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joe-2025
Skull Stripping Based on the Segmentation Models
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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.

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Publication Date
Sat Jun 01 2024
Journal Name
Computational Condensed Matter
Computational modeling study on the physical properties of Pd doped BaTiO3 perovskite
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This contribution investigates structural, electronic, and optical properties of cubic barium titanate (BaTiO3) perovskites using first-principles calculations of density functional theory (DFT). Generalized gradient approximations (GGA) alongside with PW91 functional have been implemented for the exchange–correlation potential. The obtained results display that BaTiO3 exhibits a band gap of 3.21 eV which agrees well with the previously experimental and theoretical literature. Interestingly, our results explore that when replacing Pd atom with Ba and Ti atoms at 0.125 content a clear decrease in the electronic band gap of 1.052 and 1.090 eV located within the visible range of electromagnetic wavelengths (EMW). Optical parameters such as a

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Factors Influence on the yield of Bacterial Cellulose of Kombucha (Khubdat Humza)
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Kombucha(Khubdat Humza) is composed of yeast and acetic acid bacteria especially, Acetobacter xylinum which forms a cellulose pellicle on tea broth. Kombucha(Khubdat Humza) produces bacterial cellulose pellicles, with unique purity and fine structure. It can be used in many forms, such as an emulsifier, stabilizer, dispersing agent, thickener and gelling agent but these are generally subsidiary to its most important use of holding on to water. Recently, bacterial cellulose is used in many special applications such as a scaffold for tissue engineering of cartilages and blood vessels, also for artificial skin for temporary covering of wounds, as well as its used in the clothing industry. The yield of cellulose produced were investiga

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Exploring the Impact of Petrophysical Uncertainties on Recoverable Reserves: A Case Study
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Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The effect of Dunn Dunn model on students’ achievement in Geography course
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The study seeks to investigate the effect of Dunn Dunn learning style model on students’ achievement. Besides, the way of developing students’ deductive thinking by testing the null hypothesis: there is no significant difference between experimental group who takes Dunn Dunn model as style in studying geography and control group that follows a traditional method in studying geography at the level of (0,05). Additionally, there is no significant difference between experimental group who takes Dunn Dunn model as style in studying geography and control group that follows a traditional method in studying geography at the level of (0,05) on testing developing deductive thinking skills. The researcher adopted a quasi-experimental posttest

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Engineering
Experimental Investigations on the Strength and Serviceability of Biaxial Hollow Concrete Slabs
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Biaxial hollow slab is a reinforced concrete slab system with a grid of internal spherical voids included to reduce the self-weight. This paper presents an experimental study of behavior of one-way prestressed concrete bubbled slabs. Twelve full-scale one-way concrete slabs of (3000mm) length with rectangular cross-sectional area of (460mm) width and (150mm) depth. Different parameters like type of specimen (solid or bubbled slabs), type of reinforcement (normal or prestress), range of PPR and diameter of plastic spheres (100 or 120mm) are considered. Due to the using of prestressing force in bubbled slabs (with ratio of plastic sphere diameter D to slab thickness H, D/H=0.67), the specimens showed an increase in ultimat

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
The Effect Of Curing Types On Compressive Strength Of High Performance Concrete
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The present investigation considers the effect of curing temperatures (30, 40, and 50˚C) and curing compound method on compressive strength development of high performance concrete, and compares the results with concrete cured at standard conditions and curing temperature (21˚C). The experimental results showed that at early ages, the rate of strength development at high curing temperature is greater than at lower curing temperature, the maximum increasing percentage in compressive strength is 10.83% at 50C˚ compared with 21C˚ in 7days curing age. However, at later ages, the strength achieved at higher curing temperature has been less, and the maximum percentage of reduction has been 5.70% at curing temperature 50C˚ compared with 21

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
The Effect of Dynamic Loading on Stresses Induced in Charnley Hip Prosthesis
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This study produces an image of theoretical and experimental case of high loading stumbling condition for hip prosthesis. Model had been studied namely Charnley. This model was modeled with finite element method by using ANSYS software, the effect of changing the design parameters (head diameter, neck length, neck ratio, stem length) on Charnley design, for stumbling case as impact load where the load reach to (8.7* body weight) for impact duration of 0.005sec.An experimental rig had been constructed to test the hip model, this rig consist of a wood box with a smooth sliding shaft where a load of 1 pound is dropped from three heights.
The strain produced by this impact is measured by using rosette strain gauge connected to Wheatstone

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Publication Date
Tue Apr 01 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
The Impact of Feature Importance on Spoofing Attack Detection in IoT Environment
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The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr

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Publication Date
Tue Jul 20 2021
Journal Name
Polymer Bulletin
Influence methods of preparation on the thermal stability of polyimide/silica dust
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Publication Date
Wed Jun 05 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Artificial Intelligence on Computational Thinking in Education at University
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This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b

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