Preferred Language
Articles
/
hRb3BIcBVTCNdQwCuy3S
Performance evaluation of frequency division duplex (FDD) massive multiple input multiple output (MIMO) under different correlation models
...Show More Authors

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.

Scopus Clarivate Crossref
View Publication
Publication Date
Mon Jul 01 2019
Journal Name
Arpn Journal Of Engineering And Applied Sciences
PSEUDO RANDOM NUMBER GENERATOR BASED ON NEURO-FUZZY MODELS
...Show More Authors

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

... Show More
View Publication
Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
...Show More Authors

View Publication
Scopus (18)
Crossref (10)
Scopus Clarivate Crossref
Publication Date
Sat Jun 01 2024
Journal Name
International Journal Of Advanced And Applied Sciences
High-accuracy models for iris recognition with merging features
...Show More Authors

Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

... Show More
View Publication
Scopus (3)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Wed Mar 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Review on Models for Evaluating Rock Petrophysical Properties
...Show More Authors

The evaluation of subsurface formations as applied to oil well drilling started around 50 years ago. Generally, the curent review articule includes all methods for coring, logging, testing, and sampling. Also the methods for deciphering logs and laboratory tests that are relevant to assessing formations beneath the surface, including a look at the fluids they contain are discussed. Casing is occasionally set in order to more precisely evaluate the formations; as a result, this procedure is also taken into account while evaluating the formations. The petrophysics of reservoir rocks is the branch of science interested in studying chemical and physical properties of permeable media and the components of reservoir rocks which are associated

... Show More
View Publication Preview PDF
Crossref (6)
Crossref
Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Measuring Positive and Negative Association of Apriori Algorithm with Cosine Correlation Analysis
...Show More Authors

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
...Show More Authors

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

... Show More
View Publication Preview PDF
Publication Date
Wed Mar 15 2023
Journal Name
Journal Of Survey In Fisheries Sciences
The Correlation of DAZ1 Gene Methylation with Azoospermia in Iraqi Infertile Men
...Show More Authors

After about twelve months or maybe more, some people can’t achieve pregnancy. This might be a sign of infertility as a reproductive system disease. The following study was carried out to investigate the DAZ 1 gene methylation level and its association with azoospermia in Iraqi patients. One hundred and fifty human blood samples were collected from from different regions in Baghdad governorate, including (private medicals Labs and the high institute for infertility diagnosis assisted reproductive techniques and Kamal Al- Samara'ay IVF Hospital) from both fertile and infertile men. The control group consists of 50 samples ranging from 22 to 51 years old, while the patient (infertile group) consists of 100 samples ranging between 25 and 51 y

... Show More
Publication Date
Thu May 05 2022
Journal Name
Alkindy College Medical Journal
Correlation between Body Mass Index and Nonalcoholic Fatty Liver Disease
...Show More Authors

Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time  where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as

... Show More
Crossref
Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
...Show More Authors

View Publication
Scopus (6)
Crossref (1)
Scopus Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Plant Archives J.
Phenotypic, genotypic correlation and path coefficient in sunflower (Helianthus annuus)
...Show More Authors

Scopus (1)
Scopus