• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.143-148
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• 2022

This study was to investigate an analytical method for determining dieckol content in Ecklonia stolonifera extract. According to the guidelines of International Conference on Harmonization. Method validation was performed by measuring the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of dieckol using high-performance liquid chromatography-photodiode array. The results showed that the correlation coefficient of calibration curve (R²) for dieckol was 0.9997. The LOD and LOQ for dieckol were 0.18 and 0.56 ㎍/mL, respectively. The intra- and inter-day precision values of dieckol were approximately 1.58-4.39% and 1.37-4.64%, respectively. Moreover, intra- and inter-day accuracies of dieckol were approximately 96.91-102.33% and 98.41-105.71%, respectively. Thus, we successfully validated the analytical method for estimating dieckol content in E. stolonifera extract.

• Korean Association of Arts Management
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• no.50
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• pp.101-146
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• 2019

After the enactment of the Local Culture Promotion Act in 2014, the government has been continuously trying to find the direction of the local culture that reflects the local life and conforms to the local people's emotions. In response to these efforts, the Organizing Committee for the C Region Biennale has uniquely formed the Biennale Artistic Director as a local artist who includes the historical, ecological and emotional characteristics of the C region. Therefore, I sought to explore the perception of the identity and role of the local cultural arts director through the narratives of the research participants who were appointed as the local residents of the C region and the director of the Craft Biennale. For the study, six local cultural arts directors were selected as research participants, and their identity as a local cultural arts director and its role were explored, focusing on their narratives. In this process, various types of data such as photographs, documents, in - depth interviews, and conference materials were collected and narrative was analyzed based on deterministic events. The results of the investigation are as follows. The idea of the identity of the local cultural arts directors was found to be in three directions. First, it is the view that the symbolic role of the artistic supervisory system of the 10 persons guarantees the identity. Second, the identity of local cultural arts directors was recognized as a role to find ways to be localized by developing and debating cultural and artistic discourses in various regions. Third, the participants had a concern and affection for local cultural arts, not one-time but continuous, and recognized it as their identity. The directors who participated in the interviews showed that the discourse of cultural arts in various regions were developed and discussed, and they wanted to find ways to be localized. The roles of local cultural arts directors recognized by research participants in connection with their identity are as follows. First, it should be the subject of systematic and long-term planning that can close the year and connect with the art events of the following year. Second, it should play a role of academic / research that can derive the identity of social and cultural ecological analysis connected with the area. Third, local arts professionals are required to act as cultural brokers, ie local culture professionals, who can create a venue for international cultural exchanges. Research on the form of local government supervision as a mediator of local cultural arts is to find out the origin of the identity of local artists and to establish a methodology for the direction of culture and art as a subject of local people. In addition, there is a need for continued interest and research in providing a reflection on the communication and meaning of the desirable local culture, and suggesting the system for cultivating local cultural arts intermediaries.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Food Hygiene and Safety
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• v.37 no.2
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• pp.39-45
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• 2022

This study aimed to investigate the validation and modify the analytical method to determine quercetin-3-𝑜-gentiobioside and isoquercitrin in Abelmoschus esculentus L. Moench for the standardization of ingredients in development of functional health products. The analytical method was validated based on the ICH (International Conference for Harmonization) guidelines to verify the reliability and validity there of on the specificity, linearity, accuracy, precision, detection limit and quantification limit. For the HPLC analysis method, the peak retention time of the index component of the standard solution and the peak retention time of the index component of A. esculentus L. Moench powder sample were consistent with the spectra thereof, confirming the specificity. The calibration curves of quercetin-3-𝑜-gentiobioside and isoquercitrin showed a linearity with a near-one correlation coefficient (0.9999 and 0.9999), indicating the high suitability thereof for the analysis. A. esculentus L. Moench powder sample of a known concentration were prepared with low, medium, and high concentrations of standard substances and were calculated for the precision and accuracy. The precision of quercetin-3-𝑜-gentiobioside and isoquercitrin was confirmed for intra-day and daily. As a result, the intra-day precision was found to be 0.50-1.48% and 0.77-2.87%, and the daily precision to be 0.07-3.37% and 0.58-1.37%, implying an excellent precision at level below 5%. As a result of accuracy measurement, the intra-day accuracy of quercetin-3-𝑜-gentiobioside and isoquercitrin was found to be 104.87-109.64% and the daily accuracy thereof was found to be 106.85-109.06%, reflecting high level of accuracy. The detection limits of quercetin-3-𝑜-gentiobioside and isoquercitrin were 0.24 ㎍/mL and 0.16 ㎍/mL, respectively, whereas the quantitation limits were 0.71 ㎍/mL and 0.49 ㎍/mL, confirming that detection was valid at the low concentrations as well. From the analysis, the established analytical method was proven to be excellent with high level of results from the verification on the specificity, linearity, precision, accuracy, detection limit and quantitation limit thereof. In addition, as a result of analyzing the content of A. esculentus L. Moench powder samples using a validated analytical method, quercetin-3-𝑜-gentiobioside was analyzed to contain 1.49±0.01 mg/dry weight g, while isoquercitrin contained 1.39±0.01 mg/dry weight g. The study was conducted to verify that the simultaneous analysis on quercetin-3-𝑜-gentiobioside and isoquercitrin, the indicators of A. esculentus L. Moench, is a scientifically reliable and suitable analytical method.