The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

This  investigation was conducted to recognize the structure for (RHETI version 2.5  1999) by using exploratory and confirmatory factor analysis. Sample of (620) student of Al-Mustansrya University were administered the (RHETI).

The data of their responses was analyzed by using (PAF) and oblique rotating .

The findings explored (9) factors as one factor for each type and (184) items were loaded by the factors: (60) item for feeling center, (61) items for instinctive center and (63) items for thinking center.

Results of confirmatory factorial analysis supported a model designed by the researcher depended upon a theoretical views of Riso and Hudson

A field experiment was conducted during the agricultural season 2017-2018. In the research station of the Ministry of Agriculture AL Rasheed side, and within the activities and researches of the national program to develop wheat cultivation in Iraq, Two factors were experienced in the cultivation of wheat, The first factor is the method of cultivation of five treatments were used: : Treatment of the cultivation of wheat in the plots (B), Treatment of wheat crops on bed with 50 cm width (S1), 60cm (S2), 70cm (S3) and 80cm (S4), The second factor is irrigation levels depletion of 40, 60 and 80% of available water coded as W1, W2 and W3, respectively, The experiment was designed under randomized complete block design (RCBD) with three replicat

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

Empirical equations for estimating thickening time and compressive strength of bentonitic - class "G" cement slurries were derived as a function of water to cement ratio and apparent viscosity (for any ratios). How the presence of such an equations easily extract the thickening time and compressive strength values of the oil field saves time without reference to the untreated control laboratory tests such as pressurized consistometer for thickening time test and Hydraulic Cement Mortars including water bath ( 24 hours ) for compressive strength test those may have more than one day.

Abstract

  Natural gas is characterized by features that made from it a fuel and a raw material for many industries. Deepening its position as a favorite fossil supplier between other types of fossil fuel is the efficiency, diversity of its uses, low costs and compatibility with the environment which leads to increasing of its uses then increased global demand. So, the natural gas must take its place as an important resource in Iraq and participate the oil in the economic development process of building and financing of the general budget.

  Iraq is planning to continue of increasing the export capacity of raw oil to meet ambitious production targets emanating from the mai

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The PbSe alloy was prepared in evacuated quarts tubs by the method of melt quenching from element, the PbSe thin films prepared by thermal evaporation method and deposited at different substrate temperature (Ts) =R.T ,373 and 473K . The thin films that deposited at room temperature (R.T=303)K was annealed at temperature, Ta= R.T, 373 and 473K . By depended on D.C conductivity measurements calculated the density of state (DOS), The density of extended state N(Eext) increases with increasing the Ts and Ta, while the density of localized state N(Eloc) is decreased . We investigated the absorption coefficient (?) that measurement from reflection and transmission spectrum result, and the effect of Ts and Ta on it , also we calculated the tai