The COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is frequent in COVID-19 patients. This can assist healthcare practitioners in identifying and monitoring illness development, as well as making treatment decisions. Scale U-Net is a strong U-Net design modification that can increase the performance of semantic segmentation tasks. Our model, Normalized-UNet, uses batch normalization after each convolutional layer to decrease the internal covariate shift, which dramatically improves the network's learning efficiency.
The usage of remote sensing techniques in managing and monitoring the environmental areas is increasing due to the improvement of the sensors used in the observation satellites around the earth. Resolution merge process is used to combine high resolution one band image with another one that have low resolution multi bands image to produce one image that is high in both spatial and spectral resolution. In this work different merging methods were tested to evaluate their enhancement capabilities to extract different environmental areas; Principle component analysis (PCA), Brovey, modified (Intensity, Hue ,Saturation) method and High Pass Filter methods were tested and subjected to visual and statistical comparison for evaluation. Both visu
... Show MoreThis research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri
Multi-walled carbon nanotubes from cheap tubs company MWCNT-CP were purified by alcohol \ H2O2 \ separation funnel which is simple, easy and scalable techniques. The steps of purification were characterized by X-ray diffraction, Raman spectroscopy, scanning electron microscopy SEM with energy dispersive of X-ray spectroscopy EDX and surface area measurements. The technique was succeeded to remove most the trace element from MWCNT-CP which causing increase the surface area. The ratios of impurities were reduced to less 0.6% after treatment by three steps with losing less than 5% from MWCNT-CP.
Abstract
For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
The problem of the research lies in choosing agility tests suitable to the test taker to observe the relative changes in some players. In addition to that, there are a lot of agility tests that lack special test models that coordinate gender and age. This means the youth basketball player on one hand and time and distance in applying the tests on the other. The importance of the research lies in designing agility tests for youth basketball players to achieve variations in tests a matter that will benefit coaches in their training. The subjects of the research were (30) youth basketball players from the specialized school of the National Center that sponsor gifted basketball players in Baghdad for the season 2014 – 2015. The data was colle
... Show MoreThe using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.
For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence
... Show MoreIn this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.