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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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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 management at international airports. The implementation of this method has shown superior performance to previous methods in terms of reducing errors, delays and associated costs

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
The effect of titanium oxide microparticles on mechanical properties, absorption and solubility processes of a glass ionomer cement
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Glass Ionomer Cement (GIC) is one of the important dental temporary filing materials. The aim of this study is to evaluate the effect of adding 3, 5 and 7 wt. % of TiO2 microparticles to conventional GIC powder (Riva Self Cure) on mechanical properties and its effect on absorption and solubility processes. TiO2 particles additives improved compressive strength and biaxial flexural strength, where the compressive strength increased with increasing in the added ratio, while the highest value of the biaxial flexural strength was at 3 wt.%. The addition of TiO2 particles improved the surface Vickers microhardness values, with highest value at 5 wt. %. On other hand TiO2 addition im

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Genetic Algorithm to Estimate the Parameters of the Gumbel Distribution Function by Simulation
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In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

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Publication Date
Wed Dec 01 2021
Journal Name
Ain Shams Engineering Journal
Improving the rutting resistance of asphalt pavement modified with the carbon nanotubes additive
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Publication Date
Tue Jan 01 2019
Journal Name
Inorganica Chimica Acta
Synthesis, characterisation and electrochemistry of eight Fe coordination compounds containing substituted 2-(1-(4-R-phenyl-1H-1,2,3-triazol-4-yl)pyridine ligands, R = CH3, OCH3, COOH, F, Cl, CN, H and CF3.
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Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
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Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm for Improving the Quantity and Quality of the Detected Complexes from Protein Interaction Networks
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One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
The effect of temperature and density of different host spam in efficiency and performance life of the intruder
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Studied competence spam to malicious moth figs at temperatures and Kagafat host different results showed that female intruder, despite their ability to shell larvae host and when densities of different, but it is able to lay eggs at a temperature of 14 + or -1 and finally urged the efficiency spam to malicious affected heavily host and that the greater the intensity of the host spam increased efficiency and its performance life

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Publication Date
Wed Apr 02 2025
Journal Name
Journal Of Electrochemical Science And Engineering
Improving the corrosion behaviour of Zn-Ni alloy coatings on 316 SS from chloride-sulfate bath by addition of triethanolamine or sucrose
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Corrosion of Zn-Ni alloy coatings on stainless steel 316 SS in a chloride-sulfate bath with the addition of either triethanolamine or sucrose was examined. A constant cathode potential was used to deposit zinc-nickel alloys, while cyclic voltammetry and potentio-dynamic polarization were used to measure corrosion. In addition, scanning electron microscopy was utilized to analyse Zn-Ni alloy coating surface layers formed with¬out and with additives. The outcomes discovered that the corrosion resistance of Zn-Ni alloy coat¬ings in 3.5 % NaCl solution was highly influenced by adding triethanolamine or sucrose. Decreasing the Zn:Ni molar ratio led to an increase in corrosion resistance. All Zn-Ni alloy coatings were superior to pure Z

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Publication Date
Tue Nov 18 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Quantitative detection and correlation of Epstein - Barr Virus in plasma with gingivitis and severity of chronic periodontitis by using real-time polymerase chain reaction technique
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Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

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