• Title/Summary/Keyword: BIG4

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Microplastics Intellectual Network Analysis based on Bigdata (빅데이터 기반한 미세플라스틱 지적네트워크 분석)

  • Kim, Younghee;Chang, Kwanjong
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.239-259
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    • 2022
  • Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

CoAID+ : COVID-19 News Cascade Dataset for Social Context Based Fake News Detection (CoAID+ : 소셜 컨텍스트 기반 가짜뉴스 탐지를 위한 COVID-19 뉴스 파급 데이터)

  • Han, Soeun;Kang, Yoonsuk;Ko, Yunyong;Ahn, Jeewon;Kim, Yushim;Oh, Seongsoo;Park, Heejin;Kim, Sang-Wook
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.4
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    • pp.149-156
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    • 2022
  • In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID+ that includes both the news content information and its social context information. The CoAID+ dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID+ dataset in various perspectives, we present some interesting features capable of differentiating real and fake news.

The Effects of the Bestseller Ranks on Public Library Circulation: Based on Panel Data Analysis (베스트셀러 순위가 공공도서관 대출에 미치는 영향 분석: 패널자료 분석을 중심으로)

  • Lee, Jongwook;Kang, Woojin;Park, Jungkyu
    • Journal of the Korean Society for information Management
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    • v.38 no.4
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    • pp.1-23
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    • 2021
  • The purpose of this study is to analyze the effects of the bestseller ranks on the book circulations in public libraries. To achieve this goal, the weekly data sets of 179 books' library circulation and bestseller list from January 1, 2018 to December 29, 2019 were constructed based on the data collected from BigData MarketC and YES24. Three methods for analyzing panel data including linear regression, fixed-effect, and random effect models were compared, and it turned out that fixed-effect model was better than other methods. The results show that the average ranks of bestsellers were associated with their public library circulations visually. Also, the analysis of fixed-effect model showed that the single rank decline of a book on the bestseller list decreases its average circulation of 0.108 while the size of effect varied depending on subject of books. The study empirically demonstrated the impact of a bestseller list on people's book circulation behavior, suggesting that public libraries need to reference sociocultural context as well as bestseller book lists to predict library user needs and to formulate collection development policy.

The Effect of Young Generation's Fairness Perception on Hopelessness: Mediating Effect of Perceived Control and Moderating Effect of Self-Esteem (청년세대의 공정성 인식이 무망감에 미치는 영향: 통제감의 매개효과와 자존감의 조절효과)

  • An, Kyue Han;Kim, Min Hee
    • Korean Journal of Culture and Social Issue
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    • v.26 no.4
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    • pp.457-477
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    • 2020
  • The purpose of this study is to confirm the effect of the young generation's Fairness perception on the hopelessness at the present time when the hopelessness of the future that young generation is experiencing is growing with social interest. This study examined the mediating effects of the perceived control and moderating effect self-esteem between the fairness perception and the hopelessness of the young generation. For this purpose, the self-reporting data of 313 young people in their 20s and 30s were collected. The results were as follows: First, fairness awareness was positively correlated with perceived control and self-esteem, and the hopelessness was negatively correlated with fairness awareness, perceive control and self-esteem. Second, perceived control mediated between fairness perception and the hopelessness, Third, self-esteem moderated the relationship between the fairness perception and the hopelessness. The high self-esteem group showed little change in hopelessness due to fairness perception while the low self-esteem group showed a big change in hopelessness due to fairness perception, which means that high self-esteem plays a role in alleviating hopelessness when fairness perception is low. The results of this study can be used as basic data to plan ways to improve mental health and quality of life.

Verification of Entertainment Utilization of UAS FC Data Using Machine Learning (머신러닝 기법을 이용한 무인항공기의 FC 데이터의 엔터테인먼트 드론 활용 검증)

  • Lee, Jae-Yong;Lee, Kwang-Jae
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.4
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    • pp.349-357
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    • 2021
  • Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

A Study on the Patterns and Characteristics of Spatial Changes in Unregistered Private House Gardens (문화재 미등록 민가정원의 공간변화 양상 및 특성 연구)

  • Lee, Kyeong-Mi;Bae, Jun-Gyu;Shin, Hyun-Sil
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.40 no.3
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    • pp.67-73
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    • 2022
  • This study tracked the changing process of unregistered private house gardens by using the form at the time of the construction of gardens as the prototype of each garden, investigated the spatial value of the garden, and discussed the historical spatial value of unregistered private house gardens in terms of inheritance and change of traditional gardens. To this end, targeting on unregistered private house gardens in Gangwon-do, which are in danger of preserving their gardens due to the recent increase in the number of designated cultural heritage dismantled, the patterns of unregistered private house gardens, their characteristics and values were identified through the spatial change of the garden, and the following results were derived. First, the unregistered private house gardens were able to inherit and maintain the form of a traditional garden, being located in a clan village. The garden space was divided by the influence of Confucian philosophy, and the components of the garden, tree species and planting methods appeared differently. In other words, the use of garden components according to the status hierarchy appeared. Second, space reduction was continuously confirmed at four target sites. The reduced spaces are garden spaces, and part of the garden was attributed to the state due to the building of new road and environmental improvement project. The reduced spaces are garden spaces, and part of the garden was attributed to the state due to the new road and environmental improvement project. Third, eight old big trees over 100 years old were identified in three of the four target sites, and the garden components such as stone water tanks, quickset doors, and ponds were commonly identified in Korea, China, and Japan during the Joseon Dynasty, inheriting the historicity of the traditional garden.

Effect of Disability Types by Disability Severity Levels on Employment: Based on the Employment Panel Survey for the Disabled (장애 중증도 수준에 따른 장애 유형이 고용에 미치는 영향: 장애인고용패널조사를 중심으로)

  • Choi, Junhyeok;Lee, Jisoo;Chung, Sunwoo;Oh, Sung Soo;Jo, Hoon
    • Therapeutic Science for Rehabilitation
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    • v.11 no.2
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    • pp.63-76
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    • 2022
  • Objective : The purpose of this study is to examine the relationship with employment of the disabled considering the severity and the type of disability. Methods : Data from the 4th data of the 2nd wave Panel Survey of Employment for the Disabled (PSED) by Korea Employment Agency for Persons with Disabilities (KEAD) were used. The odds ratio of employment in disability types according to severity of disability was calculated by logistic regression analysis. Results : When the related variables were adjusted, the employment of internal disability type was significantly lower than that of external disability type by 0.413(95% CI:0.271-0.629) times in the group with severe disability. On the other hand, in the group with less severe disability, internal disability was 0.475(95% CI:0.327-0.690) times lower than that of external disability (p=<.001). Conclusions : Employment may vary depending on the type of disability, even if the disability severity level is the same. It is necessary to prepare judgment criteria that can reduce the variation in employment by considering both the type and severity of the disability.

A Comparison Study of RNN, CNN, and GAN Models in Sequential Recommendation (순차적 추천에서의 RNN, CNN 및 GAN 모델 비교 연구)

  • Yoon, Ji Hyung;Chung, Jaewon;Jang, Beakcheol
    • Journal of Internet Computing and Services
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    • v.23 no.4
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    • pp.21-33
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    • 2022
  • Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.

Analysis of the Use of Insured Herbal Extracts and Korean Medicinal Treatments in Patients with Allergic Rhinitis : Data from Health Insurance Review and Assessment Service (알레르기 비염 환자의 보험 한약 제제 및 한의 처치 이용 현황 : 건강보험심사평가원 자료 분석)

  • Kim, Jeong-Hun;Ryu, Ji-In;Kang, Chae-Yeong;Hwang, Jin-Seub;Lee, Dong-Hyo
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.34 no.2
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    • pp.38-52
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    • 2021
  • Objectives : The purpose of this study is to analyze the use of insured herbal extracts and Korean medicinal treatments, which are mainly used to treat allergic rhinitis in Korean medicine. Methods : Among all HIRA(Health Insurance Review and Assessment Service) claims data in 2016, we included all statements that included J30(vasomotor and allergic rhinitis) or a subcategory of J30(J30.0, J30.1, J30.2, J30.3, or J30.4) as the main disease, using the Korean Standard Classification of Diseases(KCD-7). This study analyzed the most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis in Korean medicine. We performed a frequency analysis on subgroups based on treatment type(inpatient or outpatient), sex, age, insurance type, and medical institution type. Results : The result shows the 10 most frequently used insured herbal extracts and Korean medicinal treatments for allergic rhinitis. The total number of insured herbal extracts prescriptions was 82,533, and the most commonly prescribed insured herbal extracts was socheongryong-tang(35,131 prescriptions), followed by hyeonggaeyeongyo-tang(18,157 prescriptions), samsoeum(6,257 prescriptions), and galgeun-tang(4,465 prescriptions). The total number of Korean medicinal treatments prescriptions was 1,878,541, of which the most common Korean medicinal treatments was acupuncture(922,977 prescriptions), followed by moxibustion(372,120 prescriptions), cupping(242,094 prescriptions), and segmental acupuncture(161,553 prescriptions). Conclusions : It is expected that the results of this study can be used as a basis for establishing the priorities of evidence-based clinical research topics in the field of Korean medicine and making health care policy decisions to strengthen coverage in the future.

AI Art Creation Case Study for AI Film & Video Content (AI 영화영상콘텐츠를 위한 AI 예술창작 사례연구)

  • Jeon, Byoungwon
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.2
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    • pp.85-95
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    • 2021
  • Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.