The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

      A simple and highly sensitive cloud point extraction process was suggested for preconcentration of micrograms amount of isoxsuprine hydrochloride (ISX) in pure and pharmaceutical samples. After diazotization coupling of ISX with diazotized sulfadimidine in alkaline medium, the azo-dye product quantitatively extracted into the Triton X-114 rich phase, dissolved in ethanol and determined spectrophotometrically at 490 nm. The suggested reaction was studied with and without extraction and simple comparison between the batch and CPE methods was achieved. Analytical variables including concentrations of reagent, Triton X-114 and base, incubated temperature, and time were carefully studied. Under the selected opti

      A simple and highly sensitive cloud point extraction process was suggested for preconcentration of micrograms amount of isoxsuprine hydrochloride (ISX) in pure and pharmaceutical samples. After diazotization coupling of ISX with diazotized sulfadimidine in alkaline medium, the azo-dye product quantitatively extracted into the Triton X-114 rich phase, dissolved in ethanol and determined spectrophotometrically at 490 nm. The suggested reaction was studied with and without extraction and simple comparison between the batch and CPE methods was achieved. Analytical variables including concentrations of reagent, Triton X-114 and base, incubated temperature, and time were carefully studied. Under the selected optimum conditions,

Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

The cross section evaluation for (α,n) reaction was calculated according to the available International Atomic Energy Agency (IAEA) and other experimental published data . These cross section are the most recent data , while the well known international libraries like ENDF , JENDL , JEFF , etc. We considered an energy range from threshold to 25 M eV in interval (1 MeV). The average weighted cross sections for all available experimental and theoretical(JENDL) data and for all the considered isotopes was calculated . The cross section of the element is then calculated according to the cross sections of the isotopes of that element taking into account their abundance . A mathematical representative equation for each of the element

At the local level in the early 1990s first established an Islamic bank 1993 is called Iraqi Islamic bank and was established by Dr. abdullatef hmim and with capital of 200 Million Iraqi dinars .

After 2003 began the attention of Iraqis tend to create Islamic banks until now up to 30 banks in the present ,  He confirmed Mr. Governor of the Iraqi Central Bank recently that there is more than 40 iintroduction licence to establish an Islamic bank in Iraq , That banking activity which is compatible with Sharia law widely welcomed by savers and those in need for more development and modernization in order to gain a greater share within the Iraqi market , and allowed the Iraqi Central Bank in recent years

In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class