In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.
This study investigated a novel application of forward osmosis using different types of draw solutions for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). Magnesium chloride (MgCl2) and magnesium sulfate (MgSO4) were used as draw solutions in forward osmosis process to evaluate their effectiveness. Experiments were conducted in a laboratory scale forward osmosis system with cellulose triacetate hollow fiber membrane. In this work, sodium chloride solution was used as a feed solution with a concentration of 76 g/L (same concentration as the East Baghdad oilfield produced water) and the applied external pressure on the feed solution side was 2 bar. The impact of draw solution (DS)
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Care research examining the relationship between the variables of search presidents (employee training and organizational commitment) to determine the effect of the training of employees in organizations in achieving organizational commitment of employees towards their organizations and by the fact that training is one of the most important activities adopted by the administration and by which can benefit realized for workers and for the organization .ttjsd problem Search lack of training considered as a factor of the important factors in the development of staff skills and development work in many Iraqi companies, including vegetable oils company (where to look), which in turn raises the relevance and commitment
... Show MoreThe research deals with the important and modern two subject (career path and the type of training program), and tries to find identify the extent of the impact of the requirements of a career path in determining the type of training program in the Ministry of Oil.
In order to achieve the aim of the research was the formulation of the following hypothesis: the impact of the requirements of the career path a meaningful moral influence in determining the type of training program.
The survey was adopted in the search, and sample consisted of (75) people were a factor in the Oil Ministry of People's managers and officials and staff, and used the questionnaire as an es
... Show MoreObjective: The aim of this study is to identify the impact of training education program applied on
nurse-midwife practice concerning care during third stage of labor in labor room. Examine the
relationship between their knowledge regarding practices and some Demographic information’s.
Methodology: A quasi-experimental design conducted on non-probability (purposive) sample of fifty
two nurse-midwives selected during period from3
th August to 10thNovember 2011. The study is
conducted at the Ministry of Health (Baghdad health directorate in Al-Karhk and Al-Risafa sector) in
four hospitals. The questionnaire form is consisted of three parts which included demographic data,
knowledge concerning practice during third
Objective: The study aimed to screen the prepubertal children for idiopathic scoliosis at earlier stages, and find
out the relationship between idiopathic scoliosis and demographic data such as age, sex, body mass index,
heavy backpacks, and heart & lung diseases.
Methodology: A descriptive study was conducted on screening program for prepubertal children in primary
schools at Baghdad city, starting from 24th of February to the end of October 2010. Non- probability
(purposive) sample of 510 prepubertal children were chosen from primary schools of both sides of Al-Karkh
and Al-Russafa sectors. Data was collected through a specially constructed questionnaire format include (24)
items multiple choice questions, and
Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty
... Show MoreThe main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256) in our research, compressed them by using MLP for each
... Show MoreImage Fusion Using A Convolutional Neural Network
In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
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