• The Journal of Bigdata
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• v.6 no.2
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• pp.61-70
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• 2021

The objective of this study was to describe specific approaches for data extraction from graph when statistical information is not directly reported in some articles, enabling data intergration and meta-analysis for quantitative data synthesis. Particularly, meta-analysis is an important analysis tool that allows the right decision making for evidence-based medicine by systematically and objectively selects target literature, quantifies the results of individual studies, and provides the overall effect size. For data integration and meta-analysis, we investigated the strength points about the introduction and application of Adobe Acrobet Reader and Python-based Jupiter Lab software, a computer tool that extracts accurate statistical figures from graphs. We used as an example data that was statistically verified throught an previous studies and the original data could be obtained from ClinicalTrials.gov. As a result of meta-analysis of the original data and the extraction values of each computer software, there was no statistically significant difference between the extraction methods. In addition, the intra-rater reliability of between researchers was confirmed and the consistency was high. Therefore, In terms of maintaining the integrity of statistical information, measurement using a computational tool is recommended rather than the classically used methods.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.55-62
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• 2023

Internal erosion is one of the main causes of levee damage and collapse, and representative of this is backward erosion piping. This type of internal erosion accounts for one-third of the damage to levees, meaning it is important to predict and prevent it. In this work, experiments were conducted with the aim of detecting piping in advance by using a tracer. Experiments were undertaken by changing the head difference, soil diameter, and the installation of the cutoff wall. A tracer was injected twice, once at the beginning of the experiment and once after the piping occurred. A key finding was that the piping process significantly affectedthe concentration variation of the tracer in a soil layer. Hence, a tracer concentration curve monitored at downstream could provide information about piping occurrence. It is expected that the results of this study can be used to prevent levee damage and collapse caused by piping.

• Analytical Science and Technology
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• v.19 no.5
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• pp.383-388
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• 2006

Simple post-wash method by ion chromatography (IC) was established for the rapid and precise determination of fluoride ion in wastewater from mine in fluorite mineralized area. High sulfate in sample was retained in a pre-column and less strongly held fluoride ion was transferred to the principal separation system using modified conventional IC with switching technique. An analytical column with high capacity (AS 9 HC) was used as a pre-column to retain the amount of high sulfate. A guard column (AG 14) as a separation column was used to increase the response of fluoride and reduce the system pressure. According to the recovery of fluoride ion with one detector and the observation of sulfate peak with another conductivity detector, the optimum switching time of 10-port chromatographic injector was 4.3 min. The limit of detection (S/N = 3) of fluoride in synthetic solution containing $500mg\;L^{-1}$ sulfate was $2.4{\mu}g/L$, with $25{\mu}L$ sample volume.

• Analytical Science and Technology
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• v.19 no.6
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• pp.498-503
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• 2006

A type of dimethyl disulfide gas CRM in the ppb level was developed for the analysis of tracelevel odorous gas in environmental atmosphere. The concentration of dimethyl disulfide($(CH_3)_2S_2$) was $10{\mu}mol/mol$ level in the cylinder filled with nitrogen, 1500 psi. And the variability of the concentration for 2 years was about 0.14% due to the adsorption or instability of $(CH_3)_2S_2$. The gas standards produced simultaneously in 4 bottles and examined by GC-FID were shown with 0.4%, reproducibility of preparation and 0.25%, standard uncertainty due to weighing and purity. The relative expended uncertainty of 1.1%(95% of confidence level, k=2) was assigned to the certified value of $10{\mu}mol/mol$ level of $(CH_3)_2S_2$ after quantitative evaluation on the purity, mixing, weighing, analysis, adsorption and stability of dimethyl sulfide gas.

• Analytical Science and Technology
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• v.22 no.4
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• pp.326-335
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• 2009

A specific analytical method able to identify and quantify traces of six glucocorticoids residues in eggs were developed. The extraction and clean-up parameters for simultaneous analysis were evaluated and HPLC and spectrometric conditions were also established. For determination of glucocorticoids, 5 g of egg was transferred into a test tube, adjusted pH 5.2 with acetate buffer and was $\beta$-glucuronidase/arylsulfatase from Helix pomatia added. The mixture was centrifuged and supernatant was extracted twice with 20 mL n-hexane. The extraction was performed with HLB cartridge using methanol, followed by clean-up with silica cartridge using methanol/ethyl acetate (4/6, v/v). The analytes were determined by HPLC/ESI-MS/MS operating in the negative ion mode. Validation studies with fortified egg samples for established method were performed. The result of method validation gave good efficiency, linearity, accuracy and precision. The correlation coefficients ($r^2$) of the calibration curves appeared to be higher than 0.99 in egg, indicating excellent linearity. LOD was ranged 0.09 to $0.17{\mu}g/kg$, and recoveries for most compounds were in the range of 55.7-69.8%. This method can be used to determine ${\mu}g/kg$ levels of glucocorticoids in eggs.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.83-91
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• 2023

In this paper, we propose a robustness sensitivity index (RSI) of highway networks to analyze the effect of congestion in a specific section on the entire highway. The newly proposed RSI is defined as the change in the total mileage of the transportation network per extended unit length when the length of a particular section is extended. When the RSI value is large, traffic congestion in the section has a worse effect on the entire network than in other sections. The existing network robustness index (NRI) simply observes changes in transportation networks with and without specific sections, but the RSI proposed in this study is a kind of performance indicator that allows quantitative analysis of the ripple effect of the entire network according to the degree of congestion in a specific section. While changing the degree of congestion in a particular section, it is possible to calculate how the traffic volume increases, decreases, and the size and location of the congestion section change. This analysis proves the superiority of RSI as it cannot be analyzed with NRI. Various properties of RSI are analyzed using data from the domestic highway network. In addition, using the RSI concept, it is shown that the ripple effect on other sections in which a change in the degree of congestion of a specific section occurs can be analyzed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5A
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• pp.901-908
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• 2006

The structural integrity of containment building in Nuclear Power Plants has to be verified by the ISI(In Service Inspection) because there are some variations on the structural behavior of it due to the change of the physical properties of concrete and tendon with the lapse of time. In this study, the program 'SAPONC-CANDU' which can monitor and analyze the structural behavior of the containment building with grouted tendon (CANDU-type, 'Wolsong unit-2, 3, and 4' in Korea) was developed. This program is based on the algorithm which can calculate the prediction values of the quantities of strain variation for the vibrating-wire strain gauges embedded into the concrete of the containment building under temperature and time dependent factors which are creep, shrinkage, and prestressing force. The readings of the strain gauges are used as input data for the operation of the program. And it finally provides graphically a prediction value, line and band of the quantity of strain variation for the respective strain gauges, therefore, it is thought that the site engineers are able to assess the structural integrity of the domestic containment building with grouted tendon with easy using this program.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.493-504
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• 2023

The Republic of Korea is located far from the boundary of the earthquake plate, and the intra-plate earthquake occurring in these areas is generally small in size and less frequent than the interplate earthquake. Nevertheless, as a result of investigating and analyzing earthquakes that occurred on the Korean Peninsula between the past two years and 1904 and earthquakes that occurred after observing recent earthquakes on the Korean Peninsula, it was found that of a magnitude of 9. In this paper, the Korean Peninsula Historical Earthquake Record (2 years to 1904) published by the National Meteorological Research Institute is used to analyze the relationship between earthquakes on the Korean Peninsula and statistical self-similarity. In addition, the problem solved through this paper was the first to investigate the relationship between earthquake data occurring on the Korean Peninsula and statistical self-similarity. As a result of measuring the degree of self-similarity of earthquakes on the Korean Peninsula using three quantitative estimation methods, the self-similarity parameter H value (0.5 < H < 1) was found to be above 0.8 on average, indicating a high degree of self-similarity. And through graph visualization, it can be easily figured out in which region earthquakes occur most often, and it is expected that it can be used in the development of a prediction system that can predict damage in the event of an earthquake in the future and minimize damage to property and people, as well as in earthquake data analysis and modeling research. Based on the findings of this study, the self-similar process is expected to help understand the patterns and statistical characteristics of seismic activities, group and classify similar seismic events, and be used for prediction of seismic activities, seismic risk assessments, and seismic engineering.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.