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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A neutron induced deuteron emission spectra and double differential cross-sections (DDX), in 27Al (n, D) 26Mg, 51V (n, D)50Ti , 54Fe ( n, D)53Mn and 63Cu (n, D) 62Ni reactions, have been investigated using the phenomenological approach model of Kalbach. The pre-equilibrium stage of the compound nucleus formation is considered the main pivot in the discription of cross-section, while the equilibrium (pick up or knock out ) process is analyzed in the framework of the statistical theory of cluster reactions, Feshbach, Kerman, and Koonin (FKK) model. To constrain the applicable parameterization as much as possible and to assess the predictive power of these models, the calculated results have been compared with the experimental data and othe
... Show MoreThe aim of the research is to reveal the reality of teacher performance evaluation in the Sultanate of Oman in light of some global models. The study followed a qualitative descriptive research design. Seven forms of teacher formative and summative assessments were analyzed. Besides, an analytical template was developed, consisting of six areas related to the teaching performance of teachers. These included: lesson planning and preparation, learning environment, education, professional development, student academic, and community and parental partnership. The study reached a number of results; the most notable is the lack of change of forms for more than a decade despite the rapid development of the educational system in the sultanate in
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This study deals with segmenting the industrial market as an independent variable and targeting the industrial market as a dependent variable. Since the industrial sector represents one of the most important fundamental pillars to build the economies of countries and their development , the Iraqi industrial sector was chosen as a population for the study . Based on measuring the study variables , identifying them and testing the correlation and effect on each other , the study reached a group of findings:
1- Increasing the level of availability of study variables inside the companies “The study sample”.
2- There is a correlation between the independent v
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In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.
The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the
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ABSTRUCT
In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error ( λ ) in the model (SPSEM), estimated the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac
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Regression analysis models are adopted by using SPSS program to predict the 28-day compressive strength as dependent variable and the accelerated compressive strength as independent variable. Three accelerated curing method was adopted, warm water (35ºC) and autogenous according to ASTM C C684-99 and the British method (55ºC) according to BS1881: Part 112:1983. The experimental concrete mix design was according to ACI 211.1. Twenty eight concrete mixes with slump rang (25-50) mm and (75-100)mm for rounded and crushed coarse aggregate with cement content (585, 512, 455, 410, 372 and 341)Kg/m3.
The experimental results showed that the acc
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