• Safety and Health at Work
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• 제6권2호
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• pp.104-113
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• 2015

Background: Given the long hours on the road involving multiple and interacting work stressors (i.e., delivery pressures, irregular shifts, ergonomic hazards), commercial drivers face a plethora of health and safety risks. Researchers goal was to determine whether and to what extent long-haul trucker work schedules influence sleep duration and quality. Methods: Survey and biometric data collected from male long-haul truck drivers at a major truckstop in central North Carolina over a six month period. Results: Daily hours worked (mean = 11 hours, 55 minutes) and frequency of working over government-mandated daily HOS regulations (23.8% "frequently or always") were statistically significant predictors of sleep duration. Miles driven per week (mean = 2,812.61), irregular daily hours worked (63.8%), and frequency of working over the daily hour limit (23.8% "frequently or always") were statistically significant predictors of sleep quality. Conclusion: Implications of findings suggest a comprehensive review of the regulations and operational conditions for commercial motor vehicle drivers be undertaken.

• 보건의료산업학회지
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• 제9권3호
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• pp.145-157
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• 2015

Objectives : This study identified factors that influenced social nicotine dependence in university students using descriptive methods. Methods : Data were collected 429 university students from 2 universities in B metropolitan city. The analytical methods were the t-test, ANOVA, Scheffe's test, Pearson's Correlation Coefficient and multiple regression analysis. Results : There were significant differences in social nicotine dependence according to gender (t=3.359, p=.001), smoking status (t=8.915, p=.000), religion (t=3.841, p=.022), economic status (t=3.632, p=.027) and grade (t=8.466, p=.000). Social nicotine dependence was weakly correlated with anxiety (r=.113, p<.05). Meaningful variables that explain social nicotine dependence were anxiety, self-efficacy self-esteem, female, smokers and no religion. Conclusions : It is necessary to develop a comprehensive smoke-free policy that considers social nicotine dependence to improve the cultural and social awareness of the associated health hazards of smoking, and to develop smoking cessation education and smoking prevention programs that improve the self-efficacy and self-esteem of university students.

• Child Health Nursing Research
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• 제26권1호
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• pp.98-106
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• 2020

Purpose: This study utilized data from the Korean National Health and Nutrition Examination Survey (KNHANES) to explore differences in the timing of menarche in Korean girls according to blood heavy metal concentrations. Methods: This study performed a secondary analysis of cross-sectional data from the sixth KNHANES. Data from 179 female children and adolescents aged 10~18 were included in this study. The relationships of blood heavy metal concentrations (lead, mercury, and cadmium) with age of menarche were analyzed using complex sample multiple logistic regression. Results: In the participants of this study, the geometric mean values of blood lead, mercury, and cadmium concentrations were 1.15±0.04 ㎍/dL, 1.80±0.08 ㎍/L, and 0.30±0.03 ㎍/L, respectively. Mercury poisoning (>5 ㎍/L) was found in 1.5% of participants. Furthermore, significant relationships were found between blood lead and mercury concentrations and age at menarche (p for trend: p<.001 and p=.015, respectively). Conclusion: Through an analysis of national big data, this study found evidence that Korean girls showed a younger age at menarche in response to higher blood lead and mercury concentrations. To prevent and manage precocious puberty in Korean children and adolescents, a systematic policy that monitors both exposure to environmental hazards and blood heavy metal concentrations is needed.

• 대한치과마취과학회지
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• 제2권1호
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• pp.33-37
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• 2002

The oculo-cerebro-renal syndrome of Lowe (Lowe syndrome) is an X-linked recessive disorder involving the eyes, nervous systems, and kidneys. The clinical manifestation of this syndrome is characterized by congenital cataracts, glaucoma, seizure disorder, psychomotor growth retardation, hypotonia, renal tubular acidosis, aminoaciduria, rickets, and osteoporosis. We report a 5-year old boy underwent general anesthesia for the treatment of multiple dental carries. During intraoperative period, marked metabolic acidosis was noted and such acidosis was partially corrected by hyperventilation. We suggest that patients with Lowe's syndrome should be attention and treated to possible anesthetic hazards such as metabolic acidosis due to renal tubular dysfunction, rise of intraocular pressure in patient with glaucoma, the fragility of the bone structures due to rickets and osteoporosis.

• Smart Structures and Systems
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• 제30권3호
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• pp.303-315
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• 2022

The degradation of wheel tread may result in serious hazards in the railway operation system. Therefore, timely wheel defect diagnosis of in-service trains to avoid tragic events is of particular importance. The focus of this study is to develop a novel wheel defect detection approach based on the relevance vector machine (RVM) which enables online detection of potentially defective wheels with trackside monitoring data acquired under different running-speed conditions. With the dynamic strain responses collected by a trackside monitoring system, the cumulative Fourier amplitudes (CFA) characterizing the effect of individual wheels are extracted to formulate multiple probabilistic regression models (MPRMs) in terms of multi-kernel RVM, which accommodate both variables of vibration frequency and running speed. Compared with the general single-kernel RVM-based model, the proposed multi-kernel MPRM approach bears better local and global representation ability and generalization performance, which are prerequisite for reliable wheel defect detection by means of data acquired under different running-speed conditions. After formulating the MPRMs, we adopt a Bayesian null hypothesis indicator for wheel defect identification and quantification, and the proposed method is demonstrated by utilizing real-world monitoring data acquired by an FBG-based trackside monitoring system deployed on a high-speed trial railway. The results testify the validity of the proposed method for wheel defect detection under different running-speed conditions.

• Structural Engineering and Mechanics
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• 제80권6호
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• pp.711-726
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• 2021

This paper presents a multiple parameters-based recursive methodology for the reliability quantification of civil structures subjected to meteorological disasters. Recognizing the challenge associated with characterizing at a single stroke all the meteorological disasters that may hit a structure during its service life, the proposed methodology by contrast features a multiparameter recursive mechanism to describe the meteorological demand of the structure. The benefit of the arrangements is that the essentially inevitable deviation of the practically observed meteorological data from those in the existing model can be mitigated in an adaptive manner. In particular, the implications of potential climate change to the relevant reliability of civil structures are allowed for. The application of the formulated methodology of recursive reliability quantification is illustrated by first considering the reliability quantification of a linear shear frame against simulated strong wind loads. A parametric study is engaged in this application to examine the effect of some hyperparameters in the configured hierarchical model. Further, the application is extended to a nonlinear hysteretic shear frame involving some field-observed cyclone data, and the incompleteness of the relevant structural diagnosis data that may arise in reality is taken into account. Also investigated is another application scenario where the reliability of a building envelope is assessed under hailstone impacts, and the emphasis is to demonstrate the recursive incorporation of newly obtained meteorological data.

• 대한의용생체공학회:의공학회지
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• 제44권2호
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• pp.99-108
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• 2023

According to the COVID-19, development of various medical software based on IoT(Internet of Things) was accelerated. Especially, interest in a central software system that can remotely monitor and control ventilators is increasing to solve problems related to the continuous increase in severe COVID-19 patients. Since medical device software is closely related to human life, this study aims to develop central monitoring system that can remotely monitor and control multiple ventilators in compliance with medical device software development standards and to verify performance of system. In addition, to ensure the safety and reliability of this central monitoring system, this study also specifies risk management requirements that can identify hazardous situations and evaluate potential hazards and confirms the implementation of cybersecurity to protect against potential cyber threats, which can have serious consequences for patient safety. As a result, we obtained medical device software manufacturing certificates from MFDS(Ministry of Food and Drug Safety) through technical documents about performance verification, risk management and cybersecurity application.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.1-10
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• 2023

Open surface water body extraction is gaining popularity in recent years due to its versatile applications. Multiple techniques are used for water detection based on applications. Different applications of Radar as LADAR, Ground-penetrating, synthetic aperture, and sounding radars are used to detect water. Shortwave infrared, thermal, optical, and multi-spectral sensors are widely used to detect water bodies. A stereo camera is another way to detect water and different methods are applied to the images of stereo cameras such as deep learning, machine learning, polarization, color variations, and descriptors are used to segment water and no water areas. The Satellite is also used at a high level to get water imagery and the captured imagery is processed using various methods such as features extraction, thresholding, entropy-based, and machine learning to find water on the surface. In this paper, we have summarized all the available methods to detect water areas. The main focus of this survey is on water detection especially in small patches or in small areas. The second aim of this survey is to detect water hazards for unmanned vehicles and off-sure navigation.

• Safety and Health at Work
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• 제13권4호
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• pp.507-511
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• 2022

Law enforcement officers (LEOs) often encounter rapidly changing and uncontrolled situations that expose them to various hazards. A law enforcement agency requested an evaluation by the National Institute for Occupational Safety and Health (NIOSH) when multiple LEOs reported illness after executing a search warrant and taking a suspect into custody. NIOSH investigators interviewed LEOs and reviewed medical records, forensic laboratory results for collected evidence, and environmental testing results of samples taken after the operation. Two-thirds (25 of 38) of LEOs who participated in the operation reported ≥1 symptom. Eleven LEOs met a case definition for influenza-like illness (ILI). Members of one unit were more likely to have ILI than non-members (prevalence ratio (PR), 4.1; 95% confidence interval (CI): 1.3-13.0; p = 0.01). Influenza vaccination was associated with a lower prevalence of ILI (PR, 0.2; 95% CI, 0.1-0.9; p = 0.02). Preventing employees from working while ill and annual influenza vaccination might prevent similar occurrences.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1301-1316
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• 2024

In modern warfare, missiles play a pivotal role but typically spend the majority of their lifecycle in long-term storage or standby mode, making it difficult to detect failures. Preemptive detection of missiles that will fail is crucial to preventing severe consequences, including safety hazards and mission failures. This study proposes a contamination-based stacking ensemble model, employing the local outlier factor (LOF), to detect such missiles. The proposed model creates multiple base LOF models with different contamination values and combines their anomaly scores to achieve a robust anomaly detection. A comparative performance analysis was conducted between the proposed model and the traditional single LOF model, using production-related inspection data from missiles deployed in the military. The experimental results showed that, with the contamination parameter set to 0.1, the proposed model exhibited an increase of approximately 22 percentage points in accuracy and 71 percentage points in F1-score compared to the single LOF model. This approach enables the preemptive identification of potential failures, undetectable through traditional statistical quality control methods. Consequently, it contributes to lower missile failure rates in real battlefield scenarios, leading to significant time and cost savings in the military industry.