Engineering Commons^™

Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger

Electrical and Computer Engineering Publications

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by …

Machine Learning, Game Theory Algorithms, And Medium Access Protocols For 5g And Internet-Of-Thing (Iot) Networks, Mohamed Elkourdi

USF Tampa Graduate Theses and Dissertations

In the first part of this dissertation, a novel medium access protocol for the Internet of Thing (IoT) networks is introduced. The Internet of things (IoT), which is the network of physical devices embedded with sensors, actuators, and connectivity, is being accelerated into the mainstream by the emergence of 5G wireless networking. This work presents an uncoordinated non-orthogonal random-access protocol, which is an enhancement to the recently introduced slotted ALOHA- NOMA (SAN) protocol that provides high throughput, while being matched to the low complexity requirements and the sporadic traffic pattern of IoT devices. Under ideal conditions it has been shown …

Methods And Algorithms To Enhance The Security, Increase The Throughput, And Decrease The Synchronization Delay In 5g Networks, Asim Mazin

USF Tampa Graduate Theses and Dissertations

This dissertation presents several novel approaches to enhance security, and increase the throughput, and decrease the delay synchronization in 5G networks.

First, a new physical layer paradigm was proposed for secure key exchange between the legitimate communication parties in the presence of a passive eavesdropper was presented. The proposed method ensures secrecy via pre-equalization and guarantees reliable communications using Low-Density Parity Check (LDPC) codes. One of the main findings of this research is to demonstrate through simulations that the diversity order of the eavesdropper will be zero unless the main and eavesdropping channels are almost correlated, while the probability of …