Fusarium wilt causes economic losses on tomatoes every year. Thus, a variety of chemicals have been used to combat the disease. Pesticides have been effective in managing the disease, but they keep damaging the environment. Recently, eco-friendly approaches have been used to control plant diseases. This study aimed to achieve an environmentally safe solution using biological agents to induce systemic resistance in tomato plants to control Fusarium wilt disease caused by Fusarium oxysporum f.sp. lycopersici (FOL) in the greenhouse. The pathogen (FOL) has been molecularly confirmed and the biological agents have been isolated from the Iraqi environment. The effectiveness of the biological agents has been tested and confirmed. Results showed t

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The purpose of this research is to identify the effect of the use of project-based learning in the development of intensive reading skills at middle school students. The experimental design was chosen from one group to suit the nature of the research and its objectives. The research group consisted of 35 students. For the purpose of the research, the following materials and tools were prepared: (List of intensive reading skills, intensive reading skills test, teacher's guide, student book). The results of the study showed that there were statistically significant differences at (0.05) in favor of the post-test performance of intensive reading skills. The statistical analysis also showed that the project-based learning approach has a high

Gamma - irradiation effect on polymethylmethacrylate (PMMA) samples has been studied using Positron Annihilation Lifetime (PAL) method. The orthopositronium (o-Ps) lifetime τ₃, hence the o-ps parameters, the volume hole size (V_h) and the free volume fraction (Ꞙ_h) in the irradiated samples were measured as a function of gamma-irradiation dose up to 28.05 kGy. It has been shown that τ ₃, V_h, and Ꞙ_h, are increasing in general with increasing gamma-dose, to reach a maximum percentage increment of 22.42% in τ₃, 60% in V_h and 29.5% in Ꞙ_h, at. 2.55 kGy, whereas τ₂ reaches maximum increment of 119. 7% at 7.65 kGy. The results s

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For