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Articles 151 - 154 of 154

Full-Text Articles in Engineering

Soft Switching, Mojtaba Mehrdad Nasehi Phd Electronics, Computer Networks Feb 2016

Soft Switching, Mojtaba Mehrdad Nasehi Phd Electronics, Computer Networks

mojtaba nasehi

Bridgeless AC-LED  Driver for lighting Applications


New Flexible Channels For Room Temperature Tunneling Field Effect Transistors, Boyi Hao, Anjana Asthana, Paniz K. Hazaveh, Paul L. Bergstrom, Douglas Banyai, Madhusudan A. Savaikar, John A. Jaszczak, Yoke Khin Yap Feb 2016

New Flexible Channels For Room Temperature Tunneling Field Effect Transistors, Boyi Hao, Anjana Asthana, Paniz K. Hazaveh, Paul L. Bergstrom, Douglas Banyai, Madhusudan A. Savaikar, John A. Jaszczak, Yoke Khin Yap

John Jaszczak

No abstract provided.


An Ontology And Integration Framework For Smart Communities, Steven Ray, Shishir Kinkar, Mark Hennessy Jan 2016

An Ontology And Integration Framework For Smart Communities, Steven Ray, Shishir Kinkar, Mark Hennessy

Steven R Ray

This paper describes our work concerning the definition of a neutral, abstract ontology, and framework that supports the vision and diverse contexts of a smart community. This framework is composed of a general, core ontology that supports what many are calling the Internet of Things (IoT), a scalable number of extension ontologies to describe various application perspectives, and a mapping methodology to relate external data and/or schemas to our ontology. Finally, we show why this ontology is scalable and generic enough to support a wide range of smart devices, systems, and people.


Development Of Compressive Sensing Techniques For Wideband Spectrum Scanning In Cognitive Radio Networks, Fatima Salahdine, Naima Kaabouch, Hassan El Ghazi Dec 2015

Development Of Compressive Sensing Techniques For Wideband Spectrum Scanning In Cognitive Radio Networks, Fatima Salahdine, Naima Kaabouch, Hassan El Ghazi

fatima salahdine

Next generation of communication systems will be smart and frequency agile. They will be able to scan the wideband radio spectrum to find the available frequency channel. This process is called compressive sensing. Existing compressive sensing techniques are not accurate and have high processing time, hardware limitations, and computational cost. Thus, this project aims to develop efficient compressive sensing algorithms that deal with uncertainty and enhance the radio spectrum scanning.