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.
This paper is concerned with finding solutions to free-boundary inverse coefficient problems. Mathematically, we handle a one-dimensional non-homogeneous heat equation subject to initial and boundary conditions as well as non-localized integral observations of zeroth and first-order heat momentum. The direct problem is solved for the temperature distribution and the non-localized integral measurements using the Crank–Nicolson finite difference method. The inverse problem is solved by simultaneously finding the temperature distribution, the time-dependent free-boundary function indicating the location of the moving interface, and the time-wise thermal diffusivity or advection velocities. We reformulate the inverse problem as a non-
... Show MoreThis paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
... Show MoreThe load shedding scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po
... Show MoreTo determine the relationship between Helicobacter pylori infection and reproduction disorder (recurrent spontaneous abortion), twenty women patients who undergo spontaneous abortion during first trimester of pregnancy (20-38) years and have been investigated from 2015/12/1 -2016/3/1 and compared to fifteen healthy individuals. All subjects were carried out to measure anti-H. pylori IgA and anti- H. pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA). There was significant elevation (p≤ 0.05) in concentration of anti- H. pylori IgG Abs (6.30± 0.99) compared to control group (4.48± 0.61) and IgA Abs (5.42 ± 0.90 U /ml) as compared to control group (3.92 ± 0.41 U/ml). The percentage of H. pylori IgG and IgA was 20% and 25
... Show MoreThe role of transmembrane protease serine 2(TMPRSS2) in prostate carcinogenesis relies on overexpression of ETS transcription factors. The aim of this article was to investigate the association of TMPRSS2 polymorphism (rs12329760 (C\T)) with prostate cancer (PCa) in sample of Iraqi patients. One hundred and two individuals were involved in this study for the period from February – 2019 to February – 2020. The sample type was formalin fixed paraffin embedded tissue samples (FFPE), which involved fifty-six samples of pre-diagnosed patients with prostate cancer, aged between 48 and 86 years, and forty-six samples were found to be controls (healthy group) dependent on Prostate Gland integrity, which is the same age as in a group o
... Show MoreWith the increasing integration of computers and smartphones into our daily lives, in addition to the numerous benefits it offers over traditional paper-based methods of conducting affairs, it has become necessary to incorporate one of the most essential facilities into this integration; namely: colleges. The traditional approach for conducting affairs in colleges is mostly paper-based, which only increases time and workload and is relatively decentralized. This project provides educational and management services for the university environment, targeting the staff, the student body, and the lecturers, on two of the most used platforms: smartphones and reliable web applications by clo
In this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these measurement
... Show MoreIn this work, an efficient energy management (EEM) approach is proposed to merge IoT technology to enhance electric smart meters by working together to satisfy the best result of the electricity customer's consumption. This proposed system is called an integrated Internet of things for electrical smart meter (2IOT-ESM) architecture. The electric smart meter (ESM) is the first and most important technique used to measure the active power, current, and energy consumption for the house’s loads. At the same time, the effectiveness of this work includes equipping ESM with an additional storage capacity that ensures that the measurements are not lost in the event of a failure or sudden outage in WiFi network. Then then these
... Show MoreThis study aims to show, the strength of steel beam-concrete slab system without using shear connectors (known as a non-composite action), where the effect of the friction force between the concrete slab and the steel beam has been investigated, by using finite element simulation.
The proposed finite element model has been verified based on comparison with an experimental work. Then, the model was adopted to study the system strength with a different steel beam and concrete slab profile. ABAQUS has been adopted in the preparation of all numerical models for this study.
After validation of the numerical models, a parametric study was conducted, with linear and non-linear Regression analysis. An equation re
... Show More