Enhanced image classification using edge CNN (E-CNN)

Recently, deep learning has become a hot topic in wide fields, especially in the computer vision that proved its efficiency in processing images. However, it tends to overfit or consumes a long learning time in many platforms. The causes behind these issues return to the huge number of learning parameters and lack or incorrect training samples. In this work, two levels of deep convolutional neural network (DCNN) are proposed for classifying the images. The first one is enhancing the training images with removing unnecessary details, and the second one is detecting the edges of the processed images for further reduction of learning time in the DCNN. The proposed work is inspired by the human eye's way in recognizing an object, where a piece of object can be helpful in the recognition and not necessarily the whole object or full colors. The goal is to speed up the learning process of CNN based on the preprocessed training samples that are precise and lighter to work well in real-time applications. The obtained results proved to be more significant for real-time classification as it reduced the learning process by (94%) in Animals10 dataset with a validation accuracy of (99.2%) in accordance with the classical DCNNs

Quad-color image encryption based on Chaos and Fibonacci Q-matrix

The Information technology requires the transmission of daily-life images that may reach to millions or even more. Thus, securing them becomes an urgent matter using the encryption technique. Where, a secret key is used for converting the original image into a noisy one and restoring it back using the same key. Confusion and Diffusion are the wildly used steps in such a technique. Therefore, a new algorithm is presented in this work that uses a fusion, segmentation, random assembling, hyperchaotic and Fibonacci Q-matrix (FQ-matrix). A novel fusion method is designed for fusing four color images into four different sequences according to their contained information. Then the resulted four images are each divided into four segments to be assembled randomly into one image using a random-key; which confused later using a six-dimensional hyperchaotic system and diffused using the FQ-matrix. The performance and robustness of the proposed algorithm have been computed based on different tests; where it proved its powerful capability in securing the transmitted images

Strengthening of hollow brick infill walls with perforated steel plates

WOS: 000337304000004The infill walls, whose contribution to the earthquake resistance of a structure is generally ignored due to their limited lateral rigidities, constitute a part of the lateral load bearing system of an RC frame structure. A common method for improving the earthquake behavior of RC frame structures is increasing the contribution of the infill walls to the overall lateral rigidity by strengthening them through different techniques. The present study investigates the influence of externally bonded perforated steel plates on the load capacities, rigidities, and ductilities of hollow brick infill walls. For this purpose, a reference (unstrengthened) and twelve strengthened specimens were subjected to monotonic diagonal compression. The experiments indicated that the spacing of the bolts, connecting the plates to the wall, have a more profound effect on the behavior of a brick wall compared to the thickness of the strengthening plates. Furthermore, an increase in the plate thickness was shown to result in a considerable improvement in the behavior of the wall only if the plates are connected to the wall with closely-spaced bolts. This strengthening technique was found to increase the energy absorption capacities of the walls between 4 and 14 times the capacity of the reference wall. The strengthened walls reached ultimate loads 30-160% greater than the reference wall and all strengthened walls remained intact till the end of the test

Behavior and strength of hidden Rc beams embedded in slabs

WOS: 000529904300028Reinforced concrete (RC) beams protrude from the ceiling, unless there is an infill wall beneath. Sometimes the construction of these beams is avoided due to aesthetic concerns, and instead a reinforcement arrangement with an equivalent bending moment capacity in the slab is made; this is named as a hidden beam. However, since such a design based only on strength can change the behavior to a great extent, the drawbacks of hidden beams were experimentally investigated. A total of fourteen half-scale specimens, including conventional T-beams and slabs with identical flexural capacities (hidden beams), were tested to failure under four-point loading. Reinforcement ratio and slab thickness were adopted as test parameters. The results indicated that hidden beams were able to achieve reference strengths after excessive (up to eight times larger) deformations, or they occasionally could never achieve these capacities. Experimental data were also compared with analytical deflection approaches

Prevalence of Anosmia in 10.157 Pediatric COVID-19 Cases: Multicenter Study from Turkey.

Introduction: COVID-19-related anosmia is a remarkable and disease-specific finding. With this multicenter cohort study, we aimed to determine the prevalence of anosmia in pediatric cases with COVID-19 from Turkey and make an objective assessment with a smell awareness questionnaire. Material and Methods: This multicenter prospective cohort study was conducted with pediatric infection clinics in 37 centers in 19 different cities of Turkey between October 2020 and March 2021. The symptoms of 10.157 COVID-19 cases 10-18 years old were examined. Age, gender, other accompanying symptoms, and clinical severity of the disease of cases with anosmia and ageusia included in the study were recorded. The cases were interviewed for the smell awareness questionnaire at admission and one month after the illness. Results: Anosmia was present in 12.5% (1.266/10.157) of COVID-19 cases 10-18 years of age. The complete records of 1053 patients followed during the study period were analyzed. The most common symptoms accompanying symptoms with anosmia were ageusia in 885 (84%) cases, fatigue in 534 cases (50.7%), and cough in 466 cases (44.3%). Anosmia was recorded as the only symptom in 84 (8%) of the cases. One month later, it was determined that anosmia persisted in 88 (8.4%) cases. In the smell awareness questionnaire, the score at admission was higher than the score one month later (P < 0.001). Discussion: With this study, we have provided the examination of a large case series across Turkey. Anosmia and ageusia are specific symptoms seen in cases of COVID-19. With the detection of these symptoms, it should be aimed to isolate COVID-19 cases in the early period and reduce the spread of the infection. Such studies are important because the course of COVID-19 in children differs from adults and there is limited data on the prevalence of anosmia