The study area is located in Kirkuk governorate - northern Iraq, It covers an area of 630 km2.Twenty eight groundwater samples were collected from the study area during October 2012. pH, electrical conductivity(EC) and total dissolved solids (TDS) and chemical analysis of major ions (Ca2+, Mg2+, Na+, K+, Cl, SO42 and HCO3) were determined. Sodium adsorption ratio (SAR), residual sodium carbonate (RSC), sodium percent (Na%) and electrical conductivity were used to evaluate the suitability of groundwater for irrigation purpose. The groundwater samples mostly have no harmful effects and no hazard in terms of SAR and RSC respectively, and permissible in terms ofNa%, but they are poor, very poor and marginal as irrigation water.

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

Background: Chronic periodontitis (CP) is greatly prevalent condition of inflammatory behavior. Salivary biomarker total antioxidants capacity (T-AOC) status, may be related to both periodontal condition and oral hygiene. Aims of the study: To assess the level of salivary T-AOC of patients with chronic periodontitis in comparison to healthy control and to correlate between the level of this marker with the clinical periodontal parameters (plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD), and clinical attachment level (CAL)). Materials and Methods: Ninety subjects of males and females with an age ranged between (35-55) years were participated in this study. Participants were divided into two grou

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

A new scheme of plasma-mediated thermal coupling has been implemented which yields the temporal distributions of the thermal flux which reaches the metal surface, from which the spatial and temporal temperature profiles can be calculated. The model has shown that the temperature of evaporating surface is determined by the balance between the absorbed power and the rate of energy loss due to evaporation. When the laser power intensity range is 107 to108 W/cm2 the temperature of vapor could increase beyond the critical temperature of plasma ignition, i.e. plasma will be ignited above the metal surface. The plasma density has been analyzed at different values of vapor temperature and pressure using Boltzmann’s code for calculation of elec

The radon gas concentration in environmental samples soil and water of selected regions in Al-Najaf governorate was measured by using alpha-emitters registrations which are emitted form radon gas in (CR-39) nuclear track detector. The first part is concerned with the determination of radon gas concentration in soil samples, results of measurements indicate that the highest average radon concentration in soil samples was found in (Al-Moalmen) region which was (100.0±7.0 Bq/m3), while the lowest average radon concentration was found in (Al-Askary) region which was (38.5±4.7 Bq/m3), with an average value of (64.23±14.9 Bq/m3) ,the results show that the radon gas concentrations in soil is below the allowed limit from (ICRP) agency which is (