Articles
Han J.,
Moradi, S.,
Wang W.,
Li N.,
Zhao Q.,
Luo Z.,
Nejati far, S.,
Abedi, A.,
Ghamarani, A.,
Asanjarani, F. Frontiers in Marine Science (22967745)pp. 373-386
Infrared (IR) small dim target detection under complex background is crucial in many fields, such as maritime search and rescue. However, due to the interference of high brightness background, complex edges/corners and random noises, it is always a difficult task. Especially, when a target approaches a high brightness background area, the target will be easily submerged. In this paper, a new contrast method framework named hybrid contrast measure (HCM) is proposed, it consists of two main modules: the relative global contrast measure (RGCM) calculation, and the small patch local contrast weighting function. In the first module, instead of using some neighboring pixels as benchmark directly during contrast calculation, the sparse and low rank decomposition method is adopted to get the global background of a raw image as benchmark, and a local max dilation (LMD) operation is applied on the global background to recover edge/corner information. A Gaussian matched filtering operation is applied on the raw image to suppress noises, and the RGCM will be calculated between the filtered image and the benchmark to enhance true small dim target and eliminate flat background area simultaneously. In the second module, the Difference of Gaussians (DoG) filtering is adopted and improved as the weighting function. Since the benchmark in the first module is obtained globally rather than locally, and the patch size in the second module is very small, the proposed algorithm can avoid the problem of the targets approaching high brightness backgrounds and being submerged by them. Experiments on 14 real IR sequences and one single frame dataset show the effectiveness of the proposed algorithm, it can usually achieve better detection performance compared to the baseline algorithms from both target enhancement and background suppression point of views. Copyright © 2025 Han, Moradi, Wang, Li, Zhao and Luo.
Esfahani M.D.,
Khanlari P.,
Asanjarani, F.,
Jafari, F.,
Fatehizade, M.,
Etemadi toudeshki, O.,
De mol, J.,
De mol, J. BMC Public Health (14712458)(1)pp. 141-155
Background: Burnout is an increasing public health concern. Its prevalence has extended across diverse professions globally, posing significant challenges to individuals, organizations, and society. This phenomenon has undermined employee well-being, productivity, and organizational effectiveness, making it a critical concern in contemporary work environments. The present study aimed to examine the adaptation and assess the validity of the Persian version of the Burnout Assessment Tool (BAT). Methods: The adaptation process included the translation and back-translation of the BAT. Data were collected on a sample of 580 teachers using the convenience sampling. The BAT-Persian and Utrecht Work Engagement Scale were administered to collect the data. The reliability, factorial structure of the BAT-C and BAT-S, and the convergent and discriminant validity of BAT-C and work engagement were explored. Results: Confirmatory factor analysis supported a four-factor structure for the core dimensions (BAT-C; exhaustion, mental distance, emotional impairment, cognitive impairment), and a two-factor structure for the secondary dimensions (BAT-S; psychological distress, psychosomatic complaints). In the second-order model, the item loadings on the four factors of BAT-C ranged from 0.35 to 0.85, and on two factors of BAT-S ranged from 0.63 to 0.89. The Persian versions of the BAT-C and BAT-S showed good internal consistency (respectively, α = 0.95 and 0.90). Additional evidence supports the convergent and discriminant validity of the BAT-GR. the BAT‐C and its scales were negatively correlated with work engagement and dimensions (i.e., vigor, dedication, and absorption). Moreover, the BAT‐S and its scales negatively correlated with work engagement and dimensions. Conclusions: This study provided evidence that the Iranian version of BAT represents a reliable and valid tool for measuring burnout in the work context. A reliable and valid tool for assessing burnout in the Iranian workplace enables early detection of employee distress, allowing for timely intervention and support. This means that identifying the signs and symptoms of burnout in the early stages can prevent more severe consequences such as absenteeism, reduced productivity, or turnover. © The Author(s) 2024.
