Covid-19 Detection Based on Chest X-Ray Images Using DCT Compression and NN

Covid-19 is a highly contagious virus spreading all over the world. It is caused by SARS-CoV-2. virus. Some of the most common symptoms are fever, cough, sore throat, tiredness, and loss of smell or taste. There are two types of tests for COVID-19: the PCR test and the antigen test. Automatic detection of Covid-19 from publicly available resources is essential. This paper employs the commonly available chest x-ray (CXR) images in the classification of Covid-19, normal and viral pneumonia cases. The proposed method divides the CXR images into subblocks and computes the Discrete Cosine Transform (DCT) for every subblock. The DCT energy compaction capability is employed to produce a compressed version for each CXR image. Few spectral DCT components are incorporated as features for each image. The compressed images are scanned by average pooling windows to reduce the dimension of the final feature vectors. A multilayer artificial neural network is employed in the 3-set classification. The proposed method achieved an average accuracy of 95 %. While the proposed method achieves comparable accuracy relative to recent state-of-the-art techniques, its computational burden and implementation time is much less

Design and implementation of 2.6 GHz Phase shift using microstrip technology for mobile broadband application

This paper evolves transmission line phase shifting to optimize system cost. The design of a 1 x 2 microstrip (patch) array antenna which has an operating frequency of 2.6 GHz. Substrate FR4 dielectric with dielectric constant of 4.4 and thickness of 1.6 mm is utilized in array design. The study is performed in four steps: Firstly, through simulating radiation pattern on CST by altering two independent parameters; Spacing between patches and differential length of transmission line from source to each patch antenna. Secondly, a fabrication has been done on a sample deferential length to two ports that simulating two microstrip (patch) antennas array. Thirdly, testing of radiation fields has been performed to verify the correlation between actual records and the simulated designed antenna phase shifting. Fourth and finally, A comparison of results has been included between this paper results and previous works in sake of showing the introduced effort added value

Efficient framework for brain tumor detection using different deep learning techniques

The brain tumor is an urgent malignancy caused by unregulated cell division. Tumors are classified using a biopsy, which is normally performed after the final brain surgery. Deep learning technology advancements have assisted the health professionals in medical imaging for the medical diagnosis of several symptoms. In this paper, transfer-learning-based models in addition to a Convolutional Neural Network (CNN) called BRAIN-TUMOR-net trained from scratch are introduced to classify brain magnetic resonance images into tumor or normal cases. A comparison between the pre-trained InceptionResNetv2, Inceptionv3, and ResNet50 models and the proposed BRAIN-TUMOR-net is introduced. The performance of the proposed model is tested on three publicly available Magnetic Resonance Imaging (MRI) datasets. The simulation results show that the BRAIN-TUMOR-net achieves the highest accuracy compared to other models. It achieves 100%, 97%, and 84.78% accuracy levels for three different MRI datasets. In addition, the k-fold cross-validation technique is used to allow robust classification. Moreover, three different unsupervised clustering techniques are utilized for segmentation

Design and Fabrication a W-Shape Form Dual-Band Flexible Antenna For Biomedical Applications

This study suggests a dual band flexible antenna for use at 900 and 2450 MHz. With a footprint of 0.23 o, 0.120 o, and 0.0007 o, where o is the lowest resonance wavelength, the antenna is relatively tiny. The antenna is built from a straightforward geometrical structure consisting of a W-shaped serpentine structure supplied by a microstrip line and a partial ground plane utilizing the Defected Ground Structure (DGS) technology in order to achieve wide operational bandwidth. In order to boost resonance, an additional capacitor was inserted between the slots, creating a portable dual-band antenna. Several performance metrics\u27 findings and the ones that had been measured were compared. The antenna\u27s potential for rigid and flexible electronics is increased by its good size, bandwidth, gain, and radiation pattern

Design and Analysis of Circular Polarized Two-Port MIMO Antennas with Various Antenna Element Orientations

This article presents the circularly polarized antenna operating over 28 GHz mm-wave applications. The suggested antenna has compact size, simple geometry, wideband, high gain, and offers circular polarization. Afterward, two-port MIMO antenna are designed to get Left Hand Circular Polarization (LHCP) and Right-Hand Circular Polarization (RHCP). Four different cases are adopted to construct two-port MIMO antenna of suggested antenna. In case 1, both of the elements are placed parallel to each other; in the second case, the element is parallel but the radiating patch of second antenna element are rotated by 180°. In the third case, the second antenna element is placed orthogonally to the first antenna element. In the final case, the antenna is parallel but placed in the opposite end of substrate material. The S-parameters, axial ratio bandwidth (ARBW) gain, and radiation efficiency are studied and compared in all these cases. The two MIMO systems of all cases are designed by using Roger RT/Duroid 6002 with thickness of 0.79 mm. The overall size of two-port MIMO antennas is 20.5 mm × 12 mm × 0.79 mm. The MIMO configuration of the suggested CP antenna offers wideband, low mutual coupling, wide ARBW, high gain, and high radiation efficiency. The hardware prototype of all cases is fabricated to verify the predicated results. Moreover, the comparison of suggested two-port MIMO antenna is also performed with already published work, which show the quality of suggested work in terms of various performance parameters over them