CNN supported automated recognition of Covid-19 infection in chest X-ray images

Automatic recognition of lung system is use to identify normal and covid infected lungs from chest X-ray images of the people. In the year 2020, the coronavirus forcefully pushed the entire world into a freakish situation, the foremost challenge is to diagnosis the coronavirus. We have got standard diagnosis test called PCR test which is complex and costlier to check the patient's sample at initial stage. Keeping this in mind, we developed a work to recognize the chest X-ray image automatically and label it as Covid or normal lungs. For this work, we collected the dataset from open-source data repository and then pre-process each X-ray images from each category such as covid X-ray images and non-covid X-ray images using various techniques such as filtering, edge detection, segmentation, etc., and then the pre-processed X-ray images are trained using CNN-Resnet18 network. Using PyTorch python package, the resnet-18 network layer is created which gives more accuracy than any other algorithm. From the acquired knowledge the model is correctly classifies the testing X-ray images. Then the performance of the model is calculated and analyzed with various algorithms and hence gives that the resnet-18 network improves our model performance in terms of specificity and sensitivity with more than 90%.

Effect of Ablation Rate on the Microstructure and Electrochromic Properties of Pulsed-Laser-Deposited Molybdenum Oxide Thin Films

Molybdenum trioxide (MoO₃) is a well-known electrochromic material. In the present work, n-type α-MoO₃ thin films with both direct and indirect band gaps were fabricated by varying the laser repetition (ablation) rate in a pulsed laser deposition (PLD) system at a constant reactive O₂ pressure. The electrochromic properties of the films are compared and correlated to the microstructure and molecular-level coordination. Mixed amorphous and textured crystallites evolve at the microstructural level. At the molecular level, using NMR and EPR, we show that the change in the repetition rate results in a variation of the molybdenum coordination with oxygen: at low repetition rates (2 Hz), the larger the octahedral coordination, and greater the texture, whereas at 10 Hz, tetrahedral coordination is significant. The anion vacancies also introduce a large density of defect states into the band gap, as evidenced by XPS studies of the valence band and supported by DFT calculations. The electrochromic contrast improved remarkably by almost 100% at higher repetition rates whereas the switching speed decreased by almost 6-fold. Although the electrochromic contrast and coloration efficiency were better at higher repetition rates, the switching speed, reversibility, and stability were better at low repetition rates. This difference in the electrochromic properties of the two MoO₃ films is attributed to the variation in the defect and molecular coordination states of the Mo cation.