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Comparison of some artificial neural networks for graduate students
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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.                                                                                     

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Publication Date
Fri Jul 01 2016
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Survey Smoothly Fiber-Wireless (FiWi) Accessing Wireless Networks: Convergence and Challenges
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<p> Traditionally, wireless networks and optical fiber Networks are independent of each other. Wireless networks are designed to meet specific service requirements, while dealing with weak physical transmission, and maximize system resources to ensure cost effectiveness and satisfaction for the end user. In optical fiber networks, on the other hand, search efforts instead concentrated on simple low-cost, future-proofness against inheritance and high services and applications through optical transparency. The ultimate goal of providing access to information when needed, was considered significantly. Whatever form it is required, not only increases the requirement sees technology convergence of wireless and optical networks but

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Publication Date
Wed Apr 24 2019
Journal Name
Annals Of Telecommunications
Traveling distance estimation to mitigate unnecessary handoff in mobile wireless networks
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Publication Date
Fri Mar 15 2019
Journal Name
Journal Of The College Of Education For Women
Exploring the Effectiveness of two Scales for Measuring Cultural Intelligence of the Preparatory School Students
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The present study aims at exploring tow cultural intelligence scales of preparatory school students. It also aims at finding out the statistically significant differences according to gender and specification. Accordingly, the present study seeks to answer the following questions:

  1. Is there cultural intelligence of the preparatory school students?
  2. Is there any statistically significant differences according to gender and specification variables?
  3. Is there a scale more effective than cultural intelligence scales?

The stratified random sampling method is used to for selecting the sample of (216) students of scientific and humanistic specifications from

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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Training Program for the Development of Moral Intelligence among Preparatory Students
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This current research aims to identify the effectiveness of a training program in developing moral intelligence and mutual social confidence among middle school students. The researcher made a number of hypotheses for this purpose to achieve the goal of the research.                             

The researcher relied on the (Al Zawaida 2011) scale prepared according to Coles (1997), including (60) items, and the mutual social trust scale for (Nazmi 2001) based on Roter's theory including (38) items.               &nbsp

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Sat May 01 2010
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison of microleakage Restorative Dentistry Comparison of microleakage in three different retrograde cavity preparations with Mineral Trioxide Aggregate as filling material
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Background: The apical seal is the single most important factor in determining the success of surgical endodontics, the aim of this study was to compare the sealing ability of Mineral Trioxide Aggregate in three different cavity designs. Materials and Methods: Thirty extracted human single-rooted teeth were divided into three groups of ten teeth per group, a retrograde cavity preparation was carried out using a low speed handpiece and round bur with parallel walls in the first group, ultrasonic retrotip and unit in the second group and a low speed handpiece with a carbide inverted cone bur with undercuts in the third group, all the cavities were filled with MTA. microleakage was measured by dye penetration technique using methylene blue. Re

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Comparison Between Different DNA and Conventional
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Background: The discriminative power of the classical WHO parameters in relation to male fertility is quite low, because they only address few aspects of sperm quality and function. This has led investigators to focus their attention on the male gamete and in particular its genome.Objective: To explore which of the sperm DNA damage parameters measured by comet assay are more reliable, and their relations with the standard semen parameters.Methods: Study was done on 40 infertile men selected from couples attending the Institute of Embryo Reasearch and Infertility Treatment at Al-Kadhimiya City/ Baghdad in the period between February 2009 and May 2009, with a history of infertility of ≥1 years; and 15 healthy volunteers of proven fertili

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Speech Age Estimation Using a Ranking Convolutional Neural Network
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Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Engineering
Spike neural network as a controller in SDN network
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The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Soft Computing And Computer Applications
Enhancing Image Classification Using a Convolutional Neural Network Model
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In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

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