Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, University of Baghdad for the period from 2014-2015 to The academic year 2017-2018. The variables are use in the research is (student’s success, age, gender, job, type of study (higher diploma, master’s, doctorate), specialization (statistics, economics, accounting, industry management, administrative management, and public administration) and channel acceptance). It became clear that the best variables that affect the success of graduate students are the type of study, age and job.
Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin
The study aimed at the following:
Identify the differences in average scores core thinking skills kindergarten children by variable sex (male - female), and by variable age (5.6 - 5.11).
To achieve this researcher adopted a standardized test of core thinking skills for the kindergarten children, which was built and standardization by the researcher Meyada Asaad Mussa 2012 . applied test on a sample of (814) ) boys and girls who were randomly chosen form, from directorates of Baghdad Education Adoption of the proportional distribution.
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An efficient combination of Adomian Decomposition iterative technique coupled Elzaki transformation (ETADM) for solving Telegraph equation and Riccati non-linear differential equation (RNDE) is introduced in a novel way to get an accurate analytical solution. An elegant combination of the Elzaki transform, the series expansion method, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has
... Show MoreThe present study aims at assessing the status of heavy metals such as nickel, cadmium and lead to pollute some areas of Baghdad city. In this study the spectral absorption device and the program ArcGIS 10.2 will using. The soil samples were taken from five different locations in Baghdad, including Ameriya, Kadhimiya, Palestine Street, Jadiriyah and Taji for the 5cm depth layer on both sides of the road. This work on soil samples has been completed in two :phases 1 - Preparation of samples: For the purpose of converting solid material into a extract containing elements in the form of single ions can be estimated by the device 2-Determination of elements: Samples prepared to the device
With the increasing use of antibiotics around the world, the study and appreciation of antibiotics has become essential. An antibiotic formulation may include one or added active ingredients depending on the type and method of manufacturing the antibiotic. Antibiotics can only combat diseases of bacterial origin. As for viral diseases such as the common cold and influenza, antibiotics will not be able to combat them. The objective of this review is to digest the literature related to estimation of antibiotics and to show the methods that have been used in the estimation of the antibiotics (amoxicillin, ampicillin, cephalothin, carbenicillin, and cefotaxime) in medicinal preparations and a biological fluid for example blood
... Show MoreThe duration of sunshine is one of the important indicators and one of the variables for measuring the amount of solar radiation collected in a particular area. Duration of solar brightness has been used to study atmospheric energy balance, sustainable development, ecosystem evolution and climate change. Predicting the average values of sunshine duration (SD) for Duhok city, Iraq on a daily basis using the approach of artificial neural network (ANN) is the focus of this paper. Many different ANN models with different input variables were used in the prediction processes. The daily average of the month, average temperature, maximum temperature, minimum temperature, relative humidity, wind direction, cloud level and atmosp
... Show MoreThe current research was aimed at the following:
1. Measurement the Ambivalence among University students.
2. Identify the differences in Ambivalence among University students according to variable of Specialization (scientific / literary).
To achieve this aims of the research, the researcher set up the instrument is scale of Ambivalence that consistent (19) item. And the researchers applying this scale on the sample amounted to (200) among University students. Then after data processing statistically, the researchers reached the following results:
1. University students have Ambivalence.
2. There is no is differences in Ambivalence among University students according to variable of Specialization (scientific / literary).<
The current research aims to identify the problems and needs for both college of political science and college of engineering’s students. The sample was (100) male and female student. The results showed bunch of problems which could be organized descendingly, the scientific domain ranged between (2 - 2.42), the mean of the psychological domain was (2.85), the moral domain ranged between (2.2 – 2.28)m the problems of study earned (2.30), the material domain got (1.95), the medical and social domain obtained (1.925), and finally, the family domain received (1.887).
Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t
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