Search

Breast cancer has emerged as one of the most prevalent malignancies affecting women today, underscoring the critical need for advanced diagnostic tools. Mammography has been the conventional method for early breast cancer detection, yet recent years have witnessed the emergence of thermal infrared scans, or thermographies, as a potential contender for diagnosing breast cancer, particularly in cases of dense breast tissue. Thermographic images reveal higher temperatures in regions containing tumors compared to healthy breast tissue, providing a promising avenue for early diagnosis. In parallel, the field of radiography has seen the advent of deep learning (DL) techniques, offering a computational approach to breast cancer identification. This study presents a novel approach, the Enhanced Deep learning-based Convolutional Neural Network (EDCNN), aimed at generating heatmaps from two-dimensional thermal breast images. These heatmaps are employed to quantitatively assess breast vascularity, yielding interpretable parameters for further analysis. In addition, the study proposes a classifier that predicts the likelihood of breast cancer purely based on these extracted parameters. To enhance the accuracy of this process, the algorithm combines Fuzzy C-means clustering with the Region of Interest (ROI) technique to effectively isolate the breast from surrounding body parts. The segmentation results are evaluated using temperature profiles, revealing substantial peaks in the patterns as indicators of ROIs. This identification of hot areas hints at the potential presence of a tumor. To validate the effectiveness of this approach, the study constructs DL models using convolutional neural networks, training them with thermal breast images from the Graphical DMR datasets. The results are compelling, with the EDCNN models outperforming alternative methods, achieving an impressive accuracy of 96.8% and a specificity rate of 93.7%. This research thus offers a robust, efficient, and reliable means of early breast cancer diagnosis, marking a significant advancement in the field. [ABSTRACT FROM AUTHOR]

In this paper, SP4T (Single Pole four throw) type RF MEMS Switch is designed for Satellite applications. The beam thickness of the switch is varying from 1 μm, 1.5 μm, and 2 μm. The capacitive and series beam is designed with 3 models. The device is a combination of series and shunt made up of 4 capacitive switches and 4 series switches. By using the COMSOL Multiphysics tool, we obtained the series switch has 8.9 V pull-in voltage and the shunt switch has 10 V at a beam thickness of 1 μm and the related capacitance ratio is 112. Using the HFSS method, performance analysis is found to achieve isolation and insertion loss at 62 dB and 0.4 dB at 14 GHz. [ABSTRACT FROM AUTHOR]

The design of a wide band bandpass filter is described in this article, which is done by using ?/4 transmission lines and is designed at a frequency range of 12GHz. Sigma shaped BPF is simulated by using EM simulation software An-soft HFSSv13 and is a wide band BPF having a band width of 5.8GHz and FBW of 50% as the center frequency. To determine its applicability for wideband applications, the suggested filter is constructed and tested. To guarantee that it is acceptable for satellite communication applications, many characteristics such as reflection co-efficient, transmission coefficient, bandwidth, and group delay are tested and are compared with the measured results. [ABSTRACT FROM AUTHOR]

Any wireless signal travelling in free space undergoes degradation due to the effects of the atmosphere that are naturally created in its pathway. Amongst all the degradation3 effects scintillation is significant at elevation angles above 5 degrees and also in tropical regions. Scintillation is mainly caused due to the rapid fluctuations in the refractive index of the layers of the atmosphere. Tropospheric scintillation is significant at frequencies above 3GHz. Ionosphere acts as a transparent layer above 10 GHz Tropospheric scintillation is receiving more attention because of the demand for higher bandwidth due to the congestion on the C and Ku bands. The rapid fluctuations induce variations in the received amplitude of the signal which decreases the quality of the signal. For systems with low elevation angle and the link operating with a frequency above 10GHz the effect of tropospheric scintillation is to be taken in to consideration. So, in this paper the effect of tropospheric scintillation is estimated for a Ku band beacon signal whose receiver is installed at K.L. University at a frequency of 11.7GHz. The scintillation amplitude is estimated using the beacon data and also using models that suit the tropical region. By comparing the scintillation amplitudes derived from the models and the with the one derived using beacon data, the best model that fits this geographical location is found which is the Otung model. [ABSTRACT FROM AUTHOR]