An experimental investigation based on thirty three simple pullout cylinder specimens was conducted to study the bond-slip trend between concrete and steel reinforcement. Plain and deformed steel reinforcement bars were used in this investigation. The effect of bar diameter, concrete compressive strength and development length on bond-slip relation was detected. The results showed that the bond strength increases with increasing of compressive strength and with decreasing of bar diameter and development length. A nonlinear regression analysis for the experimental results yields in a mathematical correlation to predict the bond strength as a function of concrete compressive strength, reinforcing bar diameter and its yield stress. The minimum

This research deals with one scene from the movie Romeo and Juliet, which is the balcony scene, due to the importance of this scene in the formation of the construction of the subsequent events of the movie.

The first chapter contained the methodological framework of the research, where the research problem was identified in how Zeffirelli dealt with the balcony scene in the play Romeo and Juliet and enriched it in the cinematic language with a comparison with the original text of the scene. In the balcony scene with comparative parts between the film and the text and the limits of the research that was limited to the film Zeffirelli and the translated text by Munis Taha Hussein.

The second chapter contained the theoretic

Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

The test considers from important methods and tools when we using the evaluation because it is a basic role in diagnosis & classification & motive & selection &guiding &prediction and the problem was formatted in some questions like ( what is physical variables that tall players needs n the game and effect on the game ? what is the tests that measures these variables also the defense rebound variable and is there a references standard specialized in that ?) , the aims of research represented by knowing to some physical abilities for tall players in basketball school and their tests and putting new tests to measure defense rebound to one player and tow tall players also limiting the standards degrees ( modified un following method ) to resul

Background: This study aimed to find whether there is a relation between the mesio-distal crown diameters of the deciduous second molars and the permanent first molars in an Iraqi sample from Baghdad city. Material and methods: The sample consisted of 54 Iraqi children aged 8-9 years at the mixed dentition stage. The measurements included the mesio-distal crown width of the deciduous second molars and the permanent first molars on the study casts using digital sliding vernier. Results: The results revealed absence of the side difference of the widths of teeth measured. High significant gender difference was detected for the permanent first molars and the deciduous second molars except mandibular permanent first molar. On the other hand, hig

The research aims at identifying The Effect of Woods model in the Acquisition of Grammatical Concepts on students at the Sixth Primary. The total number of students is (49) male and female. students are distributed in two groups . The First group is the experimental group which is taught the( Woods Model) and it is (25) students . The second group is the control group which is taught according to the traditional method of teaching and it is (24) students . The researcher has matched between the two groups by the following variables : the age (in months), their intelligence, their parents, academic level of education . The research has constructed multiple choice test of (20) items . The reliability of The test has been calculated and it

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Numerous research studies have been conducted on why some learners acquire a second language more easily and quickly than others. Most of these studies have demonstrated that acquiring a second language does not depend only on learners’ cognitive ability or professional teaching strategies. The learning language process is more complicated than that. It is affected by crucial factors that are beyond the control of learners and teachers. These factors are known as sociolinguistic factors. These factors include culture, age, motivation, socio-economic status, and gender. This research paper mainly concentrates on the role of motivation in second language acquisition.

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t