this paper presents a novel method for solving nonlinear optimal conrol problems of regular type via its equivalent two points boundary value problems using the non-classical

Background: Women with previous two or
more caesarean deliveries are usually
managed by elective cesarean section to avoid
the possible risks of labor.
Objective: To compare the relative risks of
maternal and fetal outcomes in emergency
versus elective previous two or more
caesarean deliveries
Design: Randomized prospective clinical
study
Setting: Al-Elweya Maternity Teaching
Hospital, from 1st of March to 31st of
September 2008.
Methods: The study groups, those who had
previous two or more caesarean deliveries,
were included from the hospital admissions.
The 1st group (102 women) presented in labor
and was managed by caesarean delivery as
soon as it was possible. The second group (7

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

In this paper, compared eight methods for generating the initial value and the impact of these methods to estimate the parameter of a autoregressive model, as was the use of three of the most popular methods to estimate the model and the most commonly used by researchers MLL method, Barg method  and the least squares method and that using the method of simulation model  first order autoregressive through the design of a number of simulation experiments and the different sizes of the samples.

A survey of chrysidid wasps and an identification key to the genera from different localities in Iraq are provided. The genus Pseudomalus Ashmead, 1902 with Pseudomalus auratus (Linnaeus) and Omalus timidus (Nurse), are new records from Iraq. As well, a preliminary checklist of Iraq’s Chrysididae is suggested. Twenty species within nine genera in two subfamilies have been included in the current list. Historical information is provided together with remarks on the current taxonomic status and the particular validity for some species.

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For