Abdulhameed Alelaiwi

TL;DR: This paper presents a comprehensive study of representative works on Sensor-Cloud infrastructure, which will provide general readers an overview of the Sensor- Cloud platform including its definition, architecture, and applications.

TL;DR: This paper measures the depth accuracy of the newly released Kinect v2 depth sensor, and obtains a cone model to illustrate its accuracy distribution, and proposes a trilateration method to improve thedepth accuracy with multiple Kinects simultaneously.

TL;DR: A hybrid feature extraction method with a regularized extreme learning machine (RELM) for developing an accurate brain tumor classification approach and the experimental results proved that the approach is more effective compared with the existing state-of-the-art approaches.

TL;DR: A voice pathology detection system is proposed inside the monitoring framework using a local binary pattern on a Mel-spectrum representation of the voice signal, and an extreme learning machine classifier to detect the pathology.

TL;DR: The experimental results show that, compared with the existing energy-saving techniques, the proposed approaches can effectively decrease the energy consumption in Cloud datacenters while maintaining low SLA violation.