Ali Najdet Nasret -

Ali Najdet Nasret

Research Interests

Gender	MALE
Place of Work	Kirkuk Technical Medical Institute
Department	Community Health
Position	The vice of dean
Qualification	Ph.d
Speciality	Electronic and communication
Email	alinajdet@ntu.edu.iq
Phone	009647735524119
Address	iraq, mosul, Mosul, Iraq

Academic Links

Download CV

Biography

Assist. Prof. Dr. Ali Najdet Nasret Coran I'm an academic and researcher in the field of Electronics and Communication Engineering at Northern Technical University (NTU), Iraq. i had a B.Sc. in Electrical Engineering from Al-Mustansiriyah University, Baghdad, in 2010, followed by an M.Sc. in Communication and Electronics from Cankaya University, Ankara, Turkey, in 2014and later i obtained a Ph.D. in Communication Engineering in 2021.

Currently I'm serving as an Assistant Professor at NTU, and i'm also held administrative and academic responsibilities, including leadership roles at the Kirkuk Technical Institute and teaching and supervision activities cover a wide range of topics in electronics, communication systems, and signal processing.

my research focuses on the intersection of signal processing, speech analysis, and artificial intelligence, with applications in disease detection, speech recognition, fault detection, and wireless communication systems. i published published multiple papers in international journals and conferences on subjects such as neural network-based fault detection, microstrip antenna design, and speech recognition in noisy environments.

In addition to my research, i have skilled in MATLAB and Python programming, actively contributing to the development of AI-driven engineering applications. and i committed to advancing knowledge through both teaching and research collaborations with academic institutions worldwide.

Languages

ARABIC (85%)

English (84%)

Turkish (80%)

Skills

Machine learing and their application (90%)

Teaching english ( grammar and listening and speaking and writing ) (99%)

Artificial Intellegence (80%)

working experience

Academic Qualification

M.Sc. in electronic and communication

Nov 9, 2012 - Oct 6, 2014

Ph.D. in electronic and communication

Jan 1, 2016 - Dec 3, 2021

Bachelor of Electrical Engineering

Sep 1, 2005 - Jul 30, 2010

Publications

Enhancement automatic speech recognition by deep neural networks

Nov 10, 2021

Journal Periodicals of Engineering and Natural Sciences

publisher International University of Sarajevo

DOI 10.21533/pen.v9i4.2450

Issue 4

Volume 9

The performance of speech recognition tasks utilizing systems based on deep learning has improved dramatically in recent years by utilizing different deep designs and learning methodologies. A popular way to boosting the number of training data is called Data Augmentation (DA), and research shows that using DA is effective in teaching neural network models how to make invariant predictions. furthermore, EM approaches have piqued machine-learning researchers' attention as a means of improving classifier performance. In this study, have been presented a unique deep neural network speech recognition that employs both EM and DA approaches to improve the system's prediction accuracy. firstly, reveal an approach based on vocal tract length disturbance that already exists and then propose a Feature perturbation is an alternative Data Augmentation approach. in order to make amendment training data sets. This is followed by an integration of the posterior probabilities obtained from several DNN acoustic models trained on diverse datasets. The study's findings reveal that the proposed system's recognition skills have improved.

Read Publication

Separately excited DC motor speed using ANN neural network

Oct 11, 2021

Journal AIP Conference Proceedings

publisher American Institute of Physics Inc.

DOI 10.21533/pen.v9i4.2450

Separately Excited Direct Current Motors (SEDCM) is termed by high efficiency in electrical traction manufacturing. SEDCMs are utilized by high power applications such as aircrafts and ships traction. Speed control is more likely required to maintain the performance of the motor in different load scenarios. Conventional methods of speed control such as proportional integral controller (PIC) are reported good performance in error tackling but it may consume longer time and computational cost. In this paper, computational speed controller is proposed which uses neural network to predict speed and then to produce the reference voltage in order to update the armature terminal voltage. In this study have been assumed a three layers neural network to implement the control on speed of motor and the model is outperformed over the conventional controller models.

Read Publication

Design of Multiband Slot Patch Antennas for Modern Wireless Applications

Nov 30, 2019

Journal International Journal on Communications Antenna and Propagation (IRECAP)

publisher PRAISE WORHTY PRIZ

DOI https://doi.org/10.15866/irecap.v10i5.19071

Issue 10

Volume 5

In the past few years, microstrip antenna have been used in many applications because of their thin planar profile that could be easily integrated into various surfaces of aircraft, rockets and other customer-beneficial products. They are easily integrated into the same board and they allow the addition of active devices. These antennas are used in different areas like satellite navigation, mobile communication, automobiles, internet services and radars. In this study, antennas of the Coplanar (CPW-Fed) system have been used. Multi-band microstrip antennas have been designed and simulated with the help of the HFSS program about the return loss (S11). The goal of this study is to obtain multiband for working on several frequencies. Microstrip patch slot antennas using Coplanar (CPW- Fed) and working on different frequencies have been designed. This design is used in modern wireless appliances.

Read Publication

The impact of relay node deployment in vehicle ad hoc network: Reachability enhancement approach

Oct 18, 2019

Journal 2019 Global Conference for Advancement in Technology (GCAT)

publisher IEEE

DOI 10.21533/pen.v9i4.2450

Speaker VANET or vehicular ad hoc network is intelligent means of transportation which is essentially ensuring the safety norms. This technology can be established in any road such as highway or inter-city urban roads; it is basically a set of mobile vehicles connected with static base station. VANET is adopted ad hoc nature where dynamic vehicles are capable to communicate with each other due to less infrastructure network strategy as no clear administration tasks are functional. However, VANET is reported efficient in low and medium speeds i.e. 10 through 40 km/h. This paper aims to enhance network reachability in random traffic conditions. Results shown that 15% enhancement after deploying single RSU and 25% enhancement after deploying two RSUs.

Read Publication

Conferences