Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The aerodynamic characteristics of general three-dimensional rectangular wings are considered using non-linear interaction between two-dimensional viscous-inviscid panel method and vortex ring method. The potential flow of a two-dimensional airfoil by the pioneering Hess & Smith method was used with viscous laminar, transition and turbulent boundary layer to solve flow about complex configuration of airfoils including stalling effect. Viterna method was used to extend the aerodynamic characteristics of the specified airfoil to high angles of attacks. A modified vortex ring method was used to find the circulation values along span wise direction of the wing and then interacted with sectional circulation obtained by Kutta-Joukowsky theorem of

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

This study focuses on diagnosis of Candida species causing Vulvovaginal Candidiasis using phenotype and genotype analyzing methods, and frequencies of candida species also using Vulvovaginal Candidiasis patients. 130 samples (100 from patients and 30 from non infected women) were collected and cultured on biological media. Identifying the yeasts, initially some phenotypic experiments were carried out such as germ tube, from motion of pseudohyphae and clamydospores in CMA+TW80 medium, API20 candida and CHROMagar Candida. Genomic DNA of all species were extracted and analyzed with PCR and subsequent Polymerase Chain Reaction - Restriction Fragments Length Polymorphism (PCR-RFLP) methods. Frequency of C. albicans, C. krusei, C. tropicalis , C.

 A simple,  sensitive, accurate and low cost effective spectrophotometric method has been developed for the determination of Tetracycline and Doxycycline in pure and pharmaceutical formulations. The method is based on the reaction of methyldopa with 4-aminoantipyren (4-AAP) in presence of potassium ferriecyanide (PFC) in an alkaline medium. Two optimization methods were applied to determine the optimum conditions of oxidizing coupling reaction variables; univariate and design of experiment (DOE) method. The conditions effecting the  reaction; pH, buffer Volume,   reagent concentration, oxidant concentration, type of buffer, order of addition, time of reaction and stability were optimized . Under univariate and design

      In this study, simple, low cost, precise and speed spectrophotometric methods development for evaluation of sulfacetamide sodium are described. The primary approach contains conversion of sulfacetamide sodium to diazonium salt followed by a reaction with p-cresol as a reagent in the alkaline media.  The colored product has an orange colour with absorbance at λmax 450 nm. At the concentration range of (5.0-100 µg.mL^-1), the Beer̆ s Low is obeyed with correlation coefficient (R²= 0.9996), limit of detection as 0.2142 µg.mL^-1, limit of quantification as 0.707 µg.mL^-1 and molar absorptivity as 1488.249 L.mol^-1.cm^-1. The other approach, cloud point extraction w

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet