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bsj-2401
Specific Activities of Natural Radionuclides and Annual Effective Dose Due to the Intake of Some Types of Children Powdered Milk Available in Baghdad Markets
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In this research the specific activity of natural radionuclides 226Ra, 232Th and 40K were determined by sodium iodide enhanced by thallium NaI(TI) detector and assessed the annual effective dose in Dielac 1 and 2 and Nactalia 1 and 2 for children of less than 1 year which are available in Baghdad markets. The specific activity of 40K has the greater value in all the types which is in the range of allowed levels globally that suggested by UNSCEAR. The mean value of annual effective doses were 2.92, 4.005 and 1.6325 mSv/y for 226Ra, 232Th and 40K respectively.

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Publication Date
Sun May 01 2022
Journal Name
Optical Fiber Technology
Optical fiber sensor network integrating SAC-OCDMA and cladding modified optical fiber sensors coated with nanomaterial
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Tue Oct 01 2019
Journal Name
Comparative Immunology, Microbiology And Infectious Diseases
Zataria Multiflora bois as an auspicious therapeutic approach against Echinococcus granulosus: Current status and future perspectives
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Wed Nov 27 2024
Journal Name
International Journal Of Integrated Engineering
Noise Modeling and Removal from Electrocardiogram Signals: A Study Using Wavelet Transform with Graphical User Interface
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The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)

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Publication Date
Fri Sep 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Experimental Study on Carbon Steel Corrosion and its Inhibition Using Sodium Benzoate Under Different Operating Conditions
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Corrosion experiments were carried out to investigate the effect of several operating parameters on the corrosion rate and corrosion potential of carbon steel in turbulent flow conditions in the absence and presence of sodium benzoate inhibitor using electrochemical polarization technique. These parameters were rotational velocity (0 - 1.57 m/s), temperature (30oC – 50oC), and time. The effect of these parameters on the corrosion rate and inhibition efficiency were investigated and discussed. It was found that the corrosion rate represented by limiting current increases considerably with increasing velocity and temperature and that it decreased with time due to the formation of corrosion product layer. The corrosion potential shifted t

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Producing Hydrogen Energy Using Cr2O3-TNFs Nanocomposite with Animal (Chitosan) Extract via Ultrasonic and Hydrothermal Techniques
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In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct

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Publication Date
Wed Nov 27 2024
Journal Name
International Journal Of Integrated Engineering
Noise Modeling and Removal from Electrocardiogram Signals: A Study Using Wavelet Transform with Graphical User Interface
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Publication Date
Thu Jun 01 2023
Journal Name
Measurement: Sensors
Improved airborne computer system strategy for swarm drones flying based on skybrush suite and inspired technique
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Publication Date
Fri Jan 31 2025
Journal Name
Passer Journal Of Basic And Applied Sciences
Enhanced Security Taxonomy for Fog-Enabled VANETs: A Comprehensive Survey on Attacks, Challenges, Applications and Architectures
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Vehicular Ad Hoc Networks (VANETs) are integral to Intelligent Transportation Systems (ITS), enabling real-time communication between vehicles and infrastructure to enhance traffic flow, road safety, and passenger experience. However, the open and dynamic nature of VANETs presents significant privacy and security challenges, including data eavesdropping, message manipulation, and unauthorized access. This study addresses these concerns by leveraging advancements in Fog Computing (FC), which offers lowlatency, distributed data processing near-end devices to enhance the resilience and security of VANET communications. The paper comprehensively analyzes the security frameworks for fog-enabled VANETs, introducing a novel taxonomy that c

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