Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor

BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

The study evaluates the incidence of inferior alveolar nerve injuries in mandibular fractures, the duration of their recovery, and the factors associated with them. Fifty-two patients with mandibular fractures involving the ramus, angle, and body regions were included in this study; the inferior alveolar nerve was examined for neurological deficit posttraumatically using sharp/blunt differentiation method, and during the follow-up period the progression of neural recovery was assessed. The incidence of neural injury of the inferior alveolar nerve was 42.3%, comminuted and displaced linear fractures were associated with higher incidence of inferior alveolar nerve injury and prolonged recovery time, and recovery of inferior alveolar nerve fun

Background: Zinc is involved in a variety of
metabolic processes and it has a well known
antioxidant activity, so the measurement of its serum
level can have a special value in several diseases.
Objectives: The study is designed to determine the
serum zinc level in heart failure patients and to
compare it with that of healthy individuals and to
study the significance of the results obtained.
Methods: Atomic absorption spectrometer
technique was used to determine serum zinc level in
fifty heart failure patients and fifty healthy individuals
who were age and sex matched.
Results: The mean serum zinc level in healthy
individuals was about 45.5% greater than that of heart
failure patients. This diffe

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m