• Title/Summary/Keyword: 4.19 Revolution

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Study on Tendency of Cloud Computing Using R and LDA Technique : Focusing on Tendency of Overseas Studies (R과 LDA 기법을 활용한 클라우드 컴퓨팅 동향에 관한 연구: 해외 연구 동향을 중심으로)

  • Kang, Tae-Gu
    • Journal of the Korea Convergence Society
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    • v.13 no.5
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    • pp.261-266
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    • 2022
  • The full-fledged digital age derived from the fourth industrial revolution and the impact of COVID-19 lead to changes in various fields, including companies. In other words, the importance of cloud computing is being emphasized in the rapidly changing digital environment due to the rapid growth of the cloud market due to the rapid increase in digital services. The cloud may be one of the representative strategies for sustainable growth and survival in various fields as well as related industries. Although there have been a variety of studies on the cloud, the tendency of them has been not been adequately examined. This paper, therefore, analyzed the tendency of studies on the cloud computing. by using SCOPUS, the database of overseas academic journals using both R and LAD technique. The findings showed that many studies with high interest in the cloud computing have been conducted, the cloud computing were most often drawn from an analysis on key words. Moreover, various key words, including cloud, cloud and computing, data and computing were drawn, except for the theme of cloud computing. It is expected that could be used as a basic data, in that they provide the foundation for activating the related industries in terms of practice of the cloud computing.

Server State-Based Weighted Load Balancing Techniques in SDN Environments (SDN 환경에서 서버 상태 기반 가중치 부하분산 기법)

  • Kyoung-Han, Lee;Tea-Wook, Kwon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1039-1046
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    • 2022
  • After the COVID-19 pandemic, the spread of the untact culture and the Fourth Industrial Revolution, which generates various types of data, generated so much data that it was not compared to before. This led to higher data throughput, revealing little by little the limitations of the existing network system centered on vendors and hardware. Recently, SDN technology centered on users and software that can overcome these limitations is attracting attention. In addition, SDN-based load balancing techniques are expected to increase efficiency in the load balancing area of the server cluster in the data center, which generates and processes vast and diverse data. Unlike existing SDN load distribution studies, this paper proposes a load distribution technique in which a controller checks the state of a server according to the occurrence of an event rather than periodic confirmation through a monitoring technique and allocates a user's request by weighting it according to a load ratio. As a result of the desired experiment, the proposed technique showed a better equal load balancing effect than the comparison technique, so it is expected to be more effective in a server cluster in a large and packet-flowing data center.

Design and Application of App-Inventor-Software Class using Artificial Intelligence (인공지능을 활용한 앱인벤터 소프트웨어 교육 수업 설계 및 적용)

  • Park, Mi Hee;Hu, Kyeong
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.13-23
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    • 2021
  • This study requires SW education that can adapt to the advent of the fourth industrial revolution and the new normal environment of COVID-19 pandemic. Small and powerful smartphones, which have become a necessity in digital society, are designed and applied to create apps with useful apps or artificial intelligence modules that have been trained with data using the App Inventor program as a good teaching tool. After conducting the class in a blended method that combines face-to-face and non-face methods, the survey questioned the technical and cognitive maturity of artificial intelligence and the pros and cons of blended software classes. We also found changes in career orientation, which is intended to explore SW-related talent occupations that require a lot of demand in terms of national development before and after artificial intelligence classes. Significant results were reached in three of the sub-elements. Even in non-face-to-face situations, it is expected that an app vendor software education program using artificial intelligence will be provided to the actual site.

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A Development and Effectiveness of Unplugged class Using a Completion Robot (완성형 로봇을 활용한 언플러그드 수업 설계 및 적용 효과)

  • Lee, Hyemin;Shin, Seungki
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.159-165
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    • 2021
  • Through the fourth industrial revolution and coronavirus pandemic situation, the necessity and importance of SW education are being emphasized more. However, it is difficult to achieve the effect of improving students' computational thinking skills by just 17th hour, which is organized in the 2015 revised curriculum. Moreover, due to the coronavirus pandemic situation that has continued since last year, there are environmental restrictions on the equal SW education for students at the educational site. In this study, the unplugged class using a completion robot was designed to reflect the current situation at the educational site and experience of SW education was provided to the 6th graders of J elementary school. Through the application of a class, we checked whether the unplugged class using robots affect students' perception of SW education and the use of computational thinking skills. As a result, the unplugged class using a completion robot showed that students used computational thinking to solve given problems and had a positive impact on changes in perception of SW education.

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Enhancement of Enterprise Security System Using Zero Trust Security (제로 트러스트 보안을 활용한 기업보안시스템 강화 방안)

  • Lee, Seon-a;Kim, Beom Seok;Lee, Hye in;Park, Won hyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.214-216
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    • 2021
  • It proposes a plan to strengthen the limitations of existing corporate security systems based on Zero-Trust. With the advent of the era of the Fourth Industrial Revolution, the paradigm of security is also changing. As remote work becomes more active due to cloud computing and COVID-19, security issues arising from the changed IT environment are raised. At the same time, in the current situation where attack techniques are becoming intelligent and advanced, companies should further strengthen their current security systems by utilizing zero trust security. Zero-trust security increases security by monitoring all data communications based on the concept of doubting and trusting everything, and allowing strict authentication and minimal access to access requestors. Therefore, this paper introduces a zero trust security solution that strengthens the existing security system and presents the direction and validity that companies should introduce.

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A Study on hotel AI robot service built on the value-attitude-behavior(VAB) model (가치-태도-행동 모델을 적용한 호텔 AI 로봇서비스에 관한 연구)

  • Hejin Chun;Heeseung Lee
    • Smart Media Journal
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    • v.12 no.8
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    • pp.60-68
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    • 2023
  • After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.

A Study on the Factors Influencing the Competitiveness of Small and Medium Companies Applied with Smart Factory System (스마트공장 시스템 구축이 중소기업 경쟁력에 미치는 요인에 관한 연구)

  • Young-Hwan Choi;Sang Hyun Choi
    • Information Systems Review
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    • v.19 no.2
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    • pp.95-113
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    • 2017
  • The advent of information communication technology or the Fourth Industrial Revolution facilitated the fusion of equipment and management systems, such as Manufacturing Execution System, Enterprise Resource Planning, and Product Lifecycle Management, in the successful implementation of smart factories. The government supports the early adoption of these systems in small and medium companies to enhance their global competitiveness in producing products that can be recognized in a dramatically changing manufacturing environment. This study introduces smart factories to improve company competitiveness and address influences from the government assistance, CEO leadership, external consultancy, and organizational participation. We analyzed 101 results received from the questionnaires circulated to small- and medium-sized manufacturing companies. Given a successful smart factory implementation, company competitiveness is the factor that mostly influences organizational participation, government assistance, external consultancy, and CEO leadership. This study suggests several perspectives to implement a smart factory, which is the most important aspect of company competitiveness.

A Study on the intentions of early users of metaverse platforms using the Technology Acceptance Model (기술수용모델을 활용한 메타버스 플랫폼 초기 이용자들의 이용 의도에 관한 연구)

  • Park, Sunkyung;Kang, Yoon Ji
    • Journal of Digital Convergence
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    • v.19 no.10
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    • pp.275-285
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    • 2021
  • The purpose of this study is to empirically identify the process of technology acceptance of the metaverse, a virtual world-based platform that has attracted attention due to the 4th industrial revolution and the COVID-19 pandemic. The technology acceptance model (TAM) was used to identify factors affecting the use of the metaverse platforms and to analyze the causal relationship among these factors. For research, a survey was conducted on ordinary adult men and women and was analyzed using a structural equation model. The study found that perceived pleasure, interactivity, self-efficacy, and social influence had a positive effect on perceived ease-of-use. Interactivity and social influence had a statistically significant effect on perceived usefulness. The relationship between perceived ease-of-use and perceived usefulness was not statistically significant, but both perceived ease-of-use and perceived usefulness had a significant effect on positively forming attitudes toward metaverse. Lastly, favorable attitudes toward the metaverse platform had a positive effect on the intention to continue using it. Through this study, it was possible to identify the factors affecting the intention to use the metaverse and to confirm the causal relationship between the factors. A deeper understanding of users may be obtained in future if the research subject can be expanded and investigated with various factors.

Analysis of connectedness Between Energy Price, Tanker Freight Index, and Uncertainty (에너지 가격, 탱커운임지수, 불확실성 사이의 연계성 분석)

  • Kim, BuKwon;Yoon, Seong-Min
    • Journal of Korea Port Economic Association
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    • v.38 no.4
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    • pp.87-106
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    • 2022
  • Uncertainties in the energy market are increasing due to technology developments (shale revolution), trade wars, COVID-19, and the Russia-Ukraine war. Especially, since 2020, the risk of international trade in the energy market has increased significantly due to changes in the supply chain of transportation and due to prolonged demand reduction because of COVID-19 and the Russian-Ukraine war. Considering these points, this study analyzed connectedness between energy price, tanker index, and uncertainty to understand the connectedness between international trade in the energy market. Main results are summarized as follows. First, as a result of analyzing stable period and unstable period of the energy price model using the MS-VAR model, it was confirmed that both the crude oil market model and the natural gas market model had a higher probability of maintaining stable period than unstable period, increasing volatility by specific events. Second, looking at the results of the analysis of the connectedness between stable period and unstable period of the energy market, it was confirmed that in the case of total connectedness, connectedness between variables was increased in the unstable period compared to the stable period. In the case of the energy market stable period, considering the degree of connectedness, it was confirmed that the effect of the tanker freight index, which represents the demand-side factor, was significant. Third, unstable period of the natural gas market model increases rapidly compared to the crude oil market model, indicating that the volatility spillover effect of the natural gas market is greater when uncertainties affecting energy prices increase compared to the crude oil market.

Generative Adversarial Network Model for Generating Yard Stowage Situation in Container Terminal (컨테이너 터미널의 야드 장치 상태 생성을 위한 생성적 적대 신경망 모형)

  • Jae-Young Shin;Yeong-Il Kim;Hyun-Jun Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.383-384
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    • 2022
  • Following the development of technologies such as digital twin, IoT, and AI after the 4th industrial revolution, decision-making problems are being solved based on high-dimensional data analysis. This has recently been applied to the port logistics sector, and a number of studies on big data analysis, deep learning predictions, and simulations have been conducted on container terminals to improve port productivity. These high-dimensional data analysis techniques generally require a large number of data. However, the global port environment has changed due to the COVID-19 pandemic in 2020. It is not appropriate to apply data before the COVID-19 outbreak to the current port environment, and the data after the outbreak was not sufficiently collected to apply it to data analysis such as deep learning. Therefore, this study intends to present a port data augmentation method for data analysis as one of these problem-solving methods. To this end, we generate the container stowage situation of the yard through a generative adversarial neural network model in terms of container terminal operation, and verify similarity through statistical distribution verification between real and augmented data.

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