Through the early childhood and after the ablactating the child learns acquired food habbits that might studying with him throughout his life. Here the parents role arises: teaching the child the sound food habits and hygienic styles and whatever beneficial to the health and with the sufficient quantities for the body. In this way the experiences the child learns at home will be of great help in his future life in choosing the suitable food after becoming more dependent in making his decisions and choices away from his parents. The results in this study showed that the averages of the children’s consumption of the high energy foods in comparison with the other highest consumption average , after that comes the con sumption of soft drills

The aim of the present research is to identify the test wisdom and the engagement with learning and psychological tension among postgraduate students at the University of Samarra according to the variables of the department, gender, age, and whether students are employee or non-employee. The study also attempts to identify the relationship between the test wisdom and the engagement with learning and psychological tension. The research sample consisted of (75) postgraduate students randomly selected from college of Education. The researcher applied the test–wisdom of (Mellman & Ebel) and the scale of engagement with learning preparation by (Al-zaabi 2013). In addition, the researcher used the list of the psychological stress of (Abu

Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H₂S using a plant that generates the H₂S from naphtha hydrodesulphurization and a unit for the adsorption of H₂S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.

It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e

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

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

In this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction  at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted  in the theoretical cross section and compared with the experimental data for  nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when  doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with  the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi

The influence of 5-10 kHz audio frequency on the power dissipation in ac discharge of argon gas was studied experimentally, at pressures 50-80 mTorr and electrodes separation 10 cm (pd range 0.5-0.8 Torr.
cm). The measurements have shown that the discharge behavior in the ac circuit is equivalent to a series RC circuit. It is observed that the variation curve of discharge power P with the frequency f is approximately has a Gaussian shape. It is also observed that the curve of Pm- pd is the inverse of Paschen curve, where Pm is the maximum power in the frequency range. The time of breakdown is estimated from the curve of P- f.

The paper presents an investigation to the flutter speed of composite wing for different ply orientation. Structurally the composite wing was idealized as a composite beam load carrying structure. Theodorsen’s expression was used to get the 2- dimension unsteady lifting force and pitching moment in the limit of incompressible flow and subsonic speed which were integrated over the wing span. A free vibration analysis was first carried out to get the natural frequencies and mode shapes .The velocity-damping (V-g) method was used to calculate the flutter speed and the flutter frequency. A wing of unmanned aerial vehicle was manufactured from woven glass and polyester resin where the flutter speed was calculated experimentally by the wind

In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen