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Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to change its affiliation with other clusters based on a deep learning modified Element-wise Attention Gate. The modified Element-wise Attention Gate has the ability to handle the buffer capacity in all the network, thereby enriching the Quality of Service. A deep learning modified training algorithm is proposed to learn the artificial intelligent system allowing the neurons to have greater concentration ability. The simulation results demonstrate that the Root Mean Square error is minimized by 37.14% when using modified Element-wise Attention Gate when compared with a Deep Learning Recurrent Neural Network. Also, the Quality of Service of the network is improved, for example, the network lifetime is enhanced by 12.7% more than with Deep Learning Recurrent Neural Network.

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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 Sep 04 2018
Journal Name
Al-khwarizmi Engineering Journal
Modified Elman Neural-PID Controller Design for DC-DC Buck Converter System Based on Dolphin Echolocation Optimization
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This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

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Publication Date
Tue Oct 01 2019
Journal Name
Ieee Xplore
The Internet of Everything Based Smart Systems: Applications and Challenges
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Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology

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Publication Date
Mon Nov 01 2021
Journal Name
2021 International Conference On Intelligent Technology, System And Service For Internet Of Everything (itss-ioe)
Application of MQ-Sensors to Indoor Air Quality Monitoring in Lab based on IoT
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Publication Date
Fri Dec 20 2019
Journal Name
Iet Circuits, Devices & Systems
Multi‐bit error control coding with limited correction for high‐performance and energy‐efficient network on chip
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In the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Clinical And Experimental Dentistry
Bond strength of a new Kevlar fiber-reinforced composite post with semi-interpenetrating polymer network (IPN) matrix
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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed
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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
Sat Mar 01 2014
Journal Name
International Journal Of Computer Science Engineering And Technology
Streaming video content over NGA (next generation access) network technology‏
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An approach for hiding information has been proposed for securing information using Slanlet transform and the T-codes. Same as the wavelet transform the Slantlet transform is better in compression signal and good time localization signal compression than the conventional transforms like (DCT) discrete cosine transforms. The proposed method provides efficient security, because the original secret image is encrypted before embedding in order to build a robust system that is no attacker can defeat it. Some of the well known fidelity measures like (PSNR and AR) were used to measure the quality of the Steganography image and the image after extracted. The results show that the stego-image is closed related to the cover image, with (PSNR) Peak Si

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Independent Thermal Network Through Thermal Synergy Between Four Architectural Units
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The manifestations of climate change are increasing with the days: sudden rains and floods, lakes that evaporate, rivers that experience unprecedentedly low water levels, and successive droughts such as the Tigris, Euphrates, Rhine, and Lape rivers. At the same time, energy consumption is increasing, and there is no way to stop the warming of the Earth's atmosphere despite the many conferences and growing interest in environmental problems. An aspect that has not received sufficient attention is the tremendous heat produced by human activities. This work links four elements in the built environment that are known for their high energy consumption (houses, supermarkets, greenhouses, and asphalt roads) according t

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