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

Background: Controversy exists concerning the presence and amount of the Bennett mandibular immediate side shift among patients and whether it is necessary to accommodate for it in adjustable articulators. The aim of this study was to register and calculate the amount of any immediate side shift (ISS) present in patients requiring full mouth rehabilitation. Materials and methods: 3- dimensional condylar movements of 50 Iraqi TMD-free patients were recorded using a stereographic fully adjustable articulator system during protrusion, left and right eccentric mandibular movements. Protrusive angles of each patient were verified to figure out the suitable fossa analog for each case. The thickness of each right and left premade fossa analog sele

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

Purpose:  The research aims to explore the impact Business Intelligence System (BIS) and Knowledge Conversion Processes (KCP) in the Building Learning Organization (LO) in KOREK Telecom Company in Baghdad city.

Design/methodology/approach: in order to achieve the objectives of the research has been the development of a questionnaire prepared for this purpose and then has tested the search in the telecommunications sector, representatives of one of the telecommunications companies in Baghdad city, has therefore chosen KOREK Telecom company as a sample for research, and the choice was based on the best standard international companies to serve mobile communications in terms o

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

This Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.

In this paper, the method of estimating the variation of Zenith Path Delay (ZPD) estimation method will be illustrate and evaluate using Real Time Kinematic Differential Global Positioning System (RTK-DGPS). The GPS provides a relative method to remotely sense atmospheric water vapor in any weather condition. The GPS signal delay in the atmosphere can be expressed as ZPD. In order to evaluate the results, four points had been chosen in the university of Baghdad campus to be rover ones, with a fixed Base point. For each rover position a 155 day of coordinates measurements was collected to overcome the results. Many models and mathematic calculations were used to extract the ZPD using the Matlab environment. The result shows that the ZPD valu

This paper deals with constructing mixed probability distribution from mixing exponential