Article Per Year (5 Year)
p-Index From 2019 - 2024
1.288
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Electrical Engineering and Computer Science
Seifedine Kadry
Noroff University College
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

 1 
Autonomous vehicles: A study of implementation and security Firoz Khan; R. Lakshmana Kumar; Seifedine Kadry; Yunyoung Nam; Maytham N. Meqdad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3013-3021

Abstract

Autonomous vehicles have been invented to increase the safety of transportation users. These vehicles can sense their environment and make decisions without any external aid to produce an optimal route to reach a destination. Even though the idea sounds futuristic and if implemented successfully, many current issues related to transportation will be solved, care needs to be taken before implementing the solution. This paper will look at the pros and cons of implementation of autonomous vehicles. The vehicles depend highly on the sensors present on the vehicles and any tampering or manipulation of the data generated and transmitted by these can have disastrous consequences, as human lives are at stake here. Various attacks against the different type of sensors on-board an autonomous vehicle are covered.
Classification of electroencephalography using cooperative learning based on participating client balancing Maytham N. Meqdad; Saif O. Husain; Alyaa Mohammed Jawad; Seifedine Kadry; Ahlam R. Khekan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp4692-4699

Abstract

Modern technologies are widely used today to diagnose epilepsy, neurological disorders, and brain tumors. Meanwhile, it is not cost-effective in terms of time and money to use a large amount of electroencephalography (EEG) data from different centers and collect them in a central server for processing and analysis. Collecting this data correctly is challenging, and organizations avoid sharing their and client information with others due to data privacy protection. It is difficult to collect these data correctly and it is challenging to transfer them to research centers due to the privacy of the data. In this regard, collaborative learning as an extraordinary approach in this field paves the way for the use of information repositories in research matters without transferring the original data to the centers. This study focuses on the use of a heterogeneous client balancing technique with an interval selection approach and classification of EEG signals with ResNet50 deep architecture. The test results achieved an accuracy of 99.14 compared to similar methods.
Co-Authors Abdullah Hasan Hussein Ahlam R. Khekan Alyaa Mohammed Jawad Amit Ramesh Khaparde Anu Saini Anurag Singh Balamurugan Balusamy Firoz Khan Jeevanandam Joteeswaran Maytham N. Meqdad Naresh Kumar Poongodi Thangamuthu Prakash Shanmurthy R. Lakshmana Kumar R.Lakshmana Kumar Saif O. Husain Salim Shamsher Sunita Kumari Yunyoung Nam