• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.403-410
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• 2004

Recently, studies of image analysis, as the preprocessing stage for medical image analysis or image retrieval, are actively carried out. This paper intends to propose a way of utilizing color components for image retrieval. For image retrieval, it is based on color components, and for analysis of color, CLCM (Color Level Co-occurrence Matrix) and statistical techniques are used. CLCM proposed in this paper is to project color components on 3D space through geometric rotate transform and then, to interpret distribution that is made from the spatial relationship. CLCM is 2D histogram that is made in color model, which is created through geometric rotate transform of a color model. In order to analyze it, a statistical technique is used. Like CLCM, GLCM (Gray Level Co-occurrence Matrix)[1] and Invariant Moment [2,3] use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. However, even though GLCM and Invariant Moment are optimized in each domain, it is impossible to perfectly interpret irregular data available on the spatial coordinates. That is, GLCM and Invariant Moment use only the basic statistical techniques so reliability of the extracted features is low. In order to interpret the spatial relationship and weight of data, this study has used Principal Component Analysis [4,5] that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles.

• Smart Media Journal
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• v.5 no.2
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• pp.15-23
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• 2016

In this paper we propose the depth-poselets using body-part-poses and also propose the method to recognize the gesture. Since the gestures are composed of sequential poses, in order to recognize a gesture, it should emphasize to obtain the time series pose. Because of distortion and high degree of freedom, it is difficult to recognize pose correctly. So, in this paper we used partial pose for obtaining a feature of the pose correctly without full-body-pose. In this paper, we define the 16 gestures, a depth image using a learning image was generated based on the defined gestures. The depth poselets that were proposed in this paper consists of principal three-dimensional coordinates of the depth image and its depth image of the body part. In the training process after receiving the input defined gesture by using a depth camera in order to train the gesture, the depth poselets were generated by obtaining 3D joint coordinates. And part-gesture HMM were constructed using the depth poselets. In the testing process after receiving the input test image by using a depth camera in order to test, it extracts foreground and extracts the body part of the input image by comparing depth poselets. And we check part gestures for recognizing gesture by using result of applying HMM. We can recognize the gestures efficiently by using HMM, and the recognition rates could be confirmed about 89%.

• Journal of Microbiology and Biotechnology
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• v.27 no.10
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• pp.1808-1819
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• 2017

Knowledge on the functional characteristics and temporal variation of anaerobic bacterial populations is important for better understanding of the microbial process of two-stage anaerobic reactors. However, owing to the high diversity of anaerobic bacteria, close attention should be prioritized to the frequently abundant bacteria that were defined as core bacteria and putatively functionally important. In this study, using MiSeq sequencing technology, the core bacterial community of 98 operational taxonomic units (OTUs) was determined in a two-stage upflow blanket filter reactor treating pharmaceutical wastewater. The core bacterial community accounted for 61.66% of the total sequences and accurately predicted the sample location in the principal coordinates analysis scatter plot as the total bacterial OTUs did. The core bacterial community in the first-stage (FS) and second-stage (SS) reactors were generally distinct, in that the FS core bacterial community was indicated to be more related to a higher-level fermentation process, and the SS core bacterial community contained more microbes in syntrophic cooperation with methanogens. Moreover, the different responses of the FS and SS core bacterial communities to the temperature shock and influent disturbance caused by solid contamination were fully investigated. Co-occurring analysis at the Order level implied that Bacteroidales, Selenomonadales, Anaerolineales, Syneristales, and Thermotogales might play key roles in anaerobic digestion due to their high abundance and tight correlation with other microbes. These findings advance our knowledge about the core bacterial community and its temporal variability for future comparative research and improvement of the two-stage anaerobic system operation.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• International Journal of Industrial Entomology and Biomaterials
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• v.37 no.1
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• pp.1-8
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• 2018

The nerippe fritillary butterfly, Argynnis nerippe, is listed as an endangered species in Korea. Establishment of effective conservation strategies can be aided by the development and application of molecular markers that can be used to investigate the population genetics of the butterfly. Therefore, in this study, we identified ten microsatellite markers specific to A. nerippe using the Next-Seq 500 platform, and applied these markers to investigate the characteristics of five South Korean butterfly populations. Genotyping of 48 A. nerippe individuals from five localities showed that at each locus the number of alleles ranged from 4 to 14, and that the observed and expected heterozygosities were 0.324-0.863 and 0.138-0.985, respectively. Significant deviation from the Hardy-Weinberg equilibrium was not observed at any locus. Population structure analysis indicated that there are two genetic groups in Korea, but no population-based gene pool assignments were found. Analysis of $F_{ST}$, $R_{ST}$, and a principal coordinates analysis suggested that the Gureopdo and Yaecheon populations were isolated from other populations. Genetic isolation of the Gureopdo population may be a consequence of unequal population change between Gureopdo and inland populations and to the offshore habitat of Gureopdo. Genetic isolation of the Yaecheon population may be a consequence either of the southernmost location of the population or of the limited sample size available. Further studies with increased sample sizes will be necessary to draw robust conclusions on population isolation and to devise conservation strategies.

• Animal Systematics, Evolution and Diversity
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• v.36 no.2
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• pp.154-158
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• 2020

The Asian crested ibis Nipponia nippon is one of the world's most endangered species. Except for the Sanxii population from China, it is known that all of the crested ibis populations from East Asia have been extinguished. In these days, most of them are being inbred as captive populations in China, South Korea, and Japan, which caused their low expected genetic diversity. Microsatellite markers are well known as a suitable DNA marker for exploring genetic diversity among captive populations of a variety of endangered species. In the present study, ten microsatellite markers were developed for the captive populations of the South Korean crested ibis, which were employed to examine the level of genetic diversity with the two founders from Sanxii, China and the 70 descendants of them. As a result, the mean number of gene diversity, observed heterozygosity, and expected heterozygosity of the captive population were 0.70, 0.84, and 0.70 respectively. It revealed that the captive population of South Korea is as genetically more stable than we expected. In addition, the principal coordinates analysis and genetic structure analyses showed that the captive population of N. nippon can be divided into the two different genetic groups. The developed microsatellite markers here could be helpful for crested ibis conservation in East Asian countries such as China and Japan as well as South Korea.

• Journal of Biosystems Engineering
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• v.35 no.4
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• pp.257-261
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• 2010

Surface energy is the principal factor of anti-condensation. High surface energy appears hydrophilic itself and low surface energy represents hydrophobic itself. The contact angle is widely being used for measurement of surface energy of materials, evaluation of coating performances, measurement of wettability, and so on. However, the existing contact angle measuring system is so expensive for purchasing and complicated, so it takes a lot of time and money to use. This study was conducted to develop the algorithm for evaluating hydrophilic performance through measuring the contact angle of water droplet automatically, and fabricate relatively simple measuring system using a low-cost monochrome camera and image processing. A constant amount of water was firstly allocated on a slide by a micropipette, and then the image of water droplet was captured by monochrome digital camera and sent to a computer. The image was binarized and then reduced noises by labeling. Finally, the contact angle of water droplet was computed by using three points (left, right, and top coordinates), simple linear mathematics, and trigonometric function. The experimental results demonstrated the accuracy and reproducibility of the developed system showing less deviations and deviation ratio.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.1
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• pp.100-110
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• 2017

Objective: The gastrointestinal tract of sheep contain complex microbial communities that influence numerous aspects of the sheep's health and development. The objective of this study was to analyze the composition and diversity of the microbiota in the gastrointestinal tract sections (rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon, and rectum) of sheep. Methods: This analysis was performed by 454 pyrosequencing using the V3-V6 region of the 16S rRNA genes. Samples were collected from five healthy, small tailed Han sheep aged 10 months, obtained at market. The bacterial composition of sheep gastrointestinal microbiota was investigated at the phylum, class, order, family, genus, and species levels. Results: The dominant bacterial phyla in the entire gastrointestinal sections were Firmicutes, Bacteroidetes, and Proteobacteria. In the stomach, the three most dominant genera in the sheep were Prevotella, unclassified Lachnospiraceae, and Butyrivibrio. In the small intestine, the three most dominant genera in the sheep were Escherichia, unclassified Lachnospiraceae, and Ruminococcus. In the large intestine, the three most dominant genera in the sheep were Ruminococcus, unclassified Ruminococcaceae, and Prevotella. R. flavefaciens, B. fibrisolvens, and S. ruminantium were three most dominant species in the sheep gastrointestinal tract. Principal Coordinates Analysis showed that the microbial communities from each gastrointestinal section could be separated into three groups according to similarity of community composition: stomach (rumen, reticulum, omasum, and abomasum), small intestine (duodenum, jejunum, and ileum), and large intestine (cecum, colon, and rectum). Conclusion: This is the first study to characterize the entire gastrointestinal microbiota in sheep by use of 16S rRNA gene amplicon pyrosequencing, expanding our knowledge of the gastrointestinal bacterial community of sheep.

• Journal of Microbiology and Biotechnology
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• v.30 no.7
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• pp.1067-1071
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• 2020

To understand the formation of initial gut microbiota, three initial fecal samples were collected from two groups of two breast milk-fed (BM1) and seven formula milk-fed (FM1) infants, and the compositional changes in gut microbiota were determined using metagenomics. Compositional change analysis during week one showed that Bifidobacterium increased from the first to the third fecal samples in the BM1 group (1.3% to 35.1%), while Klebsiella and Serratia were detected in the third fecal sample of the FM1 group (4.4% and 34.2%, respectively), suggesting the beneficial effect of breast milk intake. To further understand the compositional changes during progression from infancy to childhood (i.e., from three weeks to five years of age), additional fecal samples were collected from four groups of two breast milk-fed infants (BM2), one formula milk-fed toddler (FM2), three weaning food-fed toddlers (WF), and three solid food-fed children (SF). Subsequent compositional change analysis and principal coordinates analysis (PCoA) revealed that the composition of the gut microbiota changed from an infant-like composition to an adult-like one in conjunction with dietary changes. Interestingly, overall gut microbiota composition analyses during the period of progression from infancy to childhood suggested increasing complexity of gut microbiota as well as emergence of a new species of bacteria capable of digesting complex carbohydrates in WF and SF groups, substantiating that diet type is a key factor in determining the composition of gut microbiota. Consequently, this study may be useful as a guide to understanding the development of initial gut microbiota based on diet.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.