• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.2
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• pp.77-83
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• 2006

Ultrasonic nonlinearity has been considered as a solution for the detection of microcracks or interfacial delamination in a layered structure. The distinguished phenomenon in nonlinear ultrasonics is the generation of higher-order harmonic waves during the propagation. Therefore, in order to quantify the nonlinearity, the conventional method measures a parameter defined as the amplitude ratio of a second-order harmonic component and a fundamental frequency component included in the propagated ultrasonic wave signal. However, its application In field inspection is not easy at the present stage because no standard methodology has yet been made to accurately estimate this parameter. Thus, the aim of this paper is to propose an advanced signal processing technique for the precise estimation of a nonlinear ultrasonic parameter, which is based on power spectral and bispectral analysis. The method of estimating power spectrum and bispectrum of the pulse-like ultrasonic wave signal used in the commercial SAM (scanning acoustic microscopy) equipment is especially considered in this study The usefulness of the proposed method Is confirmed by experiments for a Newton ring with a continuous air gap between two glasses and a real semiconductor sample with local delaminations. The results show that the nonlinear parameter obtained tv the proposed method had a good correlation with the delamination.

• Korean Journal of Food Science and Technology
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• v.41 no.3
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• pp.339-344
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• 2009

Concentrations of polycyclic aromatic hydrocarbon (PAH) in processed chestnut products were determined by HPLC/FLD. The methodology involved procedures of sonication with water, extraction with hexane, and clean-up on a Sep-pak florisil cartridge. The PAH limits of detection (LOD) and limits of quantitation (LOQ) ranged from 0.012 to 0.382 ${mu}g/kg$ and from 0.042 to 1.273 ${mu}g/kg$, respectively. The coefficients of variation for intra- and inter-day assays were 0.02-4.48% and 0.37-9.83%, respectively, and the accuracies were 81.95-125.44% and 79.89-116.53%, respectively. The overall recoveries for eight PAHs spiked into the processed chestnut products ranged from 87.83 to 100.56%. As a result, PAH contents were not detected in the processed chestnut products.

• Korean Journal of Construction Engineering and Management
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• v.11 no.1
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• pp.88-100
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• 2010

As the competition between companies are deepened, the number of companies adopting six sigma principles, which is one of the innovative management strategies, are increasing. According to this trend, the changes in both strategies and methodologies of six sigma are continuous. However, the evaluations and the management principles included in the process after the six sigma applications are insufficient, and the cooperation between the parties in the company is also not enough because the application process of six sigma is too complex and not efficient. In order to solve this problem, a research for developing the methodology which can learn about and do six sigma applications is so necessary, specifically for expanding the six sigma applications and introducing the participation of all company members. The purpose of this study, therefore, was to develop and present more efficient Six Sigma applied process by reducing the existing unnecessary steps in improvement one, by applying the examination method of wasteful elements on the potential factors, through analyzing the Six Sigma DMAIC applied case in the construction industry. The result of those application showed that the detection of potential factors using wasting elements was possible in measurement step and that it was possible for the improved process with reduced steps compared to existing process while to remain the outcomes. It is considered that the performance rate of Six Sigma project will be improved significantly because the reduction in the improvement step does not affect the improvement effect within the whole Six Sigma project.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.43-59
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• 2017

This study presents the prediction methodology of debris flow occurrence areas using the SINMAP model. Former studies used a single calibration region applying some of the soil test results to predict debris flow occurrence in SINMAP model, which couldn't subdivide the soil properties for the target areas. On the other hands, a multi-calibration region using a detailed soil map and soil strength parameters (c, ${\phi}$) for each soil series to make up for limitation of former studies is proposed. In this process, soils with soil erodibility factor (K) are classified into three types: 1) gravel and gravelly soil. 2) sand and sandy soil, and 3) silt and clay. In addition, T/R estimation method using mean elevation of target area instead of T/R method using actual occurrence time is suggested in this study. The suggested method is applied to Seobyeok-1 ri area, Bonghwa-gun where debris flow occurred. As a result of comparison between two T/R estimation method, both T/R estimations are almost equal. Therefore, the suggested methodologies in this study will contribute to set up the national-wide mitigation plan against debris flow occurrence.

• YAKHAK HOEJI
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• v.57 no.2
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• pp.87-94
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• 2013

An analytical methodology based on solid-space extraction (SPE) with with Bond Elut Certify cartridge (Varian, 130 mg) has been developed for the qualification and quantitation of strychnine in blood. After the elution layer was evaporated, the residue was reconstituted with methanol for GC/MS. Internal standard was used 10 mg/l dextromethorphan. Strychnine is a potent central nervous stimulant and convulsant, and an alkaloid found in seeds of Strychnos nux-vomica. It was used therapeutically to improve circulation and muscle tone in oral or intramuscular doses of 0.05~8 mg. The fatal dose of strychnine for humans is 50~100 mg. A man was found dead lying curled up the corner of the large room in a roof house after the fire fighter opened a locked door inside to put out the fire. The postmortem blood and gastric contents were analyzed for toxicological testing. Strychnine and brucine were detected using GC/MS first in gastric contents extracts. The contents of strychnine was 0.083 mg/l in heart blood, 0.088 mg/l in peripheral blood and 4.0 mg/kg in gastric contents, respectively. Method validation was carried out in terms of linearity, accuracy, precision (intraday, interday) in blood. The assay is linear over 0.05~10 mg/l ($r^2$=0.999). Limit of detection (LOD) and limit of quantitation (LOQ) in blood were determined 0.02 mg/l (S/N=3) and 0.07 mg/l (S/N=10), respectively. Accuracy (bias%) of strychnine with 0.1, 1 and 10 mg/l was 12.0% (n=6), 9.3% (n=6) and 6.9% (n=6), respectively. Intraday precision (CV%) of strychnine with, 0.1, 1 and 10 mg/l were 6.4%, 10.4%, 1.2% (n=6), respectively. Interday precision (CV%) of strychnine with 0.1, 1 and 10 mg/l over three days were 24.0%, 18.5%, 13.8% (n=18), respectively. Relative recovery with 0.1, 1 and 10 mg/l (in blood) were 114.9%, 99.3% and 87.4% (n=6), respectively. The described method can be applied in forensic toxicology to determine strychnine in blood samples.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.811-822
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• 2005

Automated text categorization is to classify free text documents into predefined categories automatically and whose main goals is to reduce considerable manual process required to the task. The researches to improving the text categorization performance(efficiency) in recent years, focused on enhancing existing classification models and algorithms itself, but, whose range had been limited by feature based statistical methodology. In this paper, we propose RTPost system of different style from i.ny traditional method, which takes fault tolerant system approach and data mining strategy. The 2 important parts of RTPost system are reinforcement training and post-processing part. First, the main point of training method deals with the problem of defining category to be classified before selecting training sample documents. And post-processing method deals with the problem of assigning category, not performance of classification algorithms. In experiments, we applied our system to documents getting low classification accuracy which were laid on a decision boundary nearby. Through the experiments, we shows that our system has high accuracy and stability in actual conditions. It wholly did not depend on some variables which are important influence to classification power such as number of training documents, selection problem and performance of classification algorithms. In addition, we can expect self learning effect which decrease the training cost and increase the training power with employing active learning advantage.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.170-181
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• 2015

A research on extracting croplands located nearby coastal areas using the spatial information data sets is the important task for managing the agricultural products in coastal areas. This research aims to extract the various croplands(croplands on mountains and croplands on plain areas) located nearby coastal areas using the KOMPSAT-2 imagery, the high-resolution satellite imagery, and the airborne topographic LiDAR(Light Detection And Ranging) data acquired in coastal areas of Uljin, Korea. Firstly, the NDVI(Normalized Difference Vegetation Index) imagery is generated from the KOMPSAT-2 imagery, and the vegetation areas are extracted from the NDVI imagery by using the appropriate threshold. Then, the DSM(Digital Surface Model) and DEM(Digital Elevation Model) are generated from the LiDAR data by using interpolation method, and the CHM(Canopy Height Model) is generated using the differences of the pixel values of the DSM and DEM. Then the plain areas are extracted from the CHM by using the appropriate threshold. The low slope areas are also extracted from the slope map generated using the pixel values of the DEM. Finally, the areas of intersection of the vegetation areas, the plain areas and the low slope areas are extracted with the areas higher than the threshold and they are defined as the croplands located nearby coastal areas. The statistical results show that 85% of the croplands on plain areas and 15% of the croplands on mountains located nearby coastal areas are extracted by using the proposed methodology.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.219-231
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• 2019

The specifications of signboards are set for each type of signboards, but the shape and size of the signboard actually installed are not uniform. In addition, because the colors of the signboard are not defined, so various colors are applied to the signboard. Methods for recognizing signboards can be thought of as similar methods of recognizing road signs and license plates, but due to the nature of the signboards, there are limitations in that the signboards can not be recognized in a way similar to road signs and license plates. In this study, we proposed a methodology for recognizing plate-type signboards, which are the main targets of illegal and old signboards, and automatically extracting areas of signboards, using the deep learning-based Faster R-CNN algorithm. The process of recognizing flat type signboards through signboard images captured by using smartphone cameras is divided into two sequences. First, the type of signboard was recognized using deep learning to recognize flat type signboards in various types of signboard images, and the result showed an accuracy of about 71%. Next, when the boundary recognition algorithm for the signboards was applied to recognize the boundary area of the flat type signboard, the boundary of flat type signboard was recognized with an accuracy of 85%.

• Journal of Environmental Health Sciences
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• v.47 no.1
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• pp.64-77
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• 2021

Objective: Biological monitoring of trace elements in human blood samples has become an important indicator of the health environment. The purpose of this study was to detect and evaluate multiple metal items in blood samples based on ICP-MS, to perform comparative evaluation with the existing analysis method, and to develop and verify a new method. Methods: 100 μL of whole blood from 80 healthy subjects was used to analyze ten metals (Sb, tAs, Cd, Pb, Mn, Hg, Mo, Ni, Se, Tl) using ICP-MS. Verification of the analysis method included calculation of linearity, accuracy, precision and detection limits. In addition, a comparative test with the conventional graphite furnace atomic absorption spectroscopy (GF-AAS) method was performed. In the case of Pb, Cd, and Hg in whole blood, cross-analysis between Pb, Cd, and Hg analysis methods was performed to confirm the difference between the existing method and the new method (ICP-MS). Results: The coefficient of determination (R2) was 0.999 or higher in seven items and 0.995 or higher in three items. The Pb result showed that Pearson's correlation coefficient was very high at 0.983, and the intraclass correlation coefficient was 0.966. The Cd result showed that Pearson's correlation coefficient was 0.917 between the existing method and the new analysis concentration value. Its intraclass correlation coefficient was 0.960, and there was no significant difference between the two groups. Hg had a low correlation at 0.687, and the intraclass correlation coefficient was 0.761, which was lower than that of Pb and Cd. The intra-day and inter-day accuracy of Pd and Cd were satisfactory, but Hg did not meet the criteria for both accuracy and precision when compared with the conventional analysis method. Conclusion: This study can be meaningful in that it proposes a more efficient and feasible analysis method by verifying a blood heavy metal concentration experiment using multiple simultaneous analyses. All samples were processed and analyzed using the new ICP-MS. It was confirmed that the agreement between the two methods was very high, with the agreement between the current and new methods being 0.769 to 0.998. This study proposes an efficient simultaneous methodology capable of analyzing multiple elements with small samples. In the future, studies of various applications and the reliability of ICP-MS analysis methods are required, and research on the verification of accurate, precise, and continuous analysis methods is required.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.52-63
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• 2021

In previous research, the coastal wetlands were detected by using the vegetation indices or land cover classification maps derived from the multispectral bands of the satellite or aerial imagery, and this approach caused the various limitations for detecting the coastal wetlands with high accuracy due to the difficulty of acquiring both land cover and topographic information by using the single remote sensing data. This research suggested the efficient methodology for detecting the coastal wetlands using the sentinel-2 satellite image and SRTM(Shuttle Radar Topography Mission) DEM (Digital Elevation Model) acquired in Gomsoman Bay, west coasts of South Korea through the following steps. First, the NDWI(Normalized Difference Water Index) image was generated using the green and near-infrared bands of the given Sentinel-2 satellite image. Then, the binary image that separating lands and waters was generated from the NDWI image based on the pixel intensity value 0.2 as the threshold and the other binary image that separating the upper sea level areas and the under sea level areas was generated from the SRTM DEM based on the pixel intensity value 0 as the threshold. Finally, the coastal wetland map was generated by overlaying analysis of these binary images. The generated coastal wetland map had the 94% overall accuracy. In addition, the other types of wetlands such as inland wetlands or mountain wetlands were not detected in the generated coastal wetland map, which means that the generated coastal wetland map can be used for the coastal wetland management tasks.