Despite the potential value of graduate-level research ethics training, most Middle East countries, including Jordan, do not routinely offer formal research ethics training. In students enrolled in Jordanian master’s level graduate program in pharmacy, the current study assessed: 1- differences in pre- and post-enrollment exposure to research ethics core themes, 2- whether this exposure was through a formal course or in an informal setting, and 3- student attitudes towards research ethics education and the need for integrating a dedicated research ethics course into pharmacy graduate programs. A 12-item on-line survey was developed by the authors and disseminated to a convenience sample of current and former master-level pharmacy students in Jordan. A total of 61 eligible respondents completed the survey. A minority of respondents (38%) acknowledged receiving research ethics training prior to enrollment into a postgraduate pharmacy program with nearly half (16%) describing this training as informal. In comparison, a larger percentage of the total respondents (56%) had received research ethics training during their postgraduate program enrollment, with nearly half of those (25%) indicating that this training was informal. A majority of respondents reported a strong need for integrating a formal research ethics course into postgraduate pharmacy curriculum (90%) to support their research training and thesis writing (89%). Overall, the study revealed a notable lack of research ethics education for graduate-level pharmacy students in Jordan.
Reflections in videos are obstructions that often occur when videos are taken behind reflective surfaces like glass. These reflections reduce the quality of such videos, lead to information loss and degrade the accuracy of many computer vision algorithms. A video containing reflections is a combination of background and reflection layers. Thus, reflection removal is equivalent to decomposing the video into two layers. This, however, is a challenging and ill-posed problem as there is an infinite number of valid decompositions. To address this problem, we propose a user-assisted method for video reflection removal. We rely on both spatial and temporal information and utilize sparse user hints to help improve separation. The key idea of the proposed method is to use motion cues to separate the background layer from the reflection layer with minimal user assistance. We show that user-assistance significantly improves the layer separation results. We implement and evaluate the proposed method through quantitative and qualitative results on real and synthetic videos. Our experiments show that the proposed method successfully removes reflection from video sequences, does not introduce visual distortions, and significantly outperforms the state-of-the-art reflection removal methods in the literature.
This well-structured and well-written paper introduces a novel user-assisted method for video reflection removal. The presented solution relies on both spatial and temporal information and uses sparse user hints to separate the meaningful video content from the reflection perturbations.The novelty of the proposed method consists in including user cues, propagated throughout the video frames, to improve the separation of the background and the reflection. The paper addresses complex video scenarios by tackling weak features and dead tracks -two main drawbacks of existing approaches, and by including users in the loop. The user annotations are propagated within the frame and across frames using random walk computation and point-based tracking respectively. The user hint propagation makes the annotation process feasible and practical.The feasibility of the video reflection algorithm is presented in an extensive evaluation. The authors have collected a large dataset, consisting of more than 150 natural videos (with a duration ranging over a few seconds), that will be made publicly available. Additionally, ground truth is obtained synthetically for the purpose of objectively assessing the performance of the reflection removal. Future venues for improvement will focus on subjective quality evaluation based on real user perception. he presented approach is compared against automatic state-of-the-art methods although the former relies on user assistance. The embedded user interaction plays a key role in the proposed reflection removal method as it allows for handling complex and challenging video scenes containing reflection content.
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