In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

Background: Candida albicans is a prevalent commensal that can cause severe health problems in humans. One such condition that frequently returns after treatment is oral candidiasis. Aim: the goal of this research is to evaluate the efficiency of 940 nm as a fungicidal on the growth of Candida albicans in vitro. Material and Methods: In vitro samples (fungal swabs) were taken from the oral cavity of 75 patients suffering from oral thrush. Following the process of isolating and identifying Albicans. The samples are divided into four groups:(Group 1): Suspension of C. albicans was put in a solution of saline as a control group. (Group 2): Suspension of C. albicans that had been treated with nystatin. (Group 3): Suspension of C. albica

Background: Candida albicans is a prevalent commensal that can cause severe health problems in humans. One such condition that frequently returns after treatment is oral candidiasis. Aim: the goal of this research is to evaluate the efficiency of 940 nm as a fungicidal on the growth of Candida albicans in vitro. Material and Methods: In vitro samples (fungal swabs) were taken from the oral cavity of 75 patients suffering from oral thrush. Following the process of isolating and identifying Albicans. The samples are divided into four groups:(Group 1): Suspension of C. albicans was put in a solution of saline as a control group. (Group 2): Suspension of C. albicans that had been treated wit

Abstract

The Non - Homogeneous Poisson  process is considered  as one of the statistical subjects which had an importance in other sciences and a large application in different areas as waiting raws and rectifiable systems method , computer and communication systems and the theory of reliability and many other, also it used in modeling the phenomenon that occurred by unfixed way over time (all events that changed by time).

This research deals with some of the basic concepts that are related to the Non - Homogeneous Poisson process , This research carried out two models of the Non - Homogeneous Poisson process which are the power law model , and Musa –okumto ,   to estimate th

Field experiment conducted to measured Slippage, Effective field capacity, Field Efficiency, Soil Volume Disturbed and Specific Productivity Tillage in silt clay loam soil with depth 18 cm in Baghdad- Iraq. Split – split plot design under randomized complete block design with three replications using Least Significant Design 5 % was used. Three factor used in this experiment included Two types of plows included Chisel and Disk plows which represented main plot , Three Tires Inflation Pressure was second factor included 1.1 ,1.8 and 2.7 Bar, and Three forward speeds of the tillage was third factor included 2.35 , 4.25 and 6.50 km/hr. Result show chisel plow recorded best parameters performance

In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we