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Performance evaluation of frequency division duplex (FDD) massive multiple input multiple output (MIMO) under different correlation models
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Massive multiple-input multiple-output (massive-MIMO) is considered as the key technology to meet the huge demands of data rates in the future wireless communications networks. However, for massive-MIMO systems to realize their maximum potential gain, sufficiently accurate downlink (DL) channel state information (CSI) with low overhead to meet the short coherence time (CT) is required. Therefore, this article aims to overcome the technical challenge of DL CSI estimation in a frequency-division-duplex (FDD) massive-MIMO with short CT considering five different physical correlation models. To this end, the statistical structure of the massive-MIMO channel, which is captured by the physical correlation is exploited to find sufficiently accurate DL CSI estimation. Specifically, to reduce the DL CSI estimation overhead, the training sequence is designed based on the eigenvectors of the transmit correlation matrix. To this end, the achievable sum rate (ASR) maximization and the mean square error (MSE) of CSI estimation with short CT are investigated using the proposed training sequence design. Furthermore, this article examines the effect of channel hardening in an FDD massive-MIMO system. The results demonstrate that in high correlation scenarios, a large loss in channel hardening is obtained. The results reveal that increasing the correlation level reduces the MSE but does not increase the ASR. However, exploiting the spatial correction structure is still very essential for the FDD massive-MIMO systems under limited CT. This finding holds for all the physical correlation models considered.

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Limits between the Cosmological Parameters from Strong Lensing Observations for Generalized Isothermal Models
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This paper including a gravitational lens time delays study for a general family of lensing potentials, the popular singular isothermal elliptical potential (SIEP), and singular isothermal elliptical density distribution (SIED) but allows general angular structure. At first section there is an introduction for the selected observations from the gravitationally lensed systems. Then section two shows that the time delays for singular isothermal elliptical potential (SIEP) and singular isothermal elliptical density distributions (SIED) have a remarkably simple and elegant form, and that the result for Hubble constant estimations actually holds for a general family of potentials by combining the analytic results with data for the time dela

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Wormholes Models for the Optimum Matrix Acidizing in Mi4 Unit-Ahdeb Oil Field
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Innovative laboratory research and fluid breakthroughs have improved carbonate matrix stimulation technology in the recent decade. Since oil and gas wells are stimulated often to increase output and maximum recovery, this has resulted in matrix acidizing is a less costly alternative to hydraulic fracturing; therefore, it is widely employed because of its low cost and the fact that it may restore damaged wells to their previous productivity and give extra production capacity. Limestone acidizing in the Mishrif reservoir has never been investigated; hence research revealed fresh insights into this process. Many reports have stated that the Ahdeb oil field's Mishrif reservoir has been unable to be stimulated due to high injection pressures, wh

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Wormholes Models for the Optimum Matrix Acidizing in Mi4 Unit-Ahdeb Oil Field
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Innovative laboratory research and fluid breakthroughs have improved carbonate matrix stimulation technology in the recent decade. Since oil and gas wells are stimulated often to increase output and maximum recovery, this has resulted in matrix acidizing is a less costly alternative to hydraulic fracturing; therefore, it is widely employed because of its low cost and the fact that it may restore damaged wells to their previous productivity and give extra production capacity. Limestone acidizing in the Mishrif reservoir has never been investigated; hence research revealed fresh insights into this process. Many reports have stated that the Ahdeb oil field's Mishrif reservoir has been unable to be stimulated due to high inj

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
Consistency and Consistency in Contemporary Iraqi Painting - Selected Models-: حسين شاكر قاسم العيداني
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  The tagged research is concerned with observation and investigating the concepts of consistency and harmony in contemporary Iraqi painting (selected models) in order to reveal the mechanisms and rules of these two concepts in the artistic field and their mechanisms of operation. How reflected tools Consistency and harmony in contemporary Iraqi painting? What is consistency and what are its mechanisms and principles? Is consistency a unit product quality? Are there similarities between consistency and harmony? What is harmony and its principles and rules? As for the second chapter, it included two topics that dealt with the first topic - consistency and harmony between concept and significance, while the second topic meant - histor

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

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Publication Date
Tue Mar 03 2020
Journal Name
Molecular Biology Reports
Correlation of GSTP1 gene variants of male Iraqi waterpipe (Hookah) tobacco smokers and the risk of lung cancer
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Glutathione-S-transferases (GSTs) play a role in the detoxification of environmental chemicals and mutagens, such as those inhaled during tobacco smoking. There have been conflicting reports concerning GST polymorphisms as risk factors in the development of lung cancer. No studies focused on Arab populations exposed to Waterpipe (WP) tobacco smoke have been undertaken. Here Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) and gene sequenc- ing were applied to analyze allelic variations in GSTP1-rs1695 and -rs1138272 amongst 123 lung cancer patients and 129 controls. The data suggest that WP smoking raised the risk of lung cancer more than three-fold (OR 3.6; 95% CI 2.1–6.0; p < 0.0001). However, there was no s

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Publication Date
Sat Jul 01 2017
Journal Name
Global Journal Of Bio-science And Biotechnology
Efficiency of different denture disinfection methods
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Dentures that are not cleaning and maintained properly may prone to contamination by different microbial pathogens that result in several oral conditions. This study was design to compare the antimicrobial effect of different denture cleansers oxalic, tartaric, citric acids and alkaline peroxide with microwave irradiation on the growth of Candida albicans and Staphylococcus aureus respectively. Microwave oven used to disinfect specimens of heat-activated acrylic resin and soft linear. Oxalic, citric, tartaric acids, and alkaline peroxide were also used. Microorganisms that tested were Candida albicans and Staphylococcus aureus separately. Treatment with microwave or tartaric acid could achieve sterilization of both hot cured acrylic resins

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Scope of using accounting of responsibility under contition of public badget
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Abstract

  The public budget in Iraq is still prepared according to the traditional base that allocates the  amounts of budget the current year based on the budget of previous year with an increase in estimations with random proportions without connecting the input (financial, human resources and asset )with their output (quantitatively and qualitatively)this caused waste and lose in the available resources therefore the output of budget showed be adapted is such a way that achieving connection between its input and output and to be appropriate with the organizational structure of the state without intrinsic change in its work .this may be realized by adopting the accounting of

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