• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.43-49
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• 2005

The purpose of this study was to provide the fundamental data for the gradual apartment management plan. Through the questionnaire survey, residential satisfactions and maintenance consciousness were investigated. As the result of statistic analysis, the residents' needs for improvement according to the life span of apartment communities were found out. And we can also compare the differences about maintenance consciousness to the life span of apartment. The major research findings are as follows. First, the satisfaction averages according to the life span of apartment communities were classified two groups, less than 10 years' and over than 10 years'. By the requirement for improvement according as the life span apartment communities, habitability factors was demanded in less tham 10 years' group and safety factors was required in over than 10 years' group, Second, dwellers have high preference about remodeling to reconstruction. Especially we have to pay attention to the result that positive consciousness of remodeling and long term reparative marked highly in the group which has the short elapsed years. These results represent the possibility gradual step-by-step remodeling. In other words, the object of remodeling is not only odeteriorated apartments but also new apartments to have short elapsed years.

• Wind and Structures
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• v.38 no.1
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• pp.75-91
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• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.49-55
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• 2005

Unconditional clearance levels were derived for fifteen short-lived radionuclides. Due to the uncertainty of long-term radiological impact analysis, alpha emitting nuclides and nuclides with half-lives longer than 30 years (except for C-14) were excluded from the scope of this study. The candidate waste streams are solid wastes and waste oil generated from nuclear power reactors. The clearance levels were derived by generic assessment for enveloping scenarios, along with specific assessment for each detailed scenario such as landfill, incineration and recycling. The derived values lie in the range from 0.01 to 100 Bq/g.

• Safety and Health at Work
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• v.15 no.2
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• pp.213-219
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• 2024

Background: The design, implementation, and evaluation are three important stages of occupational safety and health (OSH) interventions. Historically, there has been a tendency to prioritize implementation, often neglecting detailed design and rigorous outcome evaluation. Currently, much has changed, and contemporary approaches recognize the interdependence of these stages, considering them integral to the success of any intervention. This work presents a comprehensive procedure for implementing interventions, not only to ensure short-term effectiveness but also their long-term sustainability through continuous monitoring. The focus is on a national OSH project introducing a near-miss management system (NMS) in Italy. Methods: Initial meetings were convened among project partners, complemented by interviews with diverse stakeholders, to plan implementation steps and test the NMS. Tailored questionnaires were designed for diverse stakeholder groups - initial promoters, company managers and employers, and employees - facilitating targeted implementation, and three case studies were started in Italian regions to assess the structured implementation, involving intervention promoters and collaborating companies. Results: The primary outcome is the development of practical tools, specifically three questionnaires, which are considered valuable for establishing an effective human-centered implementation strategy, meticulously designed to facilitate ongoing monitoring of processes and continual enhancement of instruments intended for NMS integration within companies. Conclusions: This work lays the foundation for successful NMS implementation in Italy and, although the outlined procedure had specific objectives, it also provides valuable insights applicable in enhancing the effectiveness and sustainability of interventions across diverse contexts. It underscores the importance of comprehensive planning, stakeholder engagement, and continuous evaluation in achieving lasting OSH interventions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1031-1037
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• 2021

The frequency of marine accidents of vessels in Korea is steadily increasing and it is concentrated on small vessels with less than 10 tons of gross tonnage. Therefore, preventing capsizing accidents in small vessels is important to reduce the cost in terms of human and property damage due to such accidents. However, research on the seakeeping performance of small vessels has been insufficient, and there are no domestic and international regulations on seakeeping performance. Therefore, in this study, capsizing accidents caused by poor loading conditions were investigated by examining the adjudications of the small vessels in which the capsizing accidents occurred. Hydrostatic calculations and seakeeping performance analysis were performed for a representative vessel. A vessel generally performs a six-degree-of-freedom motion during operation. In this study, the response amplitude operator and response spectrum of a representative vessel were calculated to determine the roll motion. Moreover, a short-term statistical analysis of the vessel according to the loading conditions was performed for the wave stationary status for 3 h. From the results, it was estimated that, when the loading condition of a small vessel is poor, its roll motion increases, greatly reducing its stability.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.765-771
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• 2022

Objective : Stent-assisted coil embolization (SAC) has been increasingly used to treat various types of intracranial aneurysms. Delayed thromboembolic complications are major concerns regarding this procedure, so dual antiplatelet therapy with aspirin and clopidogrel is needed. However, clinicians vary the duration of dual antiplatelet therapy after SAC, and no randomized study has been performed. This study aims to compare the safety and efficacy of long-term (12 months) dual antiplatelet therapy and short-term dual antiplatelet therapy (6 months) after SAC for patients with unruptured intracranial aneurysms (UIAs). Methods : This is a prospective, randomized and multicenter trial to investigate the optimal duration of dual antiplatelet therapy after SAC in patients with UIAs. Subjects will receive dual antiplatelet therapy for 6 months (short-term group) or 12 months (long-term group) after SAC. The primary endpoint is the assessment of thromboembolic complications between 1 and 18 months after SAC. We will enroll 528 subjects (264 subjects in each group) and perform 1 : 1 randomization. This study will involve 14 top-performing, high-volume Korean institutions specializing in coil embolization. Results : The trial will begin enrollment in 2022, and clinical data will be available after enrollment and follow-up. Conclusion : This article describes that the aim of this prospective randomized multicenter trial is to compare the effect of short-term (6 months) and long-term (12 months) dual antiplatelet therapy on UIAs in patients undergoing SAC, and to find the optimal duration.

• Safety and Health at Work
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• v.8 no.3
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• pp.237-245
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• 2017

Background: Solar furnaces are used worldwide to conduct experiments to demonstrate the feasibility of solar-chemical processes with the aid of concentrated sunlight, or to qualify high temperature-resistant components. In recent years, high-flux solar simulators (HFSSs) based on short-arc xenon lamps are more frequently used. The emitted spectrum is very similar to natural sunlight but with dangerous portions of ultraviolet light as well. Due to special benefits of solar simulators the increase of construction activity for HFSS can be observed worldwide. Hence, it is quite important to protect employees against serious injuries caused by ultraviolet radiation (UVR) in a range of 100 nm to 400 nm. Methods: The UV measurements were made at the German Aerospace Center (DLR), Cologne and Paul-Scherrer-Institute (PSI), Switzerland, during normal operations of the HFSS, with a high-precision UV-A/B radiometer using different experiment setups at different power levels. Thus, the measurement results represent UV emissions which are typical when operating a HFSS. Therefore, the biological effects on people exposed to UVR was investigated systematically to identify the existing hazard potential. Results: It should be noted that the permissible workplace exposure limits for UV emissions significantly exceeded after a few seconds. One critical value was strongly exceeded by a factor of 770. Conclusion: The prevention of emissions must first and foremost be carried out by structural measures. Furthermore, unambiguous protocols have to be defined and compliance must be monitored. For short-term activities in the hazard area, measures for the protection of eyes and skin must be taken.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.183-191
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• 2021

A battery management system (BMS) provides some functions for ensuring safety and reliability that includes algorithms estimating battery states. Given the changes caused by various operating conditions, the state-of-health (SOH), which represents a figure of merit of the battery's ability to store and deliver energy, becomes challenging to estimate. Machine learning methods can be applied to perform accurate SOH estimation. In this study, we propose a Long-Term Recurrent Convolutional Network (LRCN) that combines the Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) to extract aging characteristics and learn temporal mechanisms. The dataset collected by the battery aging experiments of NASA PCoE is used to train models. The input dataset used part of the charging profile. The accuracy of the proposed model is compared with the CNN and LSTM models using the k-fold cross-validation technique. The proposed model achieves a low RMSE of 2.21%, which shows higher accuracy than others in SOH estimation.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.75-84
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• 2016

Medical cyber-physical systems (MCPS) integrate sensors, actuators, and software to improve patient safety and quality of healthcare. These systems introduce major challenges to safety analysis because the patient's physiology is complex, nonlinear, unobservable, and uncertain. To cope with the challenge that unidentified physiological parameters may exhibit short-term variances in certain clinical scenarios, we propose a novel run-time predictive safety monitoring technique that leverages a maximal model coupled with online training of a computational virtual subject (CVS) set. The proposed monitor predicts safety-critical events at run-time using only clinically available measurements. We apply the technique to a surgical glucose control case study. Evaluation on retrospective real clinical data shows that the algorithm achieves 96% sensitivity with a low average false alarm rate of 0.5 false alarm per surgery.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.4
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• pp.382-391
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• 2020

In this study, we used artificial intelligence algorithms for the prediction of dissolved oxygen in Jindong Bay. To determine missing values in the observational data, we used the Bidirectional Recurrent Imputation for Time Series (BRITS) deep learning algorithm, Auto-Regressive Integrated Moving Average (ARIMA), a widely used time series analysis method, and the Long Short-Term Memory (LSTM) deep learning method were used to predict the dissolved oxygen. We also compared accuracy of ARIMA and LSTM. The missing values were determined with high accuracy by BRITS in the surface layer; however, the accuracy was low in the lower layers. The accuracy of BRITS was unstable due to the experimental conditions in the middle layer. In the middle and bottom layers, the LSTM model showed higher accuracy than the ARIMA model, whereas the ARIMA model showed superior performance in the surface layer.