Fenpyrazamine which is a pyrazole fungicide class for controlling gray mold, sclerotinia rot, and Monilinia in grapevines, stone fruit trees, and vegetables has been registered in republic of Korea in 2013 and the maximum residue limits of fenpyrazamine is set to grape, peach, and mandarin as 5.0, 2.0, and 2.0 mg/kg, respectively. Very reliable and sensitive analytical method for determination of fenpyrazamine residues is required for ensuring the food safety in agricultural products. Fenpyrazamine residues in samples were extracted with acetonitrile, partitioned with dichloromethane, and then purified with silica-SPE cartridge and eluted with hexane and acetone mixture. The purified samples were determined by HPLC-UVD and confirmed with LC-MS and quantified using external standard method. Linear range of fenpyrazamine was between $0.1{\sim}5.0{\mu}g/mL$ with the correlation coefficient (r) 0.999. The average recovery ranged from 71.8 to 102.7% at the spiked level of 0.05, 0.5, and 5.0 mg/kg, while the relative standard deviation was between 0.1 and 7.3%. In addition, limit of detection and limit of quantitation were 0.01 and 0.05 mg/L, respectively. The results revealed that the developed and validated analytical method is possible for fenpyrazamine determination in agricultural product samples and will be used as an official analytical method.
Fluxapyroxad is classified as carboxamide fungicide that inhibits succinate dehydrogenase in complex II of mitochondrial respiratory chain, which results in inhibition of mycelial growth within the fungus target species. This study was carried out to assure the safety of fluxapyroxad residues in agricultural products by developing an official analytical method. A new, reliable analytical method was developed and validated using High Performance liquid Chromatograph-UV/visible detector (HPLC-UVD) for the determination of fluxapyroxad residues. The fluxapyroxad residues in samples were extracted with acetonitrile, partitioned with dichloromethane, and then purified with silica solid phase extraction (SPE) cartridge. Correlation coefficient($R^2$) of fluxapyroxad standard solution was 0.9999. The method was validated using apple, pear, peanut, pepper, hulled rice, potato, and soybean spiked with fluxapyroxad at 0.05 and 0.5 mg/kg. Average recoveries were 80.6~114.0% with relative standard deviation less than 10%, and limit of detection (LOD) and limit of quantification (LOQ) were 0.01 and 0.05 mg/kg, respectively. All validation parameters were followed with Codex guideline (CAC/GL 40). LC-MS (Liquid Chromatograph-Mass Spectrometer) was also applied to confirm the analytical method. Base on these results, this method was found to be appropriate fluxapyroxad residue determination and can be used as the official method of analysis.
This study was conducted to establish the standard method for the contents of biotin in milk formulas. To optimize the method, we compared several conditions for liquid extraction, purification and instrumental measurement using spiked samples and certified reference material (NIST SRM 1849a) as test materials. LC-MS/MS method for biotin was established using $C_{18}$ column and binary gradient 0.1% formic acid/acetonitrile, 0.1% formic acid/water mobile phase is applied for biotin. Product-ion traces at m/z 245.1 ${\rightarrow}$ 227.1, 166.1 are used for quantitative analysis of biotin. The linearity was over $R^2=0.999$ in range of $5{\sim}60{\mu}g/L$. For purification, chloroform was used as a solvent for eliminating lipids in milk formula. The linearity was over 0.999 in range of 5~60 ng/mL. The detection limit and quantification limit were 0.10, 0.31 ng/mL. The accuracy and precision of LC-MS/MS method using CRM were 103%, 2.5% respectively. Optimized methods were applied in sample analysis to verify the reliability. All the tested milk formulas were acceptable contents of biotin compared with component specification and standards for nutrition labeling. The standard operating procedures were prepared for biotin to provide experimental information and to strengthen the management of nutrient in milk formula.
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.
This study aims to assess the influence of climate change on the hydrological cycle at a basin level in North Korea. The selected model for this study is MRI-CGCM 3, the one used for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Moreover, this study adopted the Spatial Disaggregation-Quantile Delta Mapping (SDQDM), which is one of the stochastic downscaling techniques, to conduct the bias correction for climate change scenarios. The comparison between the preapplication and postapplication of the SDQDM supported the study's review on the technique's validity. In addition, as this study determined the influence of climate change on the hydrological cycle, it also observed the runoff in North Korea. In predicting such influence, parameters of a runoff model used for the analysis should be optimized. However, North Korea is classified as an ungauged region for its political characteristics, and it was difficult to collect the country's runoff observation data. Hence, the study selected 16 basins with secured high-quality runoff data, and the M-RAT model's optimized parameters were calculated. The study also analyzed the correlation among variables for basin characteristics to consider multicollinearity. Then, based on a phased regression analysis, the study developed an equation to calculate parameters for ungauged basin areas. To verify the equation, the study assumed the Osipcheon River, Namdaecheon Stream, Yongdang Reservoir, and Yonggang Stream as ungauged basin areas and conducted cross-validation. As a result, for all the four basin areas, high efficiency was confirmed with the efficiency coefficients of 0.8 or higher. The study used climate change scenarios and parameters of the estimated runoff model to assess the changes in hydrological cycle processes at a basin level from climate change in the Amnokgang River of North Korea. The results showed that climate change would lead to an increase in precipitation, and the corresponding rise in temperature is predicted to cause elevating evapotranspiration. However, it was found that the storage capacity in the basin decreased. The result of the analysis on flow duration indicated a decrease in flow on the 95th day; an increase in the drought flow during the periods of Future 1 and Future 2; and an increase in both flows for the period of Future 3.
Proceedings of the Korean Institute Of Construction Engineering and Management
/
autumn
/
pp.99-106
/
2002
Researches on integration of design and construction information from earlier era focused on the conceptual data models. Development and prevalent use of commercial database management system led many researchers to design database schemas for enlightening of relationship between non-graphic data items. Although these researches became the foundation fur the proceeding researches. they did not utilize the graphic data providable from CAD system which is already widely used. 4D CAD concept suggests a way of integrating graphic data with schedule data. Although this integration provided a new possibility for integration, there exists a limitation in data dependency on a specific application. This research suggests a new approach on integration for design and construction information, 'Product Model Centered Integration Methodology'. This methodology achieves integration by preliminary research on existing methodology using 4D CAD concept. and by development and application of new integration methodology, 'Product Model Centered Integration Methodology'. 'Design Component' can be converted into digital format by object based CAD system. 'Unified Object-based Graphic Modeling' shows how to model graphic product model using CAD system. Possibility of reusing design information in latter stage depends on the ways of creating CAD model, so modeling guidelines and specifications are suggested. Then prototype system for integration management, and exchange are presented, using 'Product Frameworker', and 'Product Database' which also supports multiple-viewpoints. 'Product Data Model' is designed, and main data workflows are represented using 'Activity Diagram', one of UML diagrams. These can be used for writing programming codes and developing prototype in order to automatically create activity items in actual schedule management system. Through validation processes, 'Product Model Centered Integration Methodology' is suggested as the new approach for integration of design and construction information.
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.
In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.12
no.5
/
pp.67-77
/
2017
The purpose of this study was to develop the entrepreneurial mentoring scale on start-up mentoring situation. In recent years, as the needs for entrepreneurship have grown from domestic to foreign, entrepreneurship education is actively being carried out. The entrepreneurial mentoring is strengthening its weight and contents in entrepreneurship education. However, research on the mentoring function scale designed to reflect the characteristics of entrepreneurial mentoring is rarely performed in Korea. In this study, we conducted a qualitative and quantitative research to achieve the research goal. First, we derive the entrepreneurial mentoring scales through literature review and expert group discussions, and we conducted the empirical analysis to draw conclusions. The results of this study are as follows. In the first step, literature review was conducted. In the second step, four major factors and questionnaires were derived through expert group discussion. In the third step, the doctoral level specialists developed 16 questionnaire items to measure the four factors of entrepreneurial mentoring derived from the second step and verified the content validity and the facial validity in fourth step. As a result of this survey, we conducted questionnaires on founding mentors who belonged to 17 Creation Economic Innovation Centers nationwide (153) and analyzed the problem solving, networking, communication, and motivation formation through exploratory factor analysis. This questionnaire was used to survey the entrepreneurial mentors who belonged to the 17 Center for Creative Economy and Innovation under the Ministry of Science, ICT & Future Planning of South Korea(153). In fifth step, as the results of factor analysis such as EFA and CFA, we could confirm four factors including problem solving, networking, communication, and motivation. The significance of this study is as follows. First, academic significance was the first study of the entrepreneurial mentoring function scale reflecting the characteristics of entrepreneur mentoring as a qualitative and quantitative approach in Korea. Second, it is hoped that practitioners will be able to better measure the mentoring function of entrepreneurial mentors and contribute to improving the quality of future entrepreneurial mentoring programs.
Kim, Hyunsu;Seo, Yong Bae;Choi, Seong-Seok;Kim, Jin-Hee;Shin, Jiyoung;Yang, Ji-Young;Kim, Gun-Do
Journal of Food Hygiene and Safety
/
v.30
no.1
/
pp.43-50
/
2015
In this study, single PCR and multiplex PCR tests were examined for identification of four types of squid species (giant squid, cuttlefish, octopus, beka squid) purchased from fish market as well as aquatic processed products in Busan. To design the specific primers against each species, the nucleotide sequences of the mitochondrial 16s rRNA gene of Architeuthis dux, Todarodes pacificus, Enteroctopus dofleini, Enteroctopus megalocyathus, Uroteuthis chinensis, Uroteuthis duvauceli, Uroteuthis edulis groups were analyzed for the identification of each species registered in the GeneBank (www.ncbi.nlm.nih.gov) and have been used for comparative analysis. In order to obtain the size variation of amplified fragments on multiplex PCR, we designed KOJ-F, OJ-F, OCT-F, HAN-F, ALLR primers for each species. The optimal PCR conditions and primers were selected for four types of squid species to determine target base sequences in its PCR products. In the case of single PCR, giant squid was only amplified by KOJ-F/ALLR primer; cuttlefish was only amplified by OJ-F/ALLR primer; octopus was only amplified by OCT-F/ALLR primer; and beka squid was only amplified by HAN-F/ALLR primer. For multiplex PCR, the mixture of four kinds of genomic DNA (giant squid, cuttlefish, octopus, beka squid) been prepared as a template and used together with the mixture of KOJ-F/OJ-F/OCT-F/HAN-F/ALLR primers in the reaction. By the multiplex PCR, it is confirmed that four samples are correspond to multiple simultaneous amplicon. Finally, we validated the established methods of multiplex PCR in the aquatic processed products. Although the mitochondrial 16s rRNA primers used in this study was useful as a marker for detection of each species among them, the study indicated that the established multiplex PCR method can be more useful tool for monitoring the processed products.
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