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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
Tue Oct 20 2020
Journal Name
International Journal Of Civil Engineering
Structural Performance Under Monotonic Static Loading of Reinforced Concrete Gable Roof Beams with Multiple Web Openings
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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Education Program on Secondary School Teachers Psycho-Social Changes with Menopause in Baghdad City
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Objective: To assess the effect of education program on psychological and social changes of secondary school teachers with menopause.

Method: A quasi-experimental design is carried out with the application of a pre- post –test for menopause secondary school teacher's bio-psychosocial changes. Non-probability sample consists of (60 female teachers) (40) teachers from Al- Rusafa first Education Directorate secondary schools, and (20) teachers from Al- Karkh third Education Directorate secondary schools. The sample was exposed to pretest, educational program, and posttest. Data were collected through the utilization of the study instrument (the questionnaire) and application of bio-psychosocial ed

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Publication Date
Thu Jun 15 2023
Journal Name
Bionatura
Copper-to-Zinc Ratio as an Inflammatory Marker in Serum of Iraqi Patients with Axial Spondyloarthritis
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Axial spondyloarthritis (axSpA) is a chronic rheumatic inflammatory disease affecting mainly the spine and sacroiliac joints. Since the copper-to-zinc ratio (Cu/Zn) indicates an inflammatory response, the change in ratio is expected to correlate with axSpA. This study compared levels of Cu/Zn in the serum of axSpA patients. Serum samples were obtained from 53 patients with axSpA divided according to biological treatment into cohorts A and B, and 28 healthy control as cohort C. Serum levels of Cu and Zn were determined first by a fully automated chemistry analyzer TC-Matrix Plus, then the ratio was obtained. The elevated serum Cu concentration means of cohort B (189.32 ± 13.808 µg/dL) compared to cohort A (168.85 ± 7.244 µg/dL) a

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Publication Date
Sun Mar 01 2026
Journal Name
Journal Of Pharmaceutical Sciences
Mechanistic insights into drug loading effect on dissolution performance of Loratadine–Soluplus® amorphous solid dispersions
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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Environmental Study of Epiphytic Algae on Ceratophyllum demersum in Tigris River within Baghdad City, Iraq
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The present study was conducted in the Tigris River within Baghdad (University of Baghdad campus). The study included some physicochemical parameters and qualitative of epiphytic algae on the host plant (Ceratophyllum demersum) during summer season 2013. The results revealed that the study area was alkaline, hard and oxygenated water. A total of 105 taxa of epiphytic algae was identified. Bacillariophyceae diatoms composed 44.7% of the total and were represented by 42.4% of the order Pennales and 1.9 %of the order Centrales. Chlorophyceae composed 32.3%, followed by Cyanophyceae composed 22.8 % of the total. The total number of epiphytic algae was fluctuated among the study period. Most of the identified algae were benthos type and a few

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Publication Date
Mon Apr 22 2024
Journal Name
2024 21st International Multi-conference On Systems, Signals & Devices (ssd)
Digital Twin-Based Decision-Making Technique for Diagnostic 2D Environment Line Following Error of Mobile Robot
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Publication Date
Fri Jan 31 2020
Journal Name
Iraqi Geological Journal
ESTIMATION OF SHEAR WAVE VELOCITY FROM WIRELINE LOGS DATA FOR AMARA OILFIELD, MISHRIF FORMATION, SOUTHERN IRAQ
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Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Engineering
Efficient Energy Management for a Proposed Integrated Internet of Things-Electric Smart Meter (2IOT-ESM) System
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In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurement

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

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Publication Date
Sat Aug 31 2024
Journal Name
Folia Medica
Dental plaque caries related microorganism in relation to demographic factors among a group of Iraqi children
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Introduction: Streptococcus mutans and lactobacilli are most important bacteria in the pathogenesis of dental caries. Cariogenic microflora has been associated to the primary caregiver transmission and sugary diets.

Aim: This study aimed to relate S. mutans and lactobacilli in the plaque to demographic factors in Iraqi children.

Materials and methods: The study included 135 children aged 3-10 years. Samples of their dental plaque were taken from the upper second primary molars on the buccal surfaces using a clean toothpick. Each sample was stored in 1 ml of n

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