• Korean Journal of Environmental Agriculture
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• v.22 no.2
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• pp.100-110
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• 2003

This study was conducted to evaluate influence of chemical properties in the riparian on the species diversity and to get plant information for enhancement of natural purification in Mankyeong River. The concentration of total nitrogen was high in Jeonju and Sam stream, while that of total nitrogen showed the highest peak in Winter. Concentrations of $NH_4-N$ was $0.01{\sim}0.06\;mg/L$ in Gosan and Soyang stream. The water quality of upstream along with Mankyeong River was suitable for the irrigation source. The riparian vegetation was investigated by Zurich-Montpellier school's method from June, 2001 to September, 2002. The number of riparian plants were 59 families, 129 genera, 165 species, 20 varieties in Gosancheon, on the while 53 families, 111 genera, 141 species, 19 varieties in Soyangcheon. The number of riparian plants in Bari basin was higher than that of other sites namely, 73 families, 134 genera, 218 species, 33 varieties. Riparian vegetation was consisted of 12 plant communities. The contents of organic matter, total nitrogen and electrical conductivity had negative relationship with species diversity (Species richness index, Heterogeneity index, Species evenness index Species number). On the while, species diversity had positive relationship with soil pH. Species diversify of the plant communities were affected by topography and disturbance.

• Culinary science and hospitality research
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• v.22 no.5
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• pp.151-166
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• 2016

The purpose of this study is to understand the influence of Chinese customer coffee sought benefits on satisfaction with, and attachment and loyalty to Korean coffee shops. Based on a total of 200 samples obtained for empirical research from 10 Mar. to 25 July, 2015, of self-administrated questionaries completed by patrons in Beijing, Shanghai, Haerbin in China, data were analyzed for frequency, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression and hierarchical multiple regression analysis. The results of this study are summarized as follows. First, it was found that Chinese customer sought pursuits (functional & experimental benefits, symbolic benefit) had an effect on satisfaction of Korea coffee shop. Second, satisfaction influenced Korean coffee shop attachment and loyalty. Third, Korean wave attitude had a mediating effect between satisfaction, attachment and loyalty. From the results, we can conclude following implications: First, by providing atmosphere of South Korea, menu, barista service, we can predict that Korean coffee brands can prevail in competition through active promotions of their brands. Second, Korean coffee brands can make a strategy that includes providing full service from trained South Korean baristas and hosting talk shows between baristas from South Korea. Third, providing the opportunity to visit South Korea for local cafe tours is a good social event. These results will help control marketing strategies in China. Limitations and future research directions are also discussed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1619-1637
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• 2016

With wide distribution of smart phones and development of mobile network, social network service (SNS) is displaying remarkable growth rates. Users build new social relations by sharing their interests, which brings surging growth to the SNS based on the combination between the strength of expanding the place for communication and distribution of smart phones featured with easy portability. This study is designed to understand impact factors of SNS on users in Korea and to conduct empirical research on casual relationship between the factors above and the factors affecting personal information behavior through the privacy protection and self-efficacy. In order to accomplish the objective above, the study presented a research model applied with key variables of the Health Belief Model (HBM) predicting behaviors capable of recognizing and preventing individual diseases in the field of health communication. To perform empirical verification on the research model of this study, a survey was conducted upon college students at N university located in Chungcheongnam-do and K university in rural area, who have experiences using the SNS. Through this survey, a total of 186 samples were collected, and path analysis was performed in order to analyze the relationship between the factors. Based on the findings from the survey, first, variables Perceived probability, Perceived severity, Perceived impairment of the HBM, key factors of personal information protection behavior on the SNS, were found to exhibit negative relationship with self-efficacy, and Perceived probability, Perceived benefit, Perceived impairment were found to exhibit negative relationship with privacy protection. But the above, Perceived severity showed positive relationship with privacy protection, and Perceived benefit and self-efficacy also displayed positive relationship. Second, although self-efficacy, a parameter, showed positive relationship with privacy protection, it demonstrated negative relationship with personal information protection behavior. Lastly, privacy protection exhibited positive relationship with personal information protection behavior. By presenting theoretical model reflected with characteristics of prevention based on these findings above unlike previous studies on personal information protection using technologies threatening personal information, this study is to provide theoretical and operational foundation capable of offering explanations how to predict personal information protection behavior on the SNS in the future.

• Management & Information Systems Review
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• v.32 no.5
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• pp.193-231
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• 2013

As developed IT, Word-of-Mouth(WOM) used varied terms as buzz marketing and viral marketing, and impressed that importance. Despite introduced new marketing tool on managers and professionals, online word-of-mouth including SNS lack of study on social network what based viral in marketing. In social network, patterns of relationship between individuals influence each other individual behaviors. Therefore this research grouped friendship-network and advice-network by characteristics, studied on trust of information source that antecedents of word-of-mouth in network. This study examined that affect- and cognition based trust affect WOM acceptance as WOM behaviors and examined effect of type of product as moderating variable. Additional this literature studied that WOM acceptance affect WOM recommend. To find the Influence of Trust on Word-of-Mouth Behaviors, a survey has done 206 samples(undergraduate students). The results of this study are as following : First, type of trust different friendship network and advice network. Affect-based trust is outstanding in friendship network than in advice network, while cognition-based trust stands out in advice network than another. Second, affect- and cognition based trust positive affect WOM acceptance. Contrary to expectations, what is preconceived trust in network have a similar effect for WOM acceptance regardless of type of trust. Third, WOM acceptance positive affect WOM recommend. Fourth, affect based trust affect WOM acceptance of hedonic product rather than utilitarian product. Upon especially in friendship network terms, affect-based trust has a more effect on WOM acceptance than cognition-based trust. This study has many implications. First, it is important that trust what have an influence WOM acceptance grouped affect- and cognition based trust. Second, it confirmed that trust is antecedents of positive WOM. Third, it is important that network grouped friendship network and advice-network by trust. Fourth, it gave managerial implications that they have to supply WOM through which network by type of product. We This study classified network and trust based on previous study. Then it examined relations between WOM behaviors. Further research could do enrich various things for example various age group, valence of message, quality of information.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1353-1365
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• 1997

Background : Tumor necrosis factor(TNF) has been considered as an important candidate for cancer gene therapy based on its potent anti-tumor activity. However, since the efficiency of current techniques of gene transfer is not satisfactory, the majority of current protocols is aiming the in vitro gene transfer to cancer cells and re-introducing genetically modified cancer cells to host. In the previous study, it was shown that TNF-sensitive cancer cells transfected with TNF-$\alpha$ cDNA would become highly resistant to TNF, and the probability was shown that the acquired resistance to TNF might be associated with synthesis of some protective protein. Understanding the mechanisms of TNF -resistance in TNF-$\alpha$ cDNA transfected cancer cells would be. an important step for improving the efficacy of cancer gene therapy as well as for better understandings of tumor biology. This study was designed to evaluate the role of MnSOD, an antioxidant enzyme, in the acquired resistance to TNF of TNF-$\alpha$ cDN A transfected cancer cells. Method : We transfected TNF-$\alpha$ c-DNA to WEHI164(murine fibrosarcoma cell line), NCI-H2058(human mesothelioma cell line), A549(human non-small cell lung cancer cell line), ME180(human cervix cancer cell line) cells using retroviral vector(pLT12SN(TNF)) and confirm the expression of TNF with PCR, ELISA, MIT assay. Then we determined the TNF resistance of TNF-$\alpha$ cDNA transfected cells(WEHI164-TNF, NCIH2058-TNF, A549-TNF, ME180-TNF) and the changes of MnSOD mRNA expressions with Northern blot analysis. Results : The MnSOD mRNA expressions of parental cells and genetically modified cells of WEHI164 and ME180 cells(both are naturally TNF sensitive) were not significantly different The MnSOD mRNA expressions of genetically modified cells of NCI-H2058 and A549(both are naturally TNF resistant) were higher than those of the parental cells, while those of parental cells with exogenous TNF were also elevated. Conclusion : The acquired resistance to TNF after TNF-$\alpha$ cDNA transfection may not be associated with the change in the MnSOD expression, but the difference in natural TNF sensitivity of each cell may be associated with the level of the MnSOD expression.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.105-120
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• 2020

This study explores the process of the actual content production and distribution, by creating a YouTube channel to promote the popular music contents produced by the researcher, which thus reflects the reality where the production of video contents rapidly increases. A YouTube channel titled "Alida Music", of which the focus was to promote indie musicians, was created on February 2019. The contents of 10 indie musicians were produced in one-take live format. The information of the indie musicians was displayed in the form of a screen business card, with their e-mail address and SNS account at the top. Therefore, this promotional design was named "Card Live". Promotional video contents marked with the QR code in the lower right on the screen were produced, along with the promotional phrase "Communicate directly with the artist through the QR code", which allows viewers to watch other contents of the indie musician when they scan the QR code. This research conducted a study on how to improve and promote "Card Live" contents of "Alida Music", which were produced through this process. A group interview targeting five indie musicians, among whom one participant deemed significant was selected to conduct a one-to-one in-depth interview. As a result of the study, the following three conclusions were drawn. First, YouTube was found to be the medium with the greatest influence and highest efficiency at the lowest cost. Second, the evaluation of the participants on "Card Live" were divided into the three categories: need for one-take live, the design elements of "Card Live", and scanning issues of the QR code. Third, there is a need for promotional methods that can effectively utilize the media aspects of YouTube: the channel management issues such as raising public awareness as well as the number of subscribers of "Alida Music" should be resolved and measures to effectively use various media including other SNS should be developed. In terms of its content, it is imperative to recruit diverse performers to make various contents, as well as to come up with ways to link "Card Live" contents with offline. Based on these results, "Card Live" contents should be further revised and complemented in order to provide interesting contents to consumers, which will further develop "Alida Music" as a platform where various musicians and companies meet, thereby inducing contracts with popular music agencies and generating advertising revenues. However, since this study was carried out only with the limited number of participants, future studies should include more participants to bring forth a variety of promotional plans and improvement measures. Also, in the era of consuming contents through smart devices, the fact that some features of "Card Live" were available only on PC, did not fully reflect the characteristics of the times. In the future research, various contents that smartphone users can access and view freely without PC should be produced.

• Journal of Environmental Health Sciences
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• v.49 no.2
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• pp.66-77
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• 2023

Background: Along with the increase in consumer interest in and consumption of tattoo products, the controversy over harmful heavy metals associated with the use of tattoo cosmetics is also increasing. Therefore, investigation of hazardous metals in these tattoo products is needed. Objectives: This study was performed to provide useful data for establishing reasonable standards to securely manage tattoo cosmetics, tattoo stickers, and tattoo inks distributed in the market. Methods: Thirteen kinds of hazardous metal contents (Pb, As, Cd, Sb, Ni, Co, Cu, Cr, Se, Ba, Zn, Sn, and Hg) were analyzed for 23 tattoo cosmetics, ten tattoo stickers, and 16 tattoo inks. Hg was measured through the combustion-gold amalgamation method, and other hazardous metals were measured by inductively coupled plasma-mass spectrometry (ICP-MS) after acidic decomposition using a microwave apparatus. Results: The detected ranges of Pb, As, Cd, Sb, Ni, and Hg in tattoo cosmetics were 0.07~1.18, 0.06~0.41, ND~0.07, 0.01~3.44, 0.12~2.75, and ND~0.01 ㎍/g, respectively. All of the hazardous metals detected were below the recommended maximum standards of the Ministry of Food and Drug Safety. The mean amount of Pb detected in tattoo stickers for children was 0.24 ㎍/kg and Cd was not detected, meaning both metals met the recommended criteria. There was no statistically significant difference in all measured metals between children's tattoo stickers and adults' tattoo stickers. In the results of the study on the hazardous metal content of tattoo inks, four products (25%) for Pb, one product (6%) for As, 13 products (81%) for Ni, four products (25%) for Cu, and five products (31%) for Zn exceeded the recommended standards approved by the government. The highest predicted exposure amount for hazardous metals exceeding the recommended level of tattoo inks in a single tattooing was 5.69 ㎍/kg for Ni, 8.51 ㎍/kg for Zn, 0.44 ㎍/kg for Pb, 8.07 ㎍/kg for Cu, 0.44 ㎍/kg for As, and 71.36 ㎍/kg for Ba. Conclusions: It is necessary to prepare criteria for content limitation for the management of Co, Cr, Ba and Se tattoo cosmetics, and tattoo inks require thorough quality control.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.