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Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperforms the two other methods in its estimations for different noise conditions.

Publication Date
Mon Oct 07 2019
Journal Name
Journal Of Global Pharma Technology
Contribution of Equilibrium Variables with the High Spike Accuracy of the Position Diagonal Center (4) in the National Volleyball Team Players
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What is important about this study is whether there is a relationship between the ability to balance and beating overwhelming for the Iraqi national team volleyball? The study aims to identify the percentage of the equilibrium contribution and its variables with the accuracy of the skill of beating the high spike Diagonal center (4) in the players. In the national volleyball team season (2016-2017), the researchers used the descriptive approach in the style of associative relationships to suit the problem of research. The research community included all the players specialized in the high beating of the Iraqi national team applicants in the ball The researchers concluded that the equilibrium variables contributed accurately and quickly to t

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Publication Date
Thu Jan 01 2009
Journal Name
Journal Of Global Pharma Technology
Contribution of Equilibrium Variables with the High Spike Accuracy of the Position Diagonal Center (4) in the National Volleyball Team Players
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
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Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
A Proposed Agent System for Network Monitoring
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The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente

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Publication Date
Wed Sep 07 2022
Journal Name
2022 Iraqi International Conference On Communication And Information Technologies (iiccit)
Vehicular Ad-hoc Network (VANET) – A Review
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This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.

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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Material Selection for Unmanned Aerial Vehicles (UAVs) Wings Using Ashby Indices Integrated with Grey Relation Analysis Approach Based on Weighted Entropy for Ranking
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The designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement

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