Moses Adah Agana

University of Calabar

H-index: 4

Africa-Nigeria

About Moses Adah Agana

Moses Adah Agana, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at University of Calabar, specializes in the field of Computer Science (Cyber Security).

His recent articles reflect a diverse array of research interests and contributions to the field:

Biosensor–Based vital signs data aggregation and analytics for monitoring of patients in Internet of Medical Things (IoMT) enabled e-healthcare platform

Collaborative filtering recommender system for timely arrival problem in road transport networks using viterbi and the hidden Markov algorithms

Hybrid Intrusion Detection Technique for Malicious Network Attacks with Machine Learning

Predicting Cyber Attacks in a Proxy Server using Support Vector Machine (SVM) Learning Algorithm

Optimal Power Flow-path Determination for Voltage Control in Electricity Distribution using the Modified Dijkstra’s Algorithm

A framework for a fuzzy smart home IoT e-health support system

Moses Adah Agana Information

University	University of Calabar
Position	Department of Computer Science
Citations(all)	46
Citations(since 2020)	46
Cited By	19
hIndex(all)	4
hIndex(since 2020)	4
i10Index(all)	2
i10Index(since 2020)	2
Email	Access Email
University Profile Page	University of Calabar
Google Scholar	View Google Scholar Profile

Moses Adah Agana Skills & Research Interests

Computer Science (Cyber Security)

Top articles of Moses Adah Agana

Title	Journal	Author(s)	Publication Date
Biosensor–Based vital signs data aggregation and analytics for monitoring of patients in Internet of Medical Things (IoMT) enabled e-healthcare platform		Idongesit E Eteng Moses A Agana EKORO EKORO	2023/8/8
Collaborative filtering recommender system for timely arrival problem in road transport networks using viterbi and the hidden Markov algorithms	International Journal of Software Innovation (IJSI)	Ofem Ajah Ofem Moses Adah Agana Elemue Oromena Felix	2023/1/1
Hybrid Intrusion Detection Technique for Malicious Network Attacks with Machine Learning		Ayei Ibor Moses Agana Bassey Ele Idongesit Eteng Prince Ana	2022/7/20
Predicting Cyber Attacks in a Proxy Server using Support Vector Machine (SVM) Learning Algorithm		Moses Adah Agana Joseph Ikpabi Edu	2021/5/10
Optimal Power Flow-path Determination for Voltage Control in Electricity Distribution using the Modified Dijkstra’s Algorithm	International Journal of Engineering & Technology	Ofem Ajah Ofem Moses Adah Agana E Ejogobe Owai	2021
A framework for a fuzzy smart home IoT e-health support system		Moses Adah Agana Ofem Ajah Ofem Bassey Igbo Ele	2020