• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.820-827
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• 2014

One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.67-73
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• 2012

Local color transfer is the process of assigning a given color to a local region in a target image. The local region that contains the given color has to be segmented. Conventionally, the segmentation of the corresponding local region in a target image is based on the color distance. The region which is the closest in color distance is separated. However, since the close range of color distance separating a given color from target image is ambiguous and uncertain, color distortion is often generated around a separated local region. Therefore, this paper addresses the problem of segmentation in a local color transfer. To prevent color distortion, a modified color influence map is proposed with color categories. First, the target image is roughly segmented using a color category map, which groups similar colors in color space. It restricts the color transfer to a specific color category according to a given color. Second, modified color influence map assigning different weight to lightness and chroma, respectively, is used instead of Euclidian color distance. Then, by combining a modified color influence map and color category map filtered with anisotropic diffusion, a local region that contains a given color can be segmented more strictly than conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3172-3193
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• 2018

Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.

• Journal of Microbiology
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• v.34 no.3
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• pp.225-228
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• 1996

The cellular fatty acid methyl esters (FAMEs) analysis data obtained for clusters defined at a Euclidian distance of 17.5, in the classification of lactic acid bacteria isolated from kimchi, described by Lee et al. (4), was used for the identification of 79 Leuconostoc isolates. The test strains were isolated using a selective isolation medium specific for the genus Leuconostoc. These strains were then characterized according to their fatty acid profiles. The results show that all seventy nine test strains were identified to the known Leuconostoc clusters B, C, and D. Cluster B had the highest relative amount of the saturated fatty acid 16 : 0. The saturated fatty acid 16 : 0 and summed feature 9 were found as a major components in cluster C, which had a higher level of summed feature 9 than cluster B. Cluster D is characterized by the highest relative amount of the unsaturated fatty acid 18 : 1 w9c. It is suggested that FAMEs analysis can be successfully applied in the identification of lactic acid bacteria isolated from kimchi.

• Microbiology and Biotechnology Letters
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• v.24 no.2
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• pp.234-241
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• 1996

Two hundreds and thirty lactic acid bacteria, mostly isolated from Kimchi, including type strains were used for analysis of cellular fatty acids. The 230 test strains were recoverd in 7 major and 1 single clusters defined at Euclidian distance of 17.5. These aggregate taxa were equivalent to the genus Leuconostoc (aggregate group A, B, C and D), the genus Lactobacillus (aggregate group F), the genera Lactobacillus and Pediococcus (aggregate group E) and the genera Leuconostoc and Lactobacillus (aggregate group G). It is concluded as evident that FAMEs (Fatty Acid Methyl Esters) profile of cell can be used as a criterion in classification of lactic acid bacteria from kimchi. Additional comparative taxonomic studies need to be carried out on well chosen representative strains to determine the most appropriate methods of value.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2000.04a
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• pp.150-156
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• 2000

Oligotrophic bacteria isolated from forest soil showed a specific community consisting of various taxonomic groups compared with those in other soil or aquatic habitats. Based on the cell shape, the isolates were divided into four groups: regular rod, curved/spiral rod, irregular rod, and prosthecate bacteria. The cellular fatty acids 60 oligotrophic isolates were analyzed. The 30 fatty acids which were identified or characterized are classified. At the dendrogram based on cellular fatty acid composition, four clusters(I-IV) were separated at a euclidian distance of about 50. Cluster 3 and 4-a strains were containing Q-8, these strains are accommodated in the Proteobacteria gamma and beta subdivision. The chemotaxonomic profiles of the cluster 4-a strains showed good agreement with those of the genus Burkholderia. Cluster 3 was characterized by the presence of branched-chain fatty acids, iso-C15:0, iso-C17:1, and iso-C17:0 as the major components. These chemotaxonomy suggested the close relationship of the isolates with Xathomonas/Sterotrophomonas group. Based on the 16S rDNA sequence analysis, the two representative strains(MH256 and MA828) of cluster 3 showed the close relation to genera, Xathomonas/Sterotrophomonas, but were not included in these genera. These strains were even further away from core Xanthomonas, and clearly were seen to branch outside the cluster formed by the Sterotrophomonas maltophilia. MH256 and MA828 16S rDNA sequence was different enough to put new genus on a separate branch. The isolates with Q-10 were also studied. They are corresponded to the two large groups in Proteobacteria alpha subdivision. One was incorporated in the genus Bradyrhizobium cluster, which also includes Agromonas, a genus for oligotrophic bacteria. The strains of the other group showed high similarity to the genus Agrobacterium.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.227-234
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• 2018

Recently, stitching techniques are used for obtaining wide FOV, e.g., panorama contents, from normal cameras. Despite many proposed algorithms, the no objective quality evaluation method is developed, so the comparison of algorithms are performed only in subjective way. The paper proposes a 'Delaunay-triangulation based objective assessment method' for evaluating the geometric and photometric distortions of stitched or warped images. The reference and target images are segmented by Delaunay-triangulation based on matched points between two images, the average Euclidian distance is used for geometric distortion measure, and the average or histogram of PSNR for photometric measure. We shows preliminary results with several test images and stitching methods for demonstrate the benefits and application.

• Korean Journal of Medicinal Crop Science
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• v.13 no.1
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• pp.30-34
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• 2005

Polygonatum species are a useful medical crop in Korea but basic study in the species was not well conducted. The study was carried out to analyse genetic diversity and intraspecific relationship of 47 Polygonatum species collected from Gyeongnam province. Their analysis was done through principle component analysis and average linkage cluster analysis with their twelve morphological traits. The result of principle component analysis showed the Prin 1, Prin 2 and Prin 3 represented 79% of total variation. By the 0.7 average distance of the cluster analysis and the calculated Euclidian distance, the 47 collected species were grouped into five groups. Group I included 22 collected species representing P. ordoratum var. pluriflorum, group II did 5 ones representing P. involucratum, group III was divided into two subclasses, 2 species including P. inflatum and 7 species including P. thunbergii, group IV also consisted of 2 subclasses, a species similar to P. thunbergii and P.involucratum, respectively, and finally group V included 8 species representing P.lasianthum var. coreanum. meaning that the useful germplasms can be collected from relatively small area.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.37-46
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• 2013

Similarity measure of catchments is essential for regionalization studies, which provide in depth analysis in hydrological response and flood estimations at ungauged catchments. However, this similarity measure is often biased to the selected catchments and is not clearly explained in hydrological sense. This study applied a type of hydrological similarity distance measure-Flood Estimation Handbook to 25 Geum River catchments, Korea. Three Catchment Characteristics, Area(A)-Annual precipitation(SAAR)-SCS Curve Number(CN), are used in Euclidian distance measures. Furthermore, six index of Flow Duration Curve are applied to clustering analysis of SPSS. The catchments' grouping of hydrological similarity measures suggests three groups (H1, H2 and H3) and the four catchments are not grouped in this study. The clustering analysis of FDC provides four Groups; F1, F2, F3 and F4. The six catchments (out of seven) of H1 are grouped in F1, while Sangyeogyo is grouped in F2. The four catchments (out of six) of H2 are also grouped in F2, while Cheongju and Guryong are grouped in F1. The catchments of H3 are categorized in F1. The authors examine the results (H1, H2 and H3) of similarity measure based on catchment physical descriptors with results (F1 and F2) of clustering based on catchment hydrological response. The results of hydrological similarity measures are supported by clustering analysis of FDC. This study shows a potential of hydrological catchment similarity measures in Korea.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.4
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• pp.385-389
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• 2005

To understand the pollution level by polychlorinated biphenyls (PCBs) in ambient air of industrial area, PCBs concentrations were measured at Sihwa and Banwol industrial region, Korea. The concentrations of total PCB and WHO-TEQ ranged from 2,080 to $5820\;pg/m^3$ (median value is 2,760) and from 0.19 to $1.01\;pgTEQ/m^3$ (median value is 0.42), respectively. In terms of homologues composition the fraction of highly chlorinated biphenyls(from hexa-CB to deca-CB) were higher than the air samples of other regions such as jeonju and yokohama area. The cluster analysis was conducted to study the relation between the air samples and sources such as incinerator flue gases and Aroclor samples. The isomer fractions in the homologue were used as input variables. Based on the results, the industrial ambient air samples were divided from source samples with long Euclidian distance. This suggest that the ambient air samples of Sihwa and Banwol were not on the influence of Aroclor and incinerators. Therefore, further investigation on systematical air monitoring will be required to estimate the sources of PCBs in the above industrial areas.