• (The)Study of the Eastern Classic
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• no.33
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• pp.279-304
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• 2008

This paper draws out the contents related to "Yuk(易)" Silhak(實學), and discusses the tendency in order to review the ideas shown in Wandang's Seodok(書牘). Also, it studies Taoism expressed in Seodok in terms of figuring out Wandang's Taoism. The features of his thoughts are following. The first one is the use of "Yuk(易)" for Soogichiin(修己治人). What he considered most important was Eumsiknamnyu(飮食男女) linked directly to the people's life. He maintained that a country must be ruled by doing Soogi(修己) with "Yuk(易)" and by making use of "Yuk(易)". The next one is both a view of Gyungsechiyong(經世致用) of Dongseoboolboon(東西不分) and a natural view of Iyonghooseng(利用厚生), standing on Silsagusi(實事求是). He actively accepted new learning and concepts those days, and he asserted that Western techniques should be even imitated for the sake of the nation. Thirdly, his view of Moowi(無爲) and Boolun(不言). He didn't use to do any Jakwi(作爲) of Jeosool(著述). This kind of view seems to save his life and be connected to Yangshin(養身) even though others tried to keep a jealous eye on and entrap him. Last, his concept of Jayeonsooneung(自然順應) and Jayeonhoigui(自然回歸). It is shown through his wish of farm work and his politics, saying that a king ought not to bind the people with faithfulness and propriety, and that he ought to rule the nation with humanity. In sum, Wandang's ideas shown in Seodok can be divided into two streams. One is Boshin(保身) through Moowijayeon(無爲自然), Boolun(不言), and Jayeonhoigui(自然回歸). The other is a pursuit of his studies for the purpose of Dukchi(德治) followed by Soogichiin, Kyongsechiyong, Iyonghooseng, and Injung. Here, since Boshin can be said to be advanced Soogi, and Soogichiin and others are connected directly to people's comfortable life, they can be integrated to Soogiianbaeksung(修己以安百姓). In other words, his thoughts were based on the fusion of Confucianism and Taoism, and he aimed at Soogiianbaeksung by accepting and using to take a look at the change of period and learning.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.75-88
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• 2021

The film won the Golden Palm Award at the Cannes Film Festival, and received the Academy Award for a non-English-speaking film in February 2020, respectively. It has received a monumental evaluation in the world film history. Overall, this film is about class conflict, and critics evaluate the theme of the film as "badly twisted class gap" and "anger from class." The film expresses an intrinsic conflict embodied in culture as a "tragedy in which no bad person appears," rather than the dichotomous composition of the classical class struggle from Marxism. In other words, this can be seen as expressing the substrated class relationship of the modern society that Pierre Bourdieu had argued. This film has been focused as a controversial target under Korea society with excess of ideology. Politics used to adopt the keyword, 'parasite', for political disputes not only in culture contents world. Paradoxically socialism China did not allow to release film 'Parasite.' On the other hand, Lee O-Yong argues that the movie "Parasite" does not look at social phenomena through a dichotomous perspective, but is viewed through a "double perspective" and evaluates that it does not lose eyes looking at humans through tension. This view is based upon 'Vital Capitalism'. Lee. O-Yong looks at the movie "Parasite" from the perspective of "Vital Capitalism". The theory of Vital Capitalism does not seek to find the root of historical development in class struggle conflicts, but rather figuring out history and society pays attention onto the intrinsic characteristics of life, Topophilia, Neophilia, and Biophilia. Lee Eo-ryeong argues that the development of civilization theory evolved from the stage of Hobbes' Darwinism or predatism to the stage of host vs. parasite of Michel Serres, and onto the stage of Margulis's 'Win-Win (inter-dependence)'. In this paper, after overview of vital capital concept and preceeding research, re-interpretations were tried onto scenes based upon fields from habitus, culture capital. This exploration looks for a alternative for excess of ideology in Korea society.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.450-462
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• 2023

This study suggested methodology of Citizen Science as a tool of ecosystem conservation and management to achieve Wetland Protected Area (WPA) Conservation Plan and examined whose applicability in 3 WPAs (Jangrok of Gwangju metropolitan city, Madongho of Goseong in South Gyeongsang Province, and Incheongang estuary of Gochang in North Jeolla Province). It consists of a) figuring out main interests and stakeholder or beneficiaries of WPA and their information demand based on conservation, utilization, and management target in the WPA Conservation Plan, b) conducting research activities to gain outcome to address stakeholder's demand, and c) returning the research outcome to citizen scientists and making diffusion to the society. Based on the suggested method and process, citizen scientists conducted ecosystem monitoring (plants including Invasive Alien Plants, terrestrial insects, traces of mammals, discovering unknown wetland). As a result, citizen scientists contributed to collecting species information of 16 plans, 43 species of terrestrial insects, 5 mammals including Lutra lutra (Endangered Species I) and Prionailurus bengalensis (Endangered Species II). The authors constructed and provided distribution map of Invasive Alien Plants, which included information of location and density which citizen scientists registered, for Environment Agencies and local governments who manage 3 WPAs to aid data-based ecosystem policy, In further studies, not only accumulating research data and outcomes acquired from citizen science to suffice the policy demands but also deliberate reviewing policy applicability and social·economic ripple effect should be processed for the suggested Citizen Science in WPA to be settled down as a tool of ecosystem conservation and management.

• 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.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.