The dynamic behavior of laced reinforced concrete (LRC) T‐beams could give high‐energy absorption capabilities without significantly affecting the cost, which was offered through a combination of high strength and ductile response. In this paper, LRC T‐beams, composed of inclined continuous reinforcement on each side of the beam, were investigated to maintain high deformations as predicted in blast resistance. The beams were tested under four‐point loading to create pure bending zones and obtain the ultimate flexural capacities. Transverse reinforcement using lacing reinforcement and conventional vertical stirrups were compared in terms of deformation, strain, and toughness changes of the tested beams. The inclination angles of the used lacing reinforcement with respect to the longitudinal reinforcement were 45° and 60°. The lacing reinforcement was efficient and participated actively in resisting the bending moments and shear forces at the same time. For the same diameter of lacing reinforcement, the 60° inclination angle imposed more ductility before failure than beams with lacing reinforcement of a 45° inclination angle. Moreover, the lacing bar diameter was more effective in improving the load‐carrying capacities when using the inclination angle of 45°. A finite element (FE) model was developed and validated using the experimental results based on the measured deformations and strains to conduct a parametric study. The investigated parameters included the effect of the arrangements of the applied loads, laced rebar diameter, inclination angle, tension reinforcement ratio, and concrete strength.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreAn electrolytic process for the removal of Zn(II) from aqueous solution using a parallel amalgamated copper screens cathode operated in the flow through mode is proposed. The current-potential curves recorded at a rotating amalgamated copper disc electrode were used to determine diffusion coefficient of Zn(II). The performance of electrolytic reactor was investigated by using different flow rates at initial zinc ion concentration(48 mg/L). Taking into account the residential Zn(II) concentration, the best results were obtained for cathode potential of (-1.35 V vs. SCE) at flow rate (320 L/h). Zinc ion concentration was found to decrease from 48 mg/L to 1 mg/L during 120 min. of electrolysis. The experimental data are well correlate
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreWe present a reliable algorithm for solving, homogeneous or inhomogeneous, nonlinear ordinary delay differential equations with initial conditions. The form of the solution is calculated as a series with easily computable components. Four examples are considered for the numerical illustrations of this method. The results reveal that the semi analytic iterative method (SAIM) is very effective, simple and very close to the exact solution demonstrate reliability and efficiency of this method for such problems.
The ability of Cr (VI) removal from aqueous solution using date palm fibers (leef) was investigated .The effects of pH, contact time, sorbets concentration and initial metal ions concentration on the biosorption were investigated.
The residual concentration of Cr (VI) in solution was determined colorimetrically using spectrophotometer at wave length 540 nm .The biosorption was pH-dependent, the optimum pH was 7 and adsorption isotherms obtained fitted well with Langmuir isotherms .The Langmuir equation obtained was Ce/Cs = 79.99 Ce-77.39, the correlation factor was 0.908.These results indicate that date palm fibers (leef) has a potential effect for the uptake of Cr (VI) from industrial waste water.
