• Journal of Food Hygiene and Safety
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• v.33 no.2
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• pp.118-123
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• 2018

The objective of this study was to develop a sensitive method for the identification and determination of nitrovin in fishery products by using a solid-phase extraction (SPE), as performed with a liquid chromatography-tandem mass spectrometry (LC-MS/MS). The samples were extracted with a mixture of acetonitrile and water, and were then defatted with acetonitrile saturated hexane, after which further clean-up was accomplished with SPE on the hydrophilic-lipophilic balance (HLB) cartridges. The analytes were subsequently ionized in the positive mode of an electrospray ionization (ESI), and where thereby detected in a process of multiple reaction monitoring (MRM). The linearity (expressed as correlation coefficients) of the matrix calibration curves was > 0.985. The limit of the quantification for the nitrovin was measured at 0.001 mg/kg. The accuracy (expressed as average recovery) was noted between 72.1 and 122%. The precision (expressed as coefficient variation) was noted from 2.9 to 16.9%. According to the CODEX CAC/GL-71 guideline accuracy, precision, linearity, and limit of detection were determined in three matrices (which were flatfish, eel and shrimp). The proposed method was suitable for analyzing the associated nitrovin residues. This application and result can also be a factor to contribute to the non-detection drugs management in fishery products.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.109-114
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• 2012

Honeycombs are dense structures that small cysts, which generally have about 2~10 mm in diameter, are surrounded by the wall of fibrosis. When honeycomb is found in the patients, the incidence of acute exacerbation is generally very high. Thus, the observation and quantitative measurement of honeycomb are considered as a significant marker for clinical diagnosis. In this point of view, we propose an automatic segmentation method using morphological image processing and assessment of the degree of clustering techniques. Firstly, image noises were removed by the Gaussian filtering and then a morphological dilation method was applied to segment lung regions. Secondly, honeycomb cyst candidates were detected through the 8-neighborhood pixel exploration, and then non-cyst regions were removed using the region growing method and wall pattern testing. Lastly, final honeycomb regions were segmented through the extraction of dense regions which are consisted of two or more cysts using cluster analysis. The proposed method applied to 80 High resolution computed tomography (HRCT) images and achieved a sensitivity of 89.4% and PPV (Positive Predictive Value) of 72.2%.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.1
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• pp.117-123
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• 2007

HPLC quantifications of fresh and cooked (steamed/microwaved) spinach, one of the most frequently consumed vegetables in foodservice operations, were carried out to determine carotenoids compositions. An S-3 $\mu$m C30 stationary phase for reversed-phase columns with diode-array detection was used to separate and quantify geometric isomers of provitamin A carotenoids in the fresh and cooked spinach. The carotenoids in fresh spinach were identified and quantified: Lutein (63.0%), $\beta$-carotene isomers (all-trans 29.6%, 9-cis 3.2%, 13-cis 1.8%, $\alpha$-carotene 0.4%, zeaxanthin 2.1%) and cryptoxanthin. Cryptoxanthin, detected in a trace amount in HPLC, was not quantified in this study. Lutein was little affected by cooking methods and frozen conditions. 9-cis and 13-cis-$\beta$-carotene isomers were major types formed during cooking. Cooking (steam/microwave) did not alter carotenoid profiles of the samples, but the amounts of carotenoids quantified were greater than those in the fresh samples. Heat treatment such as steaming increased total carotenoids contents, especially trans-$\beta$-carotene (p<0.05). The carotenoid contents of the frozen spinach increased even after the microwaved treatment (p<0.05). These increases were likely to result from the increased extraction efficiency and inactivation of enzymes capable of carotenoids degrading during the heat treatments.

• Journal of Ginseng Research
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• v.26 no.2
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• pp.79-84
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• 2002

In this study, cell cracker method as a non-collision method was evaluated for the possibility in manufacturing red ginseng powder. In color value of red ginseng powder, the L values indicating brightness were 68.18 for hammer mill (group A) and 72.08 for cell cracker (group B). The a values (redness) and b values (yellowness) were 4.21 26.56 for group A and 5.73, 28.36 for group B, respectively. As an extraction time increased, the absorbances at 420 nm of water extract of both groups were increased. In the loose bulk density, tapped bulk density and volume reduction radio indication the of powder in group A were less than those in group B. In both groups, the angles of side of red ginseng powder were shown less value than the angles of side of the powder. These two angles in group A were lets than those in group B. In sensory evaluation, the touchness between both groups was, not observed significant difference. In the contrary, the color and flavor, main factors affecting the overall quality of red ginseng powder product of group B were shown superior to those of group A. The overall preference of group B was shown higher than that of group A.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.225-231
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• 2021

Sesame seed oil cakes are classified as the animal or plant origin among the flammable liquids, and the fire occurs due to the spontaneous ignition through the accumulation of heat during the storage of residues after the extraction of sesame oil. In order to elucidate the cause of the spontaneous ignition of sesame seed oil cakes, the thickness (3 cm, 5 cm, 7 cm and 14 cm) of the sample container was varied, and the spontaneous ignition temperature was measured depending on the storage volume. Thus, the spontaneous ignition temperature was measured to be 180 ℃ at the thickness of 3 cm, 160 ℃ at 5 cm, 145 ℃ at 7 cm and 130 ℃ at 14 cm. As the thickness of the sample container increased, the critical ignition temperature decreased, and the induction time to spontaneous ignition and the time to reach the maximum temperature became longer. Furthermore, the apparent activation energy by the critical ignition temperature, which is the average temperature of ignition and non-ignition, was 97.10 [kJ/mol]. With these data, ignition characteristics of sesame seed oil cakes were determined.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.61-70
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• 2022

General users who use smartphone apps often use the Vault app to protect personal information such as photos and videos owned by individuals. However, there are increasing cases of criminals using the Vault app function for anti-forensic purposes to hide illegal videos. These apps are one of the apps registered on Google Play. This paper proposes a methodology for extracting feature points through XML-based keyword frequency analysis to explore Vault apps used by criminals, and text mining techniques are applied to extract feature points. In this paper, XML syntax was compared and analyzed using strings.xml files included in the app for 15 hidden Vault anti-forensics apps and non-hidden Vault apps, respectively. In hidden Vault anti-forensics apps, more hidden-related words are found at a higher frequency in the first and second rounds of terminology processing. Unlike most conventional methods of static analysis of APK files from an engineering point of view, this paper is meaningful in that it approached from a humanities and sociological point of view to find a feature of classifying anti-forensics apps. In conclusion, applying text mining techniques through XML parsing can be used as basic data for exploring hidden Vault anti-forensics apps.

• The Journal of Engineering Geology
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• v.32 no.3
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• pp.377-388
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• 2022

Recently, several studies have utilized machine learning to efficiently and accurately analyze seismic data that are exponentially increasing. In this study, we expand earthquake information such as occurrence time, hypocentral location, and magnitude to produce a dataset for applying to machine learning, reducing the dimension of the expended data into dominant features through principal component analysis. The dimensional extended data comprises statistics of the earthquake information from the Global Centroid Moment Tensor catalog containing 36,699 seismic events. We perform data preprocessing using standard and max-min scaling and extract dominant features with principal components analysis from the scaled dataset. The scaling methods significantly reduced the deviation of feature values caused by different units. Among them, the standard scaling method transforms the median of each feature with a smaller deviation than other scaling methods. The six principal components extracted from the non-scaled dataset explain 99% of the original data. The sixteen principal components from the datasets, which are applied with standardization or max-min scaling, reconstruct 98% of the original datasets. These results indicate that more principal components are needed to preserve original data information with even distributed feature values. We propose a data processing method for efficient and accurate machine learning model to analyze the relationship between seismic data and seismic behavior.

• Journal of Environmental Impact Assessment
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• v.31 no.5
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• pp.296-309
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• 2022

This study investigated the mobility of inorganic elements (As, Cd, Pb, and Zn) that existed as acid extractable and reducible forms in flooded soils with a pot experiment involving rice cultivation. In general, it is known that soil inorganic elements that existed as an acid extractable form which includes exchangeable, carbonates, non-specifically sorbed, and specifically sorbed have mobility. However, the result of the experiment revealed that each inorganic elements of rice roots grown from flooded soils had different characteristics. The concentrations of Arsenic existed as both forms and the concentrations of cadmium and lead existed as a reducible form in the soils showed a high causal relationship with the concentrations of those elements in the roots of rice plants. The concentrations of zinc, an essential plant element, didn't show a causal relationship. Therefore it is necessary to consider the soil's environmental characteristics such as drained/flooded condition, oxidation/reduction condition, etc. for the mobility assessment of inorganic elements. The concentrations of the reducible form of arsenic, cadmium, and lead in flooded environment such as a paddy field should be also considered because the mobility of these elements combined with Fe/Mn increases in the reduction condition.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.51-57
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• 2021

If a company's actions to save or avoid taxes are judged to be tax evasion rather than legal tax action by the tax authorities, the company will not only pay tax but also non-tax costs such as damage to corporate image and stock price decline due to a series of tax evasion-related news articles. Therefore, this study measures the frequency of occurrence of tax evasion controversial keywords in internet news portal as a factor to measure the severity of the case, and analyzes the effect of the frequency of occurrence on corporate value. In the Korean stock market, we crawl related articles from internet news portal by using keywords that are controversial for tax evasion targeting top companies based on market capitalization, and generate a time series of the frequency of occurrence of keywords about tax evasion by company and analyze the effect of frequency of appearance on book value versus market capitalization. Through panel regression and impulse response analysis, it is analyzed that the frequency of appearance has a negative effect on the market capitalization and the effect gradually decreases until 12 months. This study examines whether the tax evasion issue affects the corporate value of Korean companies and suggests that it is necessary to take these influences into account when entrepreneurs set up tax-planning schemes.