Objective(s): To assess mothers’ knowledge about their children with sickle cell anemia and non-Pharmacological approaches to pain management and found some relationship between mothers knowledge and their demographic data of age, level of education, and occupation.
Methodology: A descriptive design used in the present study established was for a period from September 19th, 2020 to March 30th, 2021. The study was conducted on a non-probability (purposive) sample of (30) mother their children with sickle cell anemia was chosen. The data were analyzed through the application of descriptive and inferential statistical approaches which are applied by using SPSS version 22.0.
Results: The findings of the study indicated that moderate

  In  this  paper, we  introduced   some  fact  in   2-Banach  space. Also, we define  asymptotically  non-expansive  mappings  in  the  setting  of  2-normed  spaces analogous  to  asymptotically non-expansive mappings  in  usual  normed spaces. And then prove the existence of fixed points for this type of mappings in 2-Banach spaces.

Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

COVID-19 (Coronavirus disease-2019), commonly called Coronavirus or CoV, is a dangerous disease caused by the SARS-CoV-2 virus. It is one of the most widespread zoonotic diseases around the world, which started from one of the wet markets in Wuhan city. Its symptoms are similar to those of the common flu, including cough, fever, muscle pain, shortness of breath, and fatigue. This article suggests implementing machine learning techniques (Random Forest, Logistic Regression, Naïve Bayes, Support Vector Machine) by Python to classify a series of chest X-ray images that include viral pneumonia, COVID-19, and healthy (Not infected) cases in humans. The study includes more than 1400 images that are collected from the Kaggle platform. The expe

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

    Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification f

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

      The service system has become a necessity of life in modern cities to be the most basic necessities of modern humans, they constitute a major base, which is based on the sustainability of life in the city and a standard measured through the degree of well-being and progress of civilized peoples and their interaction with the surrounding environment, making the services sector as a need not be an option, whenever the cities widened in population and space whenever provision of services and upgrading the quality and quantity more pressing, which made the subject of the services takes the biggest area of the trends and thinking of urban planners and those who in charge of drawing the cities policies. Consideri

AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

Background: Postoperative discitis is uncommon 4%, but it is the most disabling postoperative complication after lumbar discectomy.
Objective: To assess the effectiveness of intradiscal Gentamycin in prevention of lumbar discitis post operatively.
Patients and Methods: This is a prospective study involving 320 patients, who had lumbar discectomy. 140 patients (first group) from Jan. 2012 to Jan. 2013 were not had intradiscal gentamycin injection, while 180 patients (2nd group) From Jan 2013 to Jan 2014 (2nd group) had intradiscal injection of 80mg Gentamycin at the end of surgery and before closing up. Follow up was done 10 days to 6weeks after surgery by W.B.C count, ESR, C-reactive protein and clinical assessment.
Results: The