Design of a Binocular Pupil and Gaze Point Detection System Utilizing High Definition Images

This study proposes a novel binocular pupil and gaze detection system utilizing a remote full high definition (full HD) camera and employing LabVIEW. LabVIEW is inherently parallel and has fewer time-consuming algorithms. Many eye tracker applications are monocular and use low resolution cameras due to real-time image processing difficulties. We utilized the computer’s direct access memory channel for rapid data transmission and processed full HD images with LabVIEW. Full HD images make easier determinations of center coordinates/sizes of pupil and corneal reflection. We modified the camera so that the camera sensor passed only infrared (IR) images. Glints were taken as reference points for region of interest (ROI) area selection of the eye region in the face image. A morphologic filter was applied for erosion of noise, and a weighted average technique was used for center detection. To test system accuracy with 11 participants, we produced a visual stimulus set up to analyze each eye’s movement. Nonlinear mapping function was utilized for gaze estimation. Pupil size, pupil position, glint position and gaze point coordinates were obtained with free natural head movements in our system. This system also works at 2046 × 1086 resolution at 40 frames per second. It is assumed that 280 frames per second for 640 × 480 pixel images is the case. Experimental results show that the average gaze detection error for 11 participants was 0.76° for the left eye, 0.89° for right eye and 0.83° for the mean of two eyes

Square root central difference-based FastSLAM approach improved by differential evolution

This study presents a new approach to improve the performance of FastSLAM. The aim of the study is to obtain a more robust algorithm for FastSLAM applications by using a Kalman filter that uses Stirling's polynomial interpolation formula. In this paper, some new improvements have been proposed; the first approach is the square root central difference Kalman filter-based FastSLAM, called SRCD-FastSLAM. In this method, autonomous vehicle (or robot) position, landmarks' position estimations, and importance weight calculations of the particle filter are provided by the SRCD-Kalman filter. The second approach is an improved version of the SRCD-FastSLAM in which particles are improved by a differential evolution (DE) algorithm for reducing the risk of the particle depletion problem. Simulation results are given as a comparison of FastSLAM II, unscented (U)-FastSLAM, SRCD-Kalman filter-aided FastSLAM, SRCD particle filter-based FastSLAM, SRCD-FastSLAM, and DE-SRCD-FastSLAM. The results show that SRCD-based FastSLAM approaches accurately compute mean and precise uncertainty of the robot position in comparison with FastSLAM II and U-FastSLAM methods. However, the best results are obtained by DE-SRCD-FastSLAM, which provides significantly more accurate and robust estimation with the help of DE with fewer particles. Moreover, consistency of the DE-SRCD-FastSLAM is more prolonged than that of FastSLAM II, U-FastSLAM, and SRCD-FastSLAM

Solar UV index and UV dose determination with photochromic hackmanites: from the assessment of the fundamental properties to the device

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Photocatalytically Active Graphitic Carbon Nitride as an Effective and Safe 2D Material for In Vitro and In Vivo Photodynamic Therapy

Thanks to its photocatalytic property, graphitic carbon nitride (g-C3N4) is a promising candidate in various applications including nanomedicine. However, studies focusing on the suitability of g-C3N4 for cancer therapy are very limited and possible underlying molecular mechanisms are unknown. Here, it is demonstrated that photoexcitation of g-C3N4 can be used effectively in photodynamic therapy, without using any other carrier or additional photosensitizer. Upon light exposure, g-C3N4 treatment kills cancer cells, without the need of any other nanosystem or chemotherapeutic drug. The material is efficiently taken up by tumor cells in vitro. The transcriptome and proteome of g-C3N4 and light treated cells show activation in pathways related to both oxidative stress, cell death, and apoptosis which strongly suggests that only when combined with light exposure, g-C3N4 is able to kill cancer cells. Systemic administration of the mesoporous form results in elimination from urinary bladder without any systemic toxicity. Administration of the material significantly decreases tumor volume when combined with local light treatment. This study paves the way for the future use of not only g-C3N4 but also other 2D nanomaterials in cancer therapy