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

Communication has seen a big advancement through ages; concepts, procedures and technologies, it has also seen a similar advancement of language. What unites language and media is the fact that each one of them guides and contributes to the other; media exists and results from language and from the other sign systems, and what strengthens this connection is the symbolic language system, as media helps it by providing knowledge and information. The change that occurred through time must leave a significant trace in the media, for example Diction, which has changed concerning development and growth, also the ways and mediums of media have become manifold and widespread. This change affected the recipient whether it was a reader, listener o

An experimental study is conducted to investigate the effect of heat flux distribution on the boiling safety factor of its cooling channel. The water is allowed to flow in a horizontal circular pipe whose outlet surface is subjected to different heat flux profiles. Four types of heat flux distribution profiles are used during experiments: (constant distribution profile, type a, triangle distribution profile with its maximum in channel center, type b, triangle distribution profile with its maximum in the channel inlet, type c, and triangle distribution profile with its maximum in the channel outlet, type d). The study is conducted using heat sources of (1000 and 2665W), water flow rates of (5, 7 and 9 lit/min). The water

Microwave heating is caused by the ability of the materials to absorb microwave energy and convert it to heat. The aim of this study is to know the difference that will occur when heat treating the high strength aluminum alloys AA7075-T73 in a microwave furnace within different mediums (dry and acidic solution) at different times (30 and 60) minutes, on mechanical properties and fatigue life. The experimental results of microwave furnace heat energy showed that there were variations in the mechanical properties (ultimate stress, yielding stress, fatigue strength, fatigue life and hardness) with the variation in mediums and duration times when compared with samples without treatment. The ultimate stress, yielding stress and fatigue streng

Hashimoto Thyroiditis (HT) is the most common autoimmune thyroid disease and the commonest cause ofhypothyroidism. C-reactive protein (CRP) is synthesized in hepatocyte in response to autoimmune disorders;strongly induced by IL-6. This study aimed to estimate serum IL-6 and CRP levels in autoimmune and non-autoimmune hypothyroidism. The present study included 60 Iraqi female hypothyroid patients divided to 30autoimmune and 30 non-autoimmune, with age ranged between 24-50 years and 30 healthy controls withage ranged between 27-52 years. Serum samples were collected from study groups. The levels of thyroidhormones (TSH, T4 and T3) were determined by using automated Chemiluminescence Immunoassay (CLIA)analysis system. Detection the levels of t

            The increase in population resulted in an increase in the consumption of water. The present work investigates the performance of a recycling solar- powered greywater treatment system for the purposes of irrigation, used to reduce the amount of waste grey water and reduce electricity consumption and reduce the costs of constructing large scale water treatment plants. The system consumes about 3814W per hour and provides water treatment about 1.4 m³ per day. The proposed system is designed to    residential, office and governmental buildings application. Tests are conducted in an office building at the Ministry of Science and Technology site in Baghdad. Laboratorial water samples testing analyses are co

This work has been done to prepare a series of new alkene compounds derived from 4-thiozolidinones by substituting different aldehydes, P-acetamido-phenol, and 2-mercapto-benzoimidazole, which were used as starting materials to form ester [I]a,b and then make hydrazides [II]a,b, which were used to prepare 1, 3, and 4-oxadiazoles [III]a,b, which were then used for prepared Schiff bases [IV]a-f, The next step was the synthesis of 4-thiazoldinone derivatives [V]a-f  from Schiff bases. The final step was the synthesis of alkenes [VII]a-f, the prepared derivatives were identified with spectral methods (FT-IR, 1H-NMR, mass, and CHNS). The antibacterial activity of the prepared derivatives was evaluated against four types of bacteria, pos

Basically, this study aims to identify the extent to which Iraqi secondary school students use writing strategies and how proficiency level and students gender could affect writing strategy use. The study also examines the relationship between writing achievement and writing strategy use among Iraqi secondary school students. For this purpose, 140 Iraqi secondary school students were selected randomly from six different schools. Petric and Czarl’s questionnaire (2003) was adopted in the study as an instrument to collect the needed data. A software of SPSS used to analyze the collected data. The findings revealed that secondary school students appeared as low users of writing strategies; low proficient students do not show a sta

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