability rate at 57.1% in 2003 and 61.5% in 2018. According to the biological water quality assessment, in 2018, the average water quality level at each survey site was 'Ia' and 'Very Good' in terms of environmental conditions. As a result of the similarity analysis between the survey points for the species that appeared, two large groups of similarities were classified (similarity group 1: 2003 sites, similarity group 2: 2018 sites).

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.664-672
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• 2009

Recently, studies on utilizing tensor expression on image data analysis and processing have been attracting much interest. The purpose of this study is to develop an efficient system for classifying image patterns by using second order tensor expression. To achieve the goal, we propose a data generation model expressed by class factors and environment factors with second order tensor representation. Based on the data generation model, we define a function for measuring similarities between two images. The similarity function is obtained by estimating the probability density of environment factors using a matrix normal distribution. Through computational experiments on a number of benchmark data sets, we confirm that we can make improvement in classification rates by using second order tensor, and that the proposed similarity function is more appropriate for image data compared to conventional similarity measures.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.808-816
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• 2004

This paper proposes the method of implementation of practical online face verification system based on multiple feature combination and a similarity space. The main issue in face verification is to deal with the variability in appearance. It seems difficult to solve this issue by using a single feature. Therefore, combination of mutually complementary features is necessary to cope with various changes in appearance. From this point of view, we describe the feature extraction approaches based on multiple principal component analysis and edge distribution. These features are projected on a new intra-person/extra-person similarity space that consists of several simple similarity measures, and are finally evaluated by a support vector machine. From the experiments on a realistic and large database, an equal error rate of 0.029 is achieved, which is a sufficiently practical level for many real- world applications.

• Journal of Microbiology and Biotechnology
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• v.17 no.6
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• pp.945-951
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• 2007

DNA-DNA hybridization has been established as an important technology in bacterial species taxonomy and phylogenetic analysis. In this study, we analyzed how the efficiency with which the genomic DNA from one species hybridizes to the genomic DNA of another species (DNA-DNA hybridization) in microarray analysis relates to the similarity between two genomes. We found that the predicted DNA-DNA hybridization based on genome sequence similarity correlated well with the experimentally determined microarray hybridization. Between closely related strains, significant numbers of highly divergent genes (>55% identity) and/or the accumulation of mismatches between conserved genes lowered the DNA-DNA hybridization signal, and this reduced the hybridization signals to below 70% for even bacterial strains with over 97% 16S rRNA gene identity. In addition, our results also suggest that a DNA-DNA hybridization signal intensity of over 40% indicates that two genomes at least shared 30% conserved genes (>60% gene identity). This study may expand our knowledge of DNA-DNA hybridization based on genomic sequence similarity comparison and further provide insights for bacterial phylogeny analyses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1199-1206
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• 2015

This paper introduces an algorithm for computing similarity between two poses in the motion capture data with different scale of skeleton, different number of joints and different joint names. The proposed algorithm first performs the topological analysis on the skeleton hierarchy for classifying the joints into more meaningful groups. The global joints positions of each joint group then are aggregated into a point cloud. The number of joints and their positions are automatically adjusted in this process. Once we have two point clouds, the algorithm finds an optimal 2D transform matrix that transforms one point cloud to the other as closely as possible. Then, the similarity can be obtained by summing up all distance values between two points clouds after applying the 2D transform matrix. After some experiment, we found that the proposed algorithm is able to compute the similarity between two poses regardless of their scale, joint name and the number of joints.

• Korean Journal of Cognitive Science
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• v.23 no.3
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• pp.295-322
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• 2012

In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

• Korean Journal of Environmental Biology
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• v.31 no.3
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• pp.225-231
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• 2013

To study the characteristics of rocky intertidal invertebrate fauna on the coastal areas of the East Sea, seven regions including Dokdo, Ulleungdo, Gyeongju, Pohang, Yeongdeok, Uljin, and Gangwondo, the common species ratio (%) and similarity index using Bray-Curtis similarity matrix were calculated. The contributed species for dissimilarity between Dokdo and the other East Sea's coastal areas were selected by using SIMPER. The common species ratio and the cluster analysis showed that Ulleungdo presented the highest similarity. However, Yeongdeok showed the highest similarity in the eastern costal areas, and Gangwondo showed the lowest one. However the cluster analysis revealed the discrimination of the rocky intertidal invertebrate community on Dokdo with others region caused by the particularity of rocky shores exposed to strong wave action and by the particular distribution of rocky intertidal invertebrate fauna in Dokdo.

• Journal of Korean Society of Forest Science
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• v.21 no.1
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• pp.47-51
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• 1974

In order to prove the similarity relationships between the basic species of oak through Electronic Data Processing System(EDPS) and numerical analysis, The analized species and datas were selected from the list of morphological observation in the thesis of T.B. Lee, 1961, "Phytogenetic study of the subgenus Lepidobalanus of the genus Quercus in Korea", and were coded by categories shown in Table 1. The value in the list were transformed into hundred percentage to standardize the observational value by each code into dimensionless. The similarity index between species were computed through formula of non-metric coefficient, $N_{jk}=\sum\limits_{i=1}^{n}\(\frac{{\mid}x_{ij}-x_{ik}{\mid}}{x_{ij}+x_{ik}}\)$, using the UNiVAC-1106, at National Computer Center. Quercus aliena, by analysis result, is most similar to Q. mongolica with the similarity index, 71.6 and Q. dentata is most far apart from Q. serrata in the relationship with index, 121.4. The above thesis of Professor, T. Lee, are closely similar with the result of this research study. But, their similar relationship are proved in quantity through numerical method in our research study. In addition, The relationships among Q. mongolica, Q. aliena and Q. serrata are found to be very similar, but Q. dentata to be enough far in similarity to other species by dendrogram shown at Fig. 1. The numerical classification through EDPS is found to be suitable method also applicable to the plant taxonomy.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.120-125
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• 2016

Usually, a risk can be expressed as a product of likelihood and consequence of a hazard factor. Therefore, conventional risk assessment is carried out by frequency analysis and severity analysis, in turns. However, it is well known that intuitive thinking is another excellent way of thinking of human beings. This study aimed to confirm whether there exist any difference in risk assessment results derived by two different procedures - intuitive and analytical. Thus, the present study showed 10 different illustrations to 30 undergraduate students. Their responses were organized as fuzzy membership functions, and summarized as risk assessments, and compared. The results were also verified with the help of statistical hypothesis testing, which showed no significant difference. On the contrary, however, similarity measure used in fuzzy set theory was not credible as anticipated. Many cases failed to satisfy statistical hypothesis even with similarity measure higher than 0.60 so that only a trend could be accepted. In addition, a subject showed a somewhat consistent logical discrepancy in his response, which implied the necessity of sincere analysis in fuzzy formulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.101-106
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• 2012

Ship handling simulator is a virtual ship navigating system with three dimensional screen system and simulation programs. FTS simulation can produce theoretically infinite experiment tests without time constraint, but which results in collecting determinstic observations. RTS simulation can collect statistical observations but has disadvantage of spending at least 30 minutes for a single experiment. The previous studies suggested that the number of experiment conditions to be tested could be reduced to obtain random data with RTS simulation by focusing on highly difficult experiment condition for ship handling. It has the limitation of not estimating the distribution of ship handling difficulty for the route. In this paper, similarity and clustering analysis are suggested for reduction methodology of experiment conditions. Similarity of experiment conditions are measured as follows: euclidean distance of ship handling difficulty index and correlation matrix of distance differences from the designed route. Clustering analysis and multi-dimensional scaling are applied to classify experiment conditions with measured similarity into reducing the number of RTS simulation conditions. An empirical result on Dangin harbor is shown and discussed.