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A Spike Neural Controller for Traffic Load Parameter with Priority-Based Rate in Wireless Multimedia Sensor Networks
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Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffic load parameter μ for each parent node and then use in the EWPBRC algorithm to estimate the transmission rate of parent nodes and then assign a suitable transmission rate for each child node. A comparative study between (MSNTLP with EWBPRC) and fuzzy logic controller for traffic load parameter with Exponential Weight of Priority Based Rate Control algorithm (FTLP with EWBPRC) algorithm shows that the (MSNTLP with EWBPRC) is more efficient than (FTLP with EWBPRC) algorithm in terms of packet loss, queue delay and throughput. Another comparative study between (MSNTLP with EWBPRC) and EWBPRC with fixed traffic load parameter (µ) shows that the MSNTLP with EWBPRC is more efficient than EWBPRC with fixed traffic load parameter (µ) in terms of packet loss ratio and queue delay. A simulation process is developed and tested using the network simulator _2 (NS2) in a computer having the following properties: windows 7 (64-bit), core i7, RAM 8GB, hard 1TB.

 

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Publication Date
Fri Apr 01 2022
Journal Name
Journal Of Engineering
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

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Publication Date
Thu Aug 01 2019
Journal Name
The Journal Of Solid Waste Technology And Management
Recycling of Waste Compact Discs in Concrete Mix: Lab Investigations and Artificial Neural Networks Modeling
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This study aimed to investigate the incorporation of recycled waste compact discs (WCDs) powder in concrete mixes to replace the fine aggregate by 5%, 10%, 15% and 20%. Compared to the reference concrete mix, results revealed that using WCDs powder in concrete mixes improved the workability and the dry density. The results demonstrated that the compressive, flexural, and split tensile strengths values for the WCDs-modified concrete mixes showed tendency to increase above the reference mix. However, at 28 days curing age, the strengths values for WCDs-modified concrete mixes were comparable to those for the reference mix. The leaching test revealed that none of the WCDs constituents was detected in the leachant after 180 days. The

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Diagnosing Pilgrimage Common Diseases by Interactive Multimedia Courseware
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In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

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Publication Date
Sat Jan 01 2022
Journal Name
Computers, Materials & Continua
An Optimal Method for Supply Chain Logistics Management Based on Neural Network
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
PDCNN: FRAMEWORK for Potato Diseases Classification Based on Feed Foreword Neural Network
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         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Performance of humidity sensor based on photonic crystal fiber interferometer
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Photonic Crystal Fiber Interferometers (PCFIs) are greatly used
for sensing applications. This work presents the fabrication and
characterization of a relative humidity sensor based on Mach-
Zehnder Interferometer (MZI), which operates in reflection mode.
The humidity sensor operation based on the adsorption and
desorption of water vapour at the silica-air interface within the PCF.
The fabrication of this sensor is simple, it only includes splicing and
cleaving the PCF with SMF.PCF (LMA-10) with a certain length
spliced to SMF (Corning-28).
The spectrum of PCFI exhibits good sensitivity to humidity
variations. The PCFI response is observed for a range of humidity
values from (27% RH to 85% RH), the positi

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Publication Date
Wed Jun 27 2018
Journal Name
Wireless Communications And Mobile Computing
Developing a Video Buffer Framework for Video Streaming in Cellular Networks
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This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different video

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Publication Date
Mon Jan 01 2024
Journal Name
Itm Web Of Conferences
Embedded Neural Network like PID Water Heating Controller Implementing Cycle by Cycle Power Control Scheme
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This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

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Publication Date
Wed Jan 01 2020
Journal Name
Communications In Computer And Information Science
Performance Evaluation for Four Supervised Classifiers in Internet Traffic Classification
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Publication Date
Tue Mar 18 2025
Journal Name
Physica Scripta
Design and Analysis of a highly sensitive open trapezoidal channel PCF-based Plasmonic Refractometric Sensor
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Abstract<p>This study introduces a highly sensitive trapezium-shaped PCF based on an SPR refractometric sensor with unique design features. The structure of a sensor was designed and analyzed using COMSOL Multiphysics v5.6 based on Finite Element Method (FEM) with a focus on investigating the influence of various geometric parameters on its performance. The two channels were coated with a metallic gold layer to provide chemical stability, and a thin layer of TiO₂ improved the gold's adhesion to the fiber. The findings indicate that the proposed sensor achieves maximum amplitude and wavelength sensitivities of 1,779 RIU⁻¹ and 30,500 nm/RIU, respectively, with corresponding resolutions of 3.2</p> ... Show More
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