For more than a decade, externally bonded carbon fiber reinforced polymer (CFRP) composites successfully utilized in retrofitting reinforced concrete structural elements. The function of CFRP reinforcement in increasing the ductility of reinforced concrete (RC) beam is essential in such members. Flexural and shear behaviors, ductility, and confinement were the main studied properties that used the CFRP as a strengthening material. However, limited attention has been paid to investigate the energy absorption of torsion strengthening of concrete members, especially two-span concrete beams. Hence, the target of this work is to investigate the effectiveness of CFRP-strengthening technique with regard to energy absorption of two-span RC

     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.

Soaking dentures with disinfection solutions is an effective way of keeping dentures in a healthy status; however, immersions in these solutions have a negative effect on the bond strength of denture base and denture teeth. The aim of this study was to evaluate the bond strength between denture acrylic teeth and heat-cured Poly (methyl methacrylate) denture base material (with and without nano silica) after disinfection with different chemical disinfectants for a simulated period of six months. One hundred specimens of maxillary central incisors attached to PMMA were divided into two groups; 50 specimens of PMMA without nano silica and 50 specimens of PMMA reinforced with 5 wt% of nano silica. Specimens of each group were immersed in five i

Researches in the field of evaluation of industrial products emotionally are internationally new and non-existing in the Arabic speaking countries, which is considered the crux of the problem in the current research, in addition to the need of the designers and design students to know how to measure the emotional responses for the industrial product in order to get benefit from them in their designs. The research objective is to get a tool that uses emojis in measuring the emotional responses for the products. The researcher designed an emotional verbal wheel and emojis wheel. The sample of the research consisted of (7) chairs different in design and use, and the respondents were (89) students. The most important results are:
1- Desi

The electrocoagulation process became one of the most important technologies used for water treatment processes in the last few years. It’s the preferred method to remove suspended solids and heavy metals from water for treating drinking water and wastewater from textile, diary, and electroplating factories. This research aims to study the effect of using the electrocoagulation process with aluminum electrodes on the removal efficiency of suspended solids and turbidity presented in raw water and optimizing by the response surface methodology (RSM). The most important variables studied in this research included electrode spacing, the applied voltage, and the operating time of the electrocoagulation process. The samples