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Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad
Longitudinal Partitioning Waveform Relaxation Methods For The Analysis Of Transmission Line Circuits, Tarik Menkad
Electronic Thesis and Dissertation Repository
Three research projects are presented in this manuscript. Projects one and two describe two waveform relaxation algorithms (WR) with longitudinal partitioning for the time-domain analysis of transmission line circuits. Project three presents theoretical results about the convergence of WR for chains of general circuits.
The first WR algorithm uses a assignment-partition procedure that relies on inserting external series combinations of positive and negative resistances into the circuit to control the speed of convergence of the algorithm. The convergence of the subsequent WR method is examined, and fast convergence is cast as a generic optimization problem in the frequency-domain. An automatic …
Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat
Optimized Machine Learning Models Towards Intelligent Systems, Mohammadnoor Ahmad Mohammad Injadat
Electronic Thesis and Dissertation Repository
The rapid growth of the Internet and related technologies has led to the collection of large amounts of data by individuals, organizations, and society in general [1]. However, this often leads to information overload which occurs when the amount of input (e.g. data) a human is trying to process exceeds their cognitive capacities [2]. Machine learning (ML) has been proposed as one potential methodology capable of extracting useful information from large sets of data [1]. This thesis focuses on two applications. The first is education, namely e-Learning environments. Within this field, this thesis proposes different optimized ML ensemble models to …
Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Electronic Thesis and Dissertation Repository
Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …
Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma
Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma
Electrical and Computer Engineering Publications
No abstract provided.
Edge-Cloud Computing For Iot Data Analytics: Embedding Intelligence In The Edge With Deep Learning, Ananda Mohon M. Ghosh, Katarina Grolinger
Edge-Cloud Computing For Iot Data Analytics: Embedding Intelligence In The Edge With Deep Learning, Ananda Mohon M. Ghosh, Katarina Grolinger
Electrical and Computer Engineering Publications
Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …