AA Abbass, HL Hussein, WA Shukur, J Kaabi, R Tornai, Webology, 2022 Individual’s eye recognition is an important issue in applications such as security systems, credit card control and guilty identification. Using video images cause to destroy the limitation of fixed images and to be able to receive users’ image under any condition as well as doing the eye recognition. There are some challenges in these systems; changes of individual gestures, changes of light, face coverage, low quality of video images and changes of personal characteristics in each frame. There is a need for two phases in order to do the eye recognition using images; revelation and eye recognition which will use in the security systems to identify the persons. The main aim of this paper is innovation in eye recognition phase. In this paper, a new and fast method is proposed for human eye recognition that can quickly specify the human eye location in an input image. In the proposed method, eyes will be specified in an input image with a CNN neural network. This proposed method is tested on different images and provided highest accuracy for the image recognition which used in security systems.
This research includes a study of the ability of Iraqi porcelanite rocks powder to remove the basic Safranine dye from its aqueous process by adsorption. The experiments were carried out at 298Kelvin in order to determine the effect of the starting concentration for Safranin dye, mixing time, pH, and the effect of ionic Strength. The good conditions were perfect for safranine dye adsorption was performed when0.0200g from that adsorbed particles and the removal max percentage was found be 96.86% at 9 mg/L , 20 minutes adsorption time and at PH=8 and in 298 K. The isothermal equilibrum stoichiometric adsorption confirmed, the process data were examined by Langmuir, Freundlich and Temkin adsorption equations at different temperatures
... Show MoreIn this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained
Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer
... Show MoreAn investigation was conducted for the study of extraction of metal ions using aqueous biphasic systems. The extraction of iron, zinc and copper from aqueous sulphate media at different kinds of extractants SCN− , Cl- and I- , different values of pH of the feed solution, phase ratio, concentration of metals, concentration of extractant, concentration of polymer, and concentration of salt was investigated. Atomic absorption spectrophotometer was used to measure the concentration of iron, zinc and copper in the aqueous phase throughout the experiments. The results of the extraction experiments showed the use of SCN− as extractant, pH=2.5, phase ratio=1.5, concentration of metals 1g/l, concentration of extractant 0.06 %, concentration o
... Show MoreRecently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using a key-based randomly generated permutation, concatenate the permuted blocks forming a permuted binary sequence, and then utilize a plane-based Least-Significant-Bit (LSB) approach to embed the permuted binary sequence into BMP image file format. The performance of algorithm was given a preliminary evaluation through estimating the PSNR (Peak Signal-to-Noise Ratio) of the stego image for limited number of experiments comprised hiding
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The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca
A study to find the optimum separators pressures of separation stations has been performed. Stage separation of oil and gas is accomplished with a series of separators operating at sequentially reduced pressures. Liquid is discharged from a higher-pressure separator into the lower-pressure separator. The set of working separator pressures that yields maximum recovery of liquid hydrocarbon from the well fluid is the optimum set of pressures, which is the target of this work.
A computer model is used to find the optimum separator pressures. The model employs the Peng-Robinson equation of state (Peng and Robinson 1976) for volatile oil. The application of t
The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non
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