Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor the removal of brain sections can be addressed in the subsequent steps, resulting in an unfixed mistake during further analysis. Therefore, accurate skull stripping is necessary for neuroimaging diagnostic systems. This paper proposes a system based on deep learning and Image processing, an innovative method for converting a pre-trained model into another type of pre-trainer using pre-processing operations and the CLAHE filter as a critical phase. The global IBSR data set was used as a test and training set. For the system's efficacy, work was performed based on the principle of three dimensions and three sections of MR images and two-dimensional images, and the results were 99.9% accurate.
Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
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In the present study, composites were prepared by Hand lay-up molding. The composites constituents were epoxy resin as a matrix, 6% volume fractions of glass fibers (G.F) as reinforcement and 3%, 6% volume fractions of preparation natural material (Rice Husk Ash, Carrot Powder, and Sawdust) as filler. Studied the erosion wear behavior and coating by natural wastes (Rice Husk Ash) with epoxy resin after erosion. The results showed the non – reinforced epoxy have lower resistance erosion than natural based material composites and the specimen (Epoxy+6%glass fiber+6%RHA) has higher resistance erosion than composites reinforced with carrot powder and sawdust at 30cm , angle 60
... Show MoreThe aim of the research is to identify the effectiveness of the educational pillars strategy based on Vygotsky's theory in mathematical achievement and information processing of first-grade intermediate students. In pursuit of the research objectives, the experimental method was used, and the quasi-experimental design was used for two equivalent groups, one control group taught traditionally and the other experi-mental taught according to the educational pillars strategy. The research sample consisted of (66) female students from the first intermediate grade, who were inten-tionally chosen after ensuring their equivalence, taking into account several factors, most notably chronological age and their level of mathematics, and they we
... Show MoreCarbonate reservoirs are an essential source of hydrocarbons worldwide, and their petrophysical properties play a crucial role in hydrocarbon production. Carbonate reservoirs' most critical petrophysical properties are porosity, permeability, and water saturation. A tight reservoir refers to a reservoir with low porosity and permeability, which means it is difficult for fluids to move from one side to another. This study's primary goal is to evaluate reservoir properties and lithological identification of the SADI Formation in the Halfaya oil field. It is considered one of Iraq's most significant oilfields, 35 km south of Amarah. The Sadi formation consists of four units: A, B1, B2, and B3. Sadi A was excluded as it was not filled with h
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The aim of the research is to identify the effect of instructional design according to Kagan structure among the first intermediate school student’s, and how skills could help in generating information in mathematics. In accordance with the research objectives, the researcher has followed the experimental research method by adopting an experimental design with two equivalent groups of post-test to measure skills in generating information. Accordingly, the researcher raised two main null hypotheses: there were no statistically significant differences at the level of significance (0.05) between the average scores of the experimental group who studied the material according to Kagan structure and th
... Show MoreThe Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l
... Show MoreTime series is an important statistical method adopted in the analysis of phenomena, practices, and events in all areas during specific time periods and predict future values contribute to give a rough estimate of the status of the study, so the study aimed to adopt the ARIMA models to forecast the volume of cargo handled and achieved in four ports (Umm Qasr Port, Khor Al Zubair Port, Abu Flus Port, and Maqal Port(, Monthly data on the volume of cargo handled for the years (2006-2018) were collected (156) observations. The study found that the most efficient model is ARIMA (1,1,1).
The volume of go
... Show MoreThis research discusses the rehabilitation of heritage markets in the historical centers of Islamic Arab cities and their use in the field of cultural tourism as one of the most important tourist attractions and the subsequent revival of the national economy in addition to preserving the urban heritage as these markets part of the historical centers of cities. The research also discusses the preservation of the continuity of heritage markets as a product of cultural heritage value within an integrated framework to preserve the urban heritage in the historic centers of cities. The study then reviews a number of experiences of Arab and Islamic countries in the field of preserving and rehabilitating heritage markets, which qualify them to b
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