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A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
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Future wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date very challenging. Although advanced iterative algorithms have been developed to address this challenge, they exhibit slow convergence speed and thus deliver high latency and computational complexity. To overcome this challenge, we propose a computationally efficient conjugate gradient-descent (CGD) algorithm based on the Riemannian manifold in order to optimize the DL training sequence at base station (BS), while improving the convergence rate to provide a fast CSI estimation for an FDD m-MIMO system. To this end, the sum rate and the computational complexity performances of the proposed training solution are compared with the state-of-the-art iterative algorithms. The results show that the proposed training solution maximizes the achievable sum rate performance, while delivering a lower overall computational complexity owing to a faster convergence rate in comparison to the state-of-the-art iterative algorithms.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Heterogeneity on Recovery Factor for Carbonate Reservoirs. A Case Study for Mishrif Formation in West Qurna Oilfield, Southern Iraq
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Oil recovery could be impacted by the relation between vertical permeability (Kv) and horizontal permeability (Kh) (Kv/Kh). 4816 plugs that have been getting hold of 18 wells of Mishrif formation in the West Qurna oilfield were used. Kv/Kh data provided some scatter, but the mean is ~1. Kv/Kh =1 was used for the Petrel model before upscaling according to the heterogeneity of each layer.

Kv/Kh values for Mishrif Formation in West Qurna Oilfield are 0.8 for relatively homogeneous, 0.4 for heterogeneous rock, and 0.1 for cap rocks (CRII).

   Eclipse TM was used for reservoir simulation. PVT and SCAL data e

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Publication Date
Wed May 10 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Comparative Anatomical Study of Petioles to Thirteen Taxa for Scutellaria L. (Labiatae) in Iraq
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   Petioles of nine species and four subspecies for Scutellaria L. which are growing wildly in Iraq were studied anatomically. Systmatic importance for the cross sections of those petioles were found. The winged petioles were seen in all taxa but they were different in their shapes , some of them U – shaped but they were semi ellipsoid in others , also they were different in their numbers of vascular bundles in the wings , and the shapes of central vascular bundles , so those  taxa were divided into groups .

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Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
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This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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Publication Date
Fri Oct 07 2022
Journal Name
Texas Journal Of Engineering And Technology
Estimation of Pore Pressure and In-Situ Stresses for Halfaya Oil Field: A Case Study
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Publication Date
Thu Aug 01 2019
Journal Name
Ieee Internet Of Things Journal
A New Task Allocation Protocol for Extending Stability and Operational Periods in Internet of Things
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Mon Feb 21 2022
Journal Name
Научный форум: Филология, искусствоведение и культурология: сб. ст. по материалам Lvi междунар. науч.-практ. конф. – No 2 (56). – М
Comparative analysis of zoomorphic metaphors in Russian and Arabic as a method for studying linguoculturology
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: zonal are included in phraseological units, form metaphorical names for a person, give him various emotional and evaluative characteristics. This article examines the topic of zoomorphic metaphors that characterize a person in the Russian and Arabic languages in the aspect of their comparative analysis, since the comparative analysis of the metaphorical meanings of animalisms is an important method for studying cultural linguistics, since zoomorphic metaphors are a reflection of culture in a language.

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Numerical investigation for Natural Convection in a square Enclosure with partially active thermal sides' wall
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Three-dimensional cavity was investigated numerical in the current study filled with porous medium from a saturated fluid. The problem configuration consists of two insulated bottom and right wall and left vertical wall maintained at constant temperatures at variable locations, using two discretized heaters. The porous cavity fluid motion was represented by the momentum equation generalized model. The present investigation thermophysical parameters included the local thermal equilibrium condition. The isotherms and streamlines was used to examine energy transport and momentum. The meaning of changing parameters on the established average Nusselt number, temperature and velocity distribution are highlighted and discussed.

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Publication Date
Mon Jun 12 2017
Journal Name
Day 3 Wed, June 14, 2017
A New Practical Method for Predicting Equivalent Drainage Area of Well in Tight Gas Reservoirs
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Abstract<p>The tight gas is one of the main types of the unconventional gas. Typically the tight gas reservoirs consist of highly heterogeneous low permeability reservoir. The economic evaluation for the production from tight gas production is very challenging task because of prevailing uncertainties associated with key reservoir properties, such as porosity, permeability as well as drainage boundary. However one of the important parameters requiring in this economic evaluation is the equivalent drainage area of the well, which relates the actual volume of fluids (e.g gas) produced or withdrawn from the reservoir at a certain moment that changes with time. It is difficult to predict this equival</p> ... Show More
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