The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi

Background: The grading systems of salivary mucoepidermoid carcinoma depend on different histologic and morphologic features. The aim of this study was to compare between Auclair and Brandwein systems according to their histologic criteria, and the type of cell predominant. Materials and Methods: Twenty-one case included hematoxylin-eosin (H&E) stained tissue slides that were diagnosed as MEC, originally categorized into low and high grade type regardless of the grading system, have meticulously undergone histopathologic review. The sample was graded according to criteria owing to Auclair and Brandwein methods. The predominant type of cells was determined by microscopic examination according to grade of tumor. Results: Regarding the

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

The research aims to identify the effect of using the strategy of Roundhouse on the achievement of fourth-grade students of computer and their Attitudes towards it. The research sample consisted of (61) fourth-grade secondary school students distributed into the experimental group consisted of (31) students study computer according to the Roundhouse strategy, and the control group consisted of (30) students follow the traditional method. The researcher designed an achievement test consisting of (30) items of multiple choice. To measure the attitudes of students towards the computer, a questionnaire of (32) paragraphs with three alternatives was designed by the researcher. The results showed that there is a statistically significant diffe

Sewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.

 In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage