: The Aluminium (Al) material emerged as a plasmonic material in the wavelength ranges from the ultraviolet to the visible bands in different on-chip plasmonic applications. In this paper, we demonstrate the effect of using Al on the electromagnetic (EM) field distribution of a compact hybrid plasmonic waveguide (HPW) acting as a polarization rotator. We compare the performance of Al with other familiar metals that are widely used as plasmonic materials, which are Silver (Ag) and Gold (Au). Furthermore, we study the effect of reducing the geometrical dimensions of the used materials on the EM field distributions inside the HPW and, consequently, on the efficiency of the polarization rotation. We perform the study based o

This study is concerned with the effect of adding two kinds of ceramic materials on the mechanical properties of (Al-7%Si- 0.3%Mg) alloy, which are zirconia with particle size (20μm > P.S ≥ 0.1μm) and alumina with particle size (20μm > P.S ≥ 0.1μm) and adding them to the alloy with weight ratios (0.2, 0.4, 0.6, 0.8 and 1%). Stirring casting method has been used to make composite material by using vortex technique which is used to pull the particles to inside the melted metals and distributed them homogenously.

After that solution treatment was done to the samples at (520ºC) and artificial ageing at (170ºC) in different times, it has been noticed that the values of hardness is increased with the aging time of the o

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Advertising technology represents a component of elements of the visual attraction in the urban scape, made its way transmission process of messages between the ends of the source ofinformation (sender) and the Destination information (receiver) of the final recipient of themessage, It serves as a social marked and a means of cultural expression, It is part of the inalienable in creating identity and determine the spatial relationships and also is a reflection ofurban culture to the community. This technology has become an increasing feature of the present era, characterized as the era of the three revolutions: (the information revolution, the technologyrevolution, and the media revolution), Where it became an integral part of the visual

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Temperature inside the vehicle cabin is very important to provide comfortable conditions to the car passengers. Temperature inside the cabin will be increased, when the car is left or parked directly under the sunlight. Experimental studies were performed in Baghdad, Iraq (33.3 ^oN, 44.4 ^oE) to investigate the effects of solar radiation on car cabin components (dashboard, steering wheel, seat, and inside air). The test vehicle was oriented to face south to ensure maximum (thermal) sun load on the front windscreen. Six different parking conditions were investigated. A suggested car cover was examined experimentally. The measurements were recorded for clear sky summer days started at 8 A.M. till 5 P.M.

مفهوم معامل الارتباط كمقياس يربط بين متغيرين هذا يجلب انتباهنا إلى موضوع الإحصاء في كل المستويات. أكثر من ذلك هناك ثلاث نقاط خاصة هي اعتيادياً نشدد عليها كما يأتي:-

(1 معامل الارتباط هو الدليل المعياري والذي قيمته لا تعتمد على قياسات  

    المتغيرات الأصلية.

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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

An attempt was made to evaluate the PV performance of one-axis daily tracking and fixed system for Baghdad, Iraq. Two experimental simulations were conducted on a PV module for that purpose. Measurements included incident solar radiation, load voltage and load current. The first experiment was carried out for six months of winter half of year to simulate the one-axis daily tracking. The azimuth angle was due south while the tilt angle was being set to optimum according to each day of simulation. The second experiment was done at one day to simulate the PV module of fixed angles. It is found that there is a significant power gain of 29.6% for the tracking system in respect to the fixed one. The one-axis daily tracking was much more effect