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jih-2213
Dynamic Channel Assignment Using Neural Networks
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This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
A Review of Flow Migration Through Mobile Networks
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      The interesting new sources of data for official statistics are cell phone data. Electronic media has defined the way of research human behavior rapidly over the last decade. As data storage and sensing technology progressed, electronic records now cover a diverse variety of human activities from localized data (phone) to open source contributions on Wikipedia and the Open Area Map. Electronic records now encompass the numerous fields of activity. The ad hoc vehicle network is a research community-based wireless technology for the implementation of intelligent transport applications. It is necessary to estimate migration flows and predict future trends to understand the causes and effects of migration and to enforce policies t

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Evaluating the effects of reservoir level and foundation depth on the dynamic behaviour of a rockfill dam using three-dimensional finite elements modelling
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Abstract<p>This paper presents a three-dimensional Dynamic analysis of a rockfill dam with different foundation depths by considering the dam connection with both the reservoir bed and water. ANSYS was used to develop the three-dimensional Finite Element (FE) model of the rockfill dam. The essential objective of this study is the discussion of the effects of different foundation depths on the Dynamic behaviour of an embanked dam. Four foundation depths were investigated. They are the dam without foundation (fixed base), and three different depths of the foundation. Taking into consideration the changing of upstream water level, the empty, minimum, and maximum water levels, the results of the three-dimensional F</p> ... Show More
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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Diagnosis and Classification of Type II Diabetes based on Multilayer Neural Network
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     Diabetes is considered by the World Health Organization (WHO) as a main health problem globally. In recent years, the incidence of Type II diabetes mellitus was increased significantly due to metabolic disorders caused by malfunction in insulin secretion. It might result in various diseases, such as kidney failure, stroke, heart attacks, nerve damage, and damage in eye retina. Therefore, early diagnosis and classification of Type II diabetes is significant to help physician assessments.

The proposed model is based on Multilayer Neural Network using a dataset of Iraqi diabetes patients obtained from the Specialized Center for Endocrine Glands and Diabetes Diseases. The investigation includes 282 samples, o

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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
Community Tracking in Time Evolving Networks: An Evolutionary Multi-objective Approach
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In real world, almost all networks evolve over time. For example, in networks of friendships and acquaintances, people continually create and delete friendship relationship connections over time, thereby add and draw friends, and some people become part of new social networks or leave their networks, changing the nodes in the network. Recently, tracking communities encountering topological shifting drawn significant attentions and many successive algorithms have been proposed to model the problem. In general, evolutionary clustering can be defined as clustering data over time wherein two concepts: snapshot quality and temporal smoothness should be considered. Snapshot quality means that the clusters should be as precise as possible durin

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Influence of Heat Transform and Rotation of Sutterby Fluid in an Asymmetric Channel
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     In this research, the effect of the rotation variable on the peristaltic flow of Sutterby fluid in an asymmetric channel with heat transfer is investigated. The modeling of mathematics is created in the presence of the effect of rotation, using constitutive equations following the Sutterby fluid model. In flow analysis, assumptions such as long wave length approximation and low Reynolds number are utilized. The resulting nonlinear equation is numerically solved using the perturbation method. The effects of the Grashof number, the Hartmann number, the Hall parameter, the magnetic field, the Sutterby fluid parameter, and heat transfer analysis on the velocity and the pressure gradient are analyzed graphically. Utilizing MATHEMATIC

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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
An Image Coding and Embedding Strategy Based on Channel Variations and DNA Sequences
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The digital multimedia systems become standard at this time because of their extremely sensory activity effects and also the advanced development in its corresponding technology. Recently, biological techniques applied to several varieties of applications such as authentication protocols, organic chemistry, and cryptography. Deoxyribonucleic Acid (DNA) is a tool to hide the key information in multimedia platforms.
In this paper, an embedding algorithm is introduced; first, the image is divided into equally sized blocks, these blocks checked for a small amount color in all the separated blocks. The selected blocks are used to localize the necessary image information. In the second stage, a comparison is between the initial image pixel

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
The Effect of Strategic Information System in Global Marketing Channel: A Case Study
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The research dealt with the issue of strategic information systems and its impact on the global marketing channel. As the research aims to know the strategic information systems used in the cement company. Which support the senior management in supporting decisions taken in the process of global orientation and moving to foreign markets by choosing the marketing channel that will suit the company. Product and competition with it. With other companies' products. The problem of the study focused on how to move to global markets, and any marketing channel that can be followed to move the cement product globally, what are the strategic information systems used in the company and how will it contribute to supporting senior management dec

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