Nurul Mu'azzah Abdul Latiff

TL;DR: An extensive review of the state-of-the-art techniques and studies of IoT frameworks and machine learning algorithms used in the healthcare in general and in the voice pathology surveillance systems in particular is presented.

TL;DR: An algorithm which iteratively designs low-resolution (two-bit) hybrid analog-digital precoder and combiner (LrHPC), for pursuing efficiency while maximizing spectral efficiency is proposed.

TL;DR: In this paper, the authors presented a voice pathology detection and classification system by using OSELM algorithm as a classifier, and Mel-frequency cepstral coefficient (MFCC) as a featured extraction.

TL;DR: Smart agriculture and smart lifestyle can be developed by implementing this technology that manage to brilliantly control plants watering rate according to its soil moisture and user requirement, which will save the budget for hiring employees and prevent from water wastage in daily necessities.

TL;DR: Simulation results demonstrate that the proposed protocol for the movement of mobile base station using particle swarm optimization (PSO) method in wireless sensor networks can improve the network lifetime, data delivery and energy consumption compared to existing energy-efficient protocols developed for this network.