The present paper aims at evaluating the vailability quality and future horizons of potable water in the city of Shatra as a model. This is done in accordance with certain subjective and objective factors alongside the classification map of Shatra as a residential area. This system follows geographical studies specialized in urban construction. The problem of the present paper as well as the data approaching that problem have been chosen from the records of 2018. The researcher offered (919) questionnaire forms to be answered by a sample of dwellers in that area. Besides, the researcher also followed lab analysis of water samples collected from districts in the city of Shatra. GIS technology was also used to arrive at the real water shar

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

Introduction: This study aimed to evaluate the impact of ozonated water on water sorption and solubility of heat-cure acrylic resin. Methods: Thirty-three samples of heat-cured acrylic resin were manufactured and divided into three groups: control, immersion for 10 and 20 minutes in ozonated water. Water sorption and water solubility tests were carried out in line with ADA Standard No. 12 for denture-base acrylic resin. Data were analyzed using one-way ANOVA at a significance level of 5%. Results: There was a nonsignificant difference between the control and experimental groups regarding water sorption (P

Seeds of Nigella sativa were sown in containers containing 15kg Loamy soil. The seeds were divided before sewing into two groups. The first group was soaked with ordinary tap water end the second group was treated with magnetized water for 24hrs. The irrigation process was completed until 75% of capacity field with two types of water (tap water of magnetized water with three replications).The magnetized water was obtained from special electric device designed for this purposeRecorded measurements (plants height, the number of branches/ plant, dry weight ofplant, number of flowers, 1000 seed weight) during the harvest period.Results indicated that the seed group which was treated with magnetized water was more significant than the one which

An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p