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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics
Hasanain Abdalridha Abed Alshadoodee
University of Kufa
Computer Science & IT Electrical & Electronics Engineering

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Integrating security and privacy in mmWave communications Ghadah M. Faisal; Hasanain Abdalridha Abed Alshadoodee; Haider Hadi Abbas; Hassan Muwafaq Gheni; Israa Al-Barazanchi
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4314

Abstract

The aim of this paper is to integrate security and privacy in mmWave communications. MmWave communication mechanism access three major key components of secure communication (SC) operations. proposed design for mmWave communication facilitates the detection of the primary signal in physical (PHY) layer to find the spectrum throughput for primary user (PU) and secondary user (SU). The throughput of SC for PU with maximum throughput being recorded at 0.7934 while maximum throughput for SU is recorded at 0.7679. So, we will design a mmWave communication mechanism for solving this problem. The probability for sensing where the probability of detection (PD) is predicted at a defined range of 690 km with an estimated accuracy of 83.56% while the probability of false alarm (PFA) is predicted at a defined range of 230 km with an estimated accuracy of 81.39%. This conflicting but interrelated issue is investigated over three stages for the purpose of solving with a cross-layer model with MAC and PHY layers for a secure communication network (SCN) while reducing the collision effect concurrently with a 92.76% for both cross-layers. MATLAB 2019b would be forwarded in use as the increasing demand for augmenting the bandwidth in secure communications has actuated the evolutionary technology.
The role of artificial intelligence in enhancing administrative decision support systems by depend on knowledge management Hasanain Abdalridha Abed Alshadoodee; Muneer Sameer Gheni Mansoor; Hasanien Kariem Kuba; Hassan Muwafaq Gheni
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4243

Abstract

This study illustrates the role of artificial intelligence in enhancing administrative decision support systems by depend on knowledge management. As per new technologies are evolving and the workflow need more concious approach of implementation, thus the role of artificial intelligence is evolved in support to decision making. The study takes privates college administration as a varible on which the results rely. The upgrades in innovation have upgraded most techniques for leading business tasks that further develop organizations and administration conveyance. Companies in this area need to wander into digitizing of all industry cycles, business sequences linked to administration and more essential services in educational institutes over time. The need for a proper decision-making support using knowledge management stills create a big gap in the foundation of an effective and efficient eductaional system for the good governance and to improve the image of some institute. The examination interaction has been intended to follow an iterative methodology of information revelation chose for the review. Using the statistical package for social sciences (IBM-SPSS) version 23 logic instrument, the illustrative research was completed with insights into the segment profile of the respondents. Hayes' process macro v3.3 with SPSS was used to analyze the interceding effect.
Detecting community on social networks with fast and optimal online clustering algorithms Muneer Sameer Gheni Mansoor; Hasanain Abdalridha Abed Alshadoodee; Rahim Muhammad Alabdali; Ahmed Dheyaa Radhi; Poh Soon JosephNg; Jamal Fadhil Tawfeq
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 2: April 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i2.24724

Abstract

Social networks have become an essential part of our lives today, at least in their virtual dimension, and the image of the web world is almost impossible without the presence of this pervasive phenomenon. These networks are one of the important components of the information infrastructure, such as twitter networks, facebook networks, and so on. In the analysis of social networks, one of the important issues is the detection of community. Each community is a group of network nodes so that the connection between nodes within the group with each other is more than their connection with other network nodes. Various methods have been proposed for community detection. One of the existing methods is based on data stream clustering. The output data of a social network can be modeled with a data stream. Fast and accurate clustering of this data stream can be very effective in the detection of community. In this research, using a fast and accurate online clustering algorithm, the community is detected. The simulation results indicate that the method proposed in this research can calculate the number of clusters optimally and perform better than similar methods. The proposed algorithm can be used in many other applications.
Co-Authors Ahmed Dheyaa Radhi Ghadah M. Faisal Haider Hadi Abbas Hasanien Kariem Kuba Hassan Muwafaq Gheni Israa Al-Barazanchi Jamal Fadhil Tawfeq Muneer Sameer Gheni Mansoor Poh Soon JosephNg Rahim Muhammad Alabdali