Hazem noori abdulrazzak

@ruc.edu.iq

Computer communication engineering -
Al-Rafidain University College



                       

https://researchid.co/hazemnoori

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Engineering

9

Scopus Publications

45

Scholar Citations

5

Scholar h-index

1

Scholar i10-index

Scopus Publications



  • Electroluminescence Images for Solar Cell Fault Detection Using Deep Learning for Binary and Multiclass Classification
    Rawad Ahmed Ibrahim Almashhadani, Goh Chin Hock, Farah Hani Bt Nordin, and Hazem N. Abdulrazzak
    Seventh Sense Research Group Journals

  • A Multi-Layer Deep Learning System for Fault Detection Solar Cell Electroluminescence Images
    Rawad Almashhadani, Goh Chin Hock, Farah Hani Nordin, Hazem Noori Abdulrazzak, and Zaid Ali Abbas
    IEEE
    An automatic solar defect detection with a classification system was proposed using deep learning. This paper focuses on solar defects in photovoltaic systems identified through electroluminescence (EL) images. Convolutional Neural Networks (CNNS), Artificial Neural Networks (ANN), Support Vector Machine (SVM), and a pre-trained VGG16 network for feature extraction were compared in this paper. They adopted two classification strategies: binary classification (defective or non-defective) and multi-class classification the class names are 0%, 33%, 67%, and 100% (here % represents the percentage of defectiveness), which represents the defect likelihood. The effectiveness of the model was evaluated using various metrics, including the recall, precision, accuracy, and F1-score for two and four classes and obtained on, supported by confusion matrices. VGG-16 model outperformed other models and achieved an accuracy of 89% for 2-classes and 93% for 4-classes.

  • Fuzzy C-Means Clustering Approach for Green IoT in Smart Cities
    Aya Ayad Hussein and Hazem N. Abdulrazzak
    IEEE
    Cluster-based routing or Hierarchical is a widely recognized approach with particular benefits in terms of scalability and communication efficiency. In Wireless Sensor Networks supported $IoT$, the utilization of clustered routing is a cost-effective method of data collection and transmission, where nodes with the most energy remaining can be utilized to collect and transmit data. This paper proposed a soft Fuzzy C-Means Dynamic Clustering (FCM-DC) Approach. A new Cluster Head (CH) selection technique was presented also. The proposed model was compared with an existing cluster based routing protocol, LEACH protocol, and LEACH-C protocol. The proposed FCM-DC model reduce the packet delay about 16% in 50 nodes scenario and 86% in 100 nodes scenario compared with LEACH.

  • A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET
    Hazem Noori Abdulrazzak, Goh Chin Hock, Nurul Asyikin Mohamed Radzi, and Nadia Mei Lin Tan
    Institute of Electrical and Electronics Engineers (IEEE)
    Clustering evaluation techniques are important to check the clustering algorithm quality. High cluster similarity help to reduce the distance between a node to node within the cluster, also good separation was more important to avoid overlapping clusters. The network performance will increase and the signal will be high. Many researchers proposed different validation indexes such as Davies–Bouldin, Dunn, and Silhouette indexes. These cluster validation indexes focus on the internal or external cluster similarity, and some of them deal with both cases. The employing of graph-based distance to non-spherical clusters and selection of reference points will not be effective all the time because the average distance between reference points and all nodes will be changed dynamically such as in the VANET application. To solve this problem a dynamic sample node should be selected or the similarity of all nodes should be checked. This paper proposes a new Minimum intra-distance and Maximum inter-distance Index (M2I) to improve these indexes. The proposed index checks the internal similarity and the external distance among all nodes from cluster to cluster to ensure that high separation will occur. M2I checks the similarity from node to node within the cluster and cluster to cluster. The proposed index will be an improvement of all high-rank indexes. The proposed index was applied in different scenarios (VANET and real datasets scenarios) and compared with other indexes. The index result shows that the proposed M2I outperforms the others. The M2I accuracy is 100% in the VANET scenario and 89% in the real datasets scenario.

  • Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network
    Hazem Noori Abdulrazzak, Goh Chin Hock, Nurul Asyikin Mohamed Radzi, Nadia M. L. Tan, and Chiew Foong Kwong
    MDPI AG
    Many researchers have proposed algorithms to improve the network performance of vehicular ad hoc network (VANET) clustering techniques for different applications. The effectiveness of the clustering model is the most important challenge. The K-Means clustering algorithm is an effective algorithm for multi-clusters that can be used in VANETs. The problems with the K-Means algorithm concern the selection of a suitable number of clusters, the creation of a highly reliable cluster, and achieving high similarity within a cluster. To address these problems, a novel method combining a covering rough set and a K-Means clustering algorithm (RK-Means) was proposed in this paper. Firstly, RK-Means creates multi-groups of vehicles using a covering rough set based on effective parameters. Secondly, the K-value-calculating algorithm computes the optimal number of clusters. Finally, the classical K-Means algorithm is applied to create the vehicle clusters for each covering rough set group. The datasets used in this work were imported from Simulation of Urban Mobility (SUMO), representing two highway scenarios, high-density and low-density. Four evaluation indexes, namely, the root mean square error (RMSE), silhouette coefficient (SC), Davies–Bouldin (DB) index, and Dunn index (DI), were used directly to test and evaluate the results of the clustering. The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. The result of the compression showed that RK-Means had high cluster similarity, greater reliability, and error reductions of 32.5% and 24.2% compared with OK-Means and K-Means++, respectively.

  • A Novel Minimized Energy Routing Technique for IoT Assisted WSN


  • Minimizing Energy Consumption in Roadside Unit of Zigzag Distribution Based on RS-LS Technique
    Hazem Noori Abdulrazzak, Nadia M. L. Tan, and Nurul Asyikin Mohd. Radzi
    IEEE
    The dedicated vehicular ad-hoc network (VANET) is a communication model as vehicles can communicate with other vehicles directly or via fixed nodes called Roadside Units (RSU). It has become necessary to find supporting protocols for RSU to increase their efficiency, and thus increase the efficiency of the network. Since these nodes are distributed on the roads, it is important to find appropriate ways to distribute them to increase data transfer and reduce their energy consumption. In this paper, a zigzag distribution method is proposed and a mathematical model of Right Side–Left Side (RS-LS) is used to reduce the energy consumption of RSU and compare it with the main chain protocol. Two different cases were taken, Case-1-is for low density with 20 vehicles and Case-2-is for high density with 40 vehicles. The proposed method succeeded in saving energy and reduce the consumption in both cases, by 60% and 44%, respectively.

  • Variable modulation index PWM inverter using AGC fed induction motor based WSN


RECENT SCHOLAR PUBLICATIONS

  • Enhanced Solar Defect Detection via Deep Learning: A CNN-Wavelet Transform-LSTM Approach.
    R Almashhadani, GC Hock, FH Bt Nordin, HN Abdulrazzak, ZA Abbas
    International Journal of Intelligent Engineering & Systems 18 (1), 1081 - 1091 2025

  • A Multi-Layer Deep Learning System for Fault Detection Solar Cell Electroluminescence Images
    R Almashhadani, GC Hock, FH Nordin, HN Abdulrazzak, ZA Abbas
    2024 IEEE 9th International Conference on Adaptive Science and Technology 2024

  • Electroluminescence Images for Solar Cell Fault Detection Using Deep Learning for Binary and Multiclass Classification
    RAI Almashhadani, GC Hock, FHB Nordin, HN Abdulrazzak
     2024

  • Fuzzy C-Means Clustering Approach for Green IoT in Smart Cities
    AA Hussein, HN Abdulrazzak
    2024 Third International Conference on Power, Control and Computing 2024

  • The Organizing and Technical Committees of 2024 IEEE 12th Conference on Systems, Process & Control (ICSPC 2024) would like to express gratitude to all reviewers for the
    AAM Anik, A Alsaraf, G Abinaya, A Amer, A Subbiah, A Al-Obaidi, AS Nori, ...
     2024

  • A Novel High-Priority Traffic Light System Based on a Microcontroller
    H NOORI
    Al-Rafidain Journal of Engineering Sciences, 35-41 2023

  • A new unsupervised validation index model suitable for energy-efficient clustering techniques in vanet
    HN Abdulrazzak, GC Hock, NAM Radzi, NML Tan
    IEEE Access 11, 67540-67555 2023

  • Modeling and analysis of new hybrid clustering technique for vehicular ad hoc network
    HN Abdulrazzak, GC Hock, NA Mohamed Radzi, NML Tan, CF Kwong
    Mathematics 10 (24), 4720 2022

  • A Novel Minimized Energy Routing Technique for IoT Assisted WSN
    HN Abdulrazzak, AA Hussein, A Kuchansky
    CEUR Workshop Proceedings 3149, 132-140 2022

  • Minimizing energy consumption in roadside unit of zigzag distribution based on RS-LS technique
    HN Abdulrazzak, NML Tan, NAM Radzi
    2021 IEEE International Conference on Automatic Control & Intelligent 2021

  • The Organizing and Technical Committees of 2021 IEEE 11th International Conference on System Engineering and Technology (ICSET 2021) would like to express gratitude to all
    AE Hassani, A Ghazli, A Derghal, AK Halim, AN Ghafar, AAM Salih, ...
    IEEE Conference Technical Committee and Reviewers of 2021 IEEE 11th 2021

  • Variable Modulation Index PWM Inverter using AGC fed Induction Motor Based WSN
    IM Khalil, HN Abdulrazzak, HH Merzah
    International Journal of Innovative Technology and Exploring Engineering 2019

  • Monitoring of Water Purification Process Based on IoT
    IM Khalil, HN Abdulrazzak
     2019

  • Performance analysis of CSMA/CA based on D2D communication
    HN Abdulrazzak, AA Hussein
    International Journal of Computer Sciences and Engineering 7 2019

  • Pattern Recognition Based On Intelligent System
    F Ali, H Abdulrazzak
    Journal of Al-Rafidain University College For Sciences (Print ISSN: 1681 2013

  • Wireless Mesh Networks
    Hazem Noori Abdulrazzak
     2008

MOST CITED SCHOLAR PUBLICATIONS

  • Modeling and analysis of new hybrid clustering technique for vehicular ad hoc network
    HN Abdulrazzak, GC Hock, NA Mohamed Radzi, NML Tan, CF Kwong
    Mathematics 10 (24), 4720 2022
    Citations: 10

  • Monitoring of Water Purification Process Based on IoT
    IM Khalil, HN Abdulrazzak
     2019
    Citations: 9

  • Minimizing energy consumption in roadside unit of zigzag distribution based on RS-LS technique
    HN Abdulrazzak, NML Tan, NAM Radzi
    2021 IEEE International Conference on Automatic Control & Intelligent 2021
    Citations: 8

  • A new unsupervised validation index model suitable for energy-efficient clustering techniques in vanet
    HN Abdulrazzak, GC Hock, NAM Radzi, NML Tan
    IEEE Access 11, 67540-67555 2023
    Citations: 7

  • Performance analysis of CSMA/CA based on D2D communication
    HN Abdulrazzak, AA Hussein
    International Journal of Computer Sciences and Engineering 7 2019
    Citations: 5

  • Electroluminescence Images for Solar Cell Fault Detection Using Deep Learning for Binary and Multiclass Classification
    RAI Almashhadani, GC Hock, FHB Nordin, HN Abdulrazzak
     2024
    Citations: 2

  • Fuzzy C-Means Clustering Approach for Green IoT in Smart Cities
    AA Hussein, HN Abdulrazzak
    2024 Third International Conference on Power, Control and Computing 2024
    Citations: 1

  • A Novel Minimized Energy Routing Technique for IoT Assisted WSN
    HN Abdulrazzak, AA Hussein, A Kuchansky
    CEUR Workshop Proceedings 3149, 132-140 2022
    Citations: 1

  • Variable Modulation Index PWM Inverter using AGC fed Induction Motor Based WSN
    IM Khalil, HN Abdulrazzak, HH Merzah
    International Journal of Innovative Technology and Exploring Engineering 2019
    Citations: 1

  • Pattern Recognition Based On Intelligent System
    F Ali, H Abdulrazzak
    Journal of Al-Rafidain University College For Sciences (Print ISSN: 1681 2013
    Citations: 1