The study aims to follow modern methods in teaching rhythmic gymnastics skills by directing learners to develop their perceptions and absorb what the world deals with today and develop intelligence among learners, the researchers searched for the strengths of the learner by providing them with an opportunity to form their kinetic formation, hence the problem came by introducing a method of self-intelligence and social to guide the learner in the search for ways and solutions to overcome boredom and economy Time and effort in the educational process in learning and give them the freedom to express their ideas And their skills and here came the role of social and self-intelligence to teach the individual and collective kinetic formati

This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer

This study deals with formation models of gypsum barrier, chemical temporal changes, and assessments of the Sawa Lake within the Al- Muthanna province, Southern Iraq, it is a very important issue to find the water quality and water assessments of this lake. Eleven water samples are collected from Sawa Lake. Many scientific concepts are used such as major cations (Ca2+, Mg2+, Na+ and K+), major anions (SO4=,Cl-,HCO3- and CO3=) with minor anions ( PO43-, NO3-) and H2S . Trace elements (Pb, Cd, Zn, As, Ni, Co, Cu, Mn, Fe, As, Sr And B) and bacterial test were analyzed in each sample. Total dissolved solids (TDS), electrical conductivity (EC), pH and temperature (T) were directly measured in the field. The equilibrium state between the conce

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

        In this research, an investigation for the compatibility of the IRI-2016 and ASAPS international models was conducted to evaluate their accuracy in predicting the ionospheric critical frequency parameter (f_oF2) for the years 2009 and 2014 that represent the minimum and maximum years of solar cycle 24. The calculations of the monthly average f_oF2 values were performed for three different selected stations distributed over the mid-latitude region. These stations are Athens - Greece (23.7^o E, 37.9 ^o N), El Arenosillo - Spain (-6.78 ^o E, 37.09 ^o N), and Je Ju - South Korea (124.53 ^o E, 33.6 ^o N). The calculated v

Abstract

The term public budget defects became nowadays a chronic, economical phenomenon, almost all the countries weather advanced or development country suffered from it, despite the different visions to economic schools of a thought to accept or reject the deficit in public budget but the prevailed opinion that is needed to rule the role of the state by reducing the public spending which led to continuous deficits in public budget and the consequent upon increase in government borrowing, increase taxes on income and wealth, thus weakening the in contrive for private investment which contributed to the increase of in flationary stagnation, it became a duty to state covered by the lack of financial sources

This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),