Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Autoencoders (1)
- C-Arm (1)
- Circuit simulation (1)
- DRR (1)
- Data Analytics (1)
-
- Data Reduction (1)
- Deep Learning (1)
- Edge Computing (1)
- Human Activity Recognition (1)
- Human-Information Interaction (1)
- Hyper-parameter Optimization (1)
- IoT (1)
- Iteration solver (1)
- Machine Learning (1)
- Network Anomaly Detection (1)
- Non-overlapping (1)
- Optimized Ensemble Learning Model Selection (1)
- Real-Time Twitter Analysis (1)
- Simulator (1)
- Stream Processing (1)
- Student Performance Prediction (1)
- Training (1)
- Transmission line (1)
- VR (1)
- Visual Analytics (1)
- Waveform relaxation (1)
Articles 1 - 5 of 5
Full-Text Articles in Engineering
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 …
Simulation Approaches To X-Ray C-Arm-Based Interventions, Daniel R. Allen
Simulation Approaches To X-Ray C-Arm-Based Interventions, Daniel R. Allen
Electronic Thesis and Dissertation Repository
Mobile C-Arm systems have enabled interventional spine procedures, such as facet joint injections, to be performed minimally-invasively under X-ray or fluoroscopy guidance. The downside to these procedures is the radiation exposure the patient and medical staff are subject to, which can vary greatly depending on the procedure as well as the skill and experience of the team. Standard training methods for these procedures involve the use of a physical C-Arm with real X-rays training on either cadavers or via an apprenticeship-based program. Many guidance systems have been proposed in the literature which aim to reduce the amount of radiation exposure …
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 …
A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki
A Visual Analytics System For Making Sense Of Real-Time Twitter Streams, Amir Haghighatimaleki
Electronic Thesis and Dissertation Repository
Through social media platforms, massive amounts of data are being produced. Twitter, as one such platform, enables users to post “tweets” on an unprecedented scale. Once analyzed by machine learning (ML) techniques and in aggregate, Twitter data can be an invaluable resource for gaining insight. However, when applied to real-time data streams, due to covariate shifts in the data (i.e., changes in the distributions of the inputs of ML algorithms), existing ML approaches result in different types of biases and provide uncertain outputs. This thesis describes a visual analytics system (i.e., a tool that combines data visualization, human-data interaction, and …