Engineering Commons^™

Deep Learning Methods For Fingerprint-Based Indoor And Outdoor Positioning, Fahad Alhomayani

Electronic Theses and Dissertations

Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. The contribution of this dissertation is fourfold:

First, a Convolutional Neural Network (CNN)-based method for …

Approximate Pattern Matching Using Hierarchical Graph Construction And Sparse Distributed Representation, Aakanksha Mathuria

Dissertations and Theses

With recent developments in deep networks, there have been significant advances in visual object detection and recognition. However, some of these networks are still easily fooled/hacked and have shown "bag of features" kinds of failures. Some of this is due to the fact that even deep networks make only marginal use of the complex structure that exists in real-world images. Primate visual systems appear to capture the structure in images, but how?

In the research presented here, we are studying approaches for robust pattern matching using static, 2D Blocks World images based on graphical representations of the various components of …

A Comparative Study Of Bagging And Boosting Of Supervised And Unsupervised Classifiers For Outliers Detection, Yue Dang

Browse all Theses and Dissertations

The problem of outlier detection has received increasing attention recently because it plays a great role in many fields such as credit fraud detection, cyber security, etc. Machine Learning approach is an excellent choice for outlier detection due to its accuracy and efficiency. Outlier detection problem is unique due to the so-called classes imbalance: the inliers are extreme majority and the outliers are minority. Ensemble methods are popular in classification and regression task in practice to improve the performance of machine learning algorithms. Bagging and boosting are two common methods of them. In this thesis, we want to show the …

Application Aware For Byzantine Fault Tolerance, Hua Chai

ETD Archive

Driven by the need for higher reliability of many distributed systems, various replication-based fault tolerance technologies have been widely studied. A prominent technology is Byzantine fault tolerance (BFT). BFT can help achieve high availability and trustworthiness by ensuring replica consistency despite the presence of hardware failures and malicious faults on a small portion of the replicas. However, most state-of-the-art BFT algorithms are designed for generic stateful applications that require the total ordering of all incoming requests and the sequential execution of such requests. In this dissertation research, we recognize that a straightforward application of existing BFT algorithms is often inappropriate …

Wireless Impact Detection System, Shawno Auwae, Kyle Terriere

Interdisciplinary Design Senior Theses

Recently, brain trauma caused by multiple concussions has become a pressing issue for contact sports, mainly American football players. The severity of the impacts in these sports have led to discussion concerning the standard safety equipment used, as well as the rules enforcing a certain style of play. Multiple studies have shown that concussions have damaging long-term effects, including dementia and memory loss. The dominant professional football organization, the National Football League (NFL), employs qualified athletic trainers to diagnose and treat players with concussions, but many incidents still go undetected. This problem is magnified at the youth level, where the …

Multi-Label Segmentation Propagation For Materials Science Images Incorporating Topology And Interactivity, Jarrell Waggoner

Theses and Dissertations

Segmentation propagation is the problem of transferring the segmentation of an image to a neighboring image in a sequence. This problem is of particular importance to materials science, where the accurate segmentation of a series of 2D serial-sectioned images of multiple, contiguous 3D structures has important applications. Such structures may have prior-known shape, appearance, and/or topology among the underlying structures which can be considered to improve segmentation accuracy. For example, some materials images may have structures with a specific shape or appearance in each serial section slice, which only changes minimally from slice to slice; and some materials may exhibit …

Simulink Implementation Of A Cdma Transmitter, Visalakshi Ramakonar

Theses : Honours

An implementation of a Code Division Multiple Access (CDMA) transmitter has been developed using SIMULINK and MATLAB. This transmitter uses a modified carrier in modulation. This modified carrier, which is frequency modulated, has been shown to reduce intersymbol interference (ISI) and multiple access interference (MAl). These two types of interference are caused by multipath propagation which results in delayed versions of the original signal. The benefits of this modified modulation technique are apparent when there are delays involved. The spreading sequences used are 7- bit Gold codes which allow a maximum of nine users. The initial trials of the transmitter …