This research is carried out to investigate the behavior of self-compacting concrete (SCC) two-way slabs with central square opening under uniformly distributed loads. The experimental part of this research is based on casting and testing six SCC simply supported square slabs having the same dimentions and reinforcement. One of these slabs was cast without opening as a control slab. While, the other five slabs having opening ratios (O_R) of 2.78%, 6.25%, 11.11%, 17.36% and 25.00%. From the experimental results it is found that the maximum percentage decrease in cracking and ultimate uniform loads were 31.82% and 12.17% compared to control slab for opening ratios (O_R

A modified Leslie-Gower predator-prey model with fear effect and nonlinear harvesting is developed and investigated in this study. The predator is supposed to feed on the prey using Holling type-II functional response. The goal is to see how fear of predation and presence of harvesting affect the model's dynamics. The system's positivity and boundlessness are demonstrated. All conceivable equilibria's existence and stability requirements are established. All sorts of local bifurcation occurrence conditions are presented. Extensive numerical simulations of the proposed model are shown in form of Phase portraits and direction fields. That is to guarantee the correctness of the theoretical results of the dynamic behavior of the system and t

This paper demonstrates the construction designing analysis and control strategies for fully tracking concentrated solar thermal by using programmable logic control in the city of Erbil-Iraq. This work used the parabolic dish as a concentrated solar thermal. At the focal point, the collected form of energy is used for heating a (water) in the receiver, analyzing this prototype in real-time with two different shapes of the receiver and comparing the results. For tracking the parabolic dish, four light-dependent resistors are used to detect the sun's position in the sky so that the tracking system follows it to make the beam radiation perpendicular to the collector surface all of the time during the day for maximum solar p

In recent years it has spread the used of e-commerce sites quite dramatically. Thus, these sites have become display huge number of diverse products. It became difficulty for the customer to choose what he/she wants from this product. The recommender systems are used to help customers to finding the desired product of their interests and proved to be an important solution to information overload problem.
This paper, designed a recommendation system based on content, which is usually textual description. Furthermore, the proposed system uses cosine similarity function to find the similarities among the characteristics of various products, and nominate a suitable product closer to customer satisfaction. The experimental result shows tha

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

The administration on the basis of the activities designed to evaluate the performance of activities in terms of cost, time and quality by identifying activities that add value and those that are no add value and  enables the administration of making up their own continuous improvement in production, through lower costs and reduce the time and improve the quality   and reduce the incidence of spoilage and waste, y based search Ally premise that (the continuous improvement of the adoption of management style on the basis of the activities helps management in decision-making wise to reduce  costs) to prove the hypothesis has sought research to achieve its goal of  Alkadivh and Alkoppelan     &nb

Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.