Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, coronal plane, and sagittal plane. Three different thresholds, which are based on texture features: mean, energy and entropy, are obtained automatically. This allowed to accurately separating the MRI slice into normal and abnormal one. However, the abnormality detection contained some normal blocks assigned wrongly as abnormal and vice versa. This problem is surmounted by applying the fine-tuning mechanism. Finally, the MRI slice abnormality detection is achieved by selecting the abnormal slices along its tumour region (Region of Interest-ROI).
النظام السياسي اليمني : دراسة في المتغيرات الداخلية
This study aims to study argumentation in political debates by figuring out the logical fallacies employed in the debates of Clinton and Trump, the presidential nominees of the 2016 elections, and Biden and Trump, the leading contenders in the 2020 United States presidential election. The study attempts to answer the questions: (1) What relevance fallacies are adopted in the debate between Trump and Clinton? (2) What rhetorical devices are used to influence the audience and gain voters besides fallacies in the debates selected? The study analyses two texts from two arguments using Damer's (2009) taxonomy of relevance fallacy and rhetorical devices based on Perrine’s (1969) model of communication and interpersonal rhetoric to answe
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Polycystic ovary syndrome (PCOS) is a significant cause of infertility due to ovulation dysfunction in women of childbearing age. Although the pathogenesis of PCOS is still not clear, many studies have shown that many factors within the ovary promote infection. With this syndrome, the disruption of the natural monthly ovulation process causes an imbalance in the body's hormones, and the high level of insulin in the body and the blood sugar imbalance leads to the occurrence of hyperandrogenism, which is the main factor for the occurrence of pathogens, in addition to genetic factors, if any. This study aims to identify this disease and its most important causes, symptoms, and modern treatments to prevent and get rid of it. Polycystic
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.
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This study examines the structural performance of concrete-encased pultruded Glass Fiber Reinforced Polymer (GFRP) I-sections with shear connections. It specifically focuses on how different parameters affect the latter’s ductility, flexural strength, and load-carrying capacity. The key variables studied include various shear connector types, spacing, and geometries, as well as the compressive strength of concrete and the properties of GFRP. The finite element modeling and experimental validation show that the shear connectors significantly improve the ductility, ultimate capacity, and load transmission efficiency. The present review emphasizes that the shear connectors greatly enhance the structural performance when they are prop
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In this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
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The increasing requirement and use of dental implant treatments has rendered dental implantology indispensable in dentistry. The aim of this study is to determine the optimum concentration of calcium silicate to be incorporated into a polyetherketoneketone (PEKK) matrix used as an implant material to enhance the bioactivity and mechanical properties of the composite compared with unmodified PEKK. In this study, different weight percentage (wt%) of micro-calcium silicate (m-CS) is incorporated into PEKK with ethanol as a binder. Subsequently, the mixture is dried in a forced convection oven at 120°C and poured into customized molds to fabricate a bioactive composite via compression molding (310°C, 15 MPa, and 20 min holding time
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