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
... Show MoreAn analytical and clinical study has been applied for measure the bioavailability of Zinc in serum of twenty adults healthy volunteers, using flame atomic absorption spectrophotometer (FAAS) at 213.9 nm. The calibration graph is linear in the ranges of 0.25-1.5 μg.mL-1 with correlation coefficient (R) 0.09996)μg.mL1-and molar absorpitivites 22957.76(L.mol1-cm-1.The concentration of Zinc determined in serum of all volunteers before and after administered orally a tablet of 50 mg zinc sulphate, produced by Samara drugs company (SDI). All data were subjected to statistical analysis by calculating accuracy, precision in addition to other parameters. The results indicate that the average maximum concentration (C-max ± SD) of blood zinc was 0.
... Show MoreObjective: The goal of this research is to load Doxorubicin (DOX) on silver nanoparticles coupled with folic acid and test their anticancer properties against breast cancer. Methods: Chitosan-Capped silver nanoparticles (CS-AgNPs) were manufactured and loaded with folic acid as well as an anticancer drug, Doxorubicin, to form CS-AgNPs-DOX-FA conjugate. AFM, FTIR, and SEM techniques were used to characterize the samples. The produced multifunctional nano-formulation served as an intrinsic drug delivery system, allowing for effective loading and targeting of chemotherapeutics on the Breast cancer (AMJ 13) cell line. Flowcytometry was used to assess therapy efficacy by measuring apoptotic induction. Results: DOX and CS-Ag
... Show MoreAutism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson c
In this paper, some basic notions and facts in the b-modular space similar to those in the modular spaces as a type of generalization are given. For example, concepts of convergence, best approximate, uniformly convexity etc. And then, two results about relation between semi compactness and approximation are proved which are used to prove a theorem on the existence of best approximation for a semi-compact subset of b-modular space.
has experienced a step-change since the inception of ambient mass spectrometry removed the requirement for samples to be investigated under vacuum conditions. Approaches based on surface– plasma interactions are especially promising, including PADI. Whilst the mechanisms involved in generating PADI spectra still need to be unravelled, PADI shows significant promise to become a valuable and versatile tool in the instrumental arsenal available to the surface analyst
In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A
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