Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

In this work the concept of semi-generalized regular topological space was introduced and studied via semi generalized open sets. Many properties and results was investigated and studied, also it was shown that the quotient space of semi-generalized regular topological space is not, in general semi-generalizedspace.

Soil movement resulting due unsupported excavation nearby axially loaded piles imposes significant structural troubles on geotechnical engineers especially for piles that are not designed to account for loss of lateral confinement. In this study the field excavation works of 7.0 m deep open tunnel was continuously followed up by the authors. The work is related to the project of developing the Army canal in the east of Baghdad city in Iraq. A number of selected points around the field excavation are installed on the ground surface at different horizontal distance. The elevation and coordinates of points are recorded during 23 days with excavation progress period. The field excavation process was numerically simulated by using the finite

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

Background: Axial spondyloarthritis (axSpA) is an inflammatory, systemic rheumatic condition that mostly affects the axial skeleton. Tenascin-C (TN-C) is a hexameric glycoprotein of considerable size, upregulated in many inflammatory conditions, while Interleukin-17 (IL-17) a cytokine that plays an important role in SpA symptoms. Objective: to investigate the upregulation between the serum levels of TN-C and IL-17 in Iraqi axSpA patients and the disease characteristics. Patients and Methods: Seventy-four axSpA patients and 28 matched controls were studied. Fifty-four patients received a tumor necrosis factor inhibitor (TNFi) and 20 did not. Serum TN-C and IL-17 concentrations were determined using the ELISA technique. The Bath Ankyl

The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

The effect of 0.662MeV gamma radiation on the optical properties of the CdTe thin films was studied. 300nm thickness of CdTe samples were irradiated with doses (10, 20, 30,60krad) in room temperature. The absorption spectra for all the samples were recorded using UV- Visible spectrometer in order to calculate the energy gap, width of localized states and optical constants(refractive index, extinction coefficient, real and imaginary parts of dielectric constant). The optical energy gap was found to decrease from (1.53 to 1.48 eV), while the width of localized states increased from (1.34 to 1.49 eV) with the increasing of radiation dose. The behavior of energy gap with the irradiation dose makes the material a good candidate for dosimetry