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.
The existing investigation explains the consequence of irradiation of violet laser on the structure properties of MawsoniteCu6Fe2SnS8 [CFTS] thin films. The film was equipped by the utilization of semi-computerized spray pyrolysis technique (SCSPT), it is the first time that this technique is used in the preparation and irradiation using a laser. when the received films were processed by continuous red laser (700 nm) with power (>1000mW) for different laser irradiation time using different number of times a laser scan (0, 6, 9, 12, 15 and 18 times) with total irradiation time (0,30,45,60,75,90 min) respectively at room temperature.. The XRD diffraction gave polycrysta
... Show Moresix specimens of the Hg0.5Pb0.5Ba2Ca2Cu3-y
The research aims to clarify the effect of evidence in interpreting verses and what are their forms related to interpretation, which every interpreter must be familiar with, along with the necessity of knowing the sciences with which the interpreter is armed in order for the true meaning and intended meaning of the Qur’anic verses to emerge. The determinants of the clues and the extent of their relationship to the Qur’anic text were also explained, and the levels of their impact in directing the meaning were identified in terms of strength, verification, clarity, generality and
God Almighty put in his great book secrets that do not end, and wonders that do not expire, for he is the one from which the scholars are not satisfied, and he does not create due to the multitude of response, and it is the comprehensive and inhibitory book that God conceals to the worlds, and he challenged the two heavyweights to come up with something like it.
At all times, issues arise in the Noble Qur’an that fit the needs of the people of that time and their culture, for it is an eternal book, characterized by the ability to give, extend and respond to addressing the problems of the age and its variables, when the Arabs had little luck at the time of the message’s descent from the scientific culture, and their proficienc
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreA survey of fish species in the Iraqi marine waters was carried out for the period from November 2014 to March 2018. The list included 214 species representing 75 families.
The family Carangidae dominated the marine fishes in Iraq, which was represented by 24 species, followed by Haemulidae with 11 species, and then Serranidae and Sparidae with nine species for each, while 34 families contained a single species only.
Parasitological examination of gills of three species of sparid fishes in the territorial waters of Iraq was performed, two diplectanid monogenoids were isolated and described; Lamellodiscus indicus Tripathi, 1959 from both Haffara seabream Rhabdosargus haffara (Forsskål, 1775) and Goldline seabream R. sarba (Forsskål, 1775) and Protolamellodiscus senilobatus Kritsky, Jiménez-Ruiz and Sey, 2000 from King soldierbream Argyrops spinifer (Forsskål, 1775). The record of the parasites is considered new to the parasite fauna of Iraq. The redescription of L. indicus for the first time which is collected from a new distribution area (Arabian Gulf). R. haffara is considered a new host record .
Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some
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