Objectives: To choose the best mode of delivery
for term, frank or complete, breech presentation
through studying the perinatal outcome of each mode of
delivery decided when managing a group of pregnant
ladies presented with breech delivery in our centre.
Methods: One hundred and fifty pregnant ladies
presented at term with singleton, frank or complete,
breech presentation for delivery in our centre during the
period from May 2004 toAugust 2005.
Mode of delivery, parity, gestational age, maternal age,
maternal medical illness, and birth weight where the
variables that have been tested in each delivery
included in the study to verify their relationship to
perinatal outcome.
Results: No significant

The ideas and information obtained by the viewer in the cinema have always been the source of the visual image, but that doesn’t negate the fact that the mental image can produce a lot of the information and ideas in the cinematic art and the most important means to achieve this mental image in the film is the eloquent cinematic sound. This research is conducted to show this important and effective contribution of the sound in the production of the mental image. Hence the importance of this research is in that it addresses an important issue which is the eloquent performance of the sound and its role in the production of the mental image inside the space of the feature film. This research concerns those working the field of cinema and

Knowing the Messengers, peace and blessings be upon them, and explaining their obligatory, impossible, and permissible qualities is a legal necessity. It is a rooting of the faith, a means of understanding the Sharia, and a preventer from falling into the scourge of denial and bad manners against them. Therefore, sound belief in their presence is a major reason for the validity of the faith in the aspect of divinity and unseen hearing. Studying the status of prophethood is an urgent necessity in a time in which knowledge is scarce and attachment to the Messenger, may God Almighty’s prayers and peace be upon him, his family, and his companions, is weak, and suspicions and ideas hostile to the faith abound until we begin to hear - unfort

Background: With the increasing trends of global culinary boom and food revolution, and since adolescents are one of the most important age groups that intereact actively with new emerging waves, the health impacts of overweight adolescent pregnancy could be an evolving issue. Additionally, prematurity has different risks of disease and fatality in different areas and nations. Objectives: We aimed to measure the prevalence of complications of prematurity in 1000 neonates in Baghdad city born to overweight adolescent mothers and general maternal characteristics. Methods: Data of 1000 premature (case) and full-term (control) neonates were collected from hospital records in Baghdad over 12 years. The mothers of our samples were overwei

Autoría: Jehan Faris Yousif. Localización: Opción: Revista de Ciencias Humanas y Sociales. Nº. 89, 2019. Artículo de Revista en Dialnet.

The current study seeks to evaluate teacher preparation programs in the scientific disciplines at the College of Education in Al-Aqsa University in the light of the requirements of the labor market. It further aims to reveal the significance of the differences in the sample members’ response averages of to the availability of labor market requirements in the program that prepares the teacher of scientific disciplines at the Faculty of Education in Al-Aqsa University taking into account the (gender, program) variables. The study followed the descriptive analytical approach, and so a questionnaire was distributed to a sample of scientific discipline students in the teacher preparation program adopted in Al-Aqsa University, (200) male and

This work is concerned with the vibration attenuation of a smart beam interacting with fluid using proportional-derivative PD control and adaptive approximation compensator AAC. The role of the AAC is to improve the PD performance by compensating for unmodelled dynamics using the concept of function approximation technique FAT. The key idea is to represent the unknown parameters using the weighting coefficient and basis function matrices/vectors. The weighting coefficient vector is updated using Lyapunov theory. This controller is applied to a flexible beam provided with surface bonded piezo-patches while the vibrating beam system is submerged in a fluid. Two main effects are considered: 1) axial stretching of the vibrating beam that leads

Abstract  

  In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invas

   In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the  traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an