This paper presents a study (experimentally) for strengthening reinforced concrete (RC) beams with Near-Surface-Mounted (NSM) technique. The use of this technique with CFRP strips or rebars is an efficient technology for increasing the strength for flexure and shear or for repairing damaged reinforced concrete (RC) members. The objective of this research is to study, experimentally, RC beams either repaired or strengthened with NSM CFRP strips and follow their flexural behavior and failure modes. NSM-CFRP strips were used to strengthen three RC beam specimens, one of them was initially strengthened and tested up to failure. Four beam specimens have been initially subjected to preloading to 50% and 80% of ultimate load. Two of the specimens were either repaired or strengthened with NSM-CFRP strips. All the repaired/strengthened pre-damaged beams have been tested up to failure by using compression-testing machine. An appropriate-scale model was adopted. All the specimens have a cross-sectional dimension of 150 mm with an effective span of 110 mm. Depends on the experimental results, a better performance of the strengthened concrete specimens was obtained in both strength and serviceability. As a comparison with the control beam specimen, all the repaired specimens show a very good increase of about 40% in the load-carrying capacity and a high improvement in resistance to cracking of about 120% in NSM. On the other hand, the test results of NSM CFRP-strengthened concrete specimens with a preloading of 50% and 80% of the ultimate load show an increase of about 9% to 20% in the load-carrying capacity, for 50% and 80% pre-loading, respectively an improvement in deflection of about 2% to 27% in NSM, for 80% and 50% pre-loading, respectively.
Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor
... Show MoreThe proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
... Show MoreDue to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.
In this paper, new concepts which are called: left derivations and generalized left derivations in nearrings have been defined. Furthermore, the commutativity of the 3-prime near-ring which involves some
algebraic identities on generalized left derivation has been studied.
In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.
Let L be a commutative ring with identity and let W be a unitary left L- module. A submodule D of an L- module W is called s- closed submodule denoted by D ≤sc W, if D has no proper s- essential extension in W, that is , whenever D ≤ W such that D ≤se H≤ W, then D = H. In this paper, we study modules which satisfies the ascending chain conditions (ACC) and descending chain conditions (DCC) on this kind of submodules.
This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
In this paper we generalize some of the results due to Bell and Mason on a near-ring N admitting a derivation D , and we will show that the body of evidence on prime near-rings with derivations have the behavior of the ring. Our purpose in this work is to explore further this ring like behavior. Also, we show that under appropriate additional hypothesis a near-ring must be a commutative ring.