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
The research starts from a fundamental problem about how top management team can realize the uncertainty. Strategic conversation has been introduced as a way for top management team to deal with uncertainties. Within the current research model, the strategic conversation was considered as an independent variable and uncertainty as dependent variable. The researcher used the survey method by distributed a questionnaire in the Administration and Economics College, University of Baghdad. Samples are 40 faculty participant of scientific committee members were distributed in seven scientific departments. The data were statistically analyzed by mean and the standard deviation. The hypotheses were tested through the use of correlation and regressi
... Show MoreSingle long spiral tube column pressure swing adsorption (PSA) unit, 25 mm diameter, and 6 m length was constructed to study the separation of water from ethanol at azeotropic concentration of 95 wt%. The first three meters of the column length acted as a vaporizer and the remaining length acted as an adsorber filled by commercial 3A zeolite. The effect of pressure, temperature and feed flow rate on the product ethanol purity, process recovery and productivity were studied. The results showed that ethanol purity increased with temperature and pressure and decreased with feed flow rate. The purity decreased with increasing productivity. The purity range was 98.9 % to 99.6 %, the recovery range was 0.82 to 0.92 and the productivity range w
... Show MoreThe current study, performed during the period from February 2021 to June 2022 at the University of Thi- Qar/ College of Education for Pure Sciences, and aimed to follow the changes in external morphological features at different Embryonic developmental stages in pregnant rats treated with different doses of amlodipine. Usage In this study, 18 pregnant rats were randomly divided into three groups, each with six pregnant rats. Each group received different concentrations of amlodipine (0.3, 0.5) in oral doses until the 20th day of gestation, while the control group was injected with 0.9% normal saline. Teratomas are bizarre tumors derived from embryonic tissue that are normally found only in the gonadal and sacral regions of adults. Primary
... Show MoreThin films of microcrystalline and nanocrystalline -silicon carbide and silicon, where deposited on glass substrate with substrate temperature ranging from 350-400C, with deposition rate 0.5nm per pulse, by laser induced chemical vapor deposition. The deposition induced by TEACO2 laser. The reactant gases (SiH4 and C2H4) photo decompose throughout collision associated multiple photon dissociate. Such inhomogeneous film structure containing crystalline silicon, silicon carbide and amorphous silicon carbide matrix, give rise to a new type of material nanocrystalline silicon carbide in which the optical transmittance is governed by amorphous SiC phase while nanocrystalline grain are responsible for the conduction processes. This new m
... Show MoreHydrogen fuel is a good alternative to fossil fuels. It can be produced using a clean energy without contaminated emissions. This work is concerned with experimental study on hydrogen production via solar energy. Photovoltaic module is used to convert solar radiation to electrical energy. The electrical energy is used for electrolysis of water into hydrogen and oxygen by using alkaline water electrolyzer with stainless steel electrodes. A MATLAB computer program is developed to solve a four-parameter-model and predict the characteristics of PV module under Baghdad climate conditions. The hydrogen production system is tested at different NaOH mass concentration of (50,100, 200, 300) gram. The maximum hydrogen produc
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For desulfurization of naphtha, NaY zeolite was prepared from Dewekhala kaolin clay (Al-Anbar region). For the prepared zeolite adsorbent, x-ray diffraction, sodium content, silica to alumina ratio, surface area, bulk density and crushing strength were determined. From the x-ray diffraction of the prepared NaY zeolite and by a comparison with the standard NaY zeolite, it was found that the prepared adsorbent in this work has approximately the same crystal structure as the standard. Adsorption process was done in a laboratory unit at 25
... Show MoreThis investigation was carried out to study the treatment and recycling of wastewater in the Battery industry for an effluent containing lead ion. The reuse of such effluent can only be made possible by appropriate treatment method such as electro coagulation.
The electrochemical process, which uses a cell comprised aluminum electrode as anode and stainless steel electrode as cathode was applied to simulated wastewater containing lead ion in concentration 30 – 120 mg/l, at different operational conditions such as current density 0.4-1.2 mA/cm2, pH 6 -10 , and time 10 - 180 minute.
The results showed that the best operating conditions for complete lead removal (100%) at maximum concentration 120 mg/l was found to be 1.2 mA/cm2 cur
In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca
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