• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.955-961
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• 2014

This study was carried out to investigate the amounts of vitamin C in 22 sweet potato cultivars cultivated in Korea as well as evaluate the effects of cooking methods on vitamin C contents. Methods for determining vitamin C was validated by determining linearity, specificity, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy using HPLC. Results showed high linearity in the calibration curve with a coefficient of correlation ($R^2$) of 0.9999. The LOD and LOQ values for ascorbic acid (AA) were 0.03 and $0.10{\mu}g/mL$, respectively. The relative standard deviations (RSDs) for intra- and inter-day precision of AA were less than 5%. The recovery rates of AA and dehydroascorbic acid (DHA) were in the range from 98.21~98.64 and 98.28~100.68%, respectively. Depending on cultivar, contents of AA, DHA, and total ascorbic acid (TA) in sweet potatoes varied in the range from 37.76 (Sinyulmi)~89.25 (Juhwangmin), 23.37 (Sinjami)~63.94 (Sinyulmi), and 68.52 (Sinjami)~115.95 (Juhwangmin) mg/100 g, respectively, and their average levels were $56.98{\pm}12.53$, $36.46{\pm}9.03$, and $93.44{\pm}12.00mg/100g$, respectively. The average TA levels were also dependent on flesh color, whish was significantly higher in general sweet potato and orange sweet potato than in purple sweet potato. Steaming, baking, and frying processes significantly reduced AA (10.61~58.41%), DHA (2.57~52.81%), and TA (14.54~49.92%) contents in sweet potatoes. The highest reduction of AA, DHA, and TA contents was observed after baking, followed by steaming and frying. We expect that the basic information provided by this study will be useful to plant breeders and food scientists.

• Journal of Food Hygiene and Safety
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• v.30 no.2
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• pp.143-149
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• 2015

This study was conducted to simultaneous analysis methods for water soluble vitamins B group (vitamin $B_1$, vitamin $B_2$, nicotinic acid, nicotinamide, vitamin $B_6$) which is used as health functional foods etc. Analytical methods of water-soluble vitamins B group by HPLC were established through instrumental analytical conditions, and the examination of data such as domestic and foreign reliable methods, and papers of journal. HPLC method analyzing water soluble vitamins B group was established using Capcell Pak C18 UG 120 column in 270 nm through test of columns. The validation has been performed on the method to determine linearity, accuracy, limits of quantification (LOQ) and repeatability for water soluble vitamins B group. An excellent linearity ($r^2=0.999$) was observed for vitamin $B_1$, vitamin $B_2$, nicotinic acid, nicotinamide, vitamin $B_6$ in the concentration range ($0.1{\sim}2{\mu}g/mL$). Observed recovery of vitamin $B_1$ was found to be between 100 and 103%, vitamin $B^2$ was found to be between 104 and 112%, nicotinic acid was found to be between 82 and 85%, nicotinamide was found to be between 121 and 124% and vitamin $B_6$ was found to be between 95 and 104%. LOQ of vitamin $B_1$ was found to be $0.04{\mu}g/mL$, vitamin $B_2$ was found to be $0.05{\mu}g/mL$, nicotinic acid was found to be $0.15{\mu}g/mL$, nicotinamide was found to be $0.08{\mu}g/mL$ and vitamin $B_6$ was found to be $0.63{\mu}g/mL$. Repeatability precision for vitamin $B_1$ was found to be 0.4%, vitamin $B_2$ was found to be 0.4%, nicotinic acid was found to be 0.5%, nicotinamide was found to be 0.7% and vitamin $B_6$ was found to be 0.4% relative standard deviation (RSD). Also, verify the accuracy of the simultaneous analysis methods, we monitored the labeled contents of the health functional foods and children's preferred foods.

• Korean Journal of Environmental Agriculture
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• v.34 no.4
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• pp.274-281
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• 2015

BACKGROUND: A lasting release of low levels of persistence chemicals including pesticides and pharmaceuticals into river has a bad influence on aquatic ecosystems and humans. The present study monitored pesticide residues in the Yeongsan and Seomjin river basins and their tributaries as a fundamental study for water quality standard of pesticides.METHODS AND RESULTS: Nine pesticides(aldicarb, carbaryl, carbofuran, chlorpyrifos, 2,4-D, MCPA, methomyl, metolachlor, and molinate) were determined from water samples using SPE-Oasis HLB(pH 2) and LC/MS/MS. Validation of the method was conducted through matrix-matched internal calibration curve, method detection limit(MDL), limit of quantification(LOQ), accuracy, precision, and recovery. MDLs of all pesticides satisfied the GV/10 values. Linearity(r²) was 0.9965- 0.9999, and a percentage of accuracy, precision, and recovery was 89.4-113.6%, 3.1-14.0%, and 90.8-106.2%, respectively. All pesticides exclusive of aldicarb were determined in the river samples, and there was a connection between the positive monitoring results and agricultural use of the pesticides.CONCLUSION: Monitoring outcomes of the present study implied that pesticides were a possible non-point pollutant source in the Yeongsan and Seomjin river basins and tributaries. Therefore, it is required to produce and accumulate more monitoring results on pesticides in river waters to set water quality standards, finally to preserve aquatic ecosystems.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.131-140
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• 2014

The objective of this study was to develop a simultaneous method of 8 penicillin antibiotics including amoxicillin, ampicillin, cloxacillin, dicloxacillin, nafcillin, oxacillin, penicillin G and penicillin V in meat using LC-MS/MS. The procedure involves solid phase extraction with HLB cartridge and subsequent analysis by LC-MS/MS. To optimize MS analytical condition of 8 compounds, each parameter was established by multiple reaction monitoring in positive ion mode. The chromatographic separation was achieved on a $C_{18}$ column with a mobile phase of 0.05% formic acid and 0.05% formic acid in acetonitrile at a flow rate of 0.2 mL/min for 20 min with a gradient elution. The developed method was validated for specificity, linearity, accuracy and precision in beef, pork and chicken. The recoveries were 71.0~106%, and relative standard deviations (RSD) were 4.0~11.2%. The limit of detection (LOD) and the limit of quantification (LOQ) were 0.003~0.008 mg/kg and 0.01~0.03 mg/kg, respectively, that are below maximum residue limit (MRL) of the penicillins. This study also performed survey of residual penicillin antibiotics for 193 samples of beef, pork and chicken collected from 9 cities in Korea. Penicillins were not found in all the samples except a sample of pork which contained cloxacillin (concentration of 0.08 mg/kg) below the MRL (0.3 mg/kg).

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.649-663
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• 2019

The 2018 United Nations Development Programme (UNDP) report announced that deforestation in North Korea is the most extreme situation and in terms of climate change, this deforestation is a global scale issue. To respond deforestation, various study and projects are conducted based on remote sensing, but access to public data in North Korea is limited, and objectivity is difficult to be guaranteed. In this study, the forest detection based on density estimation in statistic using Landsat imagery was conducted in Gangwon province which is the only administrative district divided into South and North. The forest spatial data of South Korea was used as data for the labeling of forest and Non-forest in the Normalized Difference Vegetation Index (NDVI), and a threshold (0.6658) for forest detection was set by Gaussian Probability Density Function (PDF) estimation by category. The results show that the forest area decreased until the 2000s in both Korea, but the area increased in 2010s. It is also confirmed that the reduction of forest area on the local scale is the same as the policy direction of urbanization and industrialization at that time. The Kappa value for validation was strong agreement (0.8) and moderate agreement (0.6), respectively. The detection based on the Gaussian PDF estimation is considered a method for complementing the statistical limitations of the existing detection method using satellite imagery. This study can be used as basic data for deforestation in North Korea and Based on the detection results, it is necessary to protect and restore forest resources.

• Journal of vocational education research
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• v.37 no.6
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• pp.36-60
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• 2018

The purpose of this study is to explore the occupational personality required for high school graduates and to develop a scale to measure them objectively. In order to achieve the purpose of the study, this study constituted the delphi committee composed of the teacher group and the industrial personnel group. Afterwards, Delphi survey was conducted twice, and it was found that 12 jobs such as sincerity and honesty were related to occupational personality. As a result of the development of the scale based on the previous research and the expert group interview, 12 factors and 116 scales were developed for the pre - occupational personality test tool. In order to verify the validity and reliability of the developed preliminary test tool, we conducted a questionnaire survey of 700 students of vocational high school, and 514 questionnaires were used for final analysis. Parallel analysis was performed to determine the number of factors before exploratory factor analysis. As a result, eight factors were found to be appropriate. As a result of exploratory factor analysis using the 'maximum likelihood method' and 'direct oblimin rotation method', 78 items of 8 factors were found appropriate. However, in order to confirm whether the item reflects the contents of the factors, we conducted a content validity test for the expert group. As a result, feedback was obtained that 19 items were irrelevant or inadequate. Therefore, the validity of the existing job personality test tool and the modified job personality test tool were verified through confirmatory factor analysis. As a result, the fitness of the revised test tool was higher and the fitness level was generally good.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1423-1444
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• 2022

In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.715-727
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• 2023

To provide detailed and appropriate meteorological information in mountainous areas, the Korea Forest Service has established an Automatic Mountain Meteorology Observation Station (AMOS) network in major mountainous regions since 2012, and 464 stations are currently operated. In this study, we proposed an optimal kriging technique with lapse rate correction to produce gridded temperature data suitable for Korean forests using AMOS point observations. First, the outliers of the AMOS temperature data were removed through statistical processing. Then, an optimized theoretical variogram, which best approximates the empirical variogram, was derived to perform the optimal kriging with lapse rate correction. A 500-meter resolution Kriging map for temperature was created to reflect the elevation variations in Korean mountainous terrain. A blind evaluation of the method using a spatially unbiased validation sample showed a correlation coefficient of 0.899 to 0.953 and an error of 0.933 to 1.230℃, indicating a slight accuracy improvement compared to regular kriging without lapse rate correction. However, the critical advantage of the proposed method is that it can appropriately represent the complex terrain of Korean forests, such as local variations in mountainous areas and coastal forests in Gangwon province and topographical differences in Jirisan and Naejangsan and their surrounding forests.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.