• PNF and Movement
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• v.17 no.2
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• pp.253-261
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• 2019

Purpose: The purpose of this study was to identify the causal relationship between workplace stress and working posture and the development of work-related neck pain in office workers. Methods: The study participants included 62 office workers who had not experienced neck pain in the previous 12 months. A battery of measures to evaluate potential workplace risk factors in an office setting were conducted at baseline, and the 12-month incidence of work-related neck pain was reported via monthly questionnaires. Survival analysis was used to evaluate the longitudinal relationship between the workplace risk factors and the development of work-related neck pain. Results: The incidence of work-related neck pain was 1.91 (95% CI: 1.06-3.45) per 100 person months. The incidence of neck pain was predicted to be less likely to happen when workers had a more upright thorax posture during computer work (hazard ratio, 0.94; 95% CI: 0.89-0.99). However, stress may deteriorate the preventative effects of other risk factors on neck pain and showed a positive relationship with episodes of neck pain (hazard ratio, 1.37; 95% CI: 1.03-1.84). Conclusion: Understanding the psychophysiological effects of neck pain may explain the development of neck pain in office workers. Our interest in prevention plans and treatments should therefore involve a multifactorial pathology of neck pain in the workplace.

• Psychiatry investigation
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• v.15 no.11
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• pp.1037-1045
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• 2018

Objective The present study aimed to identify risk factors for future SI and to predict individual-level risk for future or persistent SI among college students. Methods Mental health check-up data collected over 3 years were retrospectively analyzed. Students were categorized as suicidal ideators and non-ideators at baseline. Logistic regression analyses were performed separately for each group, and the predicted probability for each student was calculated. Results Students likely to exhibit future SI had higher levels of mental health problems, including depression and anxiety, and significant risk factors for future SI included depression, current SI, social phobia, alcohol problems, being female, low self-esteem, and number of close relationships and concerns. Logistic regression models that included current suicide ideators revealed acceptable area under the curve (AUC) values (0.7-0.8) in both the receiver operating characteristic (ROC) and precision recall (PR) curves for predicting future SI. Predictive models with current suicide non-ideators revealed an acceptable level of AUCs only for ROC curves. Conclusion Several factors such as low self-esteem and a focus on short-term rather than long-term outcomes may enhance the prediction of future SI. Because a certain range of SI clearly necessitates clinical attention, further studies differentiating significant from other types of SI are necessary.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.249-261
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• 2022

Globally, COVID-19 has significantly impacted many different organizations and people. From the banks' perspective, this pandemic has affected banks' corporate and retail customers. Also, banks had to adjust to distributed workforce model. This paper analyses the lessons learned from the COVID-19 pandemic, which can be effectively used to rebuild banks' Operational Risk Management capabilities. The present study used the survey research methodology, which includes structured questionnaires completed by senior banking professionals to analyze the learnings from COVID-19 and understand the distributed workforce model and remote working effectiveness. Findings: The Pandemic accelerated the pace of digital transformation. The lockdown imposed due to the pandemic led to employees working remotely, which has been effective because of enhanced digital capabilities. However, enhanced monitoring is required to prevent data-related issues, and action needs to be taken to address challenges faced in having a remote distributed workforce model, like negative impact on on-the-job learning, data-related risks, and employee wellbeing. COVID-19 is an unprecedented event that could not have been predicted in any scenario analysis. This crisis has highlighted various systemic drawbacks that need to be addressed. Banks can apply the lesson learned from this Pandemic to become more robust in the future.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.373-385
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• 2022

Due to the lack of information, medical tourists are regarded to be at high risk. Prior medical tourism research has found that various types of perceived risks have a significant impact on medical tourists' purchase behavior. Even though medical tourism is predicted to increase, there is a lack of behavioral research to explain how perceived risks affect medical tourists' purchase behavior. In the context of Korean medical tourism, this study attempts to evaluate the effects of multi-level (macro, organizational, and personal) factors on medical tourists' perceived risks and purchase intentions. A conceptual model and hypotheses were built and empirically validated to investigate links between multi-level characteristics, perceived risks, and purchasing intentions. The data for this study was collected from Chinese tourists using a questionnaire. The impact of cognitive country image, affective country image, and medical service quality on fundamental risk is confirmed by statistical testing. Surprisingly, expectancy discrepancy risk is influenced only by cognitive country image and information search capabilities. Both fundamental and expectation discrepancy risks lower medical tourists' purchase intentions. The findings of this study show that a multi-level strategy is required to investigate the links between perceived risks and medical tourism purchasing intentions based on macro, organizational, and personal factors.

• Atmosphere
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• v.34 no.2
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• pp.107-121
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• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.

• Journal of Chest Surgery
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• v.28 no.5
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• pp.464-470
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• 1995

From Jan 1988 to Dec 1993, 196 consecutive patients with various pulmonary diseases underwent pneumonectomy. Mean age was 54.0 years[range:7-74 . The underlying diseases were lung cancer[154 cases , destroyed lung[29 cases with pulmonary tuberculosis or empyema thoracis and others[13 cases . The overall mortality and complication rate were 5.6% and 14.8%. In the groups of more than and less than 60 years of age, there was significant differences in mortality rate[P=0.004 . In the group of pneumonectomy and pleuropneumonectomy, there was no significant differences in mortality[P=0.164 and complication rate[P=0.052 . In the group of normal and abnormal EKG, there was no significant differences in mortality[P=0.560 and complication rate[P=0.693 . In the preoperative FEV1, preoperative FVC and predicted postoperative FEV1, prognostic cut-off points were 1800cc, 2600cc and 1300cc, and at points, positive predicted value were 12.3%, 10.5%.and 7.7% and negative predicted value were 97.8%, 98.3% and 96.2% respectively. The preoperative FEV1 is the most reliable indicator in assessment of prognosis of pneumonectomy.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.2
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• pp.100-104
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• 2015

Adverse effect of veterinary antibiotics (VAs) released into environment has been issued recently and concerns about analysis and management for VAs in the environment were increased. Main objective of this research was to calculate predicted environmental concentration (PEC) of the VAs in soil based on avaiable statistical data and result of previous study such as consumption rate and physiological properties of VAs. Total of 5 VAs, Chlortetracycline (CTC), Oxytetracycline (OTC), Sulfadimethoxine (SDX), Sulfamethazine (SMT), and Tylosin (TYL) were examined. Result showed that calculated PEC value in manure and soil was ordered as SMT > TYL > SDX > CTC > OTC. Range of calculated value for manure and soil was 0.50-67.04 and $0.48-64.45mg\;kg^{-1}$ respectively. Comparing to measured concentration of VAs in manure and soil, lower concentration of VAs in manure and soil was evaluated due to fate and degradation of VAs in manure and soil. Overall, evaluated simple modeling for calculating PEC of VAs in manure and soil can be adapted for preliminary screening purpose in environmental risk assessment and more refined modeling is necessary to examine detailed assessment of VAs in manure and soil.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.14-24
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• 2021

This study aims to examine probable human errors when landing an airplane by the use of SHERPA(systematic human error reduction and prediction approach) and propose methods for preventing the predictive human errors. It has been reported that human errors are concerned with a lot of accidents or incidents of an airplane. It is significant to predict presumable human errors, particularly in the operation mode of human-automation interaction, and attempt to reduce the likelihood of predicted human error. By referring to task procedures and interviewing domain experts, we analyzed airplane landing task by using HTA(hierarchical task analysis) method. In total, 6 sub-tasks and 19 operations were identified from the task analysis. SHERPA method was used for predicting probable human error types for each task. As a result, we identified 31 human errors and predicted their occurrence probability and criticality. Based on them, we suggested a set of methods for minimizing the probability of the predicted human errors. From this study, it can be said that SHERPA can be effectively used for predicting probable human error types in the context of human-automation interaction needed for navigating an airplane.

• Clean Technology
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• v.26 no.4
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• pp.279-285
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• 2020

Laboratories and industrial processes typically involve the use of flammable substances. An important property used to estimate fire and explosion risk for a flammable liquid is the flash point. In this study, flash point data at 101.3 kPa were determined using a SETA closed cup flash point tester on the following solvent mixtures: {2,2,4-trimethylpentane + methylcyclohexane}, {2,2,4-trimethylpentane + ethylbenzene}, and {2,2,4-trimethylpentane + p-xylene}. The purpose of this work is to obtain flash point data for binary mixtures of 2,2,4-trimethylpentane with three hydrocarbons (methylcyclohexane, ethylbenzene, and p-xylene), which are representative compounds of the main aromatic hydrocarbon fractions of petroleum. The measured flash points are compared with the predicted values calculated using the GE models' activity coefficient patterns: the Wilson, the Non-Random Two-Liquid (NRTL), and the UNIversal QUAsiChemical (UNIQUAC) models. The non-ideality of the mixture is also considered. The average absolute deviation between the predicted and measured lower flash point s is less than 1.99 K, except when Raoult's law is calculated. In addition, the minimum flash point behavior is not observed in any of the three binary systems. This work's predicted results can be applied to design safe petrochemical processes, such as identifying safe storage conditions for non-ideal solutions containing volatile components.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.2
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• pp.45-51
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• 2009

A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters(e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the predicted of thaw depths in cold regions is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters and temperature data can lead to significant uncertainty in predicting thaw penetration.