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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
Thu Aug 31 2023
Journal Name
Iraqi Geological Journal
Mineral Inversion Approach to Improve Ahdeb Oil Field's Mineral Classification
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Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

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Publication Date
Sun Jun 30 2013
Journal Name
Al-khwarizmi Engineering Journal
Estimated Outlet Temperatures in Shell-and-Tube Heat Exchanger Using Artificial Neural Network Approach Based on Practical Data
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The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

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Publication Date
Wed Sep 30 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Adoption of the IFRS11 Financial Reporting Standard for Oil Service Contracts Costs and its Reflection on Measurement and Disclosure for National Oil Companies: بحث تطبيق في شركة نفط ميسان (ش . ع)
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The research seeks to clarify the problems related to the aspects of the financial and accounting process resulting from entering into contractual arrangements with a period of more than 20 years, among which is the research problem represented by the lack of clarity of the foundations and procedures for the recognition of oil costs and additional costs borne by foreign invested companies, which led to a weakening of their credibility and reflection. Negatively "on the measurement and accounting disclosure of financial reports prepared by oil companies, and the research aims to lay down sound procedures for measuring and classifying oil costs and additional costs paid to foreign companies, and recognizing and recording them in th

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Publication Date
Wed Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
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Publication Date
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Science,
Monitoring Vegetation Growth of Spectrally Landsat Satellite Imagery ETM+ 7 & TM 5 for Western Region of Iraq by Using Remote Sensing Techniques.
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Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. In this paper the two sensors are used to monitoring the agriculture condition and detection the changing in the area of plant covers, the stability and calibration of the ETM+ has been monitored extensively since launch although it is not monitored for many years, TM now has a similar system in place to monitor stability and calibration. By referring to statistical values for the classification process, the results indicated that the state of vegetation in 1990 was in the proportion of 42.8%, while this percentage rose to 52.5% for the same study area in

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Analysis the Causal Relationship between Oil Exports and Economic Growth in Iraq
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The oil exports play a vital role in supporting economic development and raise the economic growth. The oil exports can increase the economic growth via three main channels which are supporting the productive, distributive and service sectors; increasing the investment and capital formation; and increasing the employment rate.

However, the oil exports did not have an important role in increasing the economic growth in Iraq. Therefore, it also did not provide the required support to other economic sectors, neither participated in increase the employees’ skills nor increase the investment rate. It may slightly contribute in enhancement the infrastructure that can attract the public and private investments

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The importance of foreign direct investment in stimulating non-oil exports Of Iraq According to the Turkish experience
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Foreign trade is very important in global economies because of its impact on the sustainability of economic growth by stimulating economic activity, creating jobs and expanding production . On the other side , this policy is a major obstacle to many developing countries and the reason is due to the nature of the economies of those countries because they rely mostly on one or a few economic resources, which makes them rely mostly on exports to that resource while they import most of the needs of their  local market Which makes them in a spiral of underdevelopment ,  dependence and economic exposure, which requires them to break that cycle and the launch of economic development Perhaps one of the most important means to a

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding Techniques for Dynamic Encryption Text based on Corner Point
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Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

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