Mutaz Hamed Hussien Khairi Editor at IgMin Research
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Biography
I have published several papers in the Electrical Engineering field, with a few more under review. Furthermore, all the courses I have attended in my B.Sc., M.Sc., and Ph.D. are closely related to Computer Engineering and Electronics System Engineering.
My research interests are mainly related to Computer Architecture and networking, with particular interests in Computer and Electronics System Engineering, such as software-defined networking (SDN), load balancing, network traffic classification, Internet-of-things (IoT), cloud computing, Network security, and future networks.
Research Interest
Software Defined Network; Modern Network; Telecommunication Network; Computer Network; Network Security; Big Data; AI, Deep Learning and Machine Learning Application; Electronic Design; IoT Application
Editor
Work Details
Assistant Professor
The Future University
Department of Engineering
Sudan
0000-0002-5904-7642 Contribution by Topic Area
Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
Which articles are now trending?
Research Articles
- Efficacy of Different Concentrations of Insect Growth Regulators (IGRs) on Maize Stem Borer Infestation
- Methodology of the Professional-Business Game for the Development of a Cadet Leader in Professional Training Courses (L-1B) of the Tactical Level of Military Education
- Enhancing Missing Values Imputation through Transformer-Based Predictive Modeling
- Contamination in Heat Exchangers: Types, Energy Effects and Prevention Methods
- A Unified Mobility Model for Semiconductor Devices and Sensors, Including Surface Hydrodynamic Viscosity
- Melanocytic Nevi Classification using Transfer Learning
