• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2034-2046
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• 2023

Industrial control systems in nuclear facilities are facing increasing cyber threats due to the widespread use of information and communication equipment. To implement cyber security programs effectively through the RG 5.71, it is necessary to quantitatively assess cyber risks. However, this can be challenging due to limited historical data on threats and customized Critical Digital Assets (CDAs) in nuclear facilities. Previous works have focused on identifying data flows, the assets where the data is stored and processed, which means that the methods are heavily biased towards information security concerns. Additionally, in nuclear facilities, cyber threats need to be analyzed from a safety perspective. In this study, we use the system theoretic process analysis to identify system-level threat scenarios that could violate safety constraints. Instead of quantifying the likelihood of exploiting vulnerabilities, we quantify Security Control Measures (SCMs) against the identified threat scenarios. We classify the system and CDAs into four consequence-based classes, as presented in NEI 13-10, to analyze the adversary impact on CDAs. This allows for the ranking of identified threat scenarios according to the quantified SCMs. The proposed framework enables stakeholders to more effectively and accurately rank cyber risks, as well as establish security and response strategies.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.72-81
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• 2023

As changes in social and economic paradigms are accelerating, and non-contact has become the new normal due to the COVID-19 pandemic, metaverse services that build societies in online activities and virtual reality are spreading rapidly. This study analyzes the perception and trend of metaverse fashion using big data. TEXTOM was used to extract metaverse and fashion-related words from Naver and Google and analyze their frequency and importance. Additionally, structural equivalence analysis based on the derived main words was conducted to identify the perception and trend of metaverse fashion. The following results were obtained: First, term frequency(TF) analysis revealed the most frequently appearing words were "metaverse," "fashion," "virtual," "brand," "platform," "digital," "world," "Zepeto," "company," and "game." After analyzing TF-inverse document frequency(TF-IDF), "virtual" was the most important, followed by "brand," "platform," "Zepeto," "digital," "world," "industry," "game," "fashion show," and "industry." "Metaverse" and "fashion" were found to have a high TF but low TF-IDF. Further, words such as "virtual," "brand," "platform," "Zepeto," and "digital" had a higher TF-IDF ranking than TF, indicating that they had high importance in the text. Second, convergence of iterated correlations analysis using UNICET revealed four clusters, classified as "virtual world," "metaverse distribution platform," "fashion contents technology investment," and "metaverse fashion week." Fashion brands are hosting virtual fashion shows and stores on metaverse platforms where the virtual and real worlds coexist, and investment in developing metaverse-related technologies is under way.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.435-439
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• 2015

It is important for Singaporean companies to manage the multifaceted risks when forming international construction joint ventures (ICJVs) with developing countries. The objectives of this study are to assess the risks associated with Singaporean ICJVs with developing countries, and investigate the risk allocation preferences in these ICJVs. To fulfill these objectives, a literature review was carried out and a questionnaire survey was performed with 38 professionals. The survey results reported "political instability" as the most critical risk, and market level risks were less critical than country and project level risks. Additionally, the results showed agreement on the risk ranking between building and infrastructure ICJVs, despite significant differences in the criticalities of five risks. Furthermore, five risks were preferably allocated to host and foreign partners, respectively, while 13 risks could be shared among partners. As few studies have explored the risk allocation preferences in ICJVs, this study expands the literature. Also, the identification of the risks allows other companies to customize their own lists of critical risks, while the preferred risk allocation provides valuable information for companies from various countries that intend to form ICJVs with developing countries. Thus, this study contributes to the global body of knowledge relating to ICJVs.

• Journal of Information Science Theory and Practice
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• v.11 no.4
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• pp.40-50
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• 2023

Research in interdisciplinary fields like biomechanics is published in a variety of journals whose visibility depends on bibliometric indexing that is often driven by citation analysis of bibliometric databases. This study documented variation in publication metrics and research subject categories assigned to 14 biomechanics journals. Authors, citation, and citation rate (CR) were collected for the top 15 cited articles in the journals retrieved from the Google Scholar service. Research subject categories were also extracted for journals from three databases (Dimensions, Journal Citation Reports, and Scopus). Despite the focus on biomechanics for the journals studied, these biomechanics journals have widely varying CR and subject categories assigned to them. There were significant (p=0.001) and meaningful (77-108%) differences in median CR between average, low, and high CR groups of these biomechanics journals. Since CR are primary data used to calculate most journal metrics and there is no one biomechanics subject category, field normalization for journal citation metrics in biomechanics is difficult. Care must be taken to accurately interpret most citation metrics of biomechanics journals as biased proxies of general usage of research, given a specific database, time frame, and area of biomechanics research.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.63-64
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• 2023

Indoor Air Quality is crucial in hospital projects to ensure the health and safety of patients, staff, and visitors. The research methodology comprises an comprehensive literature review, then a comprehensive questionnaire survey conducted among stakeholders involved in Vietnamese hospital projects. 15 variables were identified and categorized into four distinct groups, elucidating their influence on the adoption of advanced IAQ-enhancing technology. This study uses factor analysis, a mean score method and hypothesis test to analyze the factor result from the survey. two-step process, including an in-depth literature review and questionaire survey. The study's findings culminated in the ranking, examination, and categorization of these 15 variables, which were clustered into four essential categories: economic factors, design elements, governance strategies, and technical requirements. Additionally, the research explored viable solutions to improve indoor air quality in Vietnam's unique environmental context, examining the factors that impact the selection of such solutions. The study's outcomes yield practical recommendations for architects, engineers, and hospital administrators in enhancing IAQ within healthcare facilities. Furthermore, it presents a framework attuned to local environmental factors and building materials, contributing significantly to the existing body of knowledge on IAQ within hospital projects, particularly in the Vietnamese context.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2266-2273
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• 2024

A machine learning platform is proposed for the diagnosis of a severe accident progression in a nuclear power plant. To predict the key parameters for accident management including lost signals, a long short term memory (LSTM) network is proposed, where multiple accident scenarios are used for training. Training and test data were produced by MELCOR simulation of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident at unit 3. Feature variables were selected among plant parameters, where the importance ranking was determined by a recursive feature elimination technique using RandomForestRegressor. To answer the question of whether a reduced order ML model could predict the complex transient response, we performed a systematic sensitivity study for the choices of target variables, the combination of training and test data, the number of feature variables, and the number of neurons to evaluate the performance of the proposed ML platform. The number of sensitivity cases was chosen to guarantee a 95 % tolerance limit with a 95 % confidence level based on Wilks' formula to quantify the uncertainty of predictions. The results of investigations indicate that the proposed ML platform consistently predicts the target variable. The median and mean predictions were close to the true value.

• PNF and Movement
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• v.22 no.2
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• pp.289-303
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• 2024

Purpose: In this study, 100 stroke patients and 205 physical therapists were surveyed to determine the essential functions needed in the rehabilitation process of stroke patients. Methods: This study involved 100 stroke patients and 205 physical therapists. Sixteen functions suggested in the previous study as necessary in the rehabilitation process of stroke patients were selected, and a revised questionnaire was prepared and distributed to several institutions. A frequency analysis of the collected data was conducted to aggregate the functions required in rehabilitation, and a scoring process was used to determine their ranking among the 16 functions. Results: The functions required in the rehabilitation process, as selected by stroke patients, were ranked as follows: walking, toileting, eating, using products and technology for communication, and washing oneself. The functions required in the rehabilitation process, as selected by physical therapists, were ranked as follows: muscle power functions, maintaining body position, muscle tone functions, attention functions, and walking. Conclusion: The results of the study confirm the importance of an agreed goal between the stroke patient and the therapist regarding the functions required for the rehabilitation. This understanding plays a significant role in achieving the patient's expectations and the therapist's predicted performance, thereby providing reassurance and confidence in the impact of the research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.60-67
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• 2016

In cumulative transfer functions, as number of transfer increase, the impact of individual transfer to transfer cost increase linearly or non linearly. This function can effectively explain various passengers's travel behavior who choose their travel routes in integrated transit line networks including bus and railway modes. Using the function, it is possible to simulate general situations such that even though more travel times are expected, less number of transfer routes are preferred. However, because travel cost with cumulative transfer function is known as non additive cost function types in route search algorithms, finding an optimal route in integrated transit networks is confronted by the insolvable enumeration of all routes in many cases. This research proposes a methodology for finding an optimal path considering cumulative transfer function. For this purpose, the reversal phenomenon of optimal path generated in route search process is explained. Also a heuristic methodology for selecting an optimal route among multiple routes predefined by the K path algorithm. The incoming link based entire path deletion method is adopted for finding K ranking path thanks to the merit of security of route optimality condition. Through case studies the proposed methodology is discussed in terms of the applicability of real situations.

• Journal of the Korea Society of Computer and Information
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• v.16 no.10
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• pp.147-153
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• 2011

In this paper, we present a new video management technique using forward timeline to efficiently store and delete the videos on a local server. The proposed method is based on capturing the changing preference of the videos according to recentness, frequency, and playback length of the requested videos. For this purpose, we utilize the forward timeline which represents the time area within a number of predefined intervals. The local server periodically measures time popularity and request segment of all videos. Based on the measured data, time popularity and request segment, the local server calculates the mean time popularity and mean request segment of a video using forward timeline. Using mean time popularity and mean request segment of video, we estimate the ranking and allocated storage space of a video. The ranking represents the priority of deletion when the storage area of local server is running out of space and the allocated storage space means the maximum size of storage space to be allocated to a video. In addition, we propose an efficient storage space partitioning technique in order to stably store videos and present a time based free-up storage space technique using the expected variation of video data in order for avoiding the overflow on a local server in advance. The simulation results show that the proposed method performs better than other methods in terms of hit rate and number of deletion. Therefore, our video management technique for local server provides the lowest user start-up latency and the highest bandwidth saving significantly.

• Quality Improvement in Health Care
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• v.28 no.1
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• pp.45-54
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• 2022

Purpose: The study aims to identify the theme list and priority criteria of patient safety theme reports in South Korea. Methods: The survey was conducted twice, and the importance of each criterion and theme was measured on a nine-point scale using the Delphi technique by a panel of 19 patient safety experts. The criteria included severity, universality, preventability, and organizational-social impact. Descriptive statistics such as frequency, percentage, mean, standard deviation, median, and interval quartile range were used to analyze the data. Results: The parameters were assigned a weighted average of 35% for severity, 20% for universality, 30% for preventability, and 15% for organizational-social impact, respectively. The final top three rankings were surgery safety, blood transfusion safety, and medication safety. In addition to expert opinion, for the theme that is selected based on the priority ranking, one to five sub-topics can be derived from the theme based on the priority ranking, societal demands, or the yearly priority list of patient safety incidents. Conclusion: It is recommended that the official patient safety center distribute the report in the form of a summary that can be utilized nationwide at medical institutions, government institutions, and other places. Updates, as well as accumulated theme reports, will serve as the baseline data for the proposal of the system and for the policy designed to implement and improve institutions' safety practices as a standard of domestic patient safety practice guidelines.