No abstract

In this work, a modern optical system based on modulation technique is constructed to achieve the retrieval of optical defects and distortions of the images behind dark barriers.  A 800x600 analog spatial light modulator (SLM) is used in this technique with a 632.8nm He-Ne laser, a circular metallic mesh (CMM) is imaged and disturbed and then dealing with our system. The SLM was confirmed for irregularity improvement such as variable diffracted optical element (DOE) control. The obtained results showed that the effect of distortion has been treated and reduced to be minimum by controlling phase and amplitude modulation of the scattered wave front utilizing the SLM. The obtained images showed identical to the original image with limitation in the intensity distribution due to the pixelated structure of SLM. This technique represents the most appropriate solution to the problem of dispersion in images with the lowest costs and best results. The most important applications of this technology are the ability of providing high-resolution imaging where viewing through a deviant medium is inevitable.

Covid-19 is a disease that affects the respiratory system of the human body, and detecting this disease is a complex and one of the main challenges. This work proposed a technique for detection of COVID-19 by integrating multifocal images based on wavelet transduction. In order to improve the detection of COVID-19, Magnet resonant imagery (MRI) and computation tomography (CT) have been used. The multifocal image is included in order to support the diagnosis made by the clinicians. The seven-wave based algorithm bior2.2, coif2, db2, dmey, rbio2.2, sym4 and haar, respectively, was used to achieve a range of results. This approach effectively combines the data obtained from CT and MRI scans to produce a merged image that improves disease diagnosis efficiency by using MATLAB to determine the efficiency of the algorithm. The signal-to-noise ratio (PSNR) and the entropy factor are used to measure the image fusion efficiency. The statistical analysis of the final images demonstrated the superiority of the image attributes over both the CT image and the MRI.

Internet of nano things (IoNT) is a new and modern part of the internet of things (IoT). Applications that operate in the field of nano scale show a new advantage in communication networks. IoNT opened the door to many applications in various fields with new features derived from the advantages of nanotechnology. In this work, a description of the IoNT during 2015-2021 was achieved, including taxonomy, architecture, motives, applications and challenges, in addition to recommendations. The architecture of the IoNT and the most important technologies used in Nano communication networks have been identified, with an indication of the advantages of each. This study, we hope, will make a contribution to this field of science, thus contributing to providing assistance to researchers in this emerging field and covering the challenges they face in this way. That would permit communication between nano-devices to be conventional, making these calibrations to be implemented in various IoNT applications. Until the IoNT system is designed without any problems in the near future, which if achieved, will provide great services, especially in medical applications and other applications.