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: Surface treatment of machined dental zirconia for enhancement of the adhesion to resin cement, using Er,Cr:YSGG  Laser. Materials and Methods: Total number of 42 zirconia disc specimens (9 mm diameter, and 2 mm height) was sintered according to the manufacturer instruction. They are divided into six groups, each group of seven samples. Laser groups (Experiment parameters) were depend on laser total irradiation time, pulse duration, and power. Group (A): 20 sec., 60 µs pulse duration. Group (B): 30 sec., 60 µs pulse duration. Group (C): 40 sec., 60 µs pulse duration. Group (D): 20 sec., 700 µs pulse duration. Group (E): 30 sec., 700 µs pulse duration, with different powers used (1, 1

Background: The early detection of oral cancers gives the greatest chance of curing and the delay in presentation has a significant impact on the associated morbidity and mortality. The lack of general dental practitioners (GDP) knowledge in early cancer detection has been shown to contribute to delays in referral and treatment. The aim of this study was to investigate the oral cancer awareness among a group of GDP by assessing their knowledge of detection and prevention of oral cancer. Materials and methods: A questionnaire based study was designed. The questionnaire was delivered to 200 GDP assessing oral examination method, knowledge of oral cancer risk factors, clinical appearance and the most common site, point of referral and requests

Background : surface area anatomy is a proportional point to the retention of complete denture, in past there was no quantitative method to evaluate the surface area, nowadays the size and shape of maxillary arch is measured by different electronically and mathematical devices. A study was therefore, undertaken to measure surface area of upper dental cast that was taken by different final impressions. Materials and methods: twenty patients were examined. All of them had a healthy palate with no singe of injury, trauma, or deformity. Casts were taken by three different final impressions; zinc oxide, additional silicon, and poly ether. And two different devices were used; the computerized one and the Aluminum foil measure. Age, se

Breast cancer (BC) is first of the top 10 malignancies in Iraq. Dose‐volume histograms (DVHs) are most commonly used as a plan evaluation tool. This study aimed to assess DVH statistics using three‐dimensional conformal radiotherapies in BC in an adjuvant setting.

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl^-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P