The Socio-Political Significance of Paleolithic Studies in North Korea (정치·사회적 맥락에 따른 북한 구석기 연구 변화)
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- Korean Journal of Heritage: History & Science
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- v.53 no.1
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- pp.126-149
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- 2020
Considering significant words that stand for the history of Paleolithic in North Korea, these can be summarized for each decade since the 1960s. The 1960s ought to be when the earliest discovery of a Paleolithic site was made by Korean hands. The 1970s might be the earliest period for textbooks being published that were geared towards increasing general understanding of the Paleolithic era in the Korean peninsula. The 1980s can be summarized as a period of reissued Paleolithic articles from a newly introduced archaeological journal. The 1990s witnessed efforts to formulate nationalistic interpretations about the Paleolithic period in Korea. The 2000s then synthesized several of these aspects of Paleolithic studies. Gulpori, the Paleolithic site that was discovered in the 1960s, holds significance not just because of the discovery itself, but because of its prompt acceptance by North Korean academic authorities. The publications that covered general understanding of Paleolithic archaeology such as Joseon Gogohag Gaeyo, Joseon-ui Guseoggisidae, and Joseonjeonsa: Wonsipyeon in the 1970s hold immense significance themselves, as they demonstrate contemporary achievements. Reintroduction of the archaeological Journal, Joseongogoyeongu in 1986, is the beacon of alleviation of conspicuous effect to the academic sector. During the 1990s, a new emphasis on nationalism influenced Paleolithic studies. In the 2000s, the formally constructed elements of Paleolithic research such as Paleolithic chronology, social evolution, lithic assemblage, Quaternary studies, and human evolution were consistently refined. Metaphorically speaking, these parts are like a polygonal structure. As is the case with a polygonal structure, these research aspects are united and work together. Each part affects the others. Although the content of each research aspect has been altered by either academic growth or sociopolitical agenda, the fundamental part of the polygonal structure is not likely to be changed. The structure is solid enough to continue to serve the purposes of North Korean Paleolithic studies. North Korean Paleolithic archaeology seems to be a juxtaposition; some parts are easily changed while others are not. In order to ascertain these, not only the academic but also the sociopolitical context should be followed.
Despite the widespread use of chloral hydrate with hydroxyzine in the sedation of children, there is little agreement among pediatric dentists regarding its therapeutic dosage for the management of very uncooperative young children. Also, increasing concern has been raised with respect to its frequent failure to provide adequate levels of sedation when used according to the manufacturer's recommended dosage. Therefore, there has been many suggestions with respect to sedative effectiveness and safety of varying drug dosage, and some pediatric dental articles have advocated dosages exceeding manufacturer's recommendations. This study was performed to compare the effectiveness and safety in behavior management of the manufacturer's recommended dose of chloral hydrate(50mg/kg) with those of a higher dose(70mg/kg) used together with hydroxyzine(2mg/kg) and nitrous oxide(50%) when young children were sedated for dental treatment. The following results were obtained; 1. II group(70mg/kg) displayed higher mean score compared to I group(50mg/kg) with regard to the degree of sleep, crying, movement and overall behavior. The difference was statistically significant(p<0.05). 2. In comparison of success rates for sedation between the two groups, I group and II group showed 38.7% and 71.0% success rates respectively. An analysis of variance was statistically significant(p<0.05). 3. Comparing the occurrence rate hypoxia between the two groups, there were 22.6% and 19.4% occurrence of hypoxia in I group and II group. An analysis of variance was not statistically significant(p>0.05).
The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.
Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (