Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

Background: Angiogenesis is defined as the formation of new blood vessels. However, angiogenesis in cancer will lead to tumour growth and metastasis. Therefore, anti-angiogenesis is one of the ways to slow down growth and spreading of tumour. Moringa oleifera is also known as a “Miracle tree” which has high nutritive value and various therapeutics effect in different parts of the plant. This study aims to determine the anti-angiogenic property of Moringa oleifera leaves extract by using chick chorioallantoic membrane (CAM) assay. Materials and Methods: The extracts were prepared by decoction method using methanol and water. The qualitative phytochemical screening was carried out for

            Atorvastatin (ATR) is poorly soluble anti-hyperlipidemic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS) with low bioavailability due to its low solubility. Solid dispersions adsorbate is an effective technique for enhancing the solubility and dissolution of poorly soluble drugs.

          The present study aims to enhance the solubility and dissolution rate of ATR using solid dispersion adsorption technique in comparison with ordinary solid dispersion. polyethylene glycol 4000 (PEG 4000), polyethylene glycol 6000 (PEG 6000), Poloxamer188 and Poloxam

In this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Bovine milk is one of the richest nutrients that contain minerals and vitamins that enhance immunity, especially in children, but because many children do not want to drink the raw milk, therefore this study aimed to enhance the sensory characteristics of raw milk by using hibiscus plant extract, which is characterized by red color and distinctive flavor as well as studying the effect of aqueous extract of Hibiscus sabdariffa on inhibiting the growth of microorganisms, by using three concentrations of the aqueous extract (0.5, 1.0 and 1.5%), where the statistical results showed a significant difference (P≤0.05) between the concentrations in color, texture and general acceptance, and the best results appeared when using