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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Indonesian Journal of Electrical Engineering and Computer Science
Rashidah Funke Olanrewaju
International Islamic University Malaysia
Computer Science & IT Electrical & Electronics Engineering

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

 1 
Data in Transit Validation for Cloud Computing Using Cloud-Based Algorithm Detection of Injected Objects Rashidah Funke Olanrewaju; Thouhedul Islam; Othman O. Khalifa; Fawwaz Eniola Fajingbesi
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp348-353

Abstract

The recent paradigm shift in the IT sector leading to cloud computing however innovative had brought along numerous data security concerns. One major such security laps is that referred to as the Man in the Middle (MITM) attack where external data are injected to either hijack a data in transit or to manipulate the files and object by posing as a floating cloud base. Fresh algorithms for cloud data protection do exist however, they are still prone to attack especially in real-time data transmissions due to employed mechanism. Hence, a validation protocol algorithm based on hash function labelling provides a one-time security header for transferable files that protects data in transit against any unauthorized injection. The labelling header technique allows for a two-way data binding; DOM based communication between local and cloud computing that triggers automated acknowledgment immediately after file modification. A two layer encryption functions in PHP was designed for detecting injected object; bcrypt methods in Laravel and MD5 that generate 32 random keys. A sum total of 1600 different file types were used during training then evaluation of the proposed algorithm, where 87% of the injected objects were correctly detected.
Classification of ECG signals for detection of arrhythmia and congestive heart failure based on continuous wavelet transform and deep neural networks Rashidah Funke Olanrewaju; S. Noorjannah Ibrahim; Ani Liza Asnawi; Hunain Altaf
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1520-1528

Abstract

According to World Health Organization (WHO) report an estimated 17.9 million lives are being lost each year due to cardiovascular diseases (CVDs) and is the top contributor to the death causes. 80% of the cardiovascular cases include heart attacks and strokes. This work is an effort to accurately predict the common heart diseases such as arrhythmia (ARR) and congestive heart failure (CHF) along with the normal sinus rhythm (NSR) based on the integrated model developed using continuous wavelet transform (CWT) and deep neural networks. The proposed method used in this research analyses the time-frequency features of an electrocardiogram (ECG) signal by first converting the 1D ECG signals to the 2D Scalogram images and subsequently the 2D images are being used as an input to the 2D deep neural network model-AlexNet. The reason behind converting the ECG signals to 2D images is that it is easier to extract deep features from images rather than from the raw data for training purposes in AlexNet. The dataset used for this research was obtained from Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) arrhythmia database, MIT-BIH normal sinus rhythm database and Beth Israel Deaconess Medical Center (BIDMC) congestive heart failure database. In this work, we have identified the best fit parameters for the AlexNet model that could successfully predict the common heart diseases with an accuracy of 98.7%. This work is also being compared with the recent research done in the field of ECG Classification for detection of heart conditions and proves to be an effective technique for the classification.
Game Theory for Resource Allocation in Heterogeneous Wireless Networks - A Review Farhat Anwar; Mosharrof H. Masud; Burhan Ul Islam; Rashidah Funke Olanrewaju; Suhaimi Abd Latif
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp843-851

Abstract

In next-generation wireless networks, a user can be connected through Multi-Mode Device (MMD) to the multiple wireless networks in Heterogeneous Wireless Networks (HWN) considering several factors; including network technology, data service type, available bandwidth, Quality of Service (QoS), monetary cost, etc. To deal with all these multi attributes, game theory based models have been used to point out a better solution. This paper evaluates the techniques, methods, advantages, limitations of some game theory-based models for wireless resource allocation in HWN. Finally, it concludes that the Shapley Value method can be used for further research activities for its efficiency.
Design and Fabrication of an Intelligent Walking Staff for Visually Impaired Subjects Rashidah Funke Olanrewaju; Muhammad Luqman Azzaki Mohd Radzi; Mariam Rehab; Fawwaz Eniola Fajingbesi
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp266-270

Abstract

The joy we derive from our ability to commute and interact freely with the world as a result of our possession of sight with the naked eyes are enormous however the Visually impaired people find great difficulty in moving around freely without a human guide, especially in a new terrain. This research reports the design and fabrication process of an intelligent walking staff (iWalk) specially designed for the visually disabled individuals to argument their loss of sight, improve and ease their navigation. iWalk was designed around water and ultrasonic sensors to detect obstacles and water ahead. iWalk also has a wireless RF remote control buzzer for localization and detection in case it gets misplaced. The proposed system operability and efficiency was adequately tested using physical dataset composed of randomized locations with random obstacles and water. The proposed algorithm achieves an overall efficiency of 90% detection rate for water and ultrasonic sensor and 85.75% for the RF wireless remote control.
Co-Authors Amelia Wong Azman Ani Liza Asnawi Burhan Ul Islam Dua’a Mahmoud Al-Qudah Farhat Anwar Fatchul Arifin Fawwaz Eniola Fajingbesi Hunain Altaf Malik Arman Morshidi Mariam Rehab Mir Suhail Alam Mosharrof H. Masud Muhammad Luqman Azzaki Mohd Radzi Othman O. Khalifa S. Noorjannah Ibrahim Suhaimi Abd Latif Teddy Surya Gunawan Thouhedul Islam