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.
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
... Show MoreThe subject of demand on oil derivative has occupied an important position at present time in the daily life context. The fuel of benzene and gas oil and kerosene is one of basic elements of that concern, and on local , regional and international levels. The oil derivatives have played a leading role in determining the course and nature of development since early 1970 to the present time whether in the productive Arab countries or the importing. The researcher set out from the hypothesis that the increase of the local consumer demand on some of the oil derivatives is because of the internal and external factors accompanied by the inability of the productive capability and local production to confront this increase, and the resort
... Show MoreFace recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
... Show MoreLandsat-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
... Show MoreMany oil and gas processes, including oil recovery, oil transportation, and petroleum processing, are negatively impacted by the precipitation and deposition of asphaltene. Screening methods for determining the stability of asphaltenes in crude oil have been developed due to the high cost of remediating asphaltene deposition in crude oil production and processing. The colloidal instability index, the Asphaltene-resin ratio, the De Boer plot, and the modified colloidal instability index were used to predict the stability of asphaltene in crude oil in this study. The screening approaches were investigated in detail, as done for the experimental results obtained from them. The factors regulating the asphaltene precipitation are different fr
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
... Show MoreThe 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
... Show MoreThe 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
... Show MoreForeign 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
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
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