• International journal of advanced smart convergence
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• v.13 no.2
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• pp.205-213
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• 2024

This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.305-311
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• 2014

Minimum infective dose (MID) data has been recognized as an important and absolutely needed in quantitative microbiological assessment (QMRA). In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 82 published papers for total 12 species foodborne disease pathogens (bacteria 9, virus 2, and parasite 1 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "minimum infective dose", and "quantitative microbiological risk assessment". The appropriate minimum infective dose for B. cereus, C. jejuni, Cl. perfringens, Pathogenic E. coli (EHEC, ETEC, EPEC, EIEC), L. monocytogenes, Salmonella spp., Shigella spp., S. aureus, V. parahaemolyticus, Hepatitis A virus, Noro virus, and C. pavum were $10^5cells/g$ (fi = 0.32), 500 cells/g (fi = 0.57), $10^7cells/g$ (fi = 0.56), 10 cells/g (fi = 0.47) / $10^8cells/g$ (fi = 0.71) / $10^6cells/g$ (fi = 0.70) / $10^6cells/g$ (fi = 0.60), $10^2{\sim}10^3cells/g$ (fi = 0.23), 10 cells/g (fi = 0.30), 100 cells/g (fi = 0.32), $10^5cells/g$ (fi = 0.45), $10^6cells/g$ (fi = 0.64), $10{\sim}10^2particles/g$ (fi = 0.33), 10 particles/g (fi = 0.71), and $10{\sim}10^2oocyst/g$ (fi = 0.33), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.337-340
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• 2005

Context-awareness techniques in ubiquitous computing environment provide various services to users who need to get information via the analysis of collected information from sensors in a spatial area. Context-awareness has been increased in ubiquitous computing and is applied to many different applications such as disaster management system, intelligent robot system, transportation management system, shopping management system, and digital home service. Many researches have recently focused on services that provide the appropriate information, which are collected from Internet by different kinds of sensors, to users according to context of their surrounding environment. In this paper, we propose an abstraction model to manage the large-scale contextual information and their metadata which are collected from different kinds of in-situ sensors in a spatial area and are presented them on the web. This model is composed of the modules expressing functional elements of sensors using sensorML(Sensor Model Language) based on XML language and the modules managing contextual information, which is transmitted from the sensors.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.933-944
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• 2001

In the process of software development, object-oriented framework enables directly improving the productivity of the developer through the reuse of code, analysis and design informations. object-oriented framework is a set of usable and expandable classes and their connectivity. It is a meta solution that contains the code to be reused in the framework and the expert design results on a specific area. This paper constructs the framework that extracts the common services of BBS, chatting, white board and ftp applications for internet-based remote education system. These services can be mostly reused within heterogeneous applications in the form of component.

• Journal of Distribution Science
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• v.19 no.11
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• pp.69-80
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• 2021

Purpose: Consumers have unique behaviors that are classified based on their interests and considerations before buying. They are predicted will change due to the pandemic of COVID-19. This study provides insights for retailers about the dynamic of consumer behavior before and during the pandemic, including future predictions. Research design, data and methodology: The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement was applied in this study. Seven studies that were selected from five databases meet the criteria for cohort and cross-sectional analyses of gender, age, store types, and environmental concerns. Results: Consumer's gender and age contribute to consumer behavior change. Both offline and online stores can be integrated as omnichannel rather than substitute each other. Product distribution and consumer budget need to be reevaluated by retailers, while internet security is the most essential factor when developing their online transactions. Conclusions: COVID-19 pandemic has a significant impact on changing consumer behavior in most countries. Retailers are encouraged to adapt to the changes by modifying their business model with technology. However, it is still speculated and cannot be generalized due to different cultural and contextual factors. Future studies are always needed to synchronize along with the transition of consumers' behavior.

• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.299-304
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• 2014

The dose-response models are important for the quantitative microbiological risk assessment (QMRA) because they would enable prediction of infection risk to humans from foodborne pathogens. In this study, we performed a comprehensive literature review and meta-analysis to better quantify this association. The meta-analysis applied a final selection of 193 published papers for total 43 species foodborne disease pathogens (bacteria 26, virus 9, and parasite 8 species) which were identified and classified based on the dose-response models related to QMRA studies from PubMed, ScienceDirect database and internet websites during 1980-2012. The main search keywords used the combination "food", "foodborne disease pathogen", "dose-response model", and "quantitative microbiological risk assessment". The appropriate dose-response models for Campylobacter jejuni, pathogenic E. coli O157:H7 (EHEC / EPEC / ETEC), Listeria monocytogenes, Salmonella spp., Shigella spp., Staphylococcus aureus, Vibrio parahaemolyticus, Vibrio cholera, Rota virus, and Cryptosporidium pavum were beta-poisson (${\alpha}=0.15$, ${\beta}=7.59$, fi = 0.72), beta-poisson (${\alpha}=0.49$, ${\beta}=1.81{\times}10^5$, fi = 0.67) / beta-poisson (${\alpha}=0.22$, ${\beta}=8.70{\times}10^3$, fi = 0.40) / beta-poisson (${\alpha}=0.18$, ${\beta}=8.60{\times}10^7$, fi = 0.60), exponential (r=$1.18{\times}10^{-10}$, fi = 0.14), beta-poisson (${\alpha}=0.11$, ${\beta}=6,097$, fi = 0.09), beta-poisson (${\alpha}=0.21$, ${\beta}=1,120$, fi = 0.15), exponential ($r=7.64{\times}10^{-8}$, fi = 1.00), betapoisson (${\alpha}=0.17$, ${\beta}=1.18{\times}10^5$, fi = 1.00), beta-poisson (${\alpha}=0.25$, ${\beta}=16.2$, fi = 0.57), exponential ($r=1.73{\times}10{-2}$, fi = 1.00), and exponential ($r=1.73{\times}10^{-2}$, fi = 0.17), respectively. Therefore, these results provide the preliminary data necessary for the development of foodborne pathogens QMRA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.149-152
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• 2017

Big data analysis is an effective analysis techniques of unstructured data such as internet, social network services, web documents generated in mobile environment, e-mail, and social data, as well as formal data well organized in the database. Thus, meta-analysis is a statistical integration method that delivers an opportunity to overview the entire result of integrating and analyzing many quantitative research results. Today, regardless of gender and age is increasing interest in whether you can lead a younger and healthier life. With this change of life which has been developed with a variety of functional health food. Aronia melanocarpa called black chokeberry is a fruit of berry plants belonging to the Rosaceae originally growing in the North America region. In the studies for factors related to quality characteristics and antioxidant activities as the extracts of Aronia in this study, which it is only targeted factors as total sugar, acidity, polyphenol, anthocyanin, antioxidant. Thus, we present the theoretical and practical implications of these results.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.515-521
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• 2013

Purpose: To evaluate the efficacy and toxicity of induction chemotherapy followed by concurrent chemoradiotherapy (the treatment group) versus concurrent chemoradiotherapy with or without adjuvant chemotherapy (the control group) for locoregionally advanced nasopharyngeal carcinoma. Methods: The search strategy included Pubmed, Embase, the Cochrane Library, China National Knowledge Internet Web, Chinese Biomedical Database and Wanfang Database. We also searched reference lists of articles and the volumes of abstracts of scientific meetings. All randomized controlled trials were included for a meta-analysis performed with RevMan 5.1.0. The Grading of Recommendations Assessment, Development, and Evaluation system (GRADE) was used to rate the level of evidence. Results: Eleven studies were included. Risk ratios of 0.99 (95%CI 0.72-1.36), 0.37 (95%CI 0.20-0.69), 1.08 (95%CI 0.84-1.38), 0.98 (95%CI 0.75-1.27) were observed for 3 years overall survival, 3 years progression-free survival, 2 years loco-regional failure-free survival and 2 years distant metastasis failure-free survival. There were no treatment-related deaths in either group in the 11 studies. Risk ratios of 1.90 (95%CI 1.24-2.92), 2.67 (95%CI 0.64-11.1), 1.04 (95%CI 0.79-1.37), 0.98 (95%CI 0.27-3.52) were found for grade 3-4 leukopenia, grade 3-4 thrombocytopenia, grade 3-4 mucous membrane, and grade 3-4 hepatic hematologic and gastrointestinal toxicity, the most significant toxicities for patients. Conclusion: Compared with the control group, induction chemotherapy followed by concurrent chemoradiotherapy was well tolerated but could not significantly improve prognosis in terms of overall survival, loco-regional failure-free survival or distant metastasis failure-free survival.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.151-160
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• 2016

The purpose of this research is to investigate Korean popular attitudes and social perceptions of 'sharing economy' terminology at the current moment from a creative or socio-economic point of view. In Korea, this study discovers and interprets the objective and tangible annual changes and patterns of sociocultural collective intelligence that have taken place over the last five years by applying text mining in the big data analysis approach. By crawling and Googling, this study collected a significant amount of time series web meta-data with regard to the theme of the sharing economy on the world wide web from 2010 to 2014. Consequently, huge amounts of raw data concerning sharing economy are processed into the value-added meaningful 'word clouding' form of graphs or figures by using the function of word clouding with R programming. Till now, the lack of accumulated data or collective intelligence about sharing economy notwithstanding, it is worth nothing that this study carried out preliminary research on conducting a time-series big data analysis from the perspective of knowledge management and processing. Thus, the results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of future sharing economy-related markets or consumer behavior.