OBJECTIVES: In this paper, the Advanced Human-Robot Collaboration Model (AHRCM) approach is to enhance the risk assessment and to make the workplace involving security robots. The robots use perception cameras and generate scene diagrams for semantic depictions of their environment. Furthermore, Artificial Intelligence (AI) and Information and Communication Technology (ICT) have utilized to develop a highly protected security robot based risk management system in the workplace.
RESULTS: The experimental results show that the proposed AHRCM method achieves high performance in human-robot mutual adaption and reduce the risk.
CONCLUSION: Through an experiment in the field of human subjects, demonstrated that policies based on the proposed model improved the efficiency of the human-robot team significantly compared with policies assuming complete human-robot adaptation.
METHOD: A cross-sectional study was conducted, using questionnaires sent to selected medical staff in a public hospital in Shandong, China (N = 1012). Multiple regression analysis was used to investigate how psychological strains influencing life satisfactions among medical staff.
RESULTS: The findings indicate that aspiration strain and deprivation strain have significantly negative impact on medical staff's life satisfaction even with other variables controlled for. Weekly working hour was a significant predictor for life satisfaction. Family factors, such as marital status and kids in the family as well as social support were important factors in influencing individuals' life satisfaction.
CONCLUSION: The current study highlights the negative associations between aspiration strain, deprivation strain and life satisfaction. The result underlines the importance of actions taken to prevent and combat psychological strains. It also provides some evidence for policy makers to improve the work environment for medical staff, such as reduce weekly working hours and enhance social support in order to increase medical staff's life satisfaction.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
OBJECTIVE: The purpose of this study is to understand the relationship between the different variables associated with fatal falls from heights, which will help identify potential areas to work on to prevent these types of injuries.
METHODS: The study analyzed 3,321 fatal falls from height accidents from 2010 to 2020 DOSH data. Data were cleaned and normalized to extract relevant information for analysis, with agreement on variables and reliability achieved through independent sampling.
RESULTS: This study found that general workers were the most vulnerable category to fatal falls, with a 32% yearly average, whereas supervisors were the least vulnerable, with 4%. Roofers recorded a yearly fatal falls average of 15.5%, followed by electricians with 12%. Cramer's V results ranged from negligible, weak, and strong correlations; strong to moderate correlation between the dates of injuries and the factors used in this study, whereas the direct and root causes recorded a weak to negligible correlation with the rest of the variables.
CONCLUSIONS: This study provided a better understanding of the working conditions of the Malaysian construction industry. By analyzing fall injury patterns and uncovering the factors, direct and root causes relationship with other variables, it was clear how severe the Malaysian workplace conditions were.
PRACTICAL APPLICATIONS: This study will help better understand fatal fall injuries in the Malaysian construction industry and help develop prevention measures based on the uncovered patterns and associations.
MATERIALS AND METHODS: A multicentre prospective cohort study was conducted among employees from 2 different public universities in Malaysia. Interventions include at least 2 sessions of behavioural therapy combined with free nicotine replacement therapy (NRT) for 8 weeks. Participants were followed up for 6 months. Independent variables assessed were on sociodemographic and environmental tobacco smoke. Their quit status were determined at 1 week, 3 months and 6 months.
RESULTS: One hundred and eighty- five smokers volunteered to participate. Among the participants, 15% and 13% sustained quit at 3 months and 6 months respectively. Multivariate analysis revealed that at 6 months, attending all 3 behavioural sessions predicted success. None of the environmental tobacco exposure variables were predictive of sustained cessation.
CONCLUSION: Individual predictors of success in intra-workplace smoking cessation programmes do not differ from the conventional clinic-based smoking cessation. Furthermore, environmental tobacco exposure in low intensity smoke-free workplaces has limited influence on smokers who succeeded in maintaining 6 months quitting.
MATERIALS AND METHODS: This cross- sectional study was conducted among 286 non-smokers from two healthcare training centres and two nearby colleges in Malaysia from January 2015 to April 2015. A standardized questionnaire was administered via staff and student emails. The questionnaire collected information on sociodemographic characteristics, support for a tobacco-free policy and perceived respiratory and sensory symptoms due to tobacco exposure. Bivariate and multivariate logistic regression analyses were performed to estimate the independent effects of supporting a tobacco-free campus.
RESULTS: The percentage of individuals supporting completely tobacco-free facilities was 83.2% (N=238), as opposed to 16.7% (N=48) in support of partially tobacco-free facilities. Compared to the supporters of partially tobacco-free facilities, non-smokers who supported completely tobacco-free health facilities were more likely to be female, have higher education levels, to be very concerned about the effects of other people smoking on their health and to perceive a tobacco-free policy as very important. In addition, they perceived that tobacco smoke bothered them at work by causing headaches and coughs and, in the past 4 weeks, had experienced difficulty breathing. In the multivariate model, after adjusting for sociodemographic characteristics and other factors, only experiencing coughs and headaches increased the odds of supporting a completely tobacco-free campus, up to 2.5- and 1.9-fold, respectively.
CONCLUSIONS: Coughs and headaches due to other people smoking at work enhances support for a completely tobacco-free campus among non-smokers.
METHODS: A cross-sectional online survey was conducted among employees in two multinational banks in Malaysia between April and July 2019. Screening for migraine was conducted using the self-administered ID-Migraine™ questionnaire. Migraine-related disability (MIDAS) and headache frequency were recorded. Impact of migraine on work productivity and activities were evaluated using the Work Productivity and Activity Impairment (WPAI) questionnaire.
RESULTS: Of the 1268 employees who submitted complete responses, 47.2% (n = 598) were screened positive for migraine. Strikingly, the mean percent productivity loss at work (presenteeism) was almost 20-fold higher than the mean percent work time missed due to migraine (absenteeism) (39.1% versus 1.9%). The mean percent productivity loss in regular activity (activity impairment) and overall work productivity loss (work impairment) was 38.4% and 39.9%, respectively. It was also found that the costs related to presenteeism (MYR 5392.6) (US$1296) was 3.5-fold higher than absenteeism (MYR1,548.3) (US$370). Highest monetary loss related to presenteeism was reported in migraineurs with frequency of headache of above 3 days (MYR 25,691.2) (US$6176), whereas highest monetary loss related to absenteeism was reported in migraineurs with MIDAS grade IV (MYR 12,369.1) (US$2973). Only 30% of migraineurs of MIDAS grade IV reported taking prescribed medication. Notably, a vast majority (96%) of migraineurs who had three or lower episodes of migraine per month did not seek treatment.
CONCLUSION: The significant impact of migraine on work productivity and regular activity, appears to lead to substantial monetary loss attributed to not only absenteeism, but more importantly to presenteeism. This study also highlights the unmet needs in migraine management among employees in the banking sector.