• Korean Journal of Childcare and Education
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• v.18 no.6
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• pp.75-99
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• 2022

Objective: This study aims to explore ways to empirically analyze and manage childcare teachers' job stress based on their relationship with stress-related physiological indicators measured by a fitness tracker. Methods: The study participants were 27 childcare teachers in Gyeonggi-do and wore Garmin's wearable fitness tracker Vivosmart 4 for 15 days for three months. The collected information was analyzed for mean, SD, ANOVA, and correlation using JAMOVI 2.00. Results: First, among the daily changes of physiological indicators measured by a fitness tracker, the data collected on Mondays were significant. On Mondays, the stress index was high, the duration of the rest period was short, and the sleep time was short. The stress of childcare teachers showed a significant negative relationship with the body battery which was calculated by considering the duration of the rest period, heart rate variability, stress, and activity level. Also, the duration of deep sleep was positively correlated with a low degree of stress. There was a significant relationship between the childcare teachers' psychological indicators and the biomarkers measured by fitness trackers. Conclusion/Implications: Stress research using a fitness tracker is big data, and in-depth analysis is possible. Fitness trackers can collect and utilize repeated measurement data for each individual childcare teacher.

• Journal of Distribution Science
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• v.22 no.6
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• pp.115-122
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• 2024

Purpose: The main aim of this study is to analyze and suggest new online music distribution models targeted to facilitate the development of the Korean Wave (Hallyu) music market in all locations of the world. This study is conducted through a close analysis of the prevailing distribution models, the unique challenges of the K-pop market, and the trends in new technologies. Research design, data and methodology: To address the issue of how the online music distribution market could be domesticated for the Korean music industry, a systematic review of the previous studies was conducted. The use of the PRISMA approach was followed so that an accurate and transparent method for choosing the studies is ensured. Results: According to the investigation of literature analysis, the online distribution strategy may consist of four key plannings as follows, 1. Leveraging Social Media and User-Generated Content Platforms, 2. Embracing Immersive and Interactive Experiences, 3. Fostering Direct-to-Fan Connections and Monetization, 4. Harnessing Artificial Intelligence and Big Data Analytics. Conclusions: Finally, collaboration and strategic partnerships will be vital. The Korean music companies should seek to cooperate with the technology companies, social media platforms, and the global music streaming services so that they can grow their market, acquire new technologies, and to better their online distribution strategies.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.64-69
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• 2024

According to the market research report, the nuclear decommissioning services market is currently experiencing considerable growth, with a projected Compound Annual Growth Rate (CAGR) of nearly 13% during the 2020-2024 forecast period. This expansion is primarily fueled by the advancement of Industry 4.0, in conjunction with the emergence of cutting-edge technologies such as the Internet of Things, big data, artificial intelligence, and 5G. Even though the fact that robots have already been utilized in the nuclear industry, their adoption has been hindered by conservative regulations. However, the nuclear decommissioning market presents an opportunity for the advancement of robotics technology. The British have already invested heavily in encouraging the use of intelligent robots for nuclear decommissioning, and other countries, such as Taiwan, should follow suit. Taiwan's flourishing robotics development industry in manufacturing, logistics, and other domains can be leveraged to introduce advanced robotics in the decommissioning of its nuclear power plants. By doing so, Taiwan can establish itself as a competitive player in the nuclear decommissioning services market for the next two decades.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1599-1618
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• 2024

Access control has always been one of the effective methods to protect data security. However, in new computing environments such as big data, data resources have the characteristics of distributed cross-domain sharing, massive and dynamic. Traditional access control mechanisms are difficult to meet the security needs. This paper proposes CACM-MMSR to solve distributed cross-domain access control problem for massive resources. The method uses blockchain and smart contracts as a link between different security domains. A permission decision model migration method based on access control logs is designed. It can realize the migration of historical policy to solve the problems of access control heterogeneity among different security domains and the updating of the old and new policies in the same security domain. Meanwhile, a semantic reasoning-based permission decision method for unstructured text data is designed. It can achieve a flexible permission decision by similarity thresholding. Experimental results show that the proposed method can reduce the decision time cost of distributed access control to less than 28.7% of a single node. The permission decision model migration method has a high decision accuracy of 97.4%. The semantic reasoning-based permission decision method is optimal to other reference methods in vectorization and index time cost.

• Journal of Research and Publication Ethics
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• v.5 no.2
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• pp.17-23
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• 2024

Purpose: The internet, as a tool, avenue, and field, has wide-researching and specific ethical concerns. Internet-based research ethics is a field that spreads across numerous fields, scoping from natural and biomedical sciences to social sciences, and arts and humanities. Thus, this study which investigates research ethics within an Internet-based Research Setting will be quite valuable. Research design, data and methodology: The current authors widely took a look at prior and present literature dataset to explore research ethics within an Internet-based setting. Using numerous search engine, such as 'Goole Scholar', 'Scopus', and 'Web of Science', the current authors could obtain total 42 prior studies that are relevant with our research topic. Results: Based on the screening process in the literature datasets, this study could categorize four areas of the research ethics within Internet-based research setting as follows: (1) Human Subjects Ethics, (2) Big Data Ethical Issues, (3) Research Ethics and Cloud, and (4) Computing Interviews and Surveys Ethics. Conclusions: This study concludes that although internet-based research has many benefits, the accompanying ethical issues are many. The lack of uniformity in the concept and terminology of online research methods typically brings forth confusion and makes it hard for new researchers to develop mutual guidelines.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.971-978
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• 2022

Fertigation, which has been introduced in agricultural fields since 1990, has been widely practiced in upland fields as well as in plastic film houses as part of the crop production system. In accordance with demands in the agricultural sector, a huge number of scientific studies on fertigation have been conducted worldwide. Moreover, with a combination of advanced technologies such as big-data, machine learning, etc., fertigation is positioned as an indispensable tool to achieve sustainable crop production and to enhance nutrient and water use efficiency. In this review, we focused on providing valuable information in terms of crop production and nutrient/water use efficiency. A variety of fertigation studies have described that enhancement of crop production did not differ relative to conventional method or slightly increased. In contrast, fertigation significantly improved nutrient/water use efficiency, with a reduction in use ranging from 20 to 50%. Water-soluble organic resources such as livestock manure and agricultural byproducts also have been identified as useful resources like chemical fertilizers. Furthermore, the initial irrigation point was generally recommended in a range of -10 - -40 kPa, although the point differed according to the crop and crop growth stage. From this review, we suggest that fertigation, which is closely integrated with advanced technology, could be a leading technology to attain not only food security but also carbon neutrality via improvement of nutrient/water use efficiency.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.285-292
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• 2024

Physiological devices and immersive technologies are crucial innovations being implemented for construction safety. Physiological devices provide insights into the wellbeing of workers while immersive technologies have a potential to simulate or enhance construction environments. These two technologies present numerous benefits for construction safety and have been extensively implemented in various dimensions. In addition to the individual benefits of these two technologies, combining them presents more opportunities for construction safety research and numerous studies have been conducted using this approach. However, despite promising results achieved by studies which have used this technological combination, no review has been conducted to summarize the findings of these studies. This review therefore summarizes studies that have combined immersive technologies with physiological monitoring for construction safety. A systematic approach is employed, and 24 articles are reviewed. This review highlights four safety aspects which have been explored using a combination of immersive technologies and physiological monitoring. These aspects are (1) Safety training and evaluation (2) Hazard identification (3) Attention assessment and (4) Cognitive strain assessment. In addition, there are three main directions for future research. (1) Future studies should explore other types of immersive technologies such as immersive audio (2) Physiological reactions to hazard exposure should be studied and (3) More multi-physiological approaches should be adopted.

• Journal of Internet Technology
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• v.22 no.4
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• pp.903-911
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• 2021

As cyber-attacks on Cyber-Physical System (CPS) become more diverse and sophisticated, it is important to quickly detect malicious behaviors occurring in CPS. Since CPS can collect sensor data in near real time throughout the process, there have been many attempts to detect anomaly behavior through normal behavior learning from the perspective of data-driven security. However, since the CPS datasets are big data and most of the data are normal data, it has always been a great challenge to analyze the data and implement the anomaly detection model. In this paper, we propose and evaluate the Clustered Deep One-Class Classification (CD-OCC) model that combines the clustering algorithm and deep learning (DL) model using only a normal dataset for anomaly detection. We use auto-encoder to reduce the dimensions of the dataset and the K-means clustering algorithm to classify the normal data into the optimal cluster size. The DL model trains to predict clusters of normal data, and we can obtain logit values as outputs. The derived logit values are datasets that can better represent normal data in terms of knowledge distillation and are used as inputs to the OCC model. As a result of the experiment, the F1 score of the proposed model shows 0.93 and 0.83 in the SWaT and HAI dataset, respectively, and shows a significant performance improvement over other recent detectors such as Com-AE and SVM-RBF.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.193-204
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• 2009

The study was conducted investigation on land of D-dong in N city which is an urban area and D myeon of N city which is a suburban area, based on high resolution satellite image, to find out actual land usage. As for D-dong in N city, different rate between actual usage and official land information was 0.5~4.8% in terms of 5 major land types (paddy field, farm, ground, forest, and others). D myeon in N city posted 1.4~8.4%, which is higher than that of its counterpart. As for unit load, "land" which is large in terms of load presented a big difference between official information and actual usage. On the other hand, the levels of paddy, field, forest and others posted only small changes in load. In case of T-P, in particular, unit of each land type is lower than BOD and T-N, showing almost no changes in pollution loads.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.253-261
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• 2005

In this paper, we propose an efficient block-based disparity estimation algorithm fur multiple view image coding in EE2 and EE3 in 3DAV. The proposed method emphasizes on visual quality improvement to satisfy the requirements for multiple view generation. Therefore, we perform an adaptive disparity estimation that constructs variable blocks by considering given image features. Examining neighboring features around desired block search range is set up to decrease complexity and additional information than only using quad-tree coding through applying binary-tree and quad-tree coding by taking into account stereo image feature having big disparity. The experimental results show that the proposed method improves PSNR about 1 to 2dB compared to existing other methods and decreases computational complexity up to maximum 68 percentages than FBMA.