The present study aimed to asspssment the nutrition a program to sample of student from internal departments of Baghdad University (AL-Jadiriya Complex) and the University of AL-MustanSiriya four grades and aged (19-24) year study included 150 male and female students by (75) male and (75) of female register height, weight nd body mass index were study habits and food pattern of the same sample (150) and by aspecial form and take the personal information interviews and record information on food intake during 24 hour .noted adifference practie in the weights and longths of male and female (sample).
BMI rates were within the normal weight as the value of BMI for males aged (19- 21)and (22-24) and (22.21) and (23,37),respectively and th

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Permeability data has major importance work that should be handled in all reservoir simulation studies. The importance of permeability data increases in mature oil and gas fields due to its sensitivity for the requirements of some specific improved recoveries. However, the industry has a huge source of data of air permeability measurements against little number of liquid permeability values. This is due to the relatively high cost of special core analysis.
The current study suggests a correlation to convert air permeability data that are conventionally measured during laboratory core analysis into liquid permeability. This correlation introduces a feasible estimation in cases of data loose and poorly consolidated formations, or in cas

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

     Cupressus sempervirens L., Cupressaceae, that is known as evergreen cypress, Mediterranean cypress and in Arabic called “al -Sarw. It is an evergreen, medium sized, longevity, and wide distributed over all the world. The plant represents an important member of conifer plants which characterized with aromatic leaves and cones. Cupressus sempervirens have been ethnobotanical uses as an antiseptic, relief of cough, astringent, antispasmodic, wound healing and anti-inflammatory. Aims of this work are phytochemical analysis, isolation and structural identification of Quercitroside (quercitrin) and essential oil in Iraqi C. sempervirens. Isolation of quercitrin was