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Evaluation of massive multiple-input multiple-output communication performance under a proposed improved minimum mean squared error precoding
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<span lang="EN-US">The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy- issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become conflicting and divergent then leading EE to decrease so gradually while SE continues increasing logarithmically. The results achieved that for a single-cellular massive MU-MIMO downlink model, our PIMP scheme is the appropriate scenario to achieve higher precoding performance system. Furthermore, both maximum ratio transmission (MRT) and PIMP are suitable for performance improvement in massive MIMO results of EE and SE. So, the main contribution comes with this work that highest EE and SE are belong to use a PIMP which performs better appreciably than MRT at bigger ratio of number of antennas to the number of the users. </span>

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Publication Date
Sun Apr 02 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Forkhead box P3 gene expression and chromosomal analysis in a sample of Iraqi patients with multiple sclerosis
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Background: Multiple Sclerosis disease is a demyelination process which interferes with the neuronal signal transmission, thus leading to different cognitive and physical dysfunctions like optic neuritis, motor, sensory and coordination problems. Recently many researches have been directed toward studying the relation between some genes and multiple sclerosis. Among the important genes to be studied in multiple sclerosis is the forkhead box P3 gene expression.
Objectives: The aims of the present work were to study the expression of forkhead box P3 gene by real time polymerase chain reaction, and to perform chromosomal analysis on the multiple sclerosis patients peripheral blood lymphocytes.
Patients and methods: A case-control stud

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Publication Date
Fri Apr 30 2021
Journal Name
Iraqi Journal Of Science
Iris Identification Based on the Fusion of Multiple Methods
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Iris recognition occupies an important rank among the biometric types of approaches as a result of its accuracy and efficiency. The aim of this paper is to suggest a developed system for iris identification based on the fusion of scale invariant feature transforms (SIFT) along with local binary patterns of features extraction. Several steps have been applied. Firstly, any image type was converted to  grayscale. Secondly, localization of the iris was achieved using circular Hough transform. Thirdly, the normalization to convert the polar value to Cartesian using Daugman’s rubber sheet models, followed by histogram equalization to enhance the iris region. Finally, the features were extracted by utilizing the scale invariant feature

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
symmetric analysis of multiple variables classified ranked orthogonal polynomials
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MCA has gained a reputation for being a very useful statistical method for determining the association between two or more categorical variables and their graphical description. For performance this method, we must calculate the singular vectors through (SVD). Which is an important primary tool that allows user to construct a low-dimensional space to describe the association between the variables categories. As an alternative procedure to use (SVD), we can use the (BMD) method, which involves using orthogonal polynomials to reflect the structure of ordered categorical responses. When the features of BMD are combined with SVD, the (HD) is formed. The aim of study is to use alternative method of (MCA) that is appropriate with order

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Publication Date
Mon Sep 01 2014
Journal Name
19th International Conference On Methods And Models In Automation And Robotics (mmar) 2014
A PSO-optimized type-2 fuzzy logic controller for navigation of multiple mobile robots
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Publication Date
Mon Feb 01 2016
Journal Name
Ieee Transactions On Circuits And Systems Ii: Express Briefs
Adaptive Multibit Crosstalk-Aware Error Control Coding Scheme for On-Chip Communication
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The presence of different noise sources and continuous increase in crosstalk in the deep submicrometer technology raised concerns for on-chip communication reliability, leading to the incorporation of crosstalk avoidance techniques in error control coding schemes. This brief proposes joint crosstalk avoidance with adaptive error control scheme to reduce the power consumption by providing appropriate communication resiliency based on runtime noise level. By switching between shielding and duplication as the crosstalk avoidance technique and between hybrid automatic repeat request and forward error correction as the error control policies, three modes of error resiliencies are provided. The results show that, in reduced mode, the scheme achie

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Publication Date
Mon Feb 01 2021
Journal Name
Https://www.researchgate.net/journal/university-of-baghdad-engineering-journal-1726-4073
Electrical Conductivity as a General Predictor of Multiple Parameters in Tigris River Based on Statistical Regression Model
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Surface water samples from different locations within Tigris River's boundaries in Baghdad city have been analyzed for drinking purposes. Correlation coefficients among different parameters were determined. An attempt has been made to develop linear regression equations to predict the concentration of water quality constituents having significant correlation coefficients with electrical conductivity (EC). This study aims to find five regression models produced and validated using electrical conductivity as a predictor to predict total hardness (TH), calcium (Ca), chloride (Cl), sulfate (SO4), and total dissolved solids (TDS). The five models showed good/excellent prediction ability of the parameters mentioned above, which is a very

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Extend Differential Transform Methods for Solving Differential Equations with Multiple Delay
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In this paper, we present an approximate analytical and numerical solutions for the differential equations with multiple delay using the extend differential transform method (DTM). This method is used to solve many linear and non linear problems.

 

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error
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Multiple linear regressions are concerned with studying and analyzing the relationship between the dependent variable and a set of explanatory variables. From this relationship the values of variables are predicted. In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. Three methods were compared (general least squares, M robust, and Laplace robust method). We have employed the simulation studies and calculated the statistical standard mean squares error with sample sizes (15, 30, 60, 100). Further we applied the best method on the real experiment data representing the varieties of

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
SMS Spam Detection Using Multiple Linear Regression and Extreme Learning Machines
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     With the growth of the use mobile phones, people have become increasingly interested in using Short Message Services (SMS) as the most suitable communications service. The popularity of SMS has also given rise to SMS spam, which refers to any unwanted message sent to a mobile phone as a text. Spam may cause many problems, such as traffic bottlenecks or stealing important users' information. This paper,  presents a new model that extracts seven features from each message before applying a Multiple Linear Regression (MLR) to assign a weight to each of the extracted features. The message features are fed into the Extreme Learning Machine (ELM) to determine whether they are spam or ham. To evaluate the proposed model, the UCI bench

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