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Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification, including ResNet50, VGG19, and InceptionV4; They were trained and tested on an open-source satellite image dataset to analyze the algorithms' efficiency and performance and correlated the classification accuracy, precisions, recall, and f1-score. The result shows that InceptionV4 gives the best classification accuracy of 97% for cloudy, desert, green areas, and water, followed by VGG19 with approximately 96% and ResNet50 with 93%. The findings proved that the InceptionV4 algorithm is suitable for classifying oil spills and no spill with satellite images on a validated dataset.

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Publication Date
Wed Mar 18 2020
Journal Name
International Journal Of Research In Social Sciences And Humanities
THE EFFECT OF USING THE SCHOOL THEATER ON LEARNING SOME SKILLS OF THE GROUND MOVEMENT MAT GYMNASTIC ART FIFTH GRADE PRIMARY
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
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Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Rehabilitation of Reinforced Concrete Deep Beam by Epoxy Resin
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This investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be

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Publication Date
Thu Jun 10 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Study on the effect of diesel engine oil contaminated with fuel on engine performance
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An experiment was conducted to study how SAE 50 engine oil contaminated with diesel fuel affects engine performance. The engine oil was contaminated with diesel fuel at concentrations of 0%, 1%, and 3%. The following performance characteristics were studied: brake-specific fuel consumption, brake thermal efficiency, friction power, and exhaust gas temperature. Each treatment was tested three times. The three treatments (0%, 1%, and 3%) were analyzed statistically with a one-way ANOVA model at the 5% probability level to determine if the three treatments produced significant differences in engine performance. The statistical results showed that there were significant differences in engine performance metrics among the three treatments. The 3

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS
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The problem of rapid population growth is one of the main problems effecting countries of the world the reason for this the growth in different environment areas of life commercial, industrial, social, food and educational. Therefore, this study was conducted on the amount of potable water consumed using two models of the two satellite and aerial images of the Kadhimiya District-block 427 and Al-Shu,laa district-block 450 in Baghdad city for available years in the Secretariat of Baghdad (2005, 2011,2013,2015). Through the characteristics of geographic information systems, which revealed the spatial patterns of urban creep by determining the role and buildings to be created, which appear in the picture for the

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Publication Date
Thu Apr 06 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Impact of a Scenario-Based Learning Model in Mathematics Achievement and Mental Motivation for High School Students
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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Study the Effect of Solar Radiation Pressure at Several Satellite Orbits
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The effects of solar radiation pressure at several satellite (near Earth orbit satellite, low Earth orbit satellite, medium Earth orbit satellite and high Earth orbit satellite ) have been investigated. Computer simulation of the equation of motion with perturbations using step-by-step integration (Cowell's method) designed by matlab a 7.4 where using Jacobian matrix method to increase the accuracy of result.

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Attacking Jacobian Problem Using Resultant Theory
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     This paper introduces a relation between resultant and the Jacobian determinant
by generalizing Sakkalis theorem from two polynomials in two variables to the case of (n) polynomials in (n) variables. This leads us to study the results of the type:  ,            and use this relation to attack the Jacobian problem. The last section shows our contribution to proving the conjecture.

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Publication Date
Fri Jan 02 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Evaluation of en-masse retraction using microimplant versus conventional techniques: An in vitro study
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Background: The study aimed to investigate the effect of different techniques of en masse retraction on the vertical and sagittal position, axial inclination, rate of space closure, and type of movement of maxillary central incisor. Materials and methods: A typodont simulation system was used (CL II division 2 malocclusion). Three groups were used group 1(N=10, T-loop), group 2(N=10, Time-Saving loop), and group 3(N=10, Microimplant). Photographs were taken before and after retraction and measurements were made using Autodesk AutoCAD© software 2010. Kruskal-Wallis one-way analyses of variance and Mann-Whitney U test (p?0.05) were used. Results: The rate of space closure showed no significant difference among the three groups (p?0.05), whi

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Publication Date
Tue Feb 27 2018
Journal Name
Iraqi Journal Of Laser
Investigation of Densified SiO2 Sol-Gel Thin Films Using Conventional and DPSS Laser Techniques
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The prepared nanostructure SiO2 thin films were densified by two techniques (conventional and Diode Pumped Solid State Laser (DPSS) (532 nm). X-ray diffraction (XRD), Field Emission Scanning electron microscopy (FESEM), and Atomic Force Microscope (AFM) technique were used to analyze the samples. XRD results showed that the structure of SiO2 thin films was amorphous for both Oven and Laser densification. FESEM and AFM images revealed that the shape of nano silica is spherical and the particle size is in nano range. The small particle size of SiO2 thin film densified by DPSS Laser was (26 nm) , while the smallest particle size of SiO2 thin film densified by Oven was (111 nm).

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