Electrical and Computer 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 …

A Comprehensive Security Framework For Securing Sensors In Smart Devices And Applications, Amit Kumar Sikder

FIU Electronic Theses and Dissertations

This doctoral dissertation introduces novel security frameworks to detect sensor-based threats on smart devices and applications in smart settings such as smart home, smart office, etc. First, we present a formal taxonomy and in-depth impact analysis of existing sensor-based threats to smart devices and applications based on attack characteristics, targeted components, and capabilities. Then, we design a novel context-aware intrusion detection system, 6thSense, to detect sensor-based threats in standalone smart devices (e.g., smartphone, smart watch, etc.). 6thSense considers user activity-sensor co-dependence in standalone smart devices to learn the ongoing user activity contexts and builds a context-aware model to distinguish malicious …

Cloud Workload Allocation Approaches For Quality Of Service Guarantee And Cybersecurity Risk Management, Soamar Homsi

FIU Electronic Theses and Dissertations

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies.

Allowing several services or Virtual Machines (VMs) to commonly share the cloud's infrastructure enables cloud providers to optimize resource …

Adaptive Graph Construction For Isomap Manifold Learning, Loc Tran, Zezhong Zheng, Guoquing Zhou, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the ℓ₁ norm. The ℓ₁ enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than …

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 …

Precise Measurement Of The Neutron Magnetic Form Factor Gnm In The Few-Gev² Region, Clas Collaboration, J. Lachniet, H. Bagdasaryan, S. Bültmann, N. Kalantarians, G. E. Dodge, T. A. Forest, G. Gavalian, C. E. Hyde-Wright, A. Klien, S. E. Kuhn, M. R. Niroula, R. A. Niyazov, L. M. Qin, L. B. Weinstein, J. Zhang

Physics Faculty Publications

The neutron elastic magnetic form factor was extracted from quasielastic electron scattering on deuterium over the range Q² = 1.0–4.8  GeV² with the CLAS detector at Jefferson Lab. High precision was achieved with a ratio technique and a simultaneous in situ calibration of the neutron detection efficiency. Neutrons were detected with electromagnetic calorimeters and time-of-flight scintillators at two beam energies. The dipole parametrization gives a good description of the data