Preferred Language
Articles
/
9BdPS5ABVTCNdQwCG4XI
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
...Show More Authors

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Scopus Crossref
Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Detection of Genetic Modified Feed Component
...Show More Authors

There are growing concerns over the possibility of transfer genetically modified sequences from genetically modified feed component (GM feed) to animals and their products, moreover, affect these sequences on animal and human health. This study was implemented to detect P35S in modified feed by using PCR technique by detecting presence P35S promoter, which responsible for the regulation of gene expression for most of the transgenic genes. Thirty eight feed samples were collected from different sources of Baghdad markets, which have been used for feeding livestock, comprise 21 coarse mixes feed, 13 pelleted feed, and 4 expanded feed. Genomic DNA was extracted by using two methods, CTAB method and Wizard kit. In order to verify the presenc

... Show More
View Publication Preview PDF
Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
...Show More Authors

      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

... Show More
View Publication Preview PDF
Scopus (7)
Crossref (6)
Scopus Crossref
Publication Date
Wed Mar 27 2019
Journal Name
Iraqi Journal Of Science
Gravity and Magnetic Interpretation to Study Deep Crustal Structures In Karbala and Surrounding Areas-Central Iraq
...Show More Authors

Gravity and magnetic data were used to study the deep crustal structures in Karbala and surrounding areas in central Iraq. The space window method was used to separate the residual from regional anomalies of gravity and magnetic data, the spaces of window are equal to 48,36 and 24 km. The Total Horizontal Derivative (THD) techniques and local wavenumber of gravity and magnetic are used to identify the faults and their trends with the basement rocks.  The N45W, N45E, N-S and rarely E-W trends of faults are detected in the basement rock. It is believed that some of these faults extending from the basement to the uppermost layer of the sedimentary rocks.

View Publication Preview PDF
Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
...Show More Authors

This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Facies Architecture And Depositional Marine Systems of the Yamama Formation in Selected Wells, Southern Iraq
...Show More Authors

      The Yamama Formation is characterized by a wide geographic extension of southern Iraq. Microfacies analysis of this formation was studied in six wells distributed in six fields: Fayhaa, Sindbad, Siba, Zubair, Ratawi and West Qurna. This research aims to determine paleoenvironments by diagnosing biofacies and lithofacies. Miscellaneous marine fauna of foraminifera and calcareous algae, mainly green algae (dasycladacean.) and skeletal bioclasts from gastropods, pelecypods, bryozoans, sponge spicules, and echinoderms were found. Petrographic studies and well logs interpretations led to the identification of five main Microfacies ( Mudstone, Wackestone, Packestone, Grainestone and Rudstone and twelve submicrofacies (Foraminiferal-

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref
Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Material Recognition of Foreign Object Debris using Deep Learning
...Show More Authors

     Foreign Object Debris (FOD) is defined as one of the major problems in the airline maintenance industry, reducing the levels of safety. A foreign object which may result in causing serious damage to an airplane, including engine problems and personal safety risks. Therefore, it is critical to detect FOD in place to guarantee the safety of airplanes flying. FOD detection systems in the past lacked an effective method for automatic material recognition as well as high speed and accuracy in detecting materials. This paper proposes the FOD model using a variety of feature extraction approaches like Gray-level Co-occurrence Matrix (GLCM) and Linear Discriminant Analysis (LDA) to extract features and Deep Learning (DL) for classifi

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
...Show More Authors
Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
View Publication
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
...Show More Authors

View Publication
Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Based on Deep Learning: An Overview
...Show More Authors

      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

... Show More
View Publication Preview PDF
Scopus (4)
Scopus Crossref
Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Satellite Image Classification using Spectral Signature and Deep Learning
...Show More Authors

    When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref