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

Education is considered the corner stone of all nations development. It is the principal way for the development of human sources and the most achievements of the age due to the knowledge of these resources .                                           

   As its active role which accounting departments implement in Iraq universities , (public and private) through their teaching programs , they aim to supply labour-market with qualified cadre graduated as accountants auditors , tax auditors , financial analysts , ac

The research has been talked on specific an important notions concerning with the dimensions of effectiveness of good governance and sustainable development inside all Arab states, So that the scientific article reflected the role of investments in various sections of institutional business by draw attention toward different projects about analyzing the whole political reality according to the standard indications of political and social stability on the regional level and international aspects. Therefore, the study resembled scientific contains and the dimensions of political reform and administrative overhauling within governmental system in order to achieve all raw objectives for sustainable development. All international and

The main aim of this study is to investigate the ability of four local entomopathogenic isolates Beauveria bassiana (Bals.) and Metarhizium anisopliae (Met.) to control the mosquito larvae in the lab. The results revealed that the isolate (MARD48) B .bassiana reduced the survival rate of the mosquito larvae to (80%) followed by the isolate M. anisopliae (MARD10) to (90%) in the first two days of treatment, and 60 and 66% respectively in the third day. The results also showed that the isolate B. bassiana (MARD48) killed 50% of the population (LC50) with the concentration 1×104 conidia/ml compared to 1×107 conidia/ml for the isolates B. bassiana (MARD14) and M. anisopliae (MARD10), and 1×108 conidia/ml for the isolate B .bassiana (MARD76).

The study was carried out during the 2022 agricultural season in the greenhouses belonging to the-College of Agricultural-Al-Ramadi, the study aimed to investigate the efficacy of alcoholic extract of Solanum eleaegnifolium, potassium silicate and ungicide Previcur Energy in normal and nano formula to control downy mildew disease on cucumber crops caused by the fungus Pseudoperonospora cubensis. The results showed that the normal potassium silicate treatment completely prevented the disease during the length of the season, with an infection severity rate of 0.00%, compared to infection with artificial contamination of 45.90%, followed by the treatment of nano fungicide 4.60%. While the treatments of alcoholic extract and nano of nightshade

The research tried to show the importance of  Administrative Control being one of the important means in administrative work; they work on the review and audit work done and error handling explored in the work and prevent the occurrence and ascertain the extent of implementation of the planned targets, and therefore this is reflected in raising the efficiency of the performance of the tax examiner and complete the work as soon as possible and the highest efficiency and reduce the gaps that may occur between the parties of the tax settling accounts and dealt with in the theoretical side of the search to the research problem, namely with whether operating management oversight to improve the performance and increase the efficiency of t

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe