Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms

YK Saheed, MO Arowolo - IEEE Access, 2021 - ieeexplore.ieee.org
Information and communication technology (ICT) advancements have altered the entire
computing paradigm. As a result of these improvements, numerous new channels of …

Educational data mining to predict students' academic performance: A survey study

S Batool, J Rashid, MW Nisar, J Kim, HY Kwon… - Education and …, 2023 - Springer
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …

Predicting Students' Performance Using Machine Learning Algorithms: A Review

SO Oppong - Asian Journal of Research in Computer …, 2023 - eprints.go2submission.com
Educational Data Mining is a discipline focused on developing ways for studying the unique
and increasingly large-scale data generated by educational settings and applying those …

Educational data mining in higher education in sub-Saharan Africa: A systematic literature review and research agenda

M Maphosa, V Maphosa - … of the 2nd International Conference on …, 2020 - dl.acm.org
The impact of the coronavirus disease (COVTD-19) will see an increase in data generated
by higher education institutions (HEIs) in Sub-Saharan Africa as more institutions introduce …

Swarm intelligence for IoT attack detection in fog-enabled cyber-physical system

MA Alohali, M Elsadig, FN Al-Wesabi… - Computers and …, 2023 - Elsevier
To provide remote access, surveillance, and analysis, network integration is common in
Cyber-Physical Systems (CPSs). This leads to cyber attacks due to the integration of …

A comparative study of regression analysis for modelling and prediction of bitcoin price

YK Saheed, RM Ayobami, T Orje-Ishegh - Blockchain Applications in the …, 2022 - Springer
The appraisal of Bitcoin's price-changing characteristics is extremely difficult because of the
nonlinear, nonstationary, effect of multiple uncontrollable factors, and volatile nature. The …

Coastal Flood risk assessment using ensemble multi-criteria decision-making with machine learning approaches

MM Asiri, G Aldehim, N Alruwais, R Allafi… - Environmental …, 2024 - Elsevier
Coastal areas are at a higher risk of flooding, and novel changes in the climate are induced
to raise the sea level. Flood acceleration and frequency have increased recently because of …

Effective dimensionality reduction model with machine learning classification for microarray gene expression data

YK Saheed - Data Science for Genomics, 2023 - Elsevier
Microarray technology enables biologists to simultaneously monitor the activities of genome-
wide features. This method generates gene expression data that can be used to classify …

Customer churn prediction in telecom sector with machine learning and information gain filter feature selection algorithms

YK Saheed, MA Hambali - … on Data Analytics for Business and …, 2021 - ieeexplore.ieee.org
Customer churn is a significant issue and one of the primary worries of large businesses.
Due to the direct impact on firms' earnings, particularly in the telecommunications sector …

[PDF][PDF] Application of machine learning methods to predict student performance: a systematic literature review

AA Enughwure, ME Ogbise - Int. Res. J. Eng. Technol, 2020 - academia.edu
In recent times, the need for the application of machine learning in the educational frontier
has become crucial. Most educational administrators and researchers are using various …