Preferred Language
Articles
/
hxb4BIcBVTCNdQwCJS37
A Computationally Efficient Gradient Algorithm for Downlink Training Sequence Optimization in FDD Massive MIMO Systems
...Show More Authors

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.

Scopus Clarivate Crossref
View Publication
Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
...Show More Authors

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Scopus Crossref
Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
...Show More Authors

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Wed Oct 12 2022
Journal Name
Axioms
Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
...Show More Authors

Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

... Show More
View Publication
Scopus (3)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Sun Dec 01 2019
Journal Name
Applied Soft Computing
A new evolutionary multi-objective community mining algorithm for signed networks
...Show More Authors

View Publication
Scopus (8)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Tue Oct 16 2018
Journal Name
Springer Science And Business Media Llc
MOGSABAT: a metaheuristic hybrid algorithm for solving multi-objective optimisation problems
...Show More Authors

Scopus (68)
Crossref (51)
Scopus Clarivate Crossref
Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Financing Cost Optimization in Construction Sector: A Review
...Show More Authors

The main aim of this research is to introduce financing cost optimization and different financing alternatives. There are many studies about financing cost optimization. All previous studies considering the cost of financing have many shortcomings, some considered only one source of financing as a credit line without taking into account different financing alternatives. Having only one funding alternative powers, restricts contractors and leads to a very specific financing model. Although it is beneficial for the contractor to use a long-term loan to minimize interest charges and prevent a substantial withdrawal from his credit line, none of the existing financial-based planning models have considered long-term loans in

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Dec 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Hydrodynamic Pressure Gradient Correlation of Some Iraqi Oil Wells
...Show More Authors

Empirical equation has been presented to predict the optimum hydrodynamic
pressure gradient with optimum mud flow rate (one equation) of five Iraqi oil wells
to obtain the optimum carrying capacity of the drilling fluid ( optimum transport
cuttings from the hole to the surface through the annulus).
This equation is a function of mud flow rate, mud density and penetration
rate without using any charts or graphs.
The correlation coefficient accuracy is more than 0.9999.

View Publication Preview PDF
Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Suggested Model for Using a Students Attendance Management Information Systems/ A Case Study In Lebanese French University/ Erbil
...Show More Authors

This study aims to design unified  electronic information system to manage students attendance in Lebanese French university/Erbil, as a system that simplifies the process of entering and counting the students absence, and generate absence reports to expel students who passed  the acceptable limit of being absent, and by that we can replace the traditional way of  using papers to count absence,  with  a complete electronically system for managing students attendance, in a way that makes the results accurate and unchangeable by the students.

            In order to achieve the study's objectives, we designed an information syst

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri May 31 2024
Journal Name
Journal Of Current Medical Research And Opinion
Comparing Different Training Methods in Cardiopulmonary Resuscitation CPR: A Narrative Review
...Show More Authors

Publication Date
Sun Oct 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A novel data offloading scheme for QoS optimization in 5G based internet of medical things
...Show More Authors

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

... Show More