Physical Sciences and Mathematics Commons^™

Quantifying Uncertainty In Landscape Evolution And Provenance Analysis: Insights From Statistical And Numerical Modelling, Vivian Carmello Grom

LSU Doctoral Dissertations

Landscape evolution models (LEMs) and detrital zircon provenance are widely used to investigate Earth surface processes, yet both face challenges related to quantifying model behavior and interpreting sedimentary signals under realistic, heterogeneous conditions. This thesis addresses these challenges through analysis and case studies that develop and apply new approaches for analyzing landscape dynamics and assessing uncertainties in sediment provenance.

Chapter 1 introduces a quantitative framework for evaluating LEM outputs using Shannon Entropy, Moran’s I, and Geary’s C. Applied to simulations with steady uplift, periodic uplift, spatially variable uplift, and a timeseries of DEMs, these metrics capture spatial organization and information …

Charge Transport Modeling Of Multifunctional Molecular Transistors, Romena Akter

Graduate Studies Theses and Dissertations 2026

Distinguishing between the current–voltage characteristic curves associated with different transport mechanisms in a molecular electronic device and an artifact arising from device-level disorder is a central challenge in the study of molecular electronics. Characterizing these mechanisms and connecting them qualitatively to molecular-level orbital alignment, electrode coupling, voltage division, energetic disorder, and reorganization energy requires not only experimental data but also a rigorous theoretical framework for extracting physically meaningful parameters from measured transfer characteristics. This dissertation addresses this challenge in Chapters 2, 3, and 4 by developing and applying four complementary transport models —Simmons tunneling, single-level Landauer, Marcus hopping, and McConnell …

Robust Deep Learning One-Class Classification, Shahd Alnofaie

Graduate Studies Theses and Dissertations 2026

One-Class Classification (OCC) focuses on learning the characteristics of normal data and identifying observations that deviate from this learned pattern as anomalies. It is commonly used in applications such as medical diagnosis, cybersecurity, industrial monitoring, and fraud detection, where abnormal examples are often rare or unavailable during training. Classical approaches such as SVDD and LS-SVDD describe normal data using a hypersphere. While effective in some settings, these methods rely on shallow representations and can be sensitive to noise and contaminated observations. To address these limitations, this dissertation introduces a Deep LS-SVDD framework that combines hypersphere-based data description with deep neural …

Learning Weibull Loss Severity Models From Truncated And Censored Data, Majed Alkhasha

Graduate Studies Theses and Dissertations 2026

In modern actuarial science and risk management, due to various loss control mechanisms, observed severity losses are typically left-truncated at the deductible, right-censored at the policy limit, and scaled by a pre-specified co-insurance factor. This results in two types of actuarial payment random variables: payment-per-payment (PPP) and payment-per-loss (PPL). To learn ground-up Weibull loss severity models from PPP and PPL sample data, we implement two estimation techniques: Maximum Likelihood Estimation (MLE) and the dynamic Method of Trimmed Moments (MTM). MLE is employed to obtain efficient estimates of the Weibull shape and scale parameters. However, MLE may assign unnecessarily large point …

Making Unsafe Sequences Unexecutable: Formal Protocol Enforcement For Cyber-Physical Systems, Arthur Amorim

Graduate Studies Theses and Dissertations 2026

Cyber-physical systems execute physical actions in response to software commands, making their communication protocols a primary attack surface. A stealthy attack is a sequence of individually valid messages that violates a required ordering, driving the system into an unsafe state without malware or protocol violation. Existing defenses examine messages or physical state in isolation, not protocol level sequences, and cannot prevent them. Preventing them requires enforcement that makes unsafe sequences unexecutable at the communication boundary.

Formal methods offer a principled path to enforcement, but no tool spans specification to safe deployed hardware. Model checking automates proofs but has no certified …

Connecting The Existing Fiber Infrastructure To The Future With Antiresonant Hollow Core Fibers, Timothy Bate

Graduate Studies Theses and Dissertations 2026

Optical fiber systems based on solid-core silica waveguides underpin modern telecommunications, high-power laser delivery, precision sensing, and coherent optical systems. However, nonlinear effects, material absorption, and thermal limitations within silica increasingly constrain further scaling in both optical power and transmission performance. Antiresonant hollow-core fibers provide a promising alternative by guiding light predominantly in air, substantially reducing nonlinear interactions, latency, and optical damage while enabling transmission regimes inaccessible to conventional solid-core fibers. Despite rapid advances in antiresonant hollow-core fiber attenuation and power handling, one of the largest remaining barriers to widespread adoption is reliable integration with the existing solid-core fiber ecosystem. …

Advances In Active And Passive Integrated Photonic Devices On Thin-Film Lithium Niobate, Pooja S. Kulkarni

Graduate Studies Theses and Dissertations 2026

Thin-film lithium niobate (TFLN) has emerged as a powerful platform for integrated photonics, combining the exceptional electro-optic, nonlinear, and optical properties of bulk lithium niobate with the scalability and compactness of planar nanophotonic technologies. Building on these principles, advanced device architectures such as adiabatic dichroic filters have demonstrated exceptional spectral performance spanning over two octaves of bandwidth on the TFLN platform. Beyond reciprocal devices, it also offers promising pathways toward integrated nonreciprocal components. By leveraging broadband filtering structures and advanced nonlinear photonic design strategies, compact and monolithic optical isolators can be envisioned without relying on traditional magneto-optic materials. In the …

An Investigation Into The Mechanisms, Barriers, Degree And Sphere Of Risk Influence In Corporate Security, Nicola Lockhart

Theses: Doctorates and Masters

This study investigates the sphere of corporate security risk influence within organisations, addressing the conceptual and practical ambiguity surrounding the activity’s capacity to shape organisational decisions, behaviours, and risk priorities. While corporate security’s protective role is widely recognised, its broader organisational risk influence remains under-theorised. The study defines the sphere of risk influence as the range of organisational stakeholders and environments with which the corporate security activity interacts, and within which it may engage, persuade, and mobilise action. This sphere is analytically constituted through the intersection of three dimensions: the mechanisms through which influence is attempted, the barriers that constrain …

Development Of Virtual Reality Learning Environments In Science To Engage Secondary Students In Hazardous Activities, Luke Spartalis

Theses: Doctorates and Masters

This research examines the need for change in including hazardous activities in education. As different learning technologies develop, platforms that retain authentic outcomes via virtual reality are needed. The main objective of this research is to examine the inclusion of Virtual Reality Learning Environments (VRLEs) to determine their value in areas that include hazardous conditions. The research considered the ways that VR tools could be optimised to support these activities, as well as considering the challenges of VRLE implementation. The study examined whether VRLE’s allowed for authentic experiences to sufficiently drive an acceptance of VR to complement existing teaching and …