Resultaten voor 'muhammad ali'

Artificial Intelligence for Integrated Terrestrial and Non-terrestrial Networks

Microbiology in the Era of Artificial Intelligence

Written by leading experts, the book covers a broad range of topics pertaining to the myriad uses of Artificial Intelligence in microbiology.

Multimodal Intelligent Sensing in Modern Applications

Masood Ur Rehman, PhD, MSc, is a Senior Lecturer at the James Watt School of Engineering, University of Glasgow, UK and leads the Antennas & Radio-wave Propagation group. He received his MSc and PhD in Electronic Engineering from Queen Mary University of London, UK, in 2006 and 2010, respectively. Ahmed Zoha, PhD, MSc, is a Senior Lecturer at the James Watt School of Engineering, University of Glasgow, UK and leads the Distributed Learning and Intelligence group. He received his PhD degree in Electrical and Electronic Engineering from the 5G Innovation Centre at the University of Surrey, UK, and his MSc in Communication Engineering from the Chalmers University of Technology, Sweden. Muhammad Ali Jamshed, PhD, MSc, is with University of Glasgow, UK, since 2021. He is a visiting Research Fellow at the University of Sussex. He is endorsed by the Royal Academy of Engineering under exceptional talent category and was nominated for the Departmental Prize for Excellence in Research in 2019 at the University of Surrey. Naeem Ramzan, PhD, is a Full Professor in Computing Engineering and Chair of Affective and Human Computing for Smart Environment Research Centre and Co-lead of Visual Communication Cluster in AVCN at the University of the West of Scotland, Paisley, UK. He received his PhD in Electronic Engineering from Queen Mary University of London, UK in 2008.

1. Jawwad Ahmed Shamsi
2. Muhammad Ali Khojaye

Big Data Systems

Big Data Systems encompass massive challenges related to data diversity, storage mechanisms, and requirements of massive computational power. The book's purpose is to provide a detailed overview of big data systems. It adopts a challenge-centric approach in which platforms are evaluated based on their capabilities to solve specific challenges.