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ijcpe-1045
Accurate Petrophysical Interpretation of Carbonate using the Elemental Capture Spectroscopy (ECS)
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Elemental capture spectroscopy (ECS) is an important tool in the petroleum industry for determining the composition and properties of rock formations in a reservoir. Knowledge of the types and abundance of different minerals in the reservoir is crucial for accurate petrophysical interpretation, reservoir engineering practices, and stratigraphic correlation. ECS measures the elemental content of the rock, which directly impacts several physical properties that are essential for reservoir characterization, such as porosity, fluid saturation, permeability, and matrix density. The ability to accurately determine these properties leads to better reservoir mapping, improved production, and more effective resource management. Accurately determining the mineralogy and porosity of carbonate rocks and other materials is the aim of this paper. Calcite, dolomite, quartz, clay (illite), anhydrite, and pyrite, in addition to water as a fluid, are taken into account in the computation. The formation's lithology and porosity can be ascertained from this data. When compared to the core descriptions in the geological report, the results demonstrated a distinct zone of unique lithology with good prediction accuracy.

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Extraction of Monocyclic Aromatic Hydrocarbons From Petroleum Products Using Sulfolane as Industrial Solvent
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            Liquid – liquid equilibria data were measured at 293.15 K for the pseudo ternary system (sulfolane + alkanol) + octane + toluene. It is observed that the selectivity of pure sulfolane increases with cosolvent methanol but decreases with increasing the chain length of hydrocarbon in 1-alkanol. The nonrandom two liquid (NRTL) model, UNIQUAC model and UNIFAC model were used to correlate the experimental data and to predict the phase composition of the systems studied. The calculation based on NRTL model gave a good representation of the experimental tie-line data for all systems studied. The agreement between the correlated and the experimental results was very good

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Inverse Kinematics Analysis and Simulation of a 5 DOF Robotic Arm using MATLAB
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Kinematics is the mechanics branch which dealswith the movement of the bodies without taking the force into account. In robots, the forward kinematics and inverse kinematics are important in determining the position and orientation of the end-effector to perform multi-tasks. This paper presented the inverse kinematics analysis for a 5 DOF robotic arm using the robotics toolbox of MATLAB and the Denavit-Hartenberg (D-H) parameters were used to represent the links and joints of the robotic arm. A geometric approach was used in the inverse kinematics solution to determine the joints angles of the robotic arm and the path of the robotic arm was divided into successive lines to accomplish the required tasks of the robotic arm.Therefore, this

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Publication Date
Tue Dec 13 2022
Journal Name
Lecture Notes In Networks And Systems
Design and FPGA Implementation of Matrix Multiplier Using DEMUX-RCA-Based Vedic Multiplier
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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Geographical Distribution of Power Plants in Iraq in 2015 Using Geographic Information Systems
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The study aims to study the geographical distribution of electricpower plants in Iraq, except the governorates of Kurdistan Region (Dohuk, Erbil, Sulaymaniyah) due to lack of data.

In order to reach the goal of the research was based on some mathematical equations and statistical methods to determine how the geographical distribution of these stations (gas, hydropower, steam, diesel) within the provinces and the concentration of them as well as the possibility of the classification of power plants in Iraq to facilitate understanding of distribution in a scientific manner is characterized by objectively.

The most important results of the research are that there are a number of factors that led to the irregular distribution

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Adsorption of Indigo Carmen Dye by Using Corn Leaves as Natural Adsorbent Material
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    In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R2 = 0.9937) and followed pseudo second order kinetic. The hi

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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Optimal control of compliant planar robot for safe impact using steepest descent technique
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Performance Study of AODV, GRP and OSPFv3 MANET Routing Protocols Using OPNET Modeler
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A Mobile Ad hoc Network (MANET) is a collection of mobile nodes, that forms on the fly a temporary wireless multi-hop network in a self-organizing way, without relying on any established infrastructure. In MANET, a pair of nodes exchange messages either over a direct wireless link, or over a sequence of wireless links including one or more intermediate nodes. For this purpose, an efficient routing protocol is required. This paper introduced performance study of three of MANET protocols (AODV, GRP and OSPFv3). This study was one of the newer studies because wireless communication played an important role in today’s application and the field of mobile ad hoc network becomes very popular for the researchers in the last years. This study w

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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Removal of Lead (II) from Aqueous Solution Using Chitosan Impregnated Granular Activated Carbon
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The use of biopolymer material Chitosan impregnated granular activated carbon CHGAC as adsorbent in the removal of lead ions  pb.2+   from aqueous solution was studied using batch adsorption mode. The prepared CHGAC was characterized by Scanning Electronic Microscopy (SEM) and atomic-absorption  pectrophotometer. The adsorption of lead ions onto Chitosan-impregnated granular activated carbon was examined as a function of adsorbent weight, pH and
contact time in Batch system. Langmuir and Freundlich models were employed to analyze the resulting experimental data demonstrated that better fitted by Langmuir isotherm model than Freundlich model, with good correlation coefficient. The maximum adsorption capacity calculated f

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Comparative analysis of parameter estimation methods for Meixner process using wavelet packet transform
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The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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