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Multi input multi output (MIMO) based multi-hop relay (MHR) networks has become one of the promising technologies in improving the quality of wireless links. The optimal antenna selection is one of the suitable solutions to overcome the limitations of MIMO scheme. To attain the full benefits of transmitter antenna selection schemes, perfect channel quality information (CQI) is required at the transmitter. The time varying channel and the feedback delay make CQI at the transmitter outdated and also affect the antenna selection process. In this work, we have derived the symbol error probability (SEP) of M-ary quadrature amplitude modulation (QAM) for three different antenna selection schemes by considering the effect of delayed CQI. All these derived expressions are the function of correlation between CQI at the receiver and delayed CQI at the transmitter. The simulation results show that the antenna selection gain decreases with the decrease in correlation. It is also observed that scheme 1 based antenna selection is optimal for different constellations and more suited for MHR network. [ABSTRACT FROM AUTHOR]

We describe a system for the automated diagnosis of diabetic retinopathy and glaucoma using fundus and optical coherence tomography (OCT) images. Automatic screening will help the doctors to quickly identify the condition of the patient in a more accurate way. The macular abnormalities caused due to diabetic retinopathy can be detected by applying morphological operations, filters and thresholds on the fundus images of the patient. Early detection of glaucoma is done by estimating the Retinal Nerve Fiber Layer (RNFL) thickness from the OCT images of the patient. The RNFL thickness estimation involves the use of active contours based deformable snake algorithm for segmentation of the anterior and posterior boundaries of the retinal nerve fiber layer. The algorithm was tested on a set of 89 fundus images of which 85 were found to have at least mild retinopathy and OCT images of 31 patients out of which 13 were found to be glaucomatous. The accuracy for optical disk detection is found to be 97.75%. The proposed system therefore is accurate, reliable and robust and can be realized. [ABSTRACT FROM AUTHOR]