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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
Tue Jul 30 2024
Journal Name
Iraqi Journal Of Science
A Survey on Image Caption Generation in Various Languages
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      The image caption is the process of adding an explicit, coherent description to the contents of the image. This is done by using the latest deep learning techniques, which include computer vision and natural language processing, to understand the contents of the image and give it an appropriate caption. Multiple datasets suitable for many applications have been proposed. The biggest challenge for researchers with natural language processing is that the datasets are incompatible with all languages. The researchers worked on translating the most famous English data sets with Google Translate to understand the content of the images in their mother tongue. In this paper, the proposed review aims to enhance the understanding o

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Sentiment Analysis on Roman Urdu Students’ Feedback Using Enhanced Word Embedding Technique
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Students’ feedback is crucial for educational institutions to assess the performance of their teachers, most opinions are expressed in their native language, especially for people in south Asian regions. In Pakistan, people use Roman Urdu to express their reviews, and this applied in the education domain where students used Roman Urdu to express their feedback. It is very time-consuming and labor-intensive process to handle qualitative opinions manually. Additionally, it can be difficult to determine sentence semantics in a text that is written in a colloquial style like Roman Urdu. This study proposes an enhanced word embedding technique and investigates the neural word Embedding (Word2Vec and Glove) to determine which perfo

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Hiding the Type of Skin Texture in Mice based on Fuzzy Clustering Technique
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A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. T

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Publication Date
Tue May 28 2019
Journal Name
Al-khwarizmi Engineering Journal
Treatment of Waste Extract Lubricating Oil by Catalytic Cracking Process to Produce Light Fractions
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The catalytic cracking of three feeds of extract lubricating oil, that produced as a by-product from the process of furfural extraction of lubricating oil base stock in AL-Dura refinery at different operating condition, were carried out at a fixed bed laboratory reactor. The initial boiling point for these feeds was 140 ºC for sample (1), 86 ºC for sample (2) and 80 ºC for sample (3). The catalytic cracking processes were carried out at temperature range 325-400 ºC and initially at atmospheric pressure after 30 minutes over 9.88 % HY-zeolite catalyst load. The comparison between the conversion at different operating conditions of catalytic cracking processes indicates that a high yield was obtained at 375°C, according to gasoline pr

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Publication Date
Tue Mar 31 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Extraction of Aromatic Hydrocarbons from Lube Oil Using Different Co-Solvent
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An investigation was conducted effect of addition co- solvent on solvent extraction process for two types of a lubricating oil fraction (spindle) and (SAE-30) obtained from vacuum distillation unit of lube oil plant of Daura Refinery. In this study two types of co-solvents ( formamide and N-methyl, 2, pyrrolidone) were blended with furfural to extract aromatic hydrocarbons which are the undesirable materials in raw lubricating oil, in order to improve the viscosity index, viscosity and yield of produced lubricating oil. The studied operating condition are extraction temperature range from 70 to 110 °C for formamide and 80 to 120 °C for N-methyl, 2, pyrrolidone, solvent to oil ratio range from 1:1 to 2:1 (wt./wt.) for furfural with form

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Evaluating the Distance Learning Experience in light of the Spread of the Corona Pandemic - Covid 19 from the Teachers' Point of View in Islamic Science Institutes in the Sultanate of Oman
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The study aimed to evaluate the distance learning experience in light of the spread of the Corona pandemic - Covid19 - from the teachers' point of view in Islamic Science Institutes in the Sultanate of Oman, which was applied during the second semester of the 2019/2020 academic year. The study sample consisted of (77) teachers from The Islamic Science Institutes of The Sultan Qaboos Higher Center for Culture and Science. The researchers prepared a questionnaire to evaluate the reality of the experience. The study results  revealed, the followings: The Department of Educational Affairs and Training at The Sultan Qaboos Higher Center for Culture and Science was able to a moderate degree in the rapid transition to a distance learning s

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics
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The research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Comparing the Effects of Lavender Oil and Olive Oil Massage on Pain due to Muscular Cramp during Hemodialysis
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Background: Pain due to muscular cramp during hemodialysis is one of the most common problems experienced by patient undergoing hemodialysis, and is associated with poor outcomes of patients. The main aim of this study was to comparing the effects of lavender oil and olive oil massage on Pain due to muscular cramp during hemodialysis.

Methods: In this random clinical trial, 60 hemodialysis patients were enrolled randomly and allocated to two groups with 30 members in Lordegan and Brojen hospitals, Shahrekord, Iran. The intervention included flora massage on the lower leg muscles so that the first group received olive oil massage (10 drops) and the second group received lavender oil massage (10 dr

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Approximate Solution of Delay Differential Equations Using the Collocation Method Based on Bernstien Polynomials???? ???????? ????????? ????????? ????????? ???????? ?????????? ???????? ??? ??????? ???? ?????????
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In this paper a modified approach have been used to find the approximate solution of ordinary delay differential equations with constant delay using the collocation method based on Bernstien polynomials.

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

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