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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
Wed Apr 01 2015
Journal Name
Journal Of Engineering
Software Implementation of Binary BCH Decoder Using Microcontroller
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In this paper a decoder of binary BCH code is implemented using a PIC microcontroller for code length n=127 bits with multiple error correction capability, the results are presented for correcting errors up to 13 errors. The Berkelam-Massey decoding algorithm was chosen for its efficiency. The microcontroller PIC18f45k22 was chosen for the implementation and programmed using assembly language to achieve highest performance. This makes the BCH decoder implementable as a low cost module that can be used as a part of larger systems. The performance evaluation is presented in terms of total number of instructions and the bit rate.

 

 

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Publication Date
Sun Aug 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL ANALYSIS OF PATIENTS INFECTED WITHCORONAVIRUS USING MANOVA
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Statistics has an important role in studying the characteristics of diverse societies. By using statistical methods, the researcher can make appropriate decisions to reject or accept statistical hypotheses. In this paper, the statistical analysis of the data of variables related to patients infected with the Coronavirus was conducted through the method of multivariate analysis of variance (MANOVA) and the statement of the effect of these variables.

Publication Date
Fri Feb 28 2020
Journal Name
Iraqi Journal Of Agricultural Sciences (ijas)
PHYTOTOXICITY TEST OF KEROSENE-CONTAMINATED SOIL USING BARLEY
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This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c

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Publication Date
Sun Mar 30 2025
Journal Name
Iraqi Journal Of Science
Segmentation of Aerial Images Using Different Clustering Techniques
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The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Compression of an ECG Signal Using Mixed Transforms
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Electrocardiogram (ECG) is an important physiological signal for cardiac disease diagnosis. With the increasing use of modern electrocardiogram monitoring devices that generate vast amount of data requiring huge storage capacity. In order to decrease storage costs or make ECG signals suitable and ready for transmission through common communication channels, the ECG data
volume must be reduced. So an effective data compression method is required. This paper presents an efficient technique for the compression of ECG signals. In this technique, different transforms have been used to compress the ECG signals. At first, a 1-D ECG data was segmented and aligned to a 2-D data array, then 2-D mixed transform was implemented to compress the

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Publication Date
Sat Dec 01 2018
Journal Name
Al-nahrain Journal Of Science
Image Classification Using Bag of Visual Words (BoVW)
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In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

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Publication Date
Fri Jan 01 2021
Journal Name
Macromolecular Characterization Of Hydrocarbons For Sustainable Future
Feasibility of the Gas and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) Process to Enhance the Recovery of Oil in Reservoirs with Strong Aquifer
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Gas and Downhole Water Sink, Gravity Drainage, GDWS-AGD, Enhance the Recovery of Oil

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Publication Date
Thu Mar 02 2023
Journal Name
East European Journal Of Physics
Evaluation of the Influence of Body Mass Index and Signal-to-Noise Ratio on the PET/CT Image Quality in Iraqi Patients with Liver Cancer
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Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviat

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Publication Date
Tue Dec 02 2025
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of thermocycling and debonding time on the shear bond strength of different orthodontic brackets bonded with light-emitting diode adhesive (In vitro study)
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Background: Thermocycling simulates the temperature dynamics in the oral environment. This in vitro study done to measure and compare the effect of thermocycling on the shear bond strength of stainless steel and sapphire brackets bonded to human enamel teeth using light cured orthodontic adhesive and debonded at various time, and to measure adhesive remnant index after debonding. Materials and Methods: one-hundred-twenty extracted upper first premolars for orthodontic reason were used in this study; depending on weather thermocycled or not, the sample was divided into two main groups, then within each group 30 teeth were used for stainless-steel brackets (Bionic®) and for sapphire brackets (Pure®). Both groups were subdivided into three

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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Investigating the impact of non-nutritive sweeteners on the antifungal potential of alcoholic and aqueous Eucalyptus extracts against salivary candida albicans (An in-vitro study)
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Background: Eucalyptus extracts and derivatives are natural substances with potent antimicrobial properties. This study investigated the in- vitro effects of non-nutritive sweeteners on the antifungal activity of alcoholic and aqueous Eucalyptus extracts against Candida albicans, a common oral pathogen. Materials and Method: Ten isolates of Candida albicans were isolated from dental students’ salivary samples. The alcoholic and aqueous extracts were prepared from fresh Eucalyptus leaves using maceration. The sensitivity of Candida albicans isolates to various concentrations of Eucalyptus extracts ranging from 50 to 250 (mg/mL) was evaluated via agar well diffusion method, while the agar streaking method  was used to assess the minimum

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