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Go to Editorial ManagerMany mobile applications use infrared (IR) and Ultrasonic sensors for distance measurements. In this paper, these two types of sensors have been used in building obstacle detection system and the attributes of each sensor has been tested, the system consists of transmitter and receiver circuit, furthermore, Arduino UNO card has been used for transmitting and receiving signal for each type of sensor based on the Arduino software. The test was performed through distributing these sensors on the road then analyze the reflected signal. Neural network trained and used for monitoring the street and producing the number of cars in each line of street and the total number of cars in the same street.
The most important way for joining the non-welding aluminum alloy is Friction stir spot welding. Three parameters effect on efficiency of welding: tool shape, rotational speed, and plunged time, are chosen to study for welding 6061T6 aluminum alloy. Each of the above parameters has three variables as: pin shapes (square, cylinder, and hexagonal), plunged time (50, 70,100) sec and rotational speeds (710, 1120, 1800) rpm hybrid approach which is consist of the experiment run, neural network and social spider optimization is used to optimize the welding conditions by finding the maximum ultimate force. The best condition of the weldments is (square, 710rpm, 100sec) with maximum shear force 4740N. The best results obtained from hybrid optimization with experimental results; with discrepancy of 2%.
Cone-beam computed tomography (CBCT) is an indispensable method that reconstructs three dimensional (3D) images. CBCT employs a mathematical technique of reconstruction, which reveals the anatomy of the patient’s body through the measurements of projections. The mathematical techniques employed in the reconstruction process are classified as; analytical, and iterative. The iterative reconstruction methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time those methods are excluded from routine use in clinical applications. The aim of this research is to accelerate the iterative methods by performing the reconstruction process using a graphical processing unit (GPU). This method is tested on two iterative-reconstruction algorithms (IR), the algebraic reconstruction technique (ART), and the multiplicative algebraic reconstruction technique (MART). The results are compared against the traditional ART, and MART. A 3D test head phantom image is used in this research to demonstrate results of the proposed method on the reconstruction algorithms. The simulation results are executed using MATLAB (version R2018b) programming language and computer system with the following specifications: CPU core i7 (2.40 GHz) for the processing, with a NIVDIA GEFORCE GPU. Experimental results indicate, that this method reduces the reconstruction time for the iterative algorithms.
The traditional electric poles in Iraq are usually made from steel materials. Such materials induced high weight, corrosion, permanent deformation caused by high wind speed, etc. The study aimed to numerically examine the strength of few poles made from different materials. The pole subjected to pressure developed by actual measured wind speed of 140 km/h. The numerical model of different materials and cross sections, an octagonal section electric pole made from composite material FRP–HDPE–FRP is suggested to replace the traditional one. The results showed high safety factor, approximately 5.51 besides the low ratio of high strength to weight as compared to steel materials. Using HDPE as reinforced material resulted in pole elastically deformed with only 0.222 mm. Therefore, it can be assumed that the suggested pole acts partially as a damper. Straight octagonal cross - section of pole promoted high reduction (74.22%) in maximum Von–Misses stress of that obtained in cylindrical three-stage pole. High reduction (5.87 times) in maximum deformation value was obtained when composite octagonal pole was used as compare to tapered pole made from steel.
The experimental analysis is conducted under the Iraqi climate conditions to investigate the performance enhancement of a solar updraft tower system (SUTS) using the porous copper foam as an absorber plate and conventional absorber plate with absorber inclination angle of 18°. In the present work, a semicircular collector is divided into two identical quarter thermal collectors to become two identical SUTS. One of the quarter circular thermal collectors contains on the metal foam as an absorber plate, while the other quarter collector on the conventional flat copper absorber plate. In this study the air inlet height is changed of (3, 5, and 8) cm. The experimental tests carried out in Baghdad city (latitude 33.3° N). Results showed that the air inlet height variation caused to enhance the solar updraft tower performance. The highest values was recorded when the air inlet height is 3 cm using porous absorber compared to flat absorber plate. Copper material foam as an endothermic surface causes a marked decrease in average surface temperature of the plate. The maximum hourly thermal efficiency of solar collector was increased to about 41.6 % and the maximum enhancement of the power output to about 45.2 % compared with flat absorber plate.
Computed tomography (CT) imaging is an important diagnostic tool. CT imaging facilitates the internal rendering of a scanned object by measuring the attenuation of beams of X-ray radiation. CT employs a mathematical technique of image reconstruction; those techniques are classified as; analytical and iterative. The iterative reconstruction (IR) methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time, those methods are excluded from routine use in clinical applications. In this paper the reconstruction time of an IR algorithm is minimized through the employment of an adaptive region growing segmentation method that focuses the image reconstruction process on a specified region, thus ignoring unwanted pixels that increase the computation time. This method is tested on the iterative algebraic reconstruction technique (ART) algorithm. Some phantom images are used in this paper to demonstrate the effects of the segmentation process. The simulation results are executed using MATLAB (version R2018b) programming language, and a computer system with the following specifications: CPU core i7 (2.40 GHz) for processing. Simulation results indicate that this method will reduce the reconstruction time of the iterative algorithms, and will enhance the quality of the reconstructed image.
The adsorption characteristics of Nickel (II) onto Iraqi Bentonite clay from aqueous solution have been investigated with respect to changes in pH of solution, adsorbent dosage, contact time and temperature of the solution. The maximum removal efficiency of Nickel (II) ions is 96% at pH=6.5 and exposure to 100 g/L adsorbent. For the adsorption of Nickel (II) ions, the Freundlich isotherm model fitted the equilibrium data better than the Langmuir isotherm model. Experimental data are also evaluated in terms of kinetic characteristics of adsorption and it was found that the adsorption process for Ni+2 ions follows well pseudo-second-order kinetics. Thermodynamic functions, the change of free energy (?G°), enthalpy (?H°) and entropy (?S°) of adsorption are also calculated for Nickel (II) ions. The results show that the adsorption of the Nickel (II) ions on Iraqi Bentonite is feasible and exothermic at (20-50) °C.
This research study the rheological properties ( plastic viscosity, yield point and apparent viscosity) of non-Newtonian fluids under the addition of different chemical additives with different concentrations, such as (xanthan gum (xc-polymer) , carboxy methyl cellulose ( high and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch, quebracho, chrome lignosulfonate, and sodium chloride (NaCl). Fann viscometer model 800 with 8-speeds was used to measure the rheological properties of these samples, that have already been prepared. All samples were subjected to Bingham plastic model. It was concluded that the plastic viscosity, yield point and apparent viscosity should be increased with increasing the concentrations of (xanthan gum (xc-polymer) , carboxy methyl cellulose ( high and low viscosity ) ,polyacrylamide, polyvinyl alcohol, starch and sodium chloride (NaCl), while the opposite is true for quebracho, chrome lignosulfonate.
Deep learning modeling could provide to detected Corona Virus 2019 (COVID-19) which is a critical task these days to make a treatment decision according to the diagnostic results. On the other hand, advances in the areas of artificial intelligence, machine learning, deep learning, and medical imaging techniques allow demonstrating impressive performance, especially in problems of detection, classification, and segmentation. These innovations enabled physicians to see the human body with high accuracy, which led to an increase in the accuracy of diagnosis and non-surgical examination of patients. There are many imaging models used to detect COVID-19, but we use computerized tomography (CT) because is commonly used. Moreover, we use for detection a deep learning model based on convolutional neural network (CNN) for COVID-19 detection. The dataset has been used is 544 slice of CT scan which is not sufficient for high accuracy, but we can say that it is acceptable because of the few datasets available in these days. The proposed model achieves validation and test accuracy 84.4% and 90.09%, respectively. The proposed model has been compared with other models to prove superiority of our model over the other models.