Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

The Bangestan reservoir, which occurs in the Ahwaz oilfield, consists of the middle Cretaceous limestone Ilam and Sarvak Formations that were deposited in the Zagros Basin. The reservoir is divided into ten Zones (A to J) formed in the upper Albian-Santonian and contains considerable hydrocarbon accumulations. The limestones were deposited on an extensive shallow carbonate platform on a passive margin and are dominated by rudist biostrome and grainstone facies. Paleogeographical changes mean that identification of the facies is complex. Seismic stratigraphy and isotopic data are used to better understand the structural and geological setting and develop an understanding of the sedimentary environment. The results show that the rudist biostr

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

This study aimed to discover the reality of the teacher's maintainced of order and classroom management from the perspective of teachers themselves.

A social survey with an introduce sample that consist (180) male and female teachers from the provinces of Ajloun and Jerash in 2008-2009. To achieve the objective of the study was developed for this purpose and the results have shown the existence of statistically significant differences in marinating order and the management of class and in favor of females, the results also showed Statistically significant differences regarding the academic qualification and for the benefit of holders of master degrees and more compared to those with bachelor's degree.

Abstract

The purpose of our study was to develop Dabigatran Etexilate loaded nanostructured lipid carriers (DE-NLCs) using Glyceryl monostearate and Oleic acid as lipid matrix, and to estimate the potential of the developed delivery system to improve oral absorption of low bioavailability drug, different Oleic acid ratios effect on particle size, zeta potential, entrapment efficiency and loading capacity were studied, the optimized DE-NLCs shows a particle size within the nanorange, the zeta potential (ZP) was 33.81±0.73mV with drug entrapment efficiency (EE%) of  92.42±2.31% and a loading capacity (DL%) of 7.69±0.17%. about 92% of drug was released in 24hr in a controlled manner, the ex-vivo intestinal p