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

The study relied on data about the health sector in Iraq in 2006 in cooperation with the Ministry of Health and the Central Bureau of Statistics and Information Technology in 2007 Included the estimates of the population distribution of the Baghdad province and the country depending on the population distribution for 1997,evaluate the health sector which included health institutions, and health staff, and other health services. The research Aimis; Measurement an amount and size of the growth of health services (increase and decrease) and the compare of verified in Iraq and Baghdad, and evaluate the effectiveness of the distribution of supplies and health services (physical and human) of the size of the population distribution and

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Magnetic levitation (Maglev) systems are employed in a wide range of applications and are therefore of significant practical importance, which has led to growing research interest. This paper presents the design of a terminal synergetic control (TSC) and feedback linearization-based proportional-integral-derivative plus second-order derivative (FL-PIDD2) controller for the Maglev system. For developing the control law of both controllers, the mathematical model of the Maglev system is converted into a canonical system where the expression of the nonlinearity is displayed in the last differential dynamic equation of the system. The determination of the TSC and FL-PIDD2 gains for achieving the desired dynamic response is carried out using the

This study aims to test whether the institutions listed on the Iraq Stock Exchange have a significant correlation between the level of conservative accounting practice with the level of market share returns during the Coronavirus pandemic period as one of the policies to confront the economic repercussions of the Coronavirus pandemic. Furthermore, the sample included institutions listed on the Iraq Stock Exchange during the 2019 and 2020 years, i.e., the period before the Coronavirus pandemic and during the Coronavirus pandemic for the purpose of comparison. The market value to book value model was used, and the study found that conservative institutions had achieved the highest level of market share prices compared to non-conservat

The article describes a study on the role of vitamin C as a protective agent for the teeth, gum, and implants using quantum chemical calculations and polarization tests. The Density Functional Theory (DFT) at 6-311G (d, p) basis set is used to estimate the ability of vitamin C to inhibit the corrosion of the abovementioned parts. The experimental study was performed in a at human body media simulator (Hank’s balanced salt solution) at a temperature of 37°C. The compound was optimized for its ground state, physical properties, and corrosion parameters. Further, HOMO, LUMO, energy gap, dipole moment, and other parameters were used to predict the inhibitor’s efficiency. Gaussian 09, UCA-FUKUI, MGL tools, DSV, and LigPlus software was used