Maral Nizamuddin Zain Al-Abidin Ali

Year: 2024

Academic Degree: Master

Supervisor Type: Supervisor

Supervisor State: In Progress

Earthquake prediction system

PhD

Sep 1, 2013 - Jul 1, 2017

Wireless Communication Engineering
University Malaysia Pahang
Malaysia

Master degree

Sep 1, 2011 - Jul 1, 2013

Wireless Communication Engineering
University Tenaga National
Malaysia

Bachelor degree

Aug 1, 2006 - Jul 1, 2010

Computer Engineering Techniques
AlHadba University College
Iraq

رئيس قسم تقنيات الشبكات وبرمجيات الحاسوب [رئيس قسم تقنيات الشبكات وبرمجيات الحاسوب]

Aug 26, 2024 - Present

رئيس قسم، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك ، العراق

معاون العميد للشؤون العلمية والطلبة [معاون العميد للشؤون العلمية والطلبة]

Sep 13, 2022 - Aug 26, 2024

معاون عميد، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك ، العراق

رئيس قسم التقنيات الالكترونية [رئيس قسم التقنيات الالكترونية]

Mar 18, 2021 - Sep 12, 2021

رئيس قسم، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك ، العراق

معاون العميد للشؤون العلمية والطلبة [معاون العميد للشؤون العلمية والطلبة]

Mar 25, 2019 - Mar 17, 2021

معاون عميد، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك ، العراق

مسؤول الشعبة العلمية [مسؤول الشعبة العلمية]

Sep 18, 2017 - Mar 24, 2019

مسؤول شعبة، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك ، العراق

مسؤول وحدة التأهيل والتوظيف والمتابعة [مسؤول وحدة التأهيل والتوظيف والمتابعة]

Jun 18, 2017 - Sep 17, 2017

مسؤول وحدة، المعهد التقني الحويجة، الجامعة التقنية الشمالية
كركوك، العراق

مهندس حاسوب [مسؤول مختبر]

Sep 1, 2014 - Jul 1, 2015

مسؤول مختبر، جامعة بهانك الماليزية
بهانك، ماليزيا

مهندس حاسوب [مسؤول مختبر]

Sep 1, 2012 - Dec 1, 2012

مسؤول مختبر، جامعة الطاقة الوطنية
كوالالمبور، ماليزيا

مهندس حاسوب [مسؤول وحدة الحاسوب]

Feb 2, 2009 - Nov 1, 2010

مهندس حاسوب، بلدية ناحية الرياض

Design and implement a self-managed computer network for electronic exams and sharing

Jul 1, 2020

Journal Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)

publisher Institute of Advanced Engineering and Science.

Issue 1

Volume 19

To implement electronic exams and material resources sharing (which is usually limited), an operating base is must be available for trading information and correspondence management. In this paper, self-managed computer networks, no server was designed. This network aims to share information and correspondence management between the laboratory`s computers. A specific software called Packet tracer used for designing and simulating the network, also for choosing the right medium and install the IP address so that a maximum of data flowing with minimum time and no data loss can be achieved. A class-C IP address was selected since it is the famous class and it doesn`t need any special equipment. Also it has a wide range of of computers in case of expanding the network. We didn`t use a wireless medium to protect the network from hacking. The network was based on an Ethernet medium and a star-connection between the computers with an average signal distributer. An excellent result was achieved after testing the network with a low error percentage, as shown in the result section of this paper.

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MVDR algorithm based linear antenna array performance assessment for adaptive beamforming application

May 1, 2017

Journal Journal of Engineering Science and Technology

publisher School of Engineering, Taylor’s University

Issue 5

Volume 12

The performance of Minimum Variance Distortionless Response (MVDR) beamformer is sensitive to errors such as the steering vector errors, the finite snapshots, and unsatisfactory null-forming level. In this paper, a combination of MVDR with linear antenna arrays (LAAs) for two scanning angles process in the azimuth and elevation are used to illustrate the MVDR performance against error which results in acquiring the desired signal and suppressing the interference and noise. The impact of various parameters, such as the number of elements in the array, space separation between array elements, the number of interference sources, noise power level, and the number of snapshots on the MVDR are investigated. The MVDR performance is evaluated with two important metrics: beampattern of two scanning angles and Signal to Interference plus Noise Ratio (SINR). The results found that the MVDR performance improves as the number of array elements increases. The beampattern relies on the number of elements and the separation between array elements. The best interelement spacing obtained is 0.5λ that avoids grating lobes and mutual coupling effects. Besides, the SINR strongly depends on the noise power label and a number of snapshots. When the noise power label increased, the MVDR performance degraded as well the null width increases in the elevation direction as well as more accurate resolution occurred when the number of snapshots increased. Finally, it is found the proposed method achieves SINR better than existing techniques.

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Assessment of Area Energy Efficiency of LTE Macro Base Stations in Different Environments

Mar 1, 2015

Journal Journal of Telecommunications and Information Technology (JTIT)

publisher Institute of Communications - National Research Institute

Energy efficiency (EE) of wireless telecommunications has become a new challenge for the research community, governments and industries in order to reduce CO2 emission and operational costs. EE of base stations (BSs) in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall negative impact to the environment and economic issues for wireless network operators. In this paper, a framework focuses on the Area Energy Efficiency (AEE) evaluation of LTE BSs is presented. The parameters affect on the AEE and the coverage area of LTE BS in different scenarios are investigated. AEE analysis has been done using a few key performance indicators including transmit power, bandwidth, load factor with the assumption of different scenarios (urban, suburban and rural). The simulation results show that the LTE BSs have better AEE in an urban environment for cell radius less than 750 m compare with the suburban and rural environments. Furthermore, it is obvious that there is a strong influence of traffic load, BW and transmission power on AEE of LTE network. On the other hand, AEE increases significantly as the BW size increases. Finally, it has been shown that the AEE of LTE macro BS decreases with increasing the percentage of traffic load for all scenarios.

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