Engineering Commons^™

Intrinsic Functions For Securing Cmos Computation: Variability, Modeling And Noise Sensitivity, Xiaolin Xu

Doctoral Dissertations

A basic premise behind modern secure computation is the demand for lightweight cryptographic primitives, like identifier or key generator. From a circuit perspective, the development of cryptographic modules has also been driven by the aggressive scalability of complementary metal-oxide-semiconductor (CMOS) technology. While advancing into nano-meter regime, one significant characteristic of today's CMOS design is the random nature of process variability, which limits the nominal circuit design. With the continuous scaling of CMOS technology, instead of mitigating the physical variability, leveraging such properties becomes a promising way. One of the famous products adhering to this double-edged sword philosophy is the Physically …

On Physical Disorder Based Hardware Security Primitives, Arunkumar Vijayakumar

Doctoral Dissertations

With CMOS scaling extending transistors to nanometer regime, process variations from manufacturing impacts modern IC design. Fortunately, such variations have enabled an emerging hardware security primitive - Physically Unclonable Function. Physically Unclonable Functions (PUFs) are hardware primitives which utilize disorder from manufacturing variations for their core functionality. In contrast to insecure non-volatile key based roots-of-trust, PUFs promise a favorable feature - no attacker, not even the PUF manufacturer can clone the disorder and any attempt at invasive attack will upset that disorder. Despite a decade of research, certain practical problems impede the widespread adoption of PUFs. This dissertation addresses the …

Laff-O-Tron: Laugh Prediction In Ted Talks, Andrew D. Acosta

Master's Theses

Did you hear where the thesis found its ancestors? They were in the "parent-thesis"! This joke, whether you laughed at it or not, contains a fascinating and mysterious quality: humor. Humor is something so incredibly human that if you squint, the two words can even look the same. As such, humor is not often considered something that computers can understand. But, that doesn't mean we won't try to teach it to them.

In this thesis, we propose the system Laff-O-Tron to attempt to predict when the audience of a public speech would laugh by looking only at the text of …

Osem : Occupant-Specific Energy Monitoring., Anand S. Kulkarni

Electronic Theses and Dissertations

Electricity has become prevalent in modern day lives. Almost all the comforts people enjoy today, like home heating and cooling, indoor and outdoor lighting, computers, home and office appliances, depend on electricity. Moreover, the demand for electricity is increasing across the globe. The increasing demand for electricity and the increased awareness about carbon footprints have raised interest in the implementation of energy efficiency measures. A feasible remedy to conserve energy is to provide energy consumption feedback. This approach has suggested the possibility of considerable reduction in the energy consumption, which is in the range of 3.8% to 12%. Currently, research …

Rule-Based Risk Monitoring Systems For Complex Datasets, Mona Haghighi

USF Tampa Graduate Theses and Dissertations

In this dissertation we present rule-based machine learning methods for solving problems with high-dimensional or complex datasets. We are applying decision tree methods on blood-based biomarkers and neuropsychological tests to predict Alzheimer’s disease in its early stages. We are also using tree-based methods to identify disparity in dementia related biomarkers among three female ethnic groups. In another part of this research, we tried to use rule-based methods to identify homogeneous subgroups of subjects who share the same risk patterns out of a heterogeneous population. Finally, we applied a network-based method to reduce the dimensionality of a clinical dataset, while capturing …

Scale Up Bayesian Network Learning, Xiannian Fan

Dissertations, Theses, and Capstone Projects

Bayesian networks are widely used graphical models which represent uncertain relations between the random variables in a domain compactly and intuitively. The first step of applying Bayesian networks to real-word problems is typically building the network structure. Optimal structure learning via score-and-search has become an active research topic in recent years. In this context, a scoring function is used to measure the goodness of fit of a structure to given data, and the goal is to find the structure which optimizes the scoring function. The problem has been viewed as a shortest path problem, and has been shown to be …

Visualization Of Deep Convolutional Neural Networks, Dingwen Li

McKelvey School of Engineering Theses & Dissertations

Deep learning has achieved great accuracy in large scale image classification and scene recognition tasks, especially after the Convolutional Neural Network (CNN) model was introduced. Although a CNN often demonstrates very good classification results, it is usually unclear how or why a classification result is achieved. The objective of this thesis is to explore several existing visualization approaches which offer intuitive visual results. The thesis focuses on three visualization approaches: (1) image masking which highlights the region of image with high influence on the classification, (2) Taylor decomposition back-propagation which generates a per pixel heat map that describes each pixel's …

Global Thermospheric Response To Geomagnetic Storms, Padmashri Suresh

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The terrestrial atmospheric region between the altitudes of 90 km and 600 km is known as the thermosphere region. The thermosphere is continuously modulated by particle emissions and magnetic fields that originate from the sun. These fields and emissions are intensified during events known as geomagnetic storms which alter the state of the thermosphere by dumping gigawatts of energy. This energy is mostly deposited in the lower thermosphere regions of 150 km and below and can potentially have hazardous repercussions on the technological assets of mankind. These storms can disrupt radio communication systems, interrupt electric power systems, threaten the safety …

Accelerated Hyperspectral Unmixing With Endmember Variability Via The Sum-Product Algorithm, Charan Puladas

Browse all Theses and Dissertations

The rich spectral information captured by hyperspectral sensors has given rise to a number of remote sensing applications, ranging from vegetative assessment and crop health monitoring, to military surveillance and combatant identification. However, due to limited spatial resolution, multiple ground materials generally contribute, i.e. mix, to form the spectrum recorded for a single pixel. The unmixing problem considers the inverse problem of determining the underlying material spectra, called endmembers, from sensor measurements. While classical unmixing approaches were deterministic in nature and did not attempt to identify in-scene materials, recent methods use labeled training data to generate statistical models of endmember …

Improving Understandability And Uncertainty Modeling Of Data Using Fuzzy Logic Systems, Dumidu S. Wijayasekara

Theses and Dissertations

The need for automation, optimality and efficiency has made modern day control and monitoring systems extremely complex and data abundant. However, the complexity of the systems and the abundance of raw data has reduced the understandability and interpretability of data which results in a reduced state awareness of the system. Furthermore, different levels of uncertainty introduced by sensors and actuators make interpreting and accurately manipulating systems difficult. Classical mathematical methods lack the capability to capture human knowledge and increase understandability while modeling such uncertainty.

Fuzzy Logic has been shown to alleviate both these problems by introducing logic based on vague …

A Closed Loop Research Platform That Enables Dynamic Control Of Wing Gait Patterns In A Vertically Constrained Flapping Wing - Micro Air Vehicle, Hermanus Van Botha

Browse all Theses and Dissertations

Research in Flapping Wing - Micro Air Vehicles(FW-MAVs) has been growing in recent years. Work ranging from mechanical designs to adaptive control algorithms are being developed in pursuit of mimicking natural flight. FW-MAV technology can be applied in a variety of use cases such a military application and surveillance, studying natural ecological systems, and hobbyist commercialization. Recent work has produced small scale FW-MAVs that are capable of hovering and maneuvering. Researchers control maneuvering in various ways, some of which involve making small adjustments to the core wing motion patterns (wing gaits) which determine how the wings flap. Adaptive control algorithms …