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 condense study was done to compare between the ordinary estimators. In particular the maximum likelihood estimator and the robust estimator, to estimate the parameters of the mixed model of order one, namely ARMA(1,1) model.

Simulation study was done for a varieties the model.  using: small, moderate and large sample sizes, were some new results were obtained. MAPE was used as a statistical criterion for comparison.

Seasonal variations of the species composition and abundance of Cladocera were studied in two stations at the end of the Tigris River and one station at the confluence of the Tigris with Euphrates area, at the beginning of the Shatt Al-Arab River in Al-Qurnah North of Basrah Province, from October 2015 to August 2016. Samples of zooplankton were collected by plankton net 100-µm. mesh size. The population density of Cladocera ranged between 1 Ind /m³ during summer and 211 Ind./m³ during winter at station 1 (Al-Jewaber Bridge). A total of 16 species of Cladocera belonging to 12 genera were recorded in the study. The average density of Cladocera ranged from 23.2 ind./m³ at Station 2 (Hamayon Bridge) to 53.7 Ind./m³

Abstract              
          Agricultural investment is one of the main requirements in most economies of the world for its importance in the development of the agricultural sector through the agricultural and technological infrastructure and agricultural research, as well as its impact on most economic, social and service activities, especially if managed and employed scientifically, which generates income and productive capacities and services and new commodities, Unemployed as agricultural investments in Iraq fell significantly after 2003 due to economic, political, social

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

This research is a modest effort to talk about the great world of ancient lineage, Imam Majd al-Din Abu Saadat, known as Ibn al-Atheer island, through the statement of his name, surname, nickname, family, elders and his pupils and his most important works.
It also deals with the modern research on his famous book in the field of modern science called (the end in the strange talk and impact), which is one of the most wonderful books of modern and especially the strange talk, through the scientific effort of the Imam and the importance of the book and methodology, and the most prominent aspects of the service and care of Ibn Al Atheer For the modern stranger, which boils down to two aspects:
First: the linguistic rooting of the stran

Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used