• Journal of the Korean Medical Association
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• v.61 no.12
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• pp.749-755
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• 2018

Particulate matter is an air pollutant emitted from both natural and anthropogenic sources, and its adverse health effects have been well documented in time-series analyses and cohort studies. The effect size of particulate matter exposure-a roughly 0.5% increase in mortality for each $10{\mu}g/m^3$ increment of short-term exposure to particulate matter with aerodynamic diameter ${\leq}10{\mu}m$ and approximately a 10% increase for each $10{\mu}g/m^3$ increment of long-term exposure to particulate matter with aerodynamic diameter ${\leq}2.5{\mu}m$-is small compared to other risk factors, but the exposure is involuntary and affects the entire population, which makes particulate matter pollution an important public health issue. The World Health Organization and Korean government have both established guidelines for particulate matter concentrations, but the Korean guideline is less stringent than that of the World Health Organization. The annual mean concentration of particulate matter in Korea is decreasing, but the trend seems to be slowing. In addition to policy efforts to reduce particulate matter emission, personal approaches such as the use of face masks and air purifiers have been recommended. Personal approaches may not solve the fundamental problem, but can provide temporary mitigation until efforts to reduce emission make progress.

• Safety and Health at Work
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• v.10 no.2
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• pp.188-195
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• 2019

Background: Mine workers in South Africa face challenges relating to poor health and safety, including fatigue risks, and poor socioeconomic and living conditions. Fatigue results in impaired mental and physical performance. The aim of this study was to assess contributors to fatigue of mine workers in South Africa. Methods: Data collection took place at four gold mines and one platinum mine in South Africa. A total of 21 focus groups were held with individuals in management, union representatives, and mine workers, and 564 questionnaires were completed by mine workers to gather information about fatigue and potential contributors to fatigue at these mines. Results: Qualitatively (through focus groups), fatigue was attributed to extended working hours, harsh working conditions, high workloads, production pressure, and resource constraints, along with aspects relating to demographic and socioeconomic factors, living conditions, lifestyle, health, and wellness. Greater fatigue was significantly associated with younger age, indebtedness, a lack of exercise, poor nutrition, less sleep, increased alcohol use, poor self-reported health, more sick leave, higher stress, and lower job satisfaction. Conclusion: The aim of the study was achieved; numerous work-, sociodemographic-, lifestyle-, and wellness-related factors were linked to fatigue in the participating mine workers. Contributors to fatigue should be addressed to improve health, safety, and sustainability in the industry.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.205-213
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• 2021

Water infusion has long been taken as an effective way to eliminate coal burst risk as coal properties can be loosen and soften by water infusion. However, not all industrial trials of water infusion for coal burst prevention have been necessarily effective in all situations as the effectiveness of this method can be affected by water infusion time, coal properties and the parameters of water injection. Hence, some fundamental issues including the effects of water infusion time on burst propensity and energy evolution need to be further discussed. In this paper, four groups of coal specimens with 0 day, 5 days, 10 days, and 15 days water saturation time are tested under uniaxial compression load with the application of AE monitoring. To comprehensively compare the burst behavior of coal specimens under different water saturation time, stress-strain curves, AE counts, fragmentation characteristics and burst propensity of these groups are analyzed. It was found by this research that sufficient water saturation can mitigate the burst behavior of coal samples while insufficient water infusion might cannot reach the burst mitigation aims.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.14-19
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• 2022

This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.95-95
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• 2023

Common hydrological problems of developing countries include poor data management, insufficient measuring devices and ungauged watersheds, leading to small or unreliable data availability. This has greatly affected the adoption of artificial intelligence techniques for flood risk mitigation and damage control in several developing countries. While climate datasets have recorded resounding applications, but they exhibit more uncertainties than ground-based measurements. To encourage AI adoption in developing countries with small ground-based dataset, we propose data augmentation for regression tasks and compare performance evaluation of different AI models with and without data augmentation. More focus is placed on simple models that offer lesser computational cost and higher accuracy than deeper models that train longer and consume computer resources, which may be insufficient in developing countries. To implement this approach, we modelled and predicted streamflow data of the Asa River Watershed located in Ilorin, Kwara State Nigeria. Results revealed that adequate hyperparameter tuning and proper model selection improve streamflow prediction on small water dataset. This approach can be implemented in data-scarce regions to ensure timely flood intervention and early warning systems are adopted in developing countries.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.50-59
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• 2020

The 21st century is witnessing a rapid growth of tall buildings in urban centers globally to create more urban space for an anticipated urban population. Tall buildings, however suffer from incessant delays and sometimes total abandonment. Consequently, this study investigated and ranked the causes of delay in tall building projects, while focusing on the Gulf Cooperation Council (GCC) countries. Initially, 36 common delay causes investigated globally were categorized into 9 groups, and then further ranked utilizing the Relative Importance Index (RII) through a questionnaire survey. Tall building professionals in the GCC countries (Saudi Arabia, United Arab Emirates, Bahrain, Kuwait, Oman and Qatar) were contacted. The respondents' categories include Consultants, Contractors, and Clients' Representatives/Facility Managers. The results reveal that the top three causes include "client's cash flow problems/delays in contractor's payment", "contractor's financial difficulties", and "poor site organization and coordination between various parties". The findings from this study could help construction professionals develop guidelines and controls for delay mitigation, as well as support them in risk-based decision making in the planning of tall building projects.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.481-486
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• 2023

Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

• Wind and Structures
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• v.38 no.3
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• pp.171-191
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• 2024

Wind Driven Rain (WDR) poses a significant threat to the building environment, especially in hurricane prone regions by causing interior and content damage during tropical storms and hurricanes. The damage due to rain intrusion depends on the total amount of water that enters the building; however, owing to the use of inadequate empirical methods, the amount of water intrusion is difficult to estimate accurately. Hence, the need to achieve full-scale testing capable of realistically simulating rain intrusion is widely recognized. This paper presents results of a full-scale experimental simulation at the NHERI Wall of Wind Experimental Facility (WOW EF) aimed at obtaining realistic rain characteristics as experienced by structures during tropical storms and hurricanes. A full-scale simulation of rain in strong winds would allow testing WDR intrusion through typical building components. A study of rain intrusion through a sliding glass door is presented, which accounted for the effects of multiple wind directions, test durations and wind speeds; configurations with and without shuttering systems were also considered. The study showed that significant levels of water intrusion can occur during conditions well below current design levels. The knowledge gained through this work may enhance risk modeling pertaining to loss estimates due to WDR intrusion in buildings, and it may help quantify the potential reduction of losses due to the additional protection from shuttering systems on sliding glass doors during winds.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.135-141
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• 2024

Despite the innovative technological advances in the aviation industry, hard landing events that occur during aircraft landing account for 13% of all accidents. Hard landing when landing an aircraft affects normal operation by generating a large load on the landing gear and the fuselage. In order to identify these risk factors, the airline monitors the high vertical acceleration event, a precursor to hard landing, through QAR (Quick Access Recorder) flight data analysis, and prepares and implements mitigation measures. In this study, it is intended to contribute to safety management based on flight data analysis that identifies the characteristics of high vertical acceleration G event data that can cause such hard landing and detailed parameters of precursor signs, and to identify the causal relationship of the occurrence of the event by applying statistical analysis methods such as variance analysis, correlation analysis, and regression analysis models to identify the characteristics of the event occurrence and eliminate the cause in advance.

• Journal of Service Research and Studies
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• v.4 no.2
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• pp.1-10
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• 2014

According to recent trends in technological advances and globalization, medical device industry may improve the constitution to meet worldwide medical equipment management system. Also it is holding a strand of mitigation to reach the level of international regulation. In addition, recent legislation tends are to stay limited ranges of industry regulations at least and take as open attitude for integration of new technologies combined medical devices. A greater environmental risk is not likely to work in medical technology, Combinded medical device is used as close to zero risk in most of the human body, which is classified as Class 1. Even medical device such as little or no risk in handling, it is possible to minimize the unnecessary administrative power and a waste of time to occur. For the medical device may be improving people's choices and access, medical equipment operator is expanding to include dealers, because this will be exalted to particular area of the business of the company. In this paper, we investigate the legal prerequisites for the establishment of a medical device. And propose improved regulations in topics in order to facilitate the repair and distribution markets for fair trade.