• Title/Summary/Keyword: BIG4

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A Study on Changes in Korean Image of Foreign Tourists Using Big Data - Post COVID-19 -

  • Yoo, Kyoung-Mi;Choi, Youn-Hee;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.72-78
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    • 2021
  • Currently, the Korean wave is not limited to popular culture, but has a significant impact not only on Korea's national image but also on the improvement of Korean companies' products and image of Korea. In this study, using Textom to confirm the change in foreign tourists' image of Korea, the data collection period was 1 year of 2020, when COVID 19 occurred, as a collection period for "Korea and foreigner" and related key words, each Hallyu content, and ranked in the top 80 keywords were derived. Centrality analysis for semantic network visualization was performed using UCINET6, and through CONCOR analysis, 7 groups 'K-Quarantine ', 'K-Drama', 'K-Movie', 'K-Beauty', 'K-Shopping', It was clustered into 'K-Tech' and 'K-Pop'. As a result of the analysis, the image of Korea abroad generally recognized the Korean Wave as cultural content, but after the outbreak of COVID 19, it is judged that it has been recognized as a country with a successful case of K-Quarantine.

A Study on the Analysis of Museum Gamification Keywords Using Social Media Big Data

  • Jeon, Se-won;Choi, YounHee;Moon, Seok-Jae;Yoo, Kyung-Mi;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.66-71
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    • 2021
  • The purpose of this paper is to identify keywords related to museums, gamification, and visitors, and provide basic data that the museum market can be expanded by using gamification. That used to collect data for blogs, news, cafes, intellectuals, academic information by Naver and Daum which is Web documents in Korea, and Google Web, news, Facebook, Baidu, YouTube, and Twitter for analysis. For the data analysis period, a total of one year of data was selected from April 16, 2020 to April 16, 2021, after Corona. For data collection and analysis, the frequency and matrix of keywords were extracted through Textom, a social matrix site, and the relationship and connection centrality between keywords were analysed and visualized using the Netdraw function in the UCINET6 program. In addition, We performed CONCOR analysis to derive clusters for similar keywords. As a result, a total of 25,761 cases that analysing the keywords of museum, gamification and visitors were derived. This shows that the museum, gamification, and spectators are related to each other. Furthermore, if a system using gamification is developed for museums, the museum market can be developed.

Model for Quality Assessment of Data Analytics Software in Manufacturing-Based IIoT Environments (제조 기반 IIoT 환경에서 데이터 분석 소프트웨어의 품질 평가를 위한 모델)

  • Choi, Jongseok;Shin, Yongtae
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.4
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    • pp.292-299
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    • 2021
  • A form of data mining software, based on manufacturing-based IIoT environment with the development of IT technologies are increasingly growing. However, it is difficult to evaluate the software quality in the same form as general software due to the characteristics of the software of a manufacturing company that has a large amount of data that needs to be carried out with big data and data mining. In addition, in a manufacturing-based environment where heterogeneous equipment and software are mixed, it is difficult to perform quality judgment on software used by applying existing quality characteristics. Therefore, in this paper, the characteristics of the manufacturing base are investigated, and a software quality evaluation model suitable for it is developed and evaluated.

A Case of Combined Korean Medicine Treatment for Recurrent Limb Weakness after Guillain-Barré Syndrome Improvement: Case Report (길랑바레 증후군 호전 이후 재발한 사지무력 증상에 대한 한방 복합치료 1예: 증례보고)

  • Park, Song-Mi;Cho, Sung-Woo
    • Journal of Korean Medicine Rehabilitation
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    • v.29 no.4
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    • pp.135-142
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    • 2019
  • The objective of this study is to propose Korean Medicine treatment for recurrent limb weakness after Guillain-Barre syndrome (GBS) improvement by intraveinous immunoglobulin, and to report its effectiveness. Manual muscle test (MMT), Korean modified Bathel index (K-MBI), and tendon reflex were used to evaluate the patient. The patient was improved hip joint, knee joint, ankle joint MMT from grade 3-/3- to grade 5/5 and in the upper limb the patient can do big joint exercise but cannot do micromovement like writing or using cell phone. When discharge date the patient's wrist joint MMT grade is improved grade 5-/5- to grade 5/5. The K-MBI score is improved from 71 to 86 and there was a big change in walking and chair/bed transfer, there was no change in tendon reflex. This study suggests that Korean Medicine can be effective for patients who have recurrent limb weakness after GBS improvement.

The Analysis of Patent Trends and Radiation Convergence Technology (방사선 융합기술과 특허 동향 분석)

  • Park, Jang-Hoon;Ock, Young Seok
    • Journal of the Korean Society of Radiology
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    • v.13 no.5
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    • pp.785-790
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    • 2019
  • Convergence and advancement between technologies such as Artificial Intelligence, Big Data, and the Internet of Things have a significant impact on the regional flagship industry. All technical fields are used as a converged technology by connecting between technology and industry. In order to understanding the recent technical trend, it is possible to easily realized the technical trend research and analysis through keyword search using patent information. The purpose of this study is to identify patent trends applied to convergence technology in the 4th Industrial Revolution age in radiation technology development and to present patent trends and analysis for strengthening and utilizing radiation-related industrial technology competitiveness and to apply them to demand technology and forecast future promising technologies.

Next Generation Smart-City Facility Platform and Digital Chain (차세대 스마트도시 시설물의 플랫폼 정의와 디지털 체인)

  • Yang, Seung-Won;Kim, Jin-Wooung;Kim, Sung-Ah
    • Journal of KIBIM
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    • v.10 no.4
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    • pp.11-21
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    • 2020
  • With increasing interest and research on smart cities, there is also an increasing number of studies on urban facilities that can be built within smart cities. According to these studies, smart cities' urban facilities are likely to become high value-added industries. However, the concept of smart city is not clear because it involves various fields. Therefore, in this study, the definition of Next-Generation(N.G) Smart City Facilities with Digital Twin and Digital Chain is carried out through a multidisciplinary approach. Based on this, Next-Generation Smart City Facilities will be divided into High Value-Added Products and Big Data Platforms. Subsequently, the definition of the Digital Chain containing the data flow of the entire process built through the construction of the Digital Twin proceeds. The definitions derived are applied to the Next-Generation Noise Barrier Tunnel to ensure that data is exchanged at the Digital Twin stage, and to review the proposed configuration of the Digital Chain and Data Flow in this study. The platform definition and Digital Chain of Next-Generation Smart City Facilities proposed in this study suggest that it can affect not only the aspects of data management that are currently in the spotlight, but also the manufacturing industry as a whole.

Deep Learning-Based Smart Meter Wattage Prediction Analysis Platform

  • Jang, Seonghoon;Shin, Seung-Jung
    • International journal of advanced smart convergence
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    • v.9 no.4
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    • pp.173-178
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    • 2020
  • As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.

A Study on the Extraction of Living SOC Deficient Areas in Small and Medium Cities Using Big Data - Focused on Iksan-si, Jeollabuk-do - (빅데이터를 활용한 중소도시의 생활SOC 결핍지역 추출 연구 - 전라북도 익산시를 중심으로 -)

  • Han, Da-Hyuck;Kim, Dong-Woo;Lee, Min-Seok
    • Journal of the Korean Institute of Rural Architecture
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    • v.22 no.4
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    • pp.43-50
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    • 2020
  • The purpose of this study is to extract deficiency areas as basic data of policies and projects in the future Living SOC introduction and planning. In order to extract living SOC deficient areas, accessibility data for living SOC and density data for main users by facility were overlapped, focusing on the living SOC indicators presented in the National Urban Regeneration Basic Policy. According to the analysis of accessibility of the Iksan-si Living SOC, the gap between deficiency in urban and township areas was large in common with the accessibility of the village and local base units. As a result of overlapping life SOC accessibility data and density data analysis of the main users by facility, areas where accessibility is weak but not inhabited by the main users of each facility were extracted. It is meaningful that more accurate deficient areas can be extracted by simultaneously utilizing the density distribution of the main users, rather than simply accessing the facilities.

A Study on Space Consumption Behavior of Contemporary Consumers -Focusing on Analysis of Social Media Big Data- (현대 소비자의 공간소비행동에 관한 연구 -소셜미디어 데이터 분석을 중심으로-)

  • Ahn, Suh Young;Koh, Ae-Ran
    • Journal of the Korean Society of Clothing and Textiles
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    • v.44 no.5
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    • pp.1019-1035
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    • 2020
  • This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.

Design of Distributed Processing Framework Based on H-RTGL One-class Classifier for Big Data (빅데이터를 위한 H-RTGL 기반 단일 분류기 분산 처리 프레임워크 설계)

  • Kim, Do Gyun;Choi, Jin Young
    • Journal of Korean Society for Quality Management
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    • v.48 no.4
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    • pp.553-566
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    • 2020
  • Purpose: The purpose of this study was to design a framework for generating one-class classification algorithm based on Hyper-Rectangle(H-RTGL) in a distributed environment connected by network. Methods: At first, we devised one-class classifier based on H-RTGL which can be performed by distributed computing nodes considering model and data parallelism. Then, we also designed facilitating components for execution of distributed processing. In the end, we validate both effectiveness and efficiency of the classifier obtained from the proposed framework by a numerical experiment using data set obtained from UCI machine learning repository. Results: We designed distributed processing framework capable of one-class classification based on H-RTGL in distributed environment consisting of physically separated computing nodes. It includes components for implementation of model and data parallelism, which enables distributed generation of classifier. From a numerical experiment, we could observe that there was no significant change of classification performance assessed by statistical test and elapsed time was reduced due to application of distributed processing in dataset with considerable size. Conclusion: Based on such result, we can conclude that application of distributed processing for generating classifier can preserve classification performance and it can improve the efficiency of classification algorithms. In addition, we suggested an idea for future research directions of this paper as well as limitation of our work.