A
Ali Mohammed Mansoor
Researcher at Information Technology University
Publications - 27
Citations - 271
Ali Mohammed Mansoor is an academic researcher from Information Technology University. The author has contributed to research in topics: Telecommunications link & Efficient energy use. The author has an hindex of 8, co-authored 25 publications receiving 179 citations. Previous affiliations of Ali Mohammed Mansoor include University of Malaya.
Papers
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Journal ArticleDOI
A novel cell-selection optimization handover for long-term evolution (LTE) macrocellusing fuzzy TOPSIS
Yaseein Soubhi Hussein,Borhanuddin Mohd Ali,Mohd Fadlee A. Rasid,Aduwati Sali,Ali Mohammed Mansoor +4 more
TL;DR: A novel method called fuzzy multiple-criteria cell selection (FMCCS), which uses an integrated fuzzy technique for order preference by using similarity to ideal solution on S-criterion, availability of resource blocks (RBs), and uplink signal-to-interference-plus-noise ratio, is proposed in this paper.
Journal ArticleDOI
Mission-Critical Machine-Type Communication: An Overview and Perspectives Towards 5G
TL;DR: An extensive review and evaluations to highlight diverse challenges and future aspects of mcMTC on 5G-enabling technologies and research opportunities from both academic communities and industrial partners are given.
Journal ArticleDOI
Green transmission for C-RAN based on SWIPT in 5G: a review
TL;DR: C-RAN as a network and SWIPT as a promising technique with the suggesting green wireless network are discussed besides the importance of energy efficiency for the next generation.
Journal ArticleDOI
Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models
TL;DR: This paper utilizes automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network, pretrained CNN feature extractor, and hierarchical extreme learning machine) for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes.
Proceedings ArticleDOI
A hybrid classification algorithm approach for breast cancer diagnosis
Baraa M. Abed,Khalid Shaker,Hamid A. Jalab,Hothefa Shaker,Ali Mohammed Mansoor,Ahmad Fouad Alwan,Ihsan Salman Al-Gburi +6 more
TL;DR: This study suggests a hybrid classification algorithm which is based upon Genetic Algorithm and k Nearest neighbor algorithm (kNN) which has achieved 99% accuracy.