The present work included qualitative study of epiphytic algae on dead and living stems, leaves of the aquatic plant Phragmitesaustralis Trin ex Stand, in Tigris River in AL- Jadria Site in Baghdad during Autumn 2014, Winter 2015, Spring 2015, and Summer 2015. The physical and chemical parameters of River’s water were studied (water temperature, pH, electric conductivity, Salinity, TSS, TDS, turbidity, light intensity, dissolve oxygen, BOD5, alkalinity, total hardness, calcium, magnesium and plant nutrient). A total of 142 isolates of epiphytic algae were identified. Diatoms were dominant by 117 isolates followed by Cyanobacteria (13isolates), Chlorophyta (11 isolates) and Rhodophyta (1 isolate), Variations in the isolates number were rec

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

The research is exposed to an important issue, related to communication obstacles that prevent the media message contained in cultural topics published in local newspapers to reach the hands of the readers; or related to lack of awareness of aspects of that media message, Because it contains immersed vocabulary in elitism where, sometime, the average reader of the newspaper of medium-sized educated, and even the academic reader are unable to decode it and understand its significance.

After determining the problem of the study and the tools that the researcher wants to use to accomplish his research, a sample of students of college of Arts at the University of Baghdad was selected. As they are clo

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

Background: Oral health represents an important base for human well-being; the heath of the body begins from oral cavity. Great deal has been applied to increase knowledge in the field of oral health in order to develop appropriate preventive program. This study was conducted in order to estimate the percentage and severity of dental caries and gingivitis among children attending Preventive Department in Collage of Dentistry, University of Baghdad and to determine dental treatment need for those patients, further more to study the relation of these variables with dental knowledge. Materials and Methods: The study group consists of 163 children with an age ranged from 6 to 14 years, who attended the preventive clinic for the first time to be

Abstract

In light of the great technological development and the emergence of globalization has increased global competition, where it became competitive exercise pressure on all sectors. In light of this companies mast enviorment depend on the means that keeps them on the competitive position through access to information about competitors in order to help them to draw a strategy that will achieve a competitive edge either through excellence or reduce the costs of their products and this means intelligence competitive and reverse engineering that help to gain information on competitors analyze and put of the decision-maker From this point formed the idea of ​​research in the statement of the role of

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