• Title/Summary/Keyword: the $4^{th}$ Industrial revolution

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Development of Metrics to Measure Reusability of Services of IoT Software

  • Cho, Eun-Sook
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.12
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    • pp.151-158
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    • 2021
  • Internet of Things (IoT) technology, which provides services by connecting various objects in the real world and objects in the virtual world based on the Internet, is emerging as a technology that enables a hyper-connected society in the era of the 4th industrial revolution. Since IoT technology is a convergence technology that encompasses devices, networks, platforms, and services, various studies are being conducted. Among these studies, studies on measures that can measure service quality provided by IoT software are still insufficient. IoT software has hardware parts of the Internet of Things, technologies based on them, features of embedded software, and network features. These features are used as elements defining IoT software quality measurement metrics. However, these features are considered in the metrics related to IoT software quality measurement so far. Therefore, this paper presents a metric for reusability measurement among various quality factors of IoT software in consideration of these factors. In particular, since IoT software is used through IoT devices, services in IoT software must be designed to be changed, replaced, or expanded, and metrics that can measure this are very necessary. In this paper, we propose three metrics: changeability, replaceability, and scalability that can measure and evaluate the reusability of IoT software services were presented, and the metrics presented through case studies were verified. It is expected that the service quality verification of IoT software will be carried out through the metrics presented in this paper, thereby contributing to the improvement of users' service satisfaction.

Investigating Online Learning Types Based on self-regulated learning in Online Software Education: Applying Hierarchical Cluster Analysis (온라인 소프트웨어 교육에서 학습자의 자기조절학습 관련 특성에 기반한 온라인 학습 유형 분석: 계층적 군집 분석 기법을 활용하여)

  • Han, Jeongyun;Lee, Sunghye
    • The Journal of Korean Association of Computer Education
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    • v.22 no.5
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    • pp.51-65
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    • 2019
  • This study aims to provide educational implications for more strategic online software education by the types of online learning according to learners' self-regulated learning characteristics in the online software education environment and examining the characteristics of each type. For this, variables related to self-regulated learning characteristic were extracted from the log data of 809 students participating in the online software learning program of K University, and then analyzed using hierarchical cluster analysis. Based on hierarchical cluster analysis learner clusters according to the characteristics of self-regulated learning were derived and the differences between learners' learning characteristics and learning results according to cluster types were examined. As a result, the types of self-regulated learning of online software learners were classified as 'high level self-regulated learning type (group 1)', 'medium level self-regulated learning type (group 2)', and 'low level self-regulated learning type (group 3)'. The achievement level was found to be highest in 'high-level self-regulated learning type (group 1)' and 'low-level self-regulated learning type (group 3)' was the lowest. Based on these results, the implications for effective online software education were suggested.

Topic Modeling-Based Domestic and Foreign Public Data Research Trends Comparative Analysis (토픽 모델링 기반의 국내외 공공데이터 연구 동향 비교 분석)

  • Park, Dae-Yeong;Kim, Deok-Hyeon;Kim, Keun-Wook
    • Journal of Digital Convergence
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    • v.19 no.2
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    • pp.1-12
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    • 2021
  • With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

A Study on Global Blockchain Economy Ecosystem Classification and Intelligent Stock Portfolio Performance Analysis (글로벌 블록체인 경제 생태계 분류와 지능형 주식 포트폴리오 성과 분석)

  • Kim, Honggon;Ryu, Jongha;Shin, Woosik;Kim, Hee-Woong
    • Journal of Intelligence and Information Systems
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    • v.28 no.3
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    • pp.209-235
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    • 2022
  • Starting from 2010, blockchain technology, along with the development of artificial intelligence, has been in the spotlight as the latest technology to lead the 4th industrial revolution. Furthermore, previous research regarding blockchain's technological applications has been ongoing ever since. However, few studies have been examined the standards for classifying the blockchain economic ecosystem from a capital market perspective. Our study is classified into a collection of interviews of software developers, entrepreneurs, market participants and experts who use blockchain technology to utilize the blockchain economic ecosystem from a capital market perspective for investing in stocks, and case study methodologies of blockchain economic ecosystem according to application fields of blockchain technology. Additionally, as a way that can be used in connection with equity investment in the capital market, the blockchain economic ecosystem classification methodology was established to form an investment universe consisting of global blue-chip stocks. It also helped construct an intelligent portfolio through quantitative and qualitative analysis that are based on quant and artificial intelligence strategies and evaluate its performances. Lastly, it presented a successful investment strategy according to the growth of blockchain economic ecosystem. This study not only classifies and analyzes blockchain standardization as a blockchain economic ecosystem from a capital market, rather than a technical, point of view, but also constructs a portfolio that targets global blue-chip stocks while also developing strategies to achieve superior performances. This study provides insights that are fused with global equity investment from the perspectives of investment theory and the economy. Therefore, it has practical implications that can contribute to the development of capital markets.

A study on the Effect of Relational Energy and Resilience on Individual Job Performance through Job Crafting (관계적에너지와 회복탄력성이 직무재창조를 통하여 개인직무성과에 미치는 영향 연구)

  • Nam, Eun Woo;Sun, Eun Jung;Seo, Young Wook
    • The Journal of the Korea Contents Association
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    • v.22 no.2
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    • pp.529-544
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    • 2022
  • With the global pandemic in the era of the 4th industrial revolution, the business environment of companies was engulfed by rapid volatility and uncertainty. In particular, in order for an organization to have high competitiveness due to the spread of the flexible work system, relationship management with members of the organization and self-directed job crafting are recognized as important key resources. This study aims to investigate how relational energy and resilience within a corporate organization affect job crafting and to verify the effect of job crafting on individual job performance. For empirical research, 400 valid responses to employees of general companies were analyzed by SPSS 26.0 and Smart PLS 3.0. As a result of the analysis, first, it was confirmed that relational energy did not have a positive (+) effect on task crafting. Second, it was found that relational energy had a positive (+) effect on relational crafting and cognitive crafting, respectively. Third, it was found that resilience had a positive (+) effect on both task crafting, relationship crafting, and cognitive crafting that constitute job crafting. Fourth, it was found that job crafting had a positive (+) effect on individual job performance. Based on these research results, we intend to derive academic and practical implications and provide practical help to follow-up researchers and stakeholders.

A Case Study on the Application of AI-OCR for Data Transformation of Paper Records (종이기록 데이터화를 위한 AI-OCR 적용 사례연구)

  • Ahn, Sejin;Hwang, Hyunho;Yim, Jin Hee
    • Journal of the Korean Society for information Management
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    • v.39 no.3
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    • pp.165-193
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    • 2022
  • It can be said that digital technology is at the center of the change in the modern work environment. In particular, in general public institutions that prove their work with records produced by business management systems and document production systems, the record management system is also the work environment itself. Gimpo City applied for the 2021 public cloud leading project of the National Information Society Agency (NIA) to proactively respond to the 4th industrial revolution technology era and implemented a public cloud-based AI-OCR technology enhancement project with 330 million won in support of 330 million won. Through this, it was converted into data beyond the limitations of non-electronic records limited to search and image viewing that depend on standardized index values. In addition, a 98% recognition rate was realized by applying a new technology called AI-OCR. Since digital technology has been used to improve work efficiency, productivity, development cost, and record management service levels of internal and external users, we would like to share the direction of enhancing expertise in the record management and implementation of work environment innovation.

Autonomous Ship's Remote Operation Situation Occurrence Probability Estimation Model based on Navigation Areas (운항 해역별 자율운항선박 원격운항 상황 발생 확률 추산 시뮬레이션 모델)

  • Taewoong Hwang;Taemin Hwang;Dain Lee;Hyeinn Park;Ik-Hyun Youn
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.910-914
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    • 2023
  • With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

Development of Wearable Physical Activity Monitoring System (웨어러블 신체 생체 활동 모니터링 시스템 개발)

  • Park, Eun-Ju;Park, Do-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.1
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    • pp.34-39
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    • 2018
  • Along with the development of ICT technology, wearable devices of various sizes and shapes have been developed. In addition, performance and specifications are rebuilt with IOT fusion products so that they can connect with the current smartphone. This is one of the general-purpose technologies of the 4th industrial revolution, which is spot-lighted with technology that changes the quality and environment of our lives. Along with this, as new technology products combining health care technology increases, various functions are provided to users who need it. Wearable technology is ongoing trend of technology development. It also sells products developed as products in the form of smart watches. At present, various related products are made in various ways, and it is recommended to use the Arduino processor in accordance with the application. In this study, we developed wearable physical activity monitoring system using open source hardware based TinyDuino. TinyDuino is an ultra-compact Arduino compatible board made on the basis of Atmega process Board, and it can be programmed in open source integrated development environment(named Sketch). The physical activity monitoring system of the welfare body can be said to be a great advantage, as a smart u-Healthcare system that can perform daily health management.

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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Fostering Entrepreneurship by Maker Education: A Case Study in an Higher Education (메이커 교육(Maker Education)을 통한 기업가정신 함양:대학교 사례연구)

  • Kang, In-Ae;Kim, Yang-Soo;Yoon, Hyea-Jin
    • Journal of the Korea Convergence Society
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    • v.8 no.7
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    • pp.253-264
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    • 2017
  • The advent of the $4^{th}$ industrial Revolution requires entrepreneurship to the student as one able to produce creative solutions of complex problems embedded in society with active engagement. Maker Education indicates a new educational approach in which students produce a tangible output as a concrete solution to their problems, experiencing spirits of productive failure, sharing and openness with others during the process due to its educational values and effects which are well-matched with entrepreneurship. This study, in this context, aimed to verify the effect of the maker education in the sense of cultivating entrepreneurship: For this purpose, this study conducted a case study of Maker Education to 56 university students during 7 weeks (14 hours) in K university. The results based upon data analysis collected from reflective journals and interviews showed attitude change of the students in terms of entrepreneurship characterized as self-directedness, risk-taking, and creativity. For more active practices of Maker Education in higher education, both instructors' role as the facilitator, and easily and freely accessible Maker Space should be considered.