Iraq has a huge network of pipelines, transport crude oil and final hydrocarbon products as well as portable water. These networks are exposed to extensive damage due to the underground corrosion processes unless suitable protection techniques are used. In this paper we collect the information of cathodic protection for pipeline in practical fields (Oil Group in Al Doura), to obtain data base to understand and optimize the design which is made by simulation for the environmental factors and cathodic protection variables also soil resistivity using wenner four terminal methods for survey sites; and soil pH investigations were recorded for these selected fields were within 7-8, and recording the anodes voltage and its related currents for the protection of underground pipelines.
Modeling enables the designer to build cathodic protection for buried structure and predicting the places of anodes sites and its operating voltages and currents under various operational conditions, and comparing it with those in practices. In this work we compared between the field and simulation results which include, anode numbers, rectifier voltage, rectifier current and anode resistance. The most economical design for the first pipeline was at station no. 2 which need 2.5 A for protection of the pipeline for that specific length and for second pipeline station no. 4 which need 12 A for protection of the pipeline for that specific length.
In the present study, nanoporous material type MCM-41 was prepared by the sol-gel technique and was used as a carrier for prednisolone (PRD) drug delivery. The structural properties of mesoporous were fully characterized by X-ray diffraction (XRD), N2 adsorption /desorption and Fourier-transform infrared (FTIR). The mass transfer in term of adsorption process (loading) and desorption process (releasing) properties were investigated. The maximum drug loading efficiency was equal to 38% and 47.5% at different concentrations. The PRD released was prudently studied in water media of pH 6.8 simulated body fluid (SBF) in according to "United State Pharmacopeia (USP38)". The results proved that the release of prednisolone from MCM-41
... Show MoreStick-slip is kind of vibration which associated with drilling operation in around the bottom hole assembly (BHA) due to the small clearance between drill string & the open hole and due to the eccentric rotating of string. This research presents results of specific experimental study that was run by using two types of drilling mud (Fresh water Bentonite & Polymer), with/without Nanoparticle size materials of MgO in various ratios and computes the rheological properties of mud for each concentration [Yield point, plastic viscosity, Av, PH, filter loss (30 min), filter cake, Mud Cake Friction, Friction Factor]. These results then were used to find a clear effects of Nanoparticle drilling mud rheology on stick - slip strength by sev
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Small and Medium Enterprises (SMEs) in Iraq have experienced low performance due to the limited usage of accounting information systems (AIS) and the inability to exploit knowledge of management capabilities (KMC). These deficiencies have led to competitive pressures in the marketplace that have adversely affected their sales and production. This study investigates the role of AIS in terms of operation support, knowledge support, regulatory support, and the role of KMC, including knowledge acquisition, knowledge transfer, and knowledge utilized to enhance organizational performance in Iraqi SMEs. The target population was managers and owners in SMEs using AIS in Iraq’s cities. A non-probability purposive sampling technique was use
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A gracious invitation was extended to us on 9/11/2002 AD, by the University of Tikrit / the Preparatory Committee, for a symposium (Sheikh Daoud Al-Tikriti, and his Scientific Effects), to participate in it.
The symposium was scheduled to be held on the 25th and 26th of March 2003 AD, but God Almighty decreed that our country be occupied, so the Preparatory Committee set another date for the symposium on 10/21/2003 AD.
It was not possible for the symposium to be held until 25-26/4/2004 AD, and many researchers attended, who were assigned to investigate some manuscripts of Sheikh Dawood (may God have mercy on him) or to write about his personal and scientific biography.
And God (Glory be to Him) did not enable us to attend, becau
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
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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
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