• Korean Journal of Ecology and Environment
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• v.33 no.3 s.91
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• pp.206-212
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• 2000

Since some cyanobacterial isolates under selective culturing conditions are lacking of characteristic specialized cells or showing altered morphology, the morpho-taxonomic criteria are not accurate enough to discriminate between species. Instead of morphological parameters, a method based on the single or the combination of repetitive oligonucleotides in a single PCR, repetitive oligonucleotides-primed PCR (ROP-PCR), was applied to generate DNA profiles for members of the cyanobacterial genera Anabaena and Oscillatoria, both of which are responsible for causing poisonous blooms in various freshwater systems. ROP-PCR performed on 10 isolates of the cyanobacteria with ERIC and REP sequences from gram-negative bacteria, STRR1A and LTRR sequences derived from cyanobacterial genome, and eukaryotic repetitive sequences, led to the identification of distinct genotypes, and provided specific and repeatable DNA fingerprints for cyanobacterial isolates. Grouping analysis of cyanobacterial isolates showed a signifiant difference depending on the primer used in PCR.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.547-555
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• 2019

The purpose of this study was to evaluate the usefulness of routine liver ultrasonography on the basis of the scoring system according to the morphological parameters of liver ultrasound images and the histopathological results of liver biopsy. The morphological parameters of the liver through ultrasonography were divided into liver surface, liver edge and liver parenchyma. Pathologic results of liver biopsy were classified as mild fibrosis(F1), significant fibrosis(F2), severe fibrosis(F3), and cirrhosis(F4). In conclusion, routine ultrasound examination showed a sensitive predictive factor for fibrosis with mild fibrosis (F1) to severe fibrosis (F3) were liver edge>liver parenchyma>liver surface. However, the predictive factors for detecting cirrhosis (F4) were liver parenchyma>liver surface>liver edge. The use of three variable combinations rather than individual variables in routine ultrasonography may be useful in evaluating the degree and progress of liver fibrosis.

• Journal of Forest and Environmental Science
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• v.40 no.1
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• pp.1-8
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• 2024

Recently, intensive research has been conducted to develop innovative methods for diagnosing plant diseases based on hyperspectral technologies. Hyperspectral analysis is a new subject that combines optical spectroscopy and image analysis methods, which makes it possible to simultaneously evaluate both physiological and morphological parameters. Among the physiological and morphological parameters are classifying healthy and diseased plants, assessing the severity of the disease, differentiating the types of pathogens, and identifying the symptoms of biotic stresses at early stages, including during the incubation period, when the symptoms are not visible to the human eye. Plant diseases cause significant economic losses in agriculture around the world as the symptoms of diseases usually appear when the plants are infected severely. Early detection, quantification, and identification of plant diseases are crucial for the targeted application of plant protection measures in crop production. Hence, this can be done by possible applications of hyperspectral sensors and platforms on different scales for disease diagnosis. Further, the main areas of application of hyperspectral sensors in the diagnosis of plant diseases are considered, such as detection, differentiation, and identification of diseases, estimation of disease severity, and phenotyping of disease resistance of genotypes. This review provides a deeper understanding, of basic principles and implementation of hyperspectral sensors that can measure pathogen-induced changes in plant physiology. Hence, it brings together critically assessed reports and evaluations of researchers who have adopted the use of this application. This review concluded with an overview that hyperspectral sensors, as a non-invasive system of measurement can be adopted in early detection, identification, and possible solutions to farmers as it would empower prior intervention to help moderate against decrease in yield and/or total crop loss.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.37-44
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• 2013

Concentrated localized torrential rains due to global warming and climate change have resulted in much water damage each year. GIS is used as a tool for predicting the peak-outflows caused by these regional torrential rains in mountainous rivers. However, the research of the resolution of the data is limited, and most of approaches are about hydrological geographic. This paper estimates the flood discharge needed for decision of standard rainfall of automatic rainfall warning system by using GIS with GcIUH model, and establishes the criteria of flash flood warning. It also has analyzed the terrain in river basin, extracted the morphological characteristics parameters of water shed such as stream width, channel slope, channel length, shape factor, and GcIUH parameters, and analyzed the relationship between them.

• Tribology and Lubricants
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• v.22 no.5
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• pp.276-281
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• 2006

The fractal dimension is quantitatively to define the irregular characteristic of the shape in natural. It can be useful in describing morphological characteristics of various wear particles. This paper was undertaken to diagnose failure condition for sliding members in lubrication by fractal dimension. It will be possible to diagnose wear mechanism, friction and damage state of machines through analysis of shape characteristics for wear particle on driving condition by fractal parameters. In this study, the calculating and analyzing methods of fractal dimensions were constructed for the condition monitoring and wear particle analysis in lubricant condition. So, we carried out the Friction and wear test with the ball on disk type tester, and the fractal parameters of wear particle in lubricated conditions were calculated. Fractal parameters were defined as texture fractal dimension ($D_{t}$), structure fractal dimension ($D_{s}$) and total fractal dimension (D).

• Journal of The Korean Astronomical Society
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• v.43 no.6
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• pp.191-200
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• 2010

We present the Korea Institute for Advanced Study Value-Added Galaxy Catalog (KIAS VAGC), a catalog of galaxies based on the Large Scale Structure (LSS) sample of New York University Value-Added Galaxy Catalog (NYU VAGC) Data Release 7. Our catalog supplements redshifts of 10,497 galaxies with 10 < $r_P\;{\leq}\;17.6$ (1455 with 10 < $r_P\;{\leq}\;14.5$) to the NYU VAGC LSS sample. Redshifts from various existing catalogs such as the Updated Zwicky Catalog, the IRAS Point Source Catalog Redshift Survey, the Third Reference Catalogue of Bright Galaxies, and the Two Degree Field Galaxy Redshift Survey have been put into the NYU VAGC photometric catalog. Our supplementation significantly improves spectroscopic completeness: the area covered by the spectroscopic sample with completeness higher than 95% increases from 2.119 to 1.737 sr. Our catalog also provides morphological types of all galaxies that are determined by the automated morphology classification scheme of Park & Choi (2005), and related parameters, together with fundamental photometry parameters supplied by the NYU VAGC. Our catalog contains matches to objects in the Max Planck for Astronomy (MPA) & Johns Hopkins University (JHU) spectrum measurements (Data Release 7). This new catalog, the KIAS VAGC, is complementary to the NYU VAGC and MPA-JHU catalog.

• Textile Coloration and Finishing
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• v.35 no.2
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• pp.121-127
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• 2023

In this study, a comprehensive investigation was conducted on the morphological and property changes of laser-induced nanocarbon (LINC) as a function of laser process parameters. LINC was formed on the surfaces of polyimide films with different backbone structures under various process conditions, including laser power, scan speed, and resolution. Three different forms of LINC electrodes (i.e., continuous 3D porous graphene, wooly nanocarbon fibers, line cut) were formed depending on the laser power and scan speed. Furthermore, heteroatom doping induced from the chemical structure of the polyimide during laser patterning was found to be effective in modifying the electrical properties of LINC electrodes. The LINC surfaces exhibited different microstructures depending on the laser beam resolution under constant laser power and scan speed, allowing for controllable surface wettability. The correlation between the chemical structure of the polymer substrate, laser process parameters, and carbonized surface properties in this study is expected to be utilized as fundamental understanding for the manufacturing of next-generation carbon-based electronic devices.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.547-553
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• 2008

We propose a two-stage document layout segmentation method. At the first stage, as top-down segmentation, morphological distance map algorithm extracts a collection of rectangular regions from a given input image. This preliminary result from the first stage is employed as input parameters for the process of next stage. At the second stage, a machine-learning algorithm is adopted RBF network, one of neural networks based on statistical model, is selected. In order for constructing the hidden layer of RBF network, a data clustering technique bared on the self-organizing property of Kohonen network is utilized. We present a result showing that the supervised neural network, trained by 300 number of sample data, improves the preliminary results of the first stage.