Design, Development, and Characterization of Low Distortion Advanced Semitransparent Photovoltaic Glass for Buildings Applications

Aesthetic appearance of building-integrated photovoltaic (BIPV) products, such as semitransparent PV (STPV) glass, is crucial for their widespread adoption and contribution to the net-zero energy building (NZEB) goal. However, the visual distortion significantly limits the aesthetics of STPV glass. In this study, we investigate the distortion effect of transparent periodic-micropattern-based thin-film PV (PMPV) panels available in the market. To minimize the visual distortion of such PMPV glass panel types, we design and develop an aperiodic micropattern-based PV (APMP) glass that significantly reduces visual distortion. The developed APMP glass demonstrates a haze ratio of 3.7% compared to the 10.7% of PMPV glass. Furthermore, the developed AMPV glass shows an average visible transmittance (AVT) of 58.3% which is around 1.3 times higher than that of AMPV glass (43.8%). Finally, the measured CIELAB values (L* = 43.2, a* = −1.55, b* = −2.86.) indicate that our developed AMPV glass possesses excellent color neutrality, which makes them suitable for commercial applications. Based on the characterization results, this study will have a significant impact on the areas of smart window glasses that can play a vital role in developing a sustainable environment and enhancing the aesthetical appearance of net-zero energy buildings (NZEB).

Mathematical Model for Single and Multiple Object Extraction

In the image processing, noise is referred to as the visual distortion. This undesirable by-product may be captured in an image due to unpreventable assorted reasons. The interference of natural phenomena and technical problem, such as small sensor size, long exposure time, low ISO, shadow noise etc., can pollute image. The presence of noise images affects image processing outputs that include segmentation. Segmentation for noisy images is the major concern. To tackle this issue, we propose a modernistic model that is able neutralize the negative effects of outlier using the characteristic of kernel function by different approaches such as linear approach and quadratic approach for global segmentation. Moreover the weight function is used for local segmentation of noisy images. Comparing with classical models, the proposed technique shows robust performance. In comparison with the wellknown models such as Chan-Vese (CV) model , Yongfei Wu and Chuanjiang He (Wu-He) model and Chunming Li (Li) model we conclude that performance of our new model is much better.

Pointing in depth is shaped by a natural grasping distance prior

Vision in depth is distorted. A similar distortion can be observed for pointing to visual targets in depth. It has been suggested that pointing errors in depth reflect the visual distortion. However, much research has suggested that in case visual information is not rich enough, the sensorimotor system involves prior knowledge to optimally plan movement trajectories. Here, we show that pointing in depth is guided by a prior that biases movements toward the natural grasping distance at which object manipulation is usually performed. To dissociate whether pointing is guided by distorted vision only or whether it takes into account a natural grasping distance prior, we adapted pointing movements. Participants received visual feedback about the success of their pointing once the movement was finished. We distorted the feedback to signal either that pointing was not far enough or in separate sessions that pointing was too far. Participants adapted to this artificial error by either extending or shortening their pointing movements. The generalization of pointing adaptation revealed a bias in movement planning that is inconsistent with pointing being guided only by distorted vision but with the involvement of knowledge about the natural grasping distance. Adaptation was strongest for pointing movements to a middle position that corresponds to the natural grassing distance and it was weakest for movements leading away from it. It has been demonstrated that pointing adaptation in depth changes visual perception (Volcic et al., 2013). We also wondered how effects of pointing adaptation on visual space would generalize in depth.

Persistent Air Bubble Sequestered at the Silicone Oil–Silicone Intraocular Lens Interface as a Cause of Reversible Visual Distortion

Purpose: To report a novel cause of post-operative reversible visual distortion due to a persistent air bubble sequestered at the intraocular lens (IOL)–silicone oil interface. Methods: Two cases of persistent, sequestered air at the IOL-silicone oil interface were identified and reviewed. Relevant clinical information, images and surgical videos were analyzed and described. Results: Resolution of the visual distortion was achieved in both cases after silicone oil removal. Conclusions: Silicone oil adhesion to the posterior surface of silicone IOLs is a known cause of visual degradation. The IOL-silicone oil interface can sequester air that persists and causes visual distortion until the oil is removed. We report the first cases, to our knowledge, of reversible visual distortion due to sequestered air at the IOL-silicone oil interface.