• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.79-93
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• 2015

With the rapid development of information technology, the ways of usage have changed drastically. The ways and efficiency of traditional service application to data processing already could not satisfy the requirements of modern users. Nowadays, users have already understood the importance of data. Therefore, the processing and saving of big data have become the main research of the Internet service company. In China, with the rise and explosion of 115 Cloud leads to other technology companies have began to join the battle of cloud services market. Although currently Chinese cloud services are still mainly dominated by cloud storage service, the series of service contents based on cloud storage service have been affirmed by users, and users willing to try these new ways of services. Thus, how to let users to keep using cloud services has become a topic that worth for exploring and researching. The academia often uses the TAM model with statistical analysis to analyze and check the attitude of users in using the system. However, the basic TAM model obviously already could not satisfy the increasing scale of system. Therefore, the appropriate expansion and adjustment to the TAM model (i. e. TAM2 or TAM3) are very necessary. This study has used the status of Chinese internet users and the related researches in other areas in order to expand and improve the TAM model by adding the brand influence, hardware environment and external environments to fulfill the purpose of this study. Based on the research model, the questionnaires were developed and online survey was conducted targeting the cloud services users of four Chinese main cities. Data were obtained from 210 respondents were used for analysis to validate the research model. The analysis results show that the external factors which are service contents, and brand influence have a positive influence to perceived usefulness and perceived ease of use. However, the external factor hardware environment only has a positive influence to the factor of perceived ease of use. Furthermore, the perceived security factor that is influenced by brand influence has a positive influence persistent intention to use. Persistent intention to use also was influenced by the perceived usefulness and persistent intention to use was influenced by the perceived ease of use. Finally, this research analyzed external variables' attributes using other perspective and tried to explain the attributes. It presents Chinese cloud service users are more interested in fundamental cloud services than extended services. In private cloud services, both of increased user size and cooperation among companies are important in the study. This study presents useful opinions for the purpose of strengthening attitude for private cloud service users can use this service persistently. Overall, it can be summarized by considering the all three external factors could make Chinese users keep using the personal could services. In addition, the results of this study can provide strong references to technology companies including cloud service provider, internet service provider, and smart phone service provider which are main clients are Chinese users.

• Journal of Food Hygiene and Safety
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• v.33 no.4
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• pp.289-295
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• 2018

The aim of this study was to develop and validate an analytical method for determining the presence of wogonin, quercetin, and quercetin-3-O-glucuronide in extracts of Nelumbo nucifera, Morus alba L., and Raphanus sativus mixtures. We evaluated the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of analytical methods for wogonin, quercetin, and quercetin-3-O-glucuronide using high performance liquid chromatography. Our result showed that the correlation coefficients of the calibration curve for wogonin, quercetin, and quercetin-3-O-glucuronide were 0.9999. The LOD for wogonin, quercetin, and quercetin-3-O-glucuronide ranged from 0.09 to 0.16 and those for the LOQ ranged from 0.26 to $0.48{\mu}g/mL$. The inter-day and intra-day precision values of wogonin, quercetin, and quercetin-3-O-glucuronide ranged from 0.74 to 1.87 and from 0.28 to 1.12%, respectively. The inter-day and intra-day accuracies were 99.96~115.88% and 99.73~114.81%, respectively. Therefore, the analytical method was validated for the detection of wogonin, quercetin, and quercetin-3-O-glucuronide in extracts of Nelumbo nucifera, Morus alba L., and Raphanus sativus mixtures.

• Journal of Food Hygiene and Safety
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• v.33 no.4
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• pp.296-305
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• 2018

Spiroxamine, one of fungicides, is used to control powdery mildew in various crops and black yellow sigatoka in bananas. The major strength of spiroxamine is to control powdery mildew in various crops and bananas yellow sigatoka in bananas. The compound has shown a high level of activity, good persistence and crop tolerance. Besides powdery mildew, good control of rust, net blotch and Rhynchosporium diseases been indicated in cereals, together with a complementary activity against Septoria diseases. In 2017, the maximum residue limit (MRL) of spiroxamine established in Korea. According to Ministry of ood and rug afety) regulations, spiroxamine residues defined only parent compound. Thus, a analytical method is needed to estimate the residue level of the parent compound. The objective of this study was to develop and validate analytical method for spiroxamine in representative agricultural commodities. Samples were extracted with acetonitrile and partitioned with dichloromethane to remove the interfering substances. The analyte were quantified and confirmed liquid chromatograph-tandem mass spectrometer (LC-MS/MS) in positive-ion mode using multiple reaction monitoring (MRM). Matrix matched calibration curves were linear over the calibration ranges ($0.0005{\sim}0.1{\mu}g/mL$) for the analyte in blank extract with coefficient of determination ($r^2$) > 0.99. For validation purposes, recovery studies will be carried out at three different concentration levels (LOQ, 10LOQ, and 50LOQ) performing five replicates at each level. The recoveries 70.6~104.6% with relative standard deviations (RSDs) less than 10%. All values were consistent with the criteria ranges in the Codex guidelines (CAC/GL40, 2003) and MFDS guidelines. proposed analytical method be used as an official analytical method in the Republic of Korea.

• Journal of Food Hygiene and Safety
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• v.24 no.3
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• pp.232-237
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• 2009

This study was conducted to develop a model for describing the effect of storage temperature (4, 10, 15, 20, 25, 30 and $35^{\circ}C$) on the growth of Escherichia coli O157 : H7 in ready-to-eat (RTE) lettuce treated with or without (control) alkaline electrolyzed water (AIEW). The growth curves were well fitted with the Gompertz equation, which was used to determine the specific growth rate (SGR) and lag time (LT) of E. coli O157 : H7 ($R^2$ = 0.994). Results showed that the obtained SGR and LT were dependent on the storage temperature. The growth rate increased with increasing temperature from 4 to $35^{\circ}C$. The square root models were used to evaluate the effect of storage temperature on the growth of E. coli O157 : H7 in lettuce samples treated without or with AIEW. The coefficient of determination ($R^2$), adjusted determination coefficient ($R^2_{Adj}$), and mean square error (MSE) were employed to validate the established models. It showed that $R^2$ and $R^_{Adj}$ were close to 1 (> 0.93), and MSE calculated from models of untreated and treated lettuce were 0.031 and 0.025, respectively. The results demonstrated that the overall predictions of the growth of E. coli O157: H7 agreed with the observed data.

• Clinical and Experimental Reproductive Medicine
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• v.36 no.4
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• pp.265-274
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• 2009

Objective: MicroRNAs (miR) are known to repress target genes at post-transcriptional level and play important roles in development and maturation of cell. However, the expression profiles of miR during ovarian follicle maturation have not been fully elucidated. Here, we designed this study to investigate the expression profiles of miR in oocytes and granulose cells (G-cells) after in vitro culture according to gonadotropins and adding hCG. Methods: Ovaries from 12-day-old mice (C57BL6) were removed and preantral follicles were isolated and cultured in $20\;{\mu}L$-drop of culture media with supplementation of either rFSH, rLH, or rFSH+rLH. After their full maturation, follicles were incubated with rhCG and rEGF. RNA was isolated from oocytes and G-cells, and real-time PCR were performed with primers of miR known to be expressed in the mouse ovary (mmu-miR-16, -miR-27a, -miR-126, -miR-721). Results: FSH+LH group showed the highest ovulation and MII rates among gonadotropin groups. The profiles of miRs in oocytes and G-cells differed according to gonadotropin groups and adding hCG. The profiles of miRs showed divergent changes between oocytes and G-cells. Conclusion: miR expression profiles are altered by gonadotropins and supplementation of hCG during in vitro maturation of murine follicles. Target gene study must be necessary to validate these findings.

• Journal of the Korean earth science society
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• v.37 no.7
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• pp.420-433
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• 2016

The purpose of this study is to improve the calibration matrixes of 2-D and 3-D convective rainfall rates (CRR) using the brightness temperature of the infrared $10.8{\mu}m$ channel (IR), the difference of brightness temperatures between infrared $10.8{\mu}m$ and vapor $6.7{\mu}m$ channels (IR-WV), and the normalized reflectance of the visible channel (VIS) from the COMS satellite and rainfall rate from the weather radar for the period of 75 rainy days from April 22, 2011 to October 22, 2011 in Korea. Especially, the rainfall rate data of the weather radar are used to validate the new 2-D and 3-DCRR calibration matrixes suitable for the Korean peninsula for the period of 24 rainy days in 2011. The 2D and 3D calibration matrixes provide the basic and maximum CRR values ($mm\;h^{-1}$) by multiplying the rain probability matrix, which is calculated by using the number of rainy and no-rainy pixels with associated 2-D (IR, IR-WV) and 3-D (IR, IR-WV, VIS) matrixes, by the mean and maximum rainfall rate matrixes, respectively, which is calculated by dividing the accumulated rainfall rate by the number of rainy pixels and by the product of the maximum rain rate for the calibration period by the number of rain occurrences. Finally, new 2-D and 3-D CRR calibration matrixes are obtained experimentally from the regression analysis of both basic and maximum rainfall rate matrixes. As a result, an area of rainfall rate more than 10 mm/h is magnified in the new ones as well as CRR is shown in lower class ranges in matrixes between IR brightness temperature and IR-WV brightness temperature difference than the existing ones. Accuracy and categorical statistics are computed for the data of CRR events occurred during the given period. The mean error (ME), mean absolute error (MAE), and root mean squire error (RMSE) in new 2-D and 3-D CRR calibrations led to smaller than in the existing ones, where false alarm ratio had decreased, probability of detection had increased a bit, and critical success index scores had improved. To take into account the strong rainfall rate in the weather events such as thunderstorms and typhoon, a moisture correction factor is corrected. This factor is defined as the product of the total precipitable waterby the relative humidity (PW RH), a mean value between surface and 500 hPa level, obtained from a numerical model or the COMS retrieval data. In this study, when the IR cloud top brightness temperature is lower than 210 K and the relative humidity is greater than 40%, the moisture correction factor is empirically scaled from 1.0 to 2.0 basing on PW RH values. Consequently, in applying to this factor in new 2D and 2D CRR calibrations, the ME, MAE, and RMSE are smaller than the new ones.

• Tuberculosis and Respiratory Diseases
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• v.64 no.2
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• pp.102-108
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• 2008

Background: Recently, multidrug-resistant (MDR) A. baumannii has been implicated for a significant proportion of nosocominal pneumonia in many intensive care units (ICUs), and its acquisition may increase mortality and the length of stay in the ICU. Aerosolized colistin has been successfully used in patients with cystic fibrosis, but there is a lack of data regarding the use of aerosolized colistin in patients with nosocomial pneumonia. Methods: We conducted the present study to assess the effectiveness of aerosolized colistin for the treatment of MDR A. baumannii nosocomial pneumonia. We retrospectively reviewed the medical records of 10 patients who had been hospitalized in the medical ICU and had received aerosolized colistin as a therapy for MDR A. baumannii pneumonia. Results: The mean duration of aerosolized colistin therapy was $12.7{\pm}2.4$ days. Nine (90%) of 10 patients showed a favorable response to the therapy. Follow-up cultures were available for all patients, and the responsible pathogen was completely eradicated. One patient suffered from bronchospasm, which resolved after treatment with nebulized salbutamol. Conclusion: Our results corroborate previous reports that aerosolized colistin may be an effective and safe choice for the treatment of nosocomial pneumonia caused by MDR A. baumannii. Larger prospective controlled clinical studies are warranted to validate further the effectiveness and safety of aerosolized colistin therapy.

• Journal of Venture Innovation
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• v.1 no.2
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• pp.47-59
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• 2018

With the recent, rapid changes in the socio-economic environment, organizations of today are now required to present a framework of realistic consumer behaviors based on psychology, economy, and finance, in order to understand their investing customers. Stock investors show differences in terms of their decisions or evaluations in the process of investing. This is due to what is called the 'framing effect.' The decision frames of the investors are defined differently, and, as a result, this affects the decisions made by the investors. Preceding studies on stock investment rarely touched the topic of the effect of message framing on market participants in their stock investment, especially regarding the differences in terms of their risk management behaviors based on the message framing in stock investment. Therefore, the purpose of this study is to examine the influence of stock investment message framing on market participants in their investment decision making and empirically validate whether this message framing effect has a moderating effect on the factors of investment satisfaction. For this, 494 participants with stock investment experiences were interviewed from May 1 to 26, 2018, and the results were used as the data for the empirical analysis. The analysis of the data was conducted using SPSS 22.0 statistical analysis software. The results of this study were as follows; First, of the stock investment behavioral factors, the stock comprehension, recommendation by others for a stock, and the degree of risks of a stock affected stock investment satisfaction in a positive manner. And, of the behavioral factors of stock investment, stock comprehension, stock brand, recommendation on the stocks from others, past performances, and risk levels of stocks affected the intent of continued stock investment in a positive manner. Second, message framing turned out to affect stock investment satisfaction in a positive manner, and it also had a significant moderating effect to the relationship between the stock investment behavior and stock investment satisfaction. Third, message framing was found to affect continued stock investment intent significantly, with a significant moderating effect in the relationship between stock investment behavioral factor and continued stock investment intent.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.397-402
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• 2013

The pharmacological efficacy of Protaetia (P.) brevitarsis larvae has been described in the Dongui Bogam. It is believed that the larvae are particularly useful for hepatic disorders. However, natural aversion has made it difficult to consume these larvae as food. Thus, we sought to make an eatable form of the larvae by establishing optimal conditions for larvae preparation. Larvae were selectively bred, sterilized, and a powder of larvae generated by freeze-drying. Afterward, the CellTiter $96^{(R)}$ AQueous Non-Radioactive Cell Proliferation Assay (MTS) with the RAW 264.7 cell line was used to validate the safety of the powder as a food ingredient. We determined that oak sawdust sterilized by water vapor for 5 minutes could be used for larvae feed, and a feeding for 3~5 days followed by a fasting for 3 days were optimal conditions for larvae preparation. In addition, sterilization of larvae at $115^{\circ}C$ and $0.9kgf/cm^3$ (to avoid contamination of pathogenic bacteria and fungi) was successfully applied in the production of edible powder from P. brevitarsis. The optimized processes established in our experiments can be used in the industrial production of P. brevitarsis as a food ingredient.