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

OBJECTIVE: To determine the preferred specialties of graduated medical doctors working in Basra, and determine the factors behind their preferences. METHODS: The study was conducted in 38 primary health care centres and seven hospitals in Basra from January-June 2014. A cross-sectional study was adopted with the use of a self-administered questionnaire form. Two hundred ninety six graduated doctors were agreed to participate. Chisquare test and logistic regression were used to test the association between deciding a future speciality and influencing factors. RESULTS: The most preferred specialties were radiology and ultrasound, gynaecology and obstetrics, surgery, internal medicine, dermatology and paediatrics. Clinical specialties were sta

Objective(s): This study aimed to evaluate job satisfaction among nurses working at primary health care centers        in Samawa City.

Methodology: A Descriptive evolutional study has been carried out during the period from 1 February 2022 to 1 June 2022. A nonprobability (convenience) sample of (200) nurse were selected from different educational level. A questionnaire format is developed for the purpose of fulfilling the objectives of the study. Content validity of the questionnaire and reliability has been determined. Data are analyzed using IBM SPSS version 19 software (2010).

Results: The findings indicate that 52% of nurses are showing high level of job satisfa

In this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.

In the framework of this study, the phenomenon of transfer is probed pragma-linguistically and socio-linguistically concerning marriage situations among Iraqi EFL learners. The study also strives to look at the refusal strategies most commonly employed by Iraqi female English as a foreign Language (EFL) learners compared to their counterparts, American native speakers of English. The study involved 70 female participants who answered a Discourse Completion Task (DCT), which contained ten marriage proposals to be refused. Each situation entailed refusal of a person from a higher, an equal, and lower status. The researchers adapted Beebe, Takahashi, and Uliss Weltz’s (1990) taxonomy of refusal for analyzing the data comprehensively. The

In the framework of this study, the phenomenon of transfer is probed pragma-linguistically and socio-linguistically concerning marriage situations among Iraqi EFL learners. The study also strives to look at the refusal strategies most commonly employed by Iraqi female English as a foreign Language (EFL) learners compared to their counterparts, American native speakers of English. The study involved 70 female participants who answered a Discourse Completion Task (DCT), which contained ten marriage proposals to be refused. Each situation entailed refusal of a person from a higher, an equal, and lower status. The researchers adapted Beebe, Takahashi, and Uliss Weltz’s (1990) taxonomy of refusal for analyzing the data comprehensively.

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

Prediction of the formation of pore and fracture pressure before constructing a drilling wells program are a crucial since it helps to prevent several drilling operations issues including lost circulation, kick, pipe sticking, blowout, and other issues. IP (Interactive Petrophysics) software is used to calculate and measure pore and fracture pressure. Eaton method, Matthews and Kelly, Modified Eaton, and Barker and Wood equations are used to calculate fracture pressure, whereas only Eaton method is used to measure pore pressure. These approaches are based on log data obtained from six wells, three from the north dome; BUCN-52, BUCN-51, BUCN-43 and the other from the south dome; BUCS-49, BUCS-48, BUCS-47. Along with the overburden pressur

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.