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Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings, water bodies, and bare lands. During 2013-2022, vegetation cover increased from 63% in 2013 to 66% in 2022; buildings roughly increased by 1% to 3% yearly; water bodies showed a decrease of 2% to 1%; the amount of unoccupied land showed a decrease from 34% to 30%. Therefore, the classification accuracy was assessed using the approach of comparison with field data; the classification accuracy was about 85%.

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Publication Date
Thu Dec 05 2024
Journal Name
Iraqi Journal Of Applied Physics
Synthesis and Characterization of Zinc Cobalt Ferrite Embedded into PAN Nanofibers for Humidity Sensing Applications
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In this work, composite materials were prepared by mixing different concentrations of ferrites with polyacrylonitrile (PAN) polymer. Using the electrospinning technique, these composites were deposited on a p-type silicon wafer. The prepared samples demonstrated nanofibers in both pure PAN polymers and their composites with ferrite. Prior to examining the humidity sensing effectiveness with a percentage of relative humidity at a frequency of 10 kHz, based on ambient temperature and a relative humidity range of 50–100%, the composite nanofibers demonstrated stronger humidity sensing compared to the pure PAN nanofibers, which demonstrated a powerful resistance response. More precisely, the PAN@ferrite nanocomposite showed a broad adsorption

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Scopus
Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
ZnO nanostructures as low concentration NO2 gas sensor and impact the temperature on sensing properties
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Zinc oxide (ZnO) nanostructures were synthesized through the hydrothermal method at various conditions growth times (6,7 and 8 hrs.) and a growth temperature (70, 90, and 100 ºC). The prepared ZnO nanostructure samples were described using scanning electron microscopy (SEM) and X-ray diffractometer to distinguish their surface morphologies and crystal structures. The ZnO samples were confirmed to have the same crystal type, with different densities and dimensions (diameter and length). The obtained ZnO nanostructures were used to manufacture gas sensors for NO2 gas detection. Sensing characteristics for the fabricated sensor to NO2 gas were examined at different operating temperatures (180, 200, 220, and 240) ºC with a low gas concentrati

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Publication Date
Tue Apr 02 2024
Journal Name
Iraqi Journal Of Applied Physics
Effect of Substrate Temperature on Characteristics and Gas Sensing Properties of Nb2O5/Si Thin Films
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Thin films of Nb2O5 have been successfully deposited using the DC reactive magnetron sputtering technique to manufacture NH3 gas sensors. These films have been annealed at a high temperature of 800°C for one hour. The assessment of the Nb2O5 thin films structural, morphological, and electrical characteristics was carried out using several methods such as X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity assessments. The XRD analysis confirms the polycrystalline composition of the Nb2O5 thin films with a hexagonal crystal structure. Furthermore, the sensitivity, response time, and recovery time of the gas sensor were evaluated for the Nb2O5 thin film

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Investigation of nanostructured and gas sensing of tin dioxide films prepared by oxidation of Sn
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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data
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This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Publication Date
Sat Jan 12 2013
Journal Name
Pierb
RADAR SENSING FEATURING BICONICAL ANTENNA AND ENHANCED DELAY AND SUM ALGORITHM FOR EARLY-STAGE BREAST CANCER DETECTION
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A biconical antenna has been developed for ultra-wideband sensing. A wide impedance bandwidth of around 115% at bandwidth 3.73-14 GHz is achieved which shows that the proposed antenna exhibits a fairly sensitive sensor for microwave medical imaging applications. The sensor and instrumentation is used together with an improved version of delay and sum image reconstruction algorithm on both fatty and glandular breast phantoms. The relatively new imaging set-up provides robust reconstruction of complex permittivity profiles especially in glandular phantoms, producing results that are well matched to the geometries and composition of the tissues. Respectively, the signal-to-clutter and the signal-to-mean ratios of the improved method are consis

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Publication Date
Fri Dec 20 2024
Journal Name
Baghdad Science Journal
Interference with quorum sensing of Klebsiella pneumoniae by some plant extracts can affect the biofilm formation and antibiotic resistance.
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Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real tim

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Self-Evaluation of Nurses and Midwives Practices Using SBAR (Situation, Background, Assessment, Recommendation) Communication Tool on Maternal Health Documentation
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Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme

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