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.
A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co
... Show MoreConcrete structures is affected by a deleterious reaction, which is known as Alkali Aggregate Reaction (AAR). AAR can be defined as a chemical reaction between the alkali content in the pore water solution of the cement paste and reactive forms of silica hold in the aggregate. This internal reaction produces expansion and cracking in concrete, which can lead to loss of strength and stiffness. Carbon fiber-reinforced polymer (CFRP) is one of the methods used to suppress further AAR expansion and rehabilitate and support damaged concrete structures. In this research, thirty-six cylindrical specimens were fabricated from non-reactive and reactive concrete, which contained fused silica as
This study expands the state of the art in studies that assess torsional retrofit of reinforced concrete (RC) multi-cell box girders with carbon fiber reinforced polymer (CFRP) strips. The torsional behavior of non-damaged and pre-damaged RC multi-cell box girder specimens externally retrofitted by CFRP strips was investigated through a series of laboratory experiments. It was found that retrofitting the pre-damaged specimens with CFRP strips increased the ultimate torsional capacity by more than 50% as compared to the un-damaged specimens subjected to equivalent retrofitting. This indicated that the retrofit has been less effective for the girder specimen that did not develop distortion beforehand as a result of pre-loading. From
... Show MoreThis study expands the state of the art in studies that assess torsional retrofit of reinforced concrete (RC) multi-cell box girders with carbon fiber reinforced polymer (CFRP) strips. The torsional behavior of non-damaged and pre-damaged RC multi-cell box girder specimens externally retrofitted by CFRP strips was investigated through a series of laboratory experiments. It was found that retrofitting the pre-damaged specimens with CFRP strips increased the ultimate torsional capacity by more than 50% as compared to the un-damaged specimens subjected to equivalent retrofitting. This indicated that the retrofit has been less effective for the girder specimen that did not develop distortion beforehand as a result of pre-loading. From
... Show MoreIn this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreThis paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
In this paper, some relations between the flows and the Enveloping Semi-group were studied. It allows to associate some properties on the topological compactification to any pointed flows. These relations enable us to study a number of the properties of the principles of flows corresponding with using algebric properties. Also in this paper proofs to some theorems of these relations are given.
This paper aims to validate a proposed finite element model to be adopted in predicting displacement and soil stresses of a piled-raft foundation. The proposed model adopts the solid element to simulate the raft, piles, and soil mass. An explicit integration scheme has been used to simulate nonlinear static aspects of the piled-raft foundation and to avoid the computational difficulties associated with the implicit finite element analysis.
The validation process is based on comparing the results of the proposed finite element model with those of a scaled-down experimental work achieved by other researchers. Centrifuge apparatus has been used in the experimental work to generate the required stresses to simulate t
... Show MoreIn this paper, the finite element method is used to study the dynamic behavior of the damaged rotating composite blade. Three dimensional, finite element programs were developed using a nine node laminated shell as a discretization element for the blade structure (the same element type is used for damaged and non-damaged structure). In this analysis the initial stress effect (geometric stiffness) and other rotational effects except the carioles acceleration effect are included. The investigation covers the effect speed of rotation, aspect ratio, skew angle, pre-twist angle, radius to length, layer lamination and fiber orientation of composite blade. After modeling a non-damaged rotating composite blade, the work procedure was to ap
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