M
Mohamed Elhoseny
Researcher at Mansoura University
Publications - 287
Citations - 11252
Mohamed Elhoseny is an academic researcher from Mansoura University. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 49, co-authored 240 publications receiving 7044 citations. Previous affiliations of Mohamed Elhoseny include Maharaja Agrasen Institute of Technology & Cairo University.
Papers
More filters
Journal ArticleDOI
Intelligent information system to ensure quality in higher education institutions, towards an automated e-university
TL;DR: The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions and helps all higher education stockholders to handle and monitor their tasks.
Book ChapterDOI
Expand Mobile WSN Coverage in Harsh Environments
TL;DR: This chapter proposes a sensor clustering method for dynamically organizing heterogeneous WSN using Genetic Algorithm, and proposes a set of key heterogeneity factors that enhance the performance of WSNs in harsh environments.
Journal ArticleDOI
Exploring New Vista of intelligent collaborative filtering: A restaurant recommendation paradigm
Arup Roy,Soumya Banerjee,Manash Sarkar,Ashraf Darwish,Ashraf Darwish,Mohamed Elhoseny,Mohamed Elhoseny,Aboul Ella Hassanien +7 more
TL;DR: A comparative study has been incorporated that depicts the proposed algorithm successfully minimizes the sparsity problem and the experimental outcome rendering ACCF provides 37%, 59%, 53% more Coverage, Precision and F-Measure than the user-based collaborative filtering even applicable for a small sample of data.
Journal ArticleDOI
Modeling neutrosophic variables based on particle swarm optimization and information theory measures for forest fires
TL;DR: A platform for integrating information theory measures with particle swarm optimization as a meta-heuristic algorithm to model a neutrosophic variable out of concrete data to calculate the indeterminacy of the temperature in forest fire data to contribute to forecasting these fires accurately is presented.
Journal ArticleDOI
A secure real-time internet of medical smart things (IOMST)
TL;DR: A wireless system for medical data transfer must be secure through the authentication and data encryption processes and a new data encryption system is presented by first encoding data, then encrypting it with a rotated key before its transmission over the network.