We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.
In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Abstract
In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons
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Breast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.
In Iraq, breast cancer incidence exceeds any other type of cancers and the etiology not understood well.Epstein Barr virus is a gamma herpesviruses and one of carcinogenic viruses that may implicated tobreast carcinogenesis. The nuclear antigen-1 (EBNA-1) protein is the sole EBV antigen that presentedin all tumors related to EBV and plays pivotal roles in carcinogenesis of the virus. Examination appliedby immunohistochemistry (IHC) to detect and demonstrate the correlation between (EBNA-1) and tumorsuppressor protein (P53) expression. The study includes paraffin-embedded tissue blocks of ninety 90malignant breast tissues and thirty 30 normal breast autopsies. EBNA-1 was significantly expressed in 40/90(44.4%) of malignant tissues wh
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الحمدُ للهِ رب العالمين ، والصلاة والسلام على نبيه الأمين محمد r وعلى آله الطيبين الطاهرين ، وأصحابه الغر الميامين:
تعد الصورة السمعية مفهوما بيانيا نجده في البلاغة العربية واضحاً مؤثرا، مؤديا دورا جوهريا في إيصال الفكرة التي يروم الأديب إيصالها إلى المتلقي ولا تبدو السمعية واضحة إلاّ إذا نظر إليها في حالة أدبيه تهز كيان الشاعر  
... Show MoreAnalytical field target function has been considered to represent the axial magnetic field distribution of double polepiece symmetric magnetic lens. In this article, with aid of the proposed target function, the syntheses procedure is dependent. The effect of the main two coffectin optimization parameters on the lens field distribution, polepieces shape, and the objective focal prosperities for lenses operated under zero magnification mode has been studied. The results have shown that the objective properties evaluated in sense of the inverse design procedure are in an excellent correspondence with that of analysis approach. Where the optical properties enhance as the field distribution of the electron lens distributed along a narrow axi
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.
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