The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope

Background: Oncogenesis in the oral cavity is widely believed to result from cumulative genetic alterations that cause a transformation of the mucosa from normal to dysplastic to invasive carcinoma. The p16 gene produces p16 protein, which in turn inhibits phosphorylation of retinoblastoma (Rb), p16 play a significant role in early carcinogenesis. A number of epidermal growth factor receptor (EGFR) family, HER2/neu, has received much attention because of its therapeutic implications. The aims of the study were to evaluate and compare the immunohistochemical expression of the cell cycle protein P16 INK4a and c-erbB2 (HER2/neu) in NOM, OED, and OSCC. Correlate both marker expression with each other as well as with various clinicopathological

Background: In Iraqi communities, the workers considered the largest population groups, so increasing their dental education by increasing the care for their dental health knowledge and behavior is very important, the present study was aimed to evaluate the gingival health and oral hygiene in relation to knowledge and behavior among a group of a workers selected randomly from Al Fedaa company in Baghdad city. Materials and methods: A sample of 110 workers (65 men and 45 women) included in this study, a questionnaire used to evaluate their oral health knowledge and behavior. The gingival health condition of the workers was examined by using Loe and Silness index (1963), Silness and Loe index (1964) was used to asses plaque quantity, and Ramf

Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

Background: Breast lump is one of the most common prevalent complaint of patients attending breast clinics.

Objective: To determine if there is any change in the pattern of common breast, diseases presenting as breast lumps between pregnant and non-pregnant women among patients attending Al-Elwiya Breast Clinic.

Methods: This is a cross – sectional study, with convent's patient sampling setting in AL-Elwiya Breast Cancer Early Detection Clinic from 1^st Feb. to 1^st May 2018, we collected data from patients with breast lumps including the age groups, pregnancy status, parity status, previous breast diseases, hormonal drugs, menstrual cycle, breast fe

Abstract

      Objective (s): To evaluate reasons for partial compliance and non-compliance to the

                              routine childhood vaccination schedule in Al-Karkh district 

Methodology: Descriptive study , using the evaluation approach, is carried throughout the present study to determine the reasons for the Routine Childhood Vaccination at  health care sectors and primary health care centers at  Al-Karkh District in Baghdad City, Convenient, non-probability, sample of (90) mother who are recruited from health care sectors at Al-Karkh District in Baghdad City. All mothers, who ha

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne