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A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • 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 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • A Study on Medium-Sized Enterprises of Japan (일본의 중견기업에 관한 연구 : 현황과 특징, 정책을 중심으로)

    • Kang, Cheol Gu;Kim, Hyun Sung;Kim, Hyun Chul
      • Korean small business review
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      • v.32 no.2
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      • pp.209-223
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      • 2010
    • Korea's business is composed of a few large-sized enterprises (which can be abbreviated as LSE) and a majority of small-sized enterprises (SSE). Although there has been a growing recognition of the need for the development of medium-sized enterprises (MSE) which can serve as a link between SSE and LSE, as yet there has not yet been a consensus on the definition, characteristics and the function of the MSE in Korea. Nowadays, the world is being globalized, and Japan and China are in competition to ne a great economic power. While East Asia is experiencing rapid changes, promoting MSE which can secure flexibility and efficiency through covering up the limitation of LSE and SSE is needed in order to respond the global market which is being specialized. The features of MSE in Japan can be listed as follows. First, the MSE in Japan is developing the company through getting into niche markets which are hard for major companies to enter rather than developing markets in order to compete against major companies directly. While MSEs are endeavoring to build the business firmly in the domestic market, they can possess special and competitive technical skills through trials and errors; so that they can get a chance develop their business through independent business system rather than putting their effort to compete against major companies. Second, from the MSEs with competitive edge in the market, there are many contributions to the national exportation. Those MSEs produce in domestic and maintain the quality of high price products which need cutting-edge technology, while they relocate the low and middle priced goods to the country where manufacturing costs are low, so that they can maintain the price competitiveness. Third, the industrial structure in Japan is formed from dual structure between major companies and small sized companies. In other words, in Japan's industrial structure which are composed of subcontract structure, this dual structure has taken a major role of small sized companies' growth and manufacturing businesses' international competitive power. Forth, MSE in Japan adopt a strategy of putting their value on qualitative scale growth rather than quantitative scale growth. In this paper, the case of Japanese MSE is analyzed. Along with its long history of Industrialization, Japan has a corporate environment where the SSEs can develop as a MSE and later a LSE through a full-support system. Among its SSEs, there are a number of world class corporations equipped with a large domestic market, win-win cooperation with the LSEs and an independent technology development. It can also be observed that these SSEs develop into MSEs with sustainable growth potentials. This study will focus on the condition under which the MSEs of Japan have been developed, and how they have survived the competition between SSEs and LSEs. Through this study, this paper attempts to offer solutions to Korea's polarization between the SSE and LSE, while providing the basis for SSEs revitalization. In general, if both extremities phenomenon deepen between LSE and SSE, there are possible fears of occurring disutility in national economy by the monopolization of LSE. For that reason, enterprise group, which can make SSE or MSE compete LSE in some area and ease the monopoly and oligopoly problem, is needed. This awareness has been shared for ages long. Nevertheless, there is no legal definition for MSE in Japan, and there is no definition about the enterprise size or unified view of MSE between scholars, but it is defined differently by each of academical person or research institution and study meeting. For that reason, this paper will organize the definition of MSE in Japan, and then will propose the characteristics of the background which has made MSE secure competitiveness and sustainable growth in global market. This study focus on that because through this process, the positive change to the awareness of MSE can be proposed in Korea and to seek the policy direction for building institutional framework which can make SSE become MES. Through this way, the fundamentals for SSE to become MSE can be managed and some appropriate suggestions which will be able to make MSE enter the global market in the future can also be proposed. Due to these facts, this study is very important and well timed task. In a sense of this way, this study will examine the definition and role of MSE in Japan. after this examination, this study will deal with the status, special feature, and promotion policy for MSE. Through this analysis of MSE in Japan, the foundation which be able to set the desirable role model for MSE in Korea can be proposed. Also, the political implication which is needed to push ahead to contribute to creating employment and economic growth through sustainable growth of MSEs in economic system of Korea can be offered through this study. It has been found that Japan's MSE functions as an indispensable link among various industrial structures by holding a significant position in employment rate, production and value added. Although the MSEs took up less than 1% of the entire number of businesses with 2700 manufacturing firms and 7000 non-manufacturing firms, its employment ratios are about 15%, while taking about 25% of the manufacturing industry's exports. In industries such as machinery and electronics which is considered Japan's major industry, the MSEs showed a higher than average ratio of manufacturing exports and employment rate. It can be analyzed that behind Japan's advantageous industries, close and deeply knit MSEs exist. Although there are no clearly stated policies geared towards the MSEs by the Japanese government, various political measures exist such as the R&D Project and the inducement of cooperation between enterprises which gives room for MSEs to participate in the SSE policies. In relation to these findings, the following practical measures can be considered in order to revitalize Korea's MSEs: First, there is a need for a legal definition of MSE and the incentives to provide legal support for its growth. Second, if a law to support the MSEs is established, it could provide a powerful inducement for the SSE to grow as a MSE, rather than stay as a SSE. Third, there is a need for a strategy of MSEs to establish a stable base in the domestic market and then advance to the global market with the accumulated trial and error and competitiveness. Fourth, the SSE themselves need the spirit of entrepreneurship in order to make the leap to a MSE. Because if nothing is to be changed about the system on the firms that grew, and the parts of the past custom was left to be managed alone, confusion and absence of management can take place. No matter how much tax favors the government will give and no matter how much incentive there could be through the policies, there are limits for industries to higher the ability to propagate. And because of that it is a period where industries need their own innovative skills to reform their firms.

    Consumer's Negative Brand Rumor Acceptance and Rumor Diffusion (소비자의 부정적 브랜드 루머의 수용과 확산)

    • Lee, Won-jun;Lee, Han-Suk
      • Asia Marketing Journal
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      • v.14 no.2
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      • pp.65-96
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      • 2012
    • Brand has received much attention from considerable marketing research. When consumers consume product or services, they are exposed to a lot of brand related stimuli. These contain brand personality, brand experience, brand identity, brand communications and so on. A special kind of new crisis occasionally confronting companies' brand management today is the brand related rumor. An important influence on consumers' purchase decision making is the word-of-mouth spread by other consumers and most decisions are influenced by other's recommendations. In light of this influence, firms have reasonable reason to study and understand consumer-to-consumer communication such as brand rumor. The importance of brand rumor to marketers is increasing as the number of internet user and SNS(social network service) site grows. Due to the development of internet technology, people can spread rumors without the limitation of time, space and place. However relatively few studies have been published in marketing journals and little is known about brand rumors in the marketplace. The study of rumor has a long history in all major social science. But very few studies have dealt with the antecedents and consequences of any kind of brand rumor. Rumor has been generally described as a story or statement in general circulation without proper confirmation or certainty as to fact. And it also can be defined as an unconfirmed proposition, passed along from people to people. Rosnow(1991) claimed that rumors were transmitted because people needed to explain ambiguous and uncertain events and talking about them reduced associated anxiety. Especially negative rumors are believed to have the potential to devastate a company's reputation and relations with customers. From the perspective of marketer, negative rumors are considered harmful and extremely difficult to control in general. It is becoming a threat to a company's sustainability and sometimes leads to negative brand image and loss of customers. Thus there is a growing concern that these negative rumors can damage brands' reputations and lead them to financial disaster too. In this study we aimed to distinguish antecedents of brand rumor transmission and investigate the effects of brand rumor characteristics on rumor spread intention. We also found key components in personal acceptance of brand rumor. In contextualist perspective, we tried to unify the traditional psychological and sociological views. In this unified research approach we defined brand rumor's characteristics based on five major variables that had been found to influence the process of rumor spread intention. The five factors of usefulness, source credibility, message credibility, worry, and vividness, encompass multi level elements of brand rumor. We also selected product involvement as a control variable. To perform the empirical research, imaginary Korean 'Kimch' brand and related contamination rumor was created and proposed. Questionnaires were collected from 178 Korean samples. Data were collected from college students who have been experienced the focal product. College students were regarded as good subjects because they have a tendency to express their opinions in detail. PLS(partial least square) method was adopted to analyze the relations between variables in the equation model. The most widely adopted causal modeling method is LISREL. However it is poorly suited to deal with relatively small data samples and can yield not proper solutions in some cases. PLS has been developed to avoid some of these limitations and provide more reliable results. To test the reliability using SPSS 16 s/w, Cronbach alpha was examined and all the values were appropriate showing alpha values between .802 and .953. Subsequently, confirmatory factor analysis was conducted successfully. And structural equation modeling has been used to analyze the research model using smartPLS(ver. 2.0) s/w. Overall, R2 of adoption of rumor is .476 and R2 of intention of rumor transmission is .218. The overall model showed a satisfactory fit. The empirical results can be summarized as follows. According to the results, the variables of brand rumor characteristic such as source credibility, message credibility, worry, and vividness affect argument strength of rumor. And argument strength of rumor also affects rumor intention. On the other hand, the relationship between perceived usefulness and argument strength of rumor is not significant. The moderating effect of product involvement on the relations between argument strength of rumor and rumor W.O.M intention is not supported neither. Consequently this study suggests some managerial and academic implications. We consider some implications for corporate crisis management planning, PR and brand management. This results show marketers that rumor is a critical factor for managing strong brand assets. Also for researchers, brand rumor should become an important thesis of their interests to understand the relationship between consumer and brand. Recently many brand managers and marketers have focused on the short-term view. They just focused on strengthen the positive brand image. According to this study we suggested that effective brand management requires managing negative brand rumors with a long-term view of marketing decisions.

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    Applying an IPA(Importance-Performance Analysis) Model to Comparative Study on the Elementary School Students' Parents' Crime Prevention Design Element(CPTED) Awareness for Crime Prevention (범죄예방을 위한 초등학교 학부모의 범죄예방설계(CPTED)요소 인식에 관한 비교 연구: IPA(중요도-실행도 분석)기법을 중심으로)

    • Choi, Hyun-Sick
      • Korean Security Journal
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      • no.40
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      • pp.209-242
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      • 2014
    • This study is to understand sure the primary crime prevention has been incidence as a social problem intended for parents through the analysis of the Crime Prevention Design (CPTED) CPTED element of recognize elements that target crime prevention strategy to effectively help students be and an object of the present invention is to provide a policy suggestion haryeoneunde proposed basic data required for orientation. To achieve the study objectives such as the core framework in this study IPA: Importance-Performance Analysis) also was selected. Subjects of study in 2010 Gyeongju Elementary parents name and were 203 first research group investigating the secondary school population of the region in 2014 to nomadic parents of 297 people sampled selection. Questionnaire that use by this study applies "Important-Performance Analysis : IPA" technique that Martilla & James(1977) presented and analyzed awareness for CPTED elements of strategy for student's crime prevention to elementary school pupil students' parentse. It was the first group, 0.886, 0.920, 0.895 and 2nd group 0.880, 0.906, 0.878 that reliability of (Cronbach' s ${\alpha}$) the importance, and believability of run chart was the first group, 0.880, 0.917, 0.878 and 2nd group, 0.735, 0.840, 0.830. Analysis of the data carried out frequency analysis, reliability analysis, Frequency analysis was performed, paired sample t-Test for the reliability analysis, and the technical statistical analysis of the data is. The analysis of lattice bars execution through the IPA, the importance of the primary parents elements of CPTED strategies are generally very high, but found that the variation depending on the components that Performance. This study, an important element of the strategy to eliminate the school building for students from inside and outside the criminal fears CPTED is a mechanical surveillance in the first group, organizational surveillance, and the second group is the region intensified I'll showed mechanically and organizational factors in the investigation, and request that the investment is urgently important element is also execution low, crime prevention personnel security higher importance than expanding the front door. The analysis result of this study expects that basic data can be used in policy direction presentation that examines closely CPTED elements of strategy for crime prevention of students and applies CPTED's component effectively at elementary school hereafter.

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    Chemical Reactions in Surfactant Solution (I). Substituent Effects of 2-Alkylbenzimidazolide ions on Dephosphorylation in CTABr Solutions (계면활성제 용액속에서의 화학반응 (제1보). 미셀용액속에서의 탈인산화 반응에 미치는 2-알킬벤즈이미다졸음이온들의 치환기효과)

    • Young-Seuk Hong;Chan-Sik Park;Jung-Bae Kim
      • Journal of the Korean Chemical Society
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      • v.29 no.5
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      • pp.522-532
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      • 1985
    • The reactions of p-nitrophenyldiphenylphosphate (p-NPDPP) with anions of benzimidazole (BI) and its 2-alkyl derivatives (R-BI) are strongly catalyzed by the micelles of cetyltrimethyl ammonium bromide (CTABr). On the other hand, the first order rate constants $(k'_{R-BI^-})$ and the second order rate constants $(k_{m(R-BI^-)})$ of the reactions mediated by R-$BI^-$in the micellar pseudophase are much smaller than those mediated by $BI^-$. In order to explain the slower rates of the micellar reactions mediated by R-$BI^-$, we compared the concentration-ratios ([R-$BI^-$]/[$BI^-$]) with the first order rate constant-ratios $(k'_{R-BI^-}/k'_{BI^-})$ and the second order constant-ratios $(k_{m(R-BI^-)}/k_{m(BI^-)})$ for the reactions taking place in the micellar pseudophase. The rate constant-ratios were much smaller than the concentration-ratios. For example in a 5 ${\times}10^{-4}$M butyl-BI solution, the two ratios were 0.089 and 0.430 (for the first order) respectively, and in a $10^{-4}$M butyl-BI solution the former was 0.100 (for the second order). This predicts that the reactivities of R-$BI^-$ in the micellar pseudophase are much smaller than that of $BI^-$. Based on the values of several kinetic parameters measured for dephosphorylation of p-NPDPP mediated by R-$BI^-$, a schemetic model is proposed. Due to the hydrophobicity and the steric effect of the alkyl substituents, these groups would penetrate into the core of the micelle for stabilization by van der Waals interaction with long cetyl groups of CTABr. Consequently, the movements of R-$BI^-$ bound to the micelle should be restricted, leading to decreased collison frequencies between the nucleophiles and p-NPDPP. We refer this as an "anchor effect". This effect became more predominent when a larger alky group in R-BI was employed and when a greater concentration of R-BI was used.

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    A Study on Analyzing Sentiments on Movie Reviews by Multi-Level Sentiment Classifier (영화 리뷰 감성분석을 위한 텍스트 마이닝 기반 감성 분류기 구축)

    • Kim, Yuyoung;Song, Min
      • Journal of Intelligence and Information Systems
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      • v.22 no.3
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      • pp.71-89
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      • 2016
    • Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

    Latent topics-based product reputation mining (잠재 토픽 기반의 제품 평판 마이닝)

    • Park, Sang-Min;On, Byung-Won
      • Journal of Intelligence and Information Systems
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      • v.23 no.2
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      • pp.39-70
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      • 2017
    • Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

    A Study on the Method of Producing the 1 km Resolution Seasonal Prediction of Temperature Over South Korea for Boreal Winter Using Genetic Algorithm and Global Elevation Data Based on Remote Sensing (위성고도자료와 유전자 알고리즘을 이용한 남한의 겨울철 기온의 1 km 격자형 계절예측자료 생산 기법 연구)

    • Lee, Joonlee;Ahn, Joong-Bae;Jung, Myung-Pyo;Shim, Kyo-Moon
      • Korean Journal of Remote Sensing
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      • v.33 no.5_2
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      • pp.661-676
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      • 2017
    • This study suggests a new method not only to produce the 1 km-resolution seasonal prediction but also to improve the seasonal prediction skill of temperature over South Korea. This method consists of four stages of experiments. The first stage, EXP1, is a low-resolution seasonal prediction of temperature obtained from Pusan National University Coupled General Circulation Model, and EXP2 is to produce 1 km-resolution seasonal prediction of temperature over South Korea by applying statistical downscaling to the results of EXP1. EXP3 is a seasonal prediction which considers the effect of temperature changes according to the altitude on the result of EXP2. Here, we use altitude information from ASTER GDEM, satellite observation. EXP4 is a bias corrected seasonal prediction using genetic algorithm in EXP3. EXP1 and EXP2 show poorer prediction skill than other experiments because the topographical characteristic of South Korea is not considered at all. Especially, the prediction skills of two experiments are lower at the high altitude observation site. On the other hand, EXP3 and EXP4 applying the high resolution elevation data based on remote sensing have higher prediction skill than other experiments by effectively reflecting the topographical characteristics such as temperature decrease as altitude increases. In addition, EXP4 reduced the systematic bias of seasonal prediction using genetic algorithm shows the superior performance for temporal variability such as temporal correlation, normalized standard deviation, hit rate and false alarm rate. It means that the method proposed in this study can produces high-resolution and high-quality seasonal prediction effectively.

    Strategic Antitrust Policy Promoting Mergers to Enhance Domestic Competitiveness (기업결합규제(企業結合規制)와 국제경쟁력(國際競爭力))

    • Seong, So-mi
      • KDI Journal of Economic Policy
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      • v.12 no.3
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      • pp.153-172
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      • 1990
    • The present paper investigates the potential value of strategic antitrust policy in an oligopolistic international market. The market is characterized by a non-cooperative Cournot-Nash equilibrium and by asymmetry in costs among firms in the world market. The model is useful for two reasons. First, it is important in the context of policy-making to examine the conditions under which it may be beneficial to relax antitrust law to enhance competitiveness. Second, the explicit derivation of the level of cost-saving required for a gain in total domestic surplus provides an empirical rule for excluding industries that do not satisfy the requirements for a socially beneficial antitrust exemption. Results of the analysis include a criterion that tells how the cost-saving and concentration effects of a merger offset each other. The criterion is derived from fairly general assumptions on demand functions and is simple enough to be applied as a part of the merger guidelines. Another interesting policy implication of our analysis is that promoting mergers would not be a beneficial strategy in a net importing industry where cost-saving opportunities are thin. Cost-saving domestic mergers are more likely to increase national welfare in exporting industries. The best candidate industries for application of strategic antitrust policy are those with the following characteristics: (i) a large potential for efficiency enhancement; (ii) high market concentration at the world but not the domestic level; (iii) a high ratio of exports to imports. Recently, many policymakers and economists in Korea have also come to believe that the appropriate antitrust policy in an era of increased foreign competition may actually be to encourage rather than to prohibit domestic mergers. The Industry Development Act of 1986 and the proposed bill for Mergers and Conversions in the Financial Industry of 1990 reflect this changing perspective on antitrust policy. Antitrust laws may burden domestic firms in the sense that they have a more constrained strategy set. Expenditures to avoid antitrust attacks could also increase costs for domestic firms. But there is no clear evidence that the impact of antitrust policy is significant enough to harm the competitiveness of domestic firms. As a matter of fact, it is necessary for domestic financial institutions to become large in scale in this era of globalization. However, the absence of empirical evidence for efficiency enhancement from mergers suggests caution in the relaxation of antitrust standards.

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    Study of Value Estimation of Environmental Education of Gyeongnam Forest Museum using CVM (CVM을 이용한 경상남도산림박물관의 환경교육 가치추정 연구)

    • Kang, Kee-Rae;Ha, Sung-Gyone;Kim, Hee-Chae;Lim, Yeon-Jin;Kim, Dong-Pil;Park, Chang-Kun
      • Journal of Korean Society of Forest Science
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      • v.105 no.1
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      • pp.149-156
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      • 2016
    • Forest museums can be defined as facilities for the collection, exhibition, and education of the forest or forest related artifacts or data. This study was performed to measure the educational value of Gyeongnam state forest museum's forest and its environment. The tool used was the Contingent Valuation Methods (CVM) which is well known as a value estimation tool of environmental goods. The study for the value estimation is performed from April, 2014 to October of the same year through selection of the subject, decision of proposed price, and orientation of the survey staffs and total of 386 surveys were used in analysis. The value estimation tool used the DBDC logit model and the input parameters were number of visit (time), degree of environmental education (contri), the environment conservation effort of the respondent (execu), the education level of the respondent (edu), and income of the respondent (inc) and trimmed mean (WTPtruncated) was used. The estimated value of flora and environment education per each person per visit is 23,338 won. When applied to the average annual visitors deducted from 2010 to 2014, which is 430,000 per year, the environmental value that Gyeongnam state forest museum is providing to visitors each year is about 10 billion won. The result of this study is significant to propose the value of forest education and environment that the forest museum is offering to the visitors in the current currency. This is an evidence to directly determine the value of the forest museum and therefore proposing an opportunity change the recognition toward the forest and environment education.


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