• Journal of Food Hygiene and Safety
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• v.35 no.3
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• pp.225-233
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• 2020

By the standards and specifications for hygiene products, three test methods for formaldehyde are specified for each item type of hygiene product. After derivatization using acetylacetone and 2,4-dinitrophenylhydrazine (2,4-DNPH), formaldehyde is analyzed by spectrophotometer and high-performance liquid chromatography (HPLC). Validation of the three test methods was performed on tissue, diaper lining and waterproof layer, and panty liner products. The results of linearity (R²), limit of detection (LOD), limit of quantification (LOQ), recovery rate (%) and reproducibility (%), showed that all three methods are suitable for analyzing formaldehyde in hygiene products. After derivatization with 2,4-DNPH and cetylacetone, formaldehyde was analyzed at 0, 3, 6, 9, 24 and 48 hours by HPLC. Formaldehyde derivatized with 2,4-DNPH showed no statistically significant change in formaldehyde peak area over time (P>0.05). But, acetylacetone-derivatizated formaldehyde showed a negative correlation coefficient (r) over time (P<0.01). We investigated the residual amounts of formaldehyde in 205 hygiene products distributed in Busan. Among 74 disposable diaper products tested, 73 had low concentrations of formaldehyde (0.13-29.87 mg/kg). Moreover, formaldehyde was not detected in any of 78 tissue, 27 disposable paper towel, 12 disposable dishcloth, 7 paper cup, one brand of paper straw and 6 disposable napkin products.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.121-139
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• 2014

Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.269-277
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• 2014

The multiclass pesticide multiresidue method for the simultaneous determination of diflubenzuron in agricultural products was conducted by using HPLC-UVD. The method was validated through the guidelines of linearity, specificity, limit of detection (LOD), limit of quantification (LOQ), accuracy and precision with pesticide-free spinach, Korean cabbage, eggplant, squash, sweet pepper, cucumber, Korean melon. The calibration curve of diflubenzuron was linear over the concentration range of 0.05-5 mg/kg with correlation coefficient of above 0.99999. The limit of detection and quantification was 0.008 and 0.02 mg/kg. Mean recoveries of diflubenzuron for each sample were 77.5-105.6%. Relative standard deviation (RSD) in recoveries were all less than 20%. The intra-day and inter-day precision (RSD) were 0.4-1.9% and 0.7-1.9%, respectively. The result of validation indicated that this method was accurate and rapid assay.

• The Korean Journal of Pesticide Science
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• v.20 no.3
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• pp.271-279
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• 2016

To evaluate exposure characteristics of the insecticide imidacloprid to apple orchard workers during treatment on orchard fields and evaluate its potential risk using a whole body dosimetry (WBD) method, 1,000-time diluted acephate+imidacloprid 25(20+5)% solutions were sprayed on 10 apple orchard fields in Cheongju with a speed sprayer at a rate of 3,000 L/ha/person, after put on clothes such as inner/outer clothes, personal air pump with a IOM sampler, nitrile glove and mask. Exposure test included mixing, loading and application steps. The test pesticide imidacloprid residues in the collected samples were analyzed with a HPLC-DAD. Recoveries ranged from 81.5 to 108.6% for analytical method validation and from 73.8 to 86.7% for field recovery. Total exposed amounts to mixer/loader and applicator were found to be 0.0014-0.0279% of total applied active ingredient of imidacloprid. Glove exposure of both mixer/loader and applicator was higher than the other parts. Margins of safety of mixer/loader and applicator were calculated to be 97-355 and 46-196, respectively, indicating that exposure risk of imidacloprid to apple orchard workers by spraying with a speed sprayer was very low.

• Journal of Distribution Research
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• v.17 no.5
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• pp.85-111
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• 2012

Introduction : The purpose of this study was to examine the relationship between perceptual characteristics of consumers and intent of relational continuance for PB(Private Brand) products in discount stores. This study was conducted as an empirical study based on survey. For the empirical study, factors of PB products as characteristics perceived by consumers such as perceived quality, store image, brand image and perceived value were deduced from preceding studies. The effect of such factors on intent of relational continuance mediated by brand trust and brand equity of PB products was structurally examined. Research Model : Based on theory analysis and hypotheses, constructed a Structural Equation Model(SEM). The research model is shown in Figure 1. Research Method : This paper is based on s qualitative study of selected literature and empirical data. The survey for empirical study was carried out on consumers in Gyeonggi and Busan between January 2012 and May 2012. 300 surveys were distributed and 253 (84.3%) of them were returned. After excluding omissions and insincere responses, 245 surveys (81.6%) were used for final analysis as effective samples. Result : First of all, the Reliability was carried out for instrument used. The lower limit of 0.7 for Cronbach's Alpha as suggested by Hair et al. (1998). And Construct validity was established by carrying out exploratory factor analysis by Varimax rotation for all. Four factor result for the consumer's perceptual characteristics of PB Products, two mediating factors and one dependent factor. All constructs included in research framework have acceptable validity and reliability. Table 1 shows the factor loading, eigen value, explained variance and Cronbach's alpha for each factor. In order to assure validity of constructs, I implemented Confirmatory Factor Analysis (CFA), using AMOS 20.0. In confirmatory factor analysis, researcher can take control over the specification of indicators for each factor by hypothesizing that a specific factor is loaded with the relevant indicators. Moreover, CFA is particularly useful in the validation of scale for the measurement of specific construct. CFA result summarized Table 2 shows that the fit measures of all constructs fulfill the recommended level and loadings are significant. To test causal relationship between constructs in the research model, used AMOS 20.0 that provides a graphic module as method for analysing Structural Equation Modeling. The result of hypothesis test is shown in Table 3. As a result of empirical study, perceived quality, brand image and perceived value as selected attributes for PB products showed significantly positive (+) effect on brand trust and brand equity. Furthermore, brand trust and brand equity showed significantly positive (+) effect on intent of relational continuance. However, store image of discount stores selling the PB products was analyzed to have positive (+) effect on brand trust and no significant effect on brand equity. Discussion : Based on the results of this study, the relationship between overall quality, store image, brand image and value perceived by consumers about PB products and intent of relational continuance was structurally verified as being mediated by brand trust and brand equity. Looking at the results, a strategic approach that maximizes brand trust and equity value for PB products by large discount stores is required on top of basic efforts to improve quality, brand image and value of PB products in order to maximize consumer's intent of relational continuance and to continuously attract repeated purchase of products.

• The Korean Journal of Elementary Counseling
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• v.9 no.1
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• pp.41-58
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• 2010

The purpose of this study was to invent anger-inducing automatic thoughts examination for elementary school children based on its investigation for Korean one. I made the anger-inducing Automatic Thoughts Questionnaire(I, II) and made an examination of the contents of the automatic thoughts with it. Based on it, with preliminary questionnaire 90, I did principal component analysis varimax rotation and then final anger-inducting automatic thoughts examination of 40 question in 2 primary factor construction was consisted. I made 300 students carry out it to know its reliability, propriety and made 100 students carry it out at 2-week intervals test-retest. I divided them in three groups as low, middle and high according to its soore regarding anger-inducting automatic thoughts, I confirmed the variation of each group in positive thoughts, self-esteem, life satisfaction, anger, the result is same as follows; First, the content of Anger-inducting Automatic thoughts for elementary school students is revealed as unreasonableness(56.4%), retailation and passive, active offense(16.3%), blame and contempt(11.9%), injured pride and refusal(9.2%), absurd(3.9%), abandonment and avoidance(2.1%), self-abasement in turn. Second, said inventory is consist of 2 notion; first(20 questions) is blame, retaliation and second(20 questions) is injustice. Inner-item consistency of total 40 question is .97, Split-half reliability is .93, Test-retest reliability is .86. Third, criterion validity is revealed fine by reviewing the correlation between existing index related to the inventory of Anger-inducting Automatic thoughts of the elementary school students. Moreover, to find out discriminant validity, I divided three classes(low, middle, high) according to the score of said thoughts. As a result, there is certain variations when I confirmed variations in groups by reviewing the self-esteem, positive way of thinking, life satisfaction, anger.

• The Korean Journal of Food And Nutrition
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• v.29 no.4
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• pp.474-479
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• 2016

This study aimed to investigate the concentration of vitamin C in Momordica charantia (MC) by cultivar, harvest time, and maturity. The methods for determining vitamin C levels were validated by measuring their 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 0.9994. The LOD and LOQ values for vitamin C were 0.05 and $0.16{\mu}g/mL$, respectively. The relative standard deviations (RSDs) for intra- and inter-day precision of vitamin C measurements were 2.34 and 1.34%, respectively. Depending on cultivar, the concentration of vitamin C in MC varied from 20.75~107.31 mg/100 g, fresh weight, with an average level $68.85{\pm}25.57mg/100g$, FW. When MC was analyzed by harvest time, the 20150612 MC showed the highest amount of vitamin C ($113.20{\pm}1.89mg/100g$, FW). On the other hand, the highest vitamin C content by maturity was $48.59{\pm}0.87mg/100g$, FW (15 day old MC). This information on the comparative vitamin C levels of MC might be useful to food scientists and should be explored for functional food development.

• Journal of Environmental Impact Assessment
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• v.24 no.6
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• pp.607-618
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• 2015

Five years have passed since the first set of environmental samples was taken in 2011 to represent various ecosystems which would help future generations lead back to the past environment. Those samples have been preserved cryogenically in the National Environmental Specimen Bank(NESB) at the National Institute of Environmental Research. Even though there is a strict regulation (SOP, standard operating procedure) that rules over the whole sampling procedure to ensure each sample to represent the sampling area, it has not been put to the test for the validation. The question needs to be answered to clear any doubts on the representativeness and the quality of the samples. In order to address the question and ensure the sampling practice set in the SOP, many steps to the measurement of the sample, that is, from sampling in the field and the chemical analysis in the lab are broken down to evaluate the uncertainty at each level. Of the 8 species currently taken for the cryogenic preservation in the NESB, pine tree samples from two different sites were selected for this study. Duplicate samples were taken from each site according to the sampling protocol followed by the duplicate analyses which were carried out for each discrete sample. The uncertainties were evaluated by Robust ANOVA; two levels of uncertainty, one is the uncertainty from the sampling practice, and the other from the analytical process, were then compiled to give the measurement uncertainty on a measured concentration of the measurand. As a result, it was confirmed that it is the sampling practice not the analytical process that accounts for the most of the measurement uncertainty. Based on the top-down approach for the measurement uncertainty, the efficient way to ensure the representativeness of the sample was to increase the quantity of each discrete sample for the making of a composite sample, than to increase the number of the discrete samples across the site. Furthermore, the cost-effective approach to enhance the confidence level on the measurement can be expected from the efforts to lower the sampling uncertainty, not the analytical uncertainty. To test the representativeness of a composite sample of a sampling area, the variance within the site should be less than the difference from duplicate sampling. For that, a criterion, ${i.e.s^2}_{geochem}$(across the site variance) <${s^2}_{samp}$(variance at the sampling location) was proposed. In light of the criterion, the two representative samples for the two study areas passed the requirement. In contrast, whenever the variance of among the sampling locations (i.e. across the site) is larger than the sampling variance, more sampling increments need to be added within the sampling area until the requirement for the representativeness is achieved.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.158-169
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• 2019

Ergot alkaloids are mycotoxin produced by fungi of the Claviceps genus, mainly by Claviceps purpurea in EU. Recently obtained informations indicates necessity for control the ergot in imported grains. Recent occurrence data of ergot alkaloids from EU countries indicate the necessities of management and control these toxins from the imported grains like rye, wheat, oat etc. The aim of this study is to optimize the liquid chromatography-tandem mass spectrometry method for determination of ergot alkaloids (ergometrine, ergosine, ergotamine, ergocornine, ergocryptine, ergocristine and their epimers (-inines) from grain and grain-based food. The test method was optimized by extracting the sample with acetonitrile containing 2 mM ammonium carbonate, purification with Mycosep cartridge, and instrumental analysis by LC-MS/MS using Syncronis C18 column. The standard calibration curves showed linearity with correlation coefficents; $R^2$ >0.99. Mean recoveries ranged from 72.0 to 111.3% at three different fortified levels (20, 50, and $100{\mu}g/kg$). The correlation coefficient expressed as precision was within the range of 1.9-12.9%. The limit or quantifications (LOQ) ranged from 0.012 to $0.058{\mu}g/kg$. The developed analytical method met the criteria of AOAC Int. and CAC validation parameters like accuracy and sensitivity. As a result, it was confirmed that the test method developed in this study is suitable for the simultaneous analysis of six species of ergot alkaloid from grains and grain products.