Performance Evaluation and Comparison Between LDPC and Turbo Coded MC-CDMA

Aqiel N.  Almaamory; Husam Abduldaem.  Mohammed

doi:10.31026/j.eng.2012.04.05

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Publication Date

Fri Jul 21 2023

Journal Name

Journal Of Engineering

Volume

18

Issue Number

04

DOI

10.31026/j.eng.2012.04.05

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Performance Evaluation and Comparison Between LDPC and Turbo Coded MC-CDMA

MC-CDMA

PARALLEL TURBO CODE

LDPC

SUM-PRODUCT DECODING ALGORITHM

CONVOLUTIONAL CODING

Aqiel N. Almaamory

Husam Abduldaem. Mohammed

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This work presents a comparison between the Convolutional Encoding CE, Parallel Turbo code and Low density Parity Check (LDPC) coding schemes with a MultiUser Single Output MUSO Multi-Carrier Code Division Multiple Access (MC-CDMA) system over multipath fading channels. The decoding technique used in the simulation was iterative decoding since it gives maximum efficiency at higher iterations. Modulation schemes used is Quadrature Amplitude Modulation QAM. An 8 pilot carrier were
used to compensate channel effect with Least Square Estimation method. The channel model used is Long Term Evolution (LTE) channel with Technical Specification TS 25.101v2.10 and 5 MHz bandwidth bandwidth including the channels of indoor to outdoor/ pedestrian channel and Vehicular channel. The results showed that the performance of the proposed system was better when the LDPC was used as a coding technique

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Publication Date

Tue Nov 09 2021

Journal Name

Abu Dhabi International Petroleum Exhibition & Conference

Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

evolutionary algorithm

gas lift

artificial intelligence

upstream oil & gas

machine learning

optimization problem

correlation

presented

allocation

reservoir pressure

Mohammed Ahmed

Omar F.

Dhifaf Jaafar

Haider Abdulmuhsin

Mustafa Alaulddin

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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More

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Publication Date

Thu Mar 30 2023

Journal Name

Journal Of Economics And Administrative Sciences

An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type

Regression Tree Classification (CART)

Radial Basis Function (RBF)

Genetic Algorithm (GA)

شجرة الانحدار التصنيفية

شبكة دالة الاساس الشعاعي

الخوارزمية الجينية

Hiba

Sabah

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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date

Sun Jun 11 2017

Journal Name

Ibn Al-haitham Journal For Pure And Applied Sciences

Artificial Neural Network for TIFF Image Compression

image compression

MultiLayer Perceptron (MLP)

Back-Propagation algorithm

Compress ratio

Mean Square Error (MSE)

Peak signal-to-noise ratio (PSNR)

Huda Dheyauldeen

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The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256) in our research, compressed them by using MLP for each

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Publication Date

Sat Jan 01 2022

Journal Name

Turkish Journal Of Physiotherapy And Rehabilitation

classification coco dataset using machine learning algorithms

learning Machine

classification

MCOCO dataset

K Nearest Neighbor's

Stochastic Gradient Descent learning (SGD)

Logistic Regression Algorithm(LR)

and Multi-Layer Perceptron (MLP).

Rasool

Bushra

Raaid

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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Publication Date

Sat Dec 30 2023

Journal Name

Journal Of Economics And Administrative Sciences

The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data

البيانات الطولية

نموذج الشرائح B-spline التكعيبية اللامعلمية

التحليل العنقودي

طريقة الاتجاه المتناوب لخوارزمية المضاعف ADMM.

Longitudinal Data

Nonparametric Cubic B-Spline

Cluster Analysis

The Alternating Direction Method for Multiplier Algorithm ADMM.

Noor

Suhail

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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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