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.
Rheumatoid arthritis is one of the common chronic disease, which lead to great disability and chronic pain, and has a main adverse economic and social effect upon patients. The reason for the addition of quality of life as a pointer for health outcome result is attributed to the affectability of this measure for the evaluation of patient's health status after taken treatment and its health outcome. The purpose of the current study was to assess quality of life among a sample of Iraqi patients with rheumatoid arthritis and to determine the possible association between health’s related quality of life and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid arthritis pat
... Show MoreIn the present research synthesis and study of biological activity a series of new polymers modified of chitosan with compounds containing azo group. Beginning diazonium salt produced from 3,3'-dimethyl-[1,1'-biphenyl]-4,4'-diamine reacted with concentrated HCl acid and sodium nitrite. The coupling reaction between diazonium salt with substituted aromatic aldehyde to produce Azo derivatives )1-6(. Azo Schiff bases Chitosan )7-12( were synthesized by condensation of Chitosan with Azo derivatives )1-6( in ethanol with some drops of glacial acetic acid. The structural modifications of Chitosan ring (linked to a bioactive azo moiety) were expected to give new derivatives )7-12( with a diverse range of biological functions. These compounds' st
... Show MoreGurney flap (GF) is well-known as one of the most attractive plain flaps because of the simple configuration and effectiveness in improving the lift of the airfoil. Many studies were conducted, but the effects of GF on the various airfoil types need to be further investigated. This study aimed to clarify the effect of GF in the case of the supercritical airfoil RAE2822. This research includes a steady, two-dimensional computational investigation carried out on the supercritical airfoil type RAE-2822 to analyze Gurney flap (GF) effects on the aerodynamic characteristics of this type of airfoil utilizing the Spalart-Allmaras turbulence model within the commercial software Fluent. The airfoil with the Gurney flap was analyz
... Show MoreScheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the
... Show MoreMalnutrition, anemia, and micronutrient deficits may be associated with Enterobius vermicularis infection. Hence, the subject has recently received a lot of attention. The goal of this study was to analyse the nutritional, hematological and micronutrient status of children infected with E. vermicularis. This research was carried out in Baghdad from October 2021 to the end of March 2022. The study comprised 100 children of both sexes, ranging in age from 3-16 years. All individuals nutritional status was assessed using the weight-for-age Z score and the height-for-age Z score. As well as cellophane tape samples and blood samples were collected from all individuals. The cellophane tape samples were examined under microscope f
... Show MoreDetection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreModified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time
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