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bsj-1417
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The role of training human resources in the elements of administrative innovation
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The current research aims to identify the nature of the relationship between training human resources in administrative innovation elements In the General Directorate for the education of the third Rusafa one of the formations of the Iraqi Ministry of Education in Baghdad, In order to achieve the objectives of the research, the researcher provided a comprehensive theoretical framework and the preparation and development of a questionnaire as a tool for collecting data based on the prepared measurements and benefit from previous studies, which contains (28) For the purpose of obtaining realistic results for the variables of the research, the researcher used the random sample in the selection of the research sample A total of (63)

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Information And Communication Convergence Engineering
Survey on Physical Layer Security in Downlink Networks
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In this paper, we discuss physical layer security techniques in downlink networks, including eavesdroppers. The main objective of using physical layer security is delivering a perfectly secure message from a transmitter to an intended receiver in the presence of passive or active eavesdroppers who are trying to wiretap the information or disturb the network stability. In downlink networks, based on the random feature of channels to terminals, opportunistic user scheduling can be exploited as an additional tool for enhancing physical layer security. We introduce user scheduling strategies and discuss the corresponding performances according to different levels of channel state information (CSI) at the base station (BS). We show that the avai

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Publication Date
Sun Oct 01 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Enhancement the Educational Technology by Using 5G Networks
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With the spread of global markets for modern technical education and the diversity of programs for the requirements of the local and global market for information and communication technology, the universities began to race among themselves to earn their academic reputation. In addition, they want to enhance their technological development by developing IMT systems with integrated technology as the security and fastest response with the speed of providing the required service and sure information and linking it The network and using social networking programs with wireless networks which in turn is a driver of the emerging economies of technical education. All of these facilities opened the way to expand the number of students and s

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Abstract Pattern Image Generation using Generative Adversarial Networks
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Publication Date
Sun Mar 01 2015
Journal Name
Computer Systems Science & Engineering
Parameters' fine tuning of differential evolution algorithm
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Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
IMPROVED STRUCTURE OF DATA ENCRYPTION STANDARD ALGORITHM
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The Internet is providing vital communications between millions of individuals. It is also more and more utilized as one of the commerce tools; thus, security is of high importance for securing communications and protecting vital information. Cryptography algorithms are essential in the field of security. Brute force attacks are the major Data Encryption Standard attacks. This is the main reason that warranted the need to use the improved structure of the Data Encryption Standard algorithm. This paper proposes a new, improved structure for Data Encryption Standard to make it secure and immune to attacks. The improved structure of Data Encryption Standard was accomplished using standard Data Encryption Standard with a new way of two key gene

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Journal Of Political Science
Terrorist organizations employ technological development to threaten international security and stability
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Technological development intersects with terrorism to a large extent, beyond the use of the Internet and social media, in order to spread ideas, obtain support and financing, and recruit new elements, to the area of tactics and techniques of terrorist attacks, and everything related to the arsenal of terrorist weapons in the present and future, while technology offers many benefits. In various fields, and contribute to achieving multiple gains for humanity, they provide extremist and terrorist organizations and elements with a set of weapons and means through which they attempt to bypass monitoring and control efforts and the restrictions imposed on the use of weapons. They also help in planning and implementing their terrorist operations,

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Emulsion Liquid Membrane for Pesticides Removal from Aqueous Solution: Emulsion Stability, Extraction Efficiency and Mass Transfer Studies
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The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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