Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
The subject of the strategic vision is of great importance to all companies because they live in an environment of rapid change in various areas of life. Supports the performance of its operations in a better way, towards appropriate strategic growth and achieving success. The research aims to determine the level of interest of the researched company in the research variables (strategic vision and growth strategy), and the importance of the research came in being an attempt to provide the theoretical and scientific foundations for the research variables (strategic vision and growth strategy). As for the research method, it was relied on the descriptive analytical method, relying on the questionnaire as a means of obtaining data from the
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The various countries seek to encourage their local investments through the various policies they follow. The most important of these is the monetary policy, which is a means and procedures taken by the monetary authority to control the supply of money and maintain its stability of its financial impact on economic activity.
The effect of monetary policy is to stimulate domestic investment through money supply that is inversely related to the interest rate and a direct relationship with domestic investment. When money supply increases, interest rates fall and local investment growth rates rise, but when the rise in money supply is high, Inflationary measure
Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreGeneral Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
... Show MoreRegarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
... Show MoreThe local asphalt concrete fracture properties represented by the fracture energy, J-integral, and stress intensity factor are calculated from the results of the three point bending beam test made for pre notches beams specimens with deformation rate of 1.27 mm/min. The results revealed that the stress intensity factor has increased by more than 40% when decreasing the testing temperature 10˚C and increasing the notch depth from 5 to 30mm. The change of asphalt type and content have a limited effect of less than 6%.
This study aims to reach the right of governorates that are not organized in a region to impose local legislation, including tax legislation, and the extent of the constitutionality of this legislation and its consistency with constitutional texts and legal rules. The imposition of local taxes finds its constitutional and legal basis in the Iraqi constitution for the year 2005 and the law of governorates not organized in a region.The imposition of local taxes corresponds to the principle of tax legality, which is reflected in the necessity of issuing tax laws from a competent authority, whether this authority is federal, regional or local. Rather, it is sufficient that it be competent