This work presents a novel CCRW receiver that utilizes a window of variable width, for e˙ectively mitigating multipath and ambiguity in both civil and military positioning applica-tions using Global Navigation Satellite Systems (GNSS). This CCRW receiver incorporates a single stroboscopic window, whose width is iteratively reduced until the e˙ect of...
This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
This dissertation proposes the use of advanced time-varying approaches for modeling the dynamics of the multipath channel in wireless communication networks. These advanced time-varying approaches include linear Kalman innovation models in observable block companion form, and neural network-based models. The e˙ectiveness of these type of models is evaluated through three...
The objective of this dissertation is to enhance the monitoring of forest ecosystems through the utilization of remotely sensed data to address the exigencies posed by the Anthropocene. On a global scale, rising temperatures and fluctuating precipitation patterns have strained forests and produced shifts in natural disturbance regimes. Additionally, the...
1,4-Dioxane (dioxane) and cis-dichloroethylene (cDCE) are compounds commonly found in industrial cleaning and degreasing agents that are frequently present as groundwater contaminants. In an effort to develop a more effective treatment method for these compounds, hydrogel beads were fabricated with either gellan gum or a combination of polyvinyl alcohol (PVA)...
Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
The interactions of chemical species with a solid surface play a role in many everyday applications such as heterogeneous catalysis, corrosion, and degradation reactions. Understanding the reaction kinetics and thermodynamics via rate constants and equilibrium constants, which require knowledge of the adsorbed species’ entropy, is essential for tuning these surface...
My work has focused on using density functional theory to elucidate mechanisms of organocatalytic and transition metal catalyzed reactions by considering competing mechanisms. In each of the three presented studies computational investigation complemented experimental work by predicting stereoselectivity or revealing origins of stereo, regio, or chemoselectivity.
A study on the...
Most of today’s Internet of Things (IoT) applications assume that data will be moved offdevices into centralized cloud platforms. While existing IoT systems leverage cloud-based analytics for meaningful data reasoning, the assumption that data should always be moved off the devices is problematic. The amount of data to be moved...