The mass attenuation coefficient for beta particles through pure Polyvinyl chloride (PVC) and flax fibers- reinforced PVC composite were investigated as a function of the absorber thickness and the absorber to source distance. The beta particles mass attenuation coefficients were obtained using a NaI(Tl) energy selective scintillation counter with 90Sr/ 90Y beta source having an energy range from (0.546-2.275) MeV. Pure PVC polymer samples were prepared by compacting the PVC powder in a mould at high pressure (10bar) and temperature about 140°C for 30 minutes. A hot press system was used for this process. The experimentally obtained values of mass attenuation coefficients for 90Sr and 90Y were found to be 7.72 cm2.g-1and 0.842 cm2.g-1 r

The design of safe pedestrian facilities usually depends on the assessment of pedestrian characteristics and behavior. In this investigation, pedestrian walking speed through the religious occasion have been monitored at three locations, Al- Kadhimiya (Imam AL-Kadim), Najaf and Karbala (Imam AL-Husain) holy shrines. Video captures of the pedestrian through their walking to the two holy shrines have been prepared and analyzed for walking speed, gender, age groups, and clothing tradition. The pedestrian sample size is 468, 501, and 447 for Al- Kadhimiya, Karbala, and Najaf respectively. When the gender is taken into consideration, it can be noted that the walking speed of male and female pedestrian is (0.97, 1.68, and 1.63

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

One of the most important problems facing the world today is the energy problem. The solution was in finding renewable energy sources such as solar energy. The solar energy applications in Iraq is facing many problems . One of the most important problems is the accumulation of dust on the solar panels surface which causes decreasing its performance sharply. In the present work, a new technique was presented by using two-axis solar tracking system to reduce the accumulated dust on the solar panel surface and compared it with the fixed solar panels which installed at tilt angles 30° and 45°. The results indicated that the maximum losses of the output power due to accumulation of dust on the fixed solar panels is about 31.4% and 23.1% res

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

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