• Journal of Animal Reproduction and Biotechnology
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• v.38 no.4
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• pp.209-214
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• 2023

Background: Single nucleotide polymorphisms (SNPs) are widely used genetic markers with applications in human disease diagnostics, animal breeding, and evolutionary studies, but existing genotyping methods can be labor-intensive and costly. The aim of this study is to develop a simple and rapid method for identification of a single nucleotide change. Methods: A modified Polymerase Chain Reaction Amplification of Multiple Specific Alleles (PAMSA) and high resolution melt (HRM) analysis was performed to discriminate a bovine polymorphism in the NCAPG gene (rs109570900, 1326T > G). Results: The inclusion of tails in the primers enabled allele discrimination based on PCR product lengths, detected through agarose gel electrophoresis, successfully determining various genotypes, albeit with some time and labor intensity due to the use of relatively costly high-resolution agarose gels. Additionally, high-resolution melt (HRM) analysis with tailed primers effectively distinguished the GG genotype from the TT genotype in bovine muscle cell lines, offering a reliable way to distinguish SNP polymorphisms without the need for time-consuming AS-PCR. Conclusions: Our experiments demonstrated the importance of incorporating unique mismatched bases in the allele-specific primers to prevent cross-amplification by fragmented primers. This efficient and cost-effective method, as presented here, enables genotyping laboratories to analyze SNPs using standard real-time PCR.

• Tribology and Lubricants
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• v.40 no.1
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• pp.24-27
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• 2024

A monotype valve body for a dual clutch transmission has the potential to reduce costs, weight, and manufacturing time by modularizing various parts, including those of existing solenoid packs and valve bodies, into one through the application of super-precision die casting technology. However, this approach may lead to challenges such as reduced rigidity and increased interference due to modularization and compactness, impacting both product performance due to the reduced weight as well as durability and reliability. Unlike existing products, this approach requires a high-precision thin-wall block to avoid more complicated flow line formation, interference between flow lines, and leaks, as well as a strict quality requirement standard and precise inspections including detection of internal defects. To conduct precise inspections, we built an equivalent model corresponding to a driving distance of 300,000 km. Testing involved simulating actual road loads using a real vehicle and a chassis dynamometer in the FTP-75 mode (EPA Federal Test Procedure). The aim of the study was to establish a vehicle load-based part durability model for manufacturing a mono-type valve body and to develop fundamental technology for part weight reduction through preliminary design by introducing analytical weight reduction technology based on the derived results.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• Economic and Environmental Geology
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• v.40 no.5
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• pp.563-574
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• 2007

Laser induced breakdown spectroscopy (LIBS) is a recently developed analytical technique that is based upon the measurement of emission lines generated by atomic species close to the surface of the sample, thus allowing their chemical detection, identification and quantification. With powerful advantages of LIBS compared to the conventional analytical methodology, this technique can be applied in the detection of heavy metals in the field. LIBS allows the rapid analysis by avoiding laborious chemical steps. LES have already been applied for the determination of element concentration in a wide range of materials in the solid, liquid and gaseous phase with simplicity of the instrument and diversity of the analytical application. These feasibility of rapid multi elemental analysis are appealing proprieties for the in-situ analytical technique in geochemical investigation, exploration and environmental analysis. There remain still some limitations to be solved for LIBS to be applied in soil environment as an in-situ analytical technology. We would like to provide the basic principle related to the plasma formation and laser-induced breakdown of sample materials. In addition, the matrix effect, laser properties and the various factors affecting on the analytical signal of LIBS was dealt with to enhance understanding of LIBS through literature review. Ultimately, it was investigated the feasibility of LIBS application in soil environment monitoring by considering the basic idea to enhance the data quality of LIBS including the calibration method for the various effects on the analytical signal of LIBS.

• Journal of the Korean Chemical Society
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• v.54 no.4
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• pp.451-459
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• 2010

The fluorescence detection of intracellular metal ions are high interest in the fields of organic molecular chemistry and cellular biology. This study was purposed to detection for mercury and zinc in the cell using fluorescent chemosensor (FS). FS exhibits a weak fluorescence, but emits strong fluorescence upon Zn$^{2+}$ complexation. The increased fluorescence of the 2FS/Zn$^{2+}$ can be quenched completely by addition of only 1 equiv of Hg$^{2+}$ with the formation of complex FS-Hg$^{2+}$. Four cell lines (LLC-MK2, Hela, HT29 and AMC-HN3) were used for fluorescence imaging by confocal microscope. The cell viability MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was evaluated after cell treatment of FS, Zn$^{2+}$, FS-Zn$^{2+}$, Hg$^{2+}$ on LLC-MK2 cell line. The cytotoxicity of FS was showed to viability over 80%. This study has shown that FS can be detected for selective imaging of Zn$^{2+}$ and Hg$^{2+}$ in living cells.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.836-841
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• 2016

An indoor positioning system using Wi-Fi is essential to produce a radio map that combines the indoor space of two or more dimensions, the information of node positions, and etc. in processing for constructing the radio map, the measurement of the received signal strength indicator(RSSI) and the confirmation of node placement information counsume substantial time. Especially, when the installed wireless environment is changed or a new space is created, easy installation of the node and fast indoor radio mapping are needed to provide indoor location-based services. In this paper, to reduce the time consumption, we propose an algorithm to distinguish the straight and curve lines of a corridor section by RSSI visualization and Sobel filter-based edge detection that enable accurate node deployment and space analysis using cable-type Wi-Fi node installed at a 3 m interval. Because the cable type Wi-Fi is connected by a same power line, it has an advantage that the installation order of nodes at regular intervals could be confirmed accurately. To be able to analyze specific sections in space based on this advantage, the distribution of the signal was confirmed and analyzed by Sobel filter based edge detection and total RSSI distribution(TRD) computation through a visualization process based on the measured RSSI. As a result to compare the raw data with the performance of the proposed algorithm, the signal intensity of proposed algorithm is improved by 13.73 % in the curve section. Besides, the characteristics of the straight and the curve line were enhanced as the signal intensity of the straight line decreased by an average of 34.16 %.

• Geophysics and Geophysical Exploration
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• v.22 no.3
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• pp.107-115
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• 2019

Recently, since earthquakes have happened frequently in Gyeongju and Pohang areas in Korea, the earthquake detection research gets lots of attention. Geophysical monitoring data have been changed during the earthquake activity because the huge amount of energy is accumulated. The change of telluric current can be predicted by both of piezoelectric and electrokinetic effects before or during the earthquake occurrence, and if the change value exceeds the conventional telluric current noise, we can measure changes in the electric field associated with earthquakes. In this study, we have self-developed and verified the system that can monitor the telluric current. In order to verify our telluric current monitoring system, we installed lines of 40 m (E-W direction) and 28 m (N-S direction) on the site in Pohang. The telluric currents were sampled at 1 kHz for about a month. We have compared and analyzed the data of earthquake signals and electrical noises based on the earthquakes that occurred during the monitoring period. We have monitored if there were significant signals related to the earthquake on measured time series data. Through this study, we will suggest the direction of continuous research in the future.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.78-88
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• 2024

Ship-radiated noise received by passive sonar that can measure underwater noise can be identified and classified ship using Detection of Envelope Modulation on Noise (DEMON) analysis. However, in a low Signal-to-Noise Ratio (SNR) environment, it is difficult to analyze and identify the target frequency line containing ship information in the DEMONgram. In this paper, we conducted a study to extract target frequency lines using semantic segmentation among deep learning techniques for more accurate target identification in a low SNR environment. The semantic segmentation models U-Net, UNet++, and DeepLabv3+ were trained and evaluated using simulated DEMONgram data generated by changing SNR and fundamental frequency, and the DEMONgram prediction performance of DeepShip, a dataset of ship-radiated noise recordings on the strait of Georgia in Canada, was compared using the trained models. As a result of evaluating the trained model with the simulated DEMONgram, it was confirmed that U-Net had the highest performance and that it was possible to extract the target frequency line of the DEMONgram made by DeepShip to some extent.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.359-368
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• 2002

In this paper, we propose effective boundary line extraction algorithm for moving objects by matching error image and moving vectors, and fast tracking algorithm for moving object by partial boundary lines. We extracted boundary line for moving object by generating seeds with probability distribution function based on Watershed algorithm, and by extracting boundary line for moving objects through extending seeds, and then by using moving vectors. We processed tracking algorithm for moving object by using a part of boundary lines as features. We set up a part of every-direction boundary line for moving object as the initial feature vectors for moving objects. Then, we tracked moving object within current frames by using feature vector for the previous frames. As the result of the simulation for tracking moving object on the real images, we found that tracking processing of the proposed algorithm was simple due to tracking boundary line only for moving object as a feature, in contrast to the traditional tracking algorithm for active contour line that have varying processing cost with the length of boundary line. The operations was reduced about 39% as contrasted with the full search BMA. Tracking error was less than 4 pixel when the feature vector was $(15\times{5)}$ through the information of every-direction boundary line. The proposed algorithm just needed 200 times of search operation.

• BMB Reports
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• v.38 no.6
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• pp.703-708
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• 2005

We cloned and expressed human pyridoxal-5'-phosphate (PLP) phosphatase, the coenzymatically active form of vitamin $B_6$, in Escherichia coli using pET15b vector. Monoclonal antibodies (mAb) were generated against purified human brain PLP phosphatase in mice, and four antibodies recognizing different epitopes were obtained, one of which inhibited PLP phosphatase. The binding affinities of these four mAbs to PLP phosphatase, as determined using biosensor technology, showed that they had similar binding affinities. Using the anti-PLP phosphatase antibodies as probes, we investigated their cross-reactivities in various mammalian and human tissues and cell lines. The immunoreactive bands obtained on Western blots had molecular masses of ca. 33 kDa. Similarly fractionated extracts of several mammalian cell lines all produced a single band of molecular mass 33 kDa. We believe that these PLP phosphatase mAbs could be used as valuable immunodiagnostic reagents for the detection, identification, and characterization of various neurological diseases related to vitamin $B_6$ abnormalities.