Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze medical images with favorable results. It can help save lives faster and rectify some medical errors. In this study, we look at the most up-to-date methodologies for medical image analytics that use convolutional neural networks on MRI images. There are several approaches to diagnosing and classifying brain cancers. Inside the brain, irregular cells grow so that a brain tumor appears. The size of the tumor and the part of the brain affected impact the symptoms.
The availability of low- cost adsorbent namely Al-Khriet ( a substance found in the legs of Typha Domingensis) as an agricultural waste material, for the removal of lead and cadmium from aqueous solution was investigated. In the batch tests experimental parameters were studied, including adsorbent dosage between (0.2-1) g, initial metal ions concentration between (50-200) ppm (single and binary) and contact time (1/2-6) h. The removal percentage of each ion onto Al-Khriet reached equilibrium in about 4 hours. The highest adsorption capacity was for lead (96%) while for cadmium it was (90%) with 50 ppm ions concentration, 1 g dosage of adsorbent and pH 5.5. Adsorption capacity in the binary mixture were reduce at about 8% for lead a
... Show MoreMeasuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.
Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr
... Show MoreThis research studies the possibility of producing Bone China with available local and geological substitutes and other manufactured ones since it’s traditionally produced by Bone ash, Cornish stone, and China clay, while the substitutes are Kaolin instead of China clay and Feldspar potash instead of Cornish stone. Because of the unavailability of Feldspar in Iraq, it was substituted with the manufactured alternative Feldspar. Bone ash was prepared from cow bones with heating treatments, grinding and sifting. The alternative Feldspar was prepared by chemical analysis of the natural Feldspar potash with local materials that include Dwaikhla Kaolin, Urdhuma Silica sand, Potassium Carbonate, and Sodium Carbonate. The mixture was burned at
... Show MoreInvasomes are newly developed types of nanovesicles. A vesicular drug delivery system is considered one of the approaches for transdermal delivery to enhance permeation and improve drug bioavailability. Ondansetron is a serotonin receptor antagonist used for treating vomiting associated with different clinical cases. The study aimed to prepare invasomal dispersions for improving permeation of ondansetron across the skin with a controlled release pattern. Twenty-seven formulas of ondansetron-loaded invasomes were prepared by a modified mechanical dispersion method. These formulas were optimized by studying the effect of variables on entrapment efficiency. Vesicle size, polydispersity, zeta potential, in-vitro release and ex-vivo perm
... Show MoreThis paper discusses using H2 and H∞ robust control approaches for designing control systems. These approaches are applied to elementary control system designs, and their respective implementation and pros and cons are introduced. The H∞ control synthesis mainly enforces closed-loop stability, covering some physical constraints and limitations. While noise rejection and disturbance attenuation are more naturally expressed in performance optimization, which can represent the H2 control synthesis problem. The paper also applies these two methodologies to multi-plant systems to study the stability and performance of the designed controllers. Simulation results show that the H2 controller tracks a desirable cl
... Show MoreIn light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
... Show MoreBased on the results of standard penetration tests (SPTs) conducted in Al-Basrah governorate, this research aims to present thematic maps and equations for estimating the bearing capacity of driven piles having several lengths. The work includes drilling 135 boreholes to a depth of 10 m below the existing ground level and three standard penetration tests (SPT) at depths of 1.5, 6, and 9.5 m were conducted in each borehole. MATLAB software and corrected SPT values were used to determine the bearing capacity of driven piles in Al-Basrah. Several-order interpolation polynomials are suggested to estimate the bearing capacity of driven piles, but the first-order polynomial is considered the most straightforward. Furthermore, the root means squar
... Show MoreIn this study, the electro-hydraulic servo system for speed control of fixed displacement hydraulic motor using proportional valve and (PID) controller is investigated theoretically ,experimentally and simulation . The theoretical part includes the derivation of the nonlinear mathematical model equation of (valve – motor ) combination system and the derivation of the transfer function for the complete hydraulic system , the stability test of the system during the operation through the transfer function using MATLAB package
V7.1 have been done. An experimental part includes design and built hydraulic test rig and simple PID controller .The best PID gains have been calculated experimentally and simulation, speed control performance te