Physical Sciences and Mathematics Commons^™

Near-Infrared Spectroscopy Analysis Of The Nutrient Content Of Dairy Pastures, R C. Kellaway, C Stimson, R J. Tassell

IGC Proceedings (1993-2023)

Pasture samples from temperate and tropical species were collected before and after grazing, at regular intervals, on 3 dairy farms in New South Wales over a period of 3 years. All samples (n=693) were analysed on a near-infrared (NIR) spectrophotometer with a scanning monochromator. Subsets of samples selected for calibration and validation, were analysed by wet chemistry methods for estimated metabolisable energy (MID), crude protein (CP), organic matter (OM), acid-detergent fibre (ADF), Ca, P, Mg, K, Na, S, Cu, Mn and Zn. These data were used lo develop NIR equations using partial least squares analyses. Standard errors of laboratory analysis …

Influence Of Oxygen Leakage Through Stretch Film On Quality Of Round Bale Silage, P Lingvall, C M. Pettersson, P Wilhelmsson

IGC Proceedings (1993-2023)

The ensiling-process is based on anaerobic conditions. Therefore, it is important to get "air tight" parcels covering big-bale silage. Wrapping round bales wilh stretch film has improved silage quality, and reduced diy matter (OM) and energy losses. In this experiment we studied the influence of stretch film quality, film thickness, .storage temperature and storage place on fermentation, microbial growth/ and DM losses. Additionally, oxygen permeability of stretch film wrapped in 4 or 6 layers around artificial bales (metal) and DM losses was tested In a model. High storage temperature, low total film thickness and high film permeability to oxygen increased …

Container Migration: A Perfomance Evaluation Between Migrror And Pre-Copy, Xinwen Liang

Electronic Thesis and Dissertation Repository

The concept of migration and checkpoint/restore has been a very important topic in research for many types of applications including any distributed systems/applications or single massive systems/applications; and low latency vehicular use cases, augmented reality(AR) and virtual reality(VR) applications. Migrating a service requires that the state of the service is preserved. This requires checkpointing the state and restoring it on a different server in multiple rounds to avoid a total loss of all data in case of a failure, fault or error. There are many different types of migration techniques utilized such as cold migration, pre-copy migration, post-copy migration.

Compared …

We Train Ai, Why Not Humans, Too? An Exploration Of Human-Ai Team Training For Future Workplace Viability, Caitlin M. Lancaster

All Dissertations

The integration of Artificial Intelligence (AI) in the workforce is transforming team dynamics, leading to the emergence of Human-AI Teams (HATs). These teams offer opportunities to capitalize on human strengths with AI's prowess, offering significant opportunities for innovation and efficiency. Effective HAT functioning requires aligning human expectations with AI capabilities and bridging knowledge gaps between teammates. Despite this potential, key integration challenges remain, such as developing shared mental models, addressing skill limitations, and overcoming negative AI perceptions. Existing training efforts often apply human-human teaming principles directly to HATs, overlooking AI's role as a teammate and limiting the development of HAT-specific …

Relating Elasticity And Other Multiplicative Properties Among Orders In Number Fields And Related Rings, Grant Moles

All Dissertations

This dissertation will explore factorization within orders in a number ring. By far the most well-understood of these orders are rings of algebraic integers. We will begin by examining how certain types of subrings may relate to the larger rings in which they are contained. We will then apply this knowledge, along with additional techniques, to determine how the elasticity in an order relates to the elasticity of the full ring of algebraic integers. Using many of the same strategies, we will develop a corresponding result in the rings of formal power series. Finally, we will explore a number of …

Probabilistic Frames And Concepts From Optimal Transport, Dongwei Chen

All Dissertations

As the generalization of frames in the Euclidean space $\mathbb{R}^n$, a probabilistic frame is a probability measure on $\mathbb{R}^n$ that has a finite second moment and whose support spans $\mathbb{R}^n$. The p-Wasserstein distance with $p \geq 1$ from optimal transport is often used to compare probabilistic frames. It is particularly useful to compare frames of various cardinalities in the context of probabilistic frames. We show that the 2-Wasserstein distance appears naturally in the fundamental objects of frame theory and draws consequences leading to a geometric viewpoint of probabilistic frames.

We convert the classic lower bound estimates of 2-Wasserstein distance \cite{Gelbrich90, …

Exploring Intraplate Seismicity In The Midwest, Alexa Fernández

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Intraplate seismicity represents a notable occurrence within the stable North American Craton. This research explores the potential sources of stresses that could reactivate older faults and influence seismic activity within this region. Among these sources, the enduring impact of the last glacial period is considered, which includes continued glacial isostatic adjustments (GIA). During GIA the lithosphere rebounds due to the retreating ice, and the forebulge caused by far-field flexure in response to the glacial load, collapses. This results in significant faulting, fracturing, and seismic activity associated with the deglaciation phase. The adjustment of the lithosphere manifests as both near surface …

Instantons In Φ4 Theories: Transseries, Virial Theorems, And Numerical Aspects, Ludovico T. Giorgini, Ulrich D. Jentschura, Enrico M. Malatesta, Tommaso Rizzo, Jean Zinn-Justin

Physics Faculty Research & Creative Works

We discuss numerical aspects of instantons in two- and three-dimensional φ4 theories with an internal O(N) symmetry group, the so-called N-vector model. By combining asymptotic transseries expansions for large arguments with convergence acceleration techniques, we obtain high-precision values for certain integrals of the instanton that naturally occur in loop corrections around instanton configurations. Knowledge of these numerical properties is necessary in order to evaluate corrections to the large-order factorial growth of perturbation theory in φ4 theories. The results contribute to the understanding of the mathematical structures underlying the instanton configurations.

Perturbative Versus Non-Perturbative Renormalization, S. Hariharakrishnan, Ulrich D. Jentschura, I. G. Marian, K. Szabo, I. Nandori

Physics Faculty Research & Creative Works

Approximated functional renormalization group (FRG) equations lead to regulator-dependent β-functions, in analogy to the scheme-dependence of the perturbative renormalization group (pRG) approach. A scheme transformation redefines the couplings to relate the β-functions of the FRG method with an arbitrary regulator function to the pRG ones obtained in a given scheme. Here, we consider a periodic sine-Gordon scalar field theory in d = 2 dimensions and show that the relation of the FRG and pRG approaches is intricate. Although both the FRG and the pRG methods are known to be sufficient to obtain the critical frequency β c 2 = 8 …

Doubly Differential Cross Sections For Ionization In Proton Collisions With Atomic Hydrogen: Energy And Angular Distribution Of Emitted Electrons, C. T. Plowman, K. H. Spicer, N. W. Antonio, M. S. Schöffler, Michael Schulz, I. Bray, A. S. Kadyrov

Physics Faculty Research & Creative Works

We use the two-center wave-packet convergent close-coupling approach to ion-atom collisions to calculate the energy and angular distribution of electrons emitted in proton collisions with atomic hydrogen. Results are provided across a wide range of intermediate energies where many competing reaction channels make calculations challenging. The present data consistently agree with the available experimental measurements and improve upon previously available results based on perturbative and classical methods. Furthermore, we extend the range of electron angles and energies over which theoretical data are available for the doubly differential cross section for ionization. This provides strong evidence that at the level of …

Methods For Improving Low Frequency Selection And Electrode Firing Order In Cochlear Implants, James H. Keen Jr.

University of New Orleans Theses and Dissertations

The Advanced Bionics cochlear implant devices allocate static frequency bins to electrode channels based on the natural tonotopic organization of the cochlea. These frequency bins are wide and limited, especially in the lower range. Considering that the fundamental tones of the human voice and the primary melodic tones in music are in this lower range, it is important to have accurate representation of this frequency content. Here, adjustments to the frequency bin allocation algorithm used in the crowdsourced CI Hackathon code are made to allow a more accurate representation of the original signal. First, the frequency bins allocated to each …

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Sparse Neural Network To Enhance Performance Under Limited Parameter Constraints., Nailah Rawnaq

Graduate Theses and Dissertations

Over the past decade, the widespread adoption of deep neural networks has been a breakthrough driven by significant computational advancements. Additionally, the number of parameters of those models is exponentially increasing for performing complex tasks and achieving better performance. However, in most practical cases, often there are constraints in the number of parameters due to limited resources in storage size and computational cost. Network pruning can lead to an optimal solution to this problem. In this thesis, I present supporting evidence to the hypothesis that higher sparsity leads to better performance for a convolution-based neural network. I perform performance studies …

Gan With Skip Patch Discriminator For Biological Electron Microscopy Image Generation, Nishith Ranjon Roy

Graduate Theses and Dissertations

GAN models have been successfully used for image generation in various sections such as real-life objects like human faces, cars, animal faces, landscapes, etc. This work focuses on biological electron microscopy (EM) image generation. Unlike other real-life objects, biological EM images are obtained through electron microscopy techniques to study biological specimens. Electron microscopy offers high resolution and magnification capabilities, making it a powerful tool for visualizing biological structures at the nanoscale. However, using GAN models for biological EM image generation poses challenges due to the complex and unique arrangements of biological structures and the sparse and asymmetrical patterns in EM …

A Framework For The Foundation Of The Philosophy Of Artificial Intelligence, Emily Barnes, James Hutson

Faculty Scholarship

In recent years, the rapid advancement of artificial intelligence (AI) technology has sparked profound questions about the nature of machine intelligence and the possibility of AI consciousness. As AI systems become increasingly sophisticated, examining their philosophical foundations has become imperative. This article investigates the intricate relationship between AI and existential thought, aiming to establish a comprehensive framework for understanding AI's philosophical underpinnings. The historical development of AI, from symbolic AI to contemporary machine learning paradigms, highlights the increasing complexity and sophistication of AI systems, prompting significant philosophical debates about machine consciousness. Theoretical models such as the Independent Core Observer Model …

Techno-Economic And Environmental Assessments Of Produced Water Treatment Technologies For Beneficial Reuse, Elora Afrin

Water Resources Science and Technology Theses and Graduate Research Reports

Produced water (PW) is a bulk portion of byproduct generated during oil and gas extraction operations and can be potentially reused for various purposes. However, the treatment costs and associated environmental issues call for a multitude of factors for proper management. This research aims to evaluate the viability of technologies for treating PW in terms of their technical performance, cost-effectiveness, and environmental considerations. Technologies evaluated include well-established processes such as electrodialysis (ED), electrodialysis reversal (EDR), ion exchange, chemical oxidation, electrocoagulation (EC), chemical coagulation (CC), nanofiltration (NF) etc. Associated case studies have been studied. However, except EC and CC, other technologies …

Rock Wall Fracturing As A Potential Control On River Valley Width In The Buffalo National River, Arkansas, Kindle Hon

Graduate Theses and Dissertations

Quantifying bedrock properties that control the persistence of fallen rock material (talus) along bedrock walls bounding river valleys may be a key factor in understanding what controls the rate at which these river valleys widen. My work is a component of a collaborative research project focused on the overarching hypothesis that the persistence vs. erodibility of talus that buffers river valley walls can be a first-order control on valley widening rates. I hypothesize that the primary control for creating erodible or persistent talus is the fracture spacing of bedrock valley walls as it sets the maximum block size of collapsed …

Rabi Oscillations And Entanglement Between Two Atoms Interacting By The Rydberg Blockade And With A Quantized Radiation Field Studied By The Jaynes-Cummings Model, Francisco D. Santillan, Andreas Hanke

Physics and Astronomy Faculty Publications and Presentations

The interaction between atoms and a quantized radiation field is fundamentally important in quantum optics and quantum information science. Due to their unusual properties, Rydberg atoms are promising building blocks for two-qubit gates and atom-light quantum interfaces, exploiting the Rydberg blockade interaction which prevents two atoms at close distance from being simultaneously excited to Rydberg states. Recently, this effect was used to engineer quantum processors based on arrays of interacting Rydberg atoms illuminated by Raman lasers. Motivated by these experiments, we extend the Jaynes-Cummings model to study the interaction between two Rydberg atoms interacting by the Rydberg blockade and a …

The Geometry Of Ancient Solutions To Curvature Flows, Sathyanarayanan Rengaswami

Doctoral Dissertations

Following the tremendous success of the mean curvature flow, other variants such as the Gauss curvature flow, inverse mean curvature flow have been investigated in great detail, leading to interesting applications to other fields including partial differential equations, convex geometry etc. This calls for an investigation of curvature flow as a general phenomenon. While basic existence and uniqueness results, roundness estimates etc have been obtained, there isn't a substantial body of work that addresses the geometry of solutions of curvature flows and their relation to the choice of speed function used. It is therefore interesting to investigate curvature flows as …

Causvsr: Causality Inspired Visual Sentiment Recognition, Xinyue Zhang, Zhaoxia Wang, Hailing Wang, Jing Xiang, Chunwei Wu, Guitao Cao

Research Collection School Of Computing and Information Systems

Visual Sentiment Recognition (VSR) is an evolving field that aims to detect emotional tendencieswithin visual content. Despite its growing significance, detecting emotions depicted in visual content,such as images, faces challenges, notably the emergence of misleading or spurious correlationsof the contextual information. In response to these challenges, we propose a causality inspired VSRapproach, called CausVSR. CausVSR is rooted in the fundamental principles of Emotional Causalitytheory, mimicking the human process from receiving emotional stimuli to deriving emotional states.CausVSR takes a deliberate stride toward conquering the VSR challenges. It harnesses the power of astructural causal model, intricately designed to encapsulate the dynamic causal …

Neural Network Semantic Backdoor Detection And Mitigation: A Causality-Based Approach, Bing Sun, Jun Sun, Wayne Koh, Jie Shi

Research Collection School Of Computing and Information Systems

Different from ordinary backdoors in neural networks which are introduced with artificial triggers (e.g., certain specific patch) and/or by tampering the samples, semantic backdoors are introduced by simply manipulating the semantic, e.g., by labeling green cars as frogs in the training set. By focusing on samples with rare semantic features (such as green cars), the accuracy of the model is often minimally affected. Since the attacker is not required to modify the input sample during training nor inference time, semantic backdoors are challenging to detect and remove. Existing backdoor detection and mitigation techniques are shown to be ineffective with respect …

Watme: Towards Lossless Watermarking Through Lexical Redundancy, Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Text watermarking has emerged as a pivotal technique for identifying machine-generated text. However, existing methods often rely on arbitrary vocabulary partitioning during decoding to embed watermarks, which compromises the availability of suitable tokens and significantly degrades the quality of responses. This study assesses the impact of watermarking on different capabilities of large language models (LLMs) from a cognitive science lens. Our finding highlights a significant disparity; knowledge recall and logical reasoning are more adversely affected than language generation. These results suggest a more profound effect of watermarking on LLMs than previously understood. To address these challenges, we introduce Watermarking with …

Clamber: A Benchmark Of Identifying And Clarifying Ambiguous Information Needs In Large Language Models, Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, Dingnan Jin, Hongru Liang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Large language models (LLMs) are increasingly used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity remains unknown, ultimately risking user trust and satisfaction. To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy. Building upon the taxonomy, we construct 12K high-quality data to assess the strengths, weaknesses, and potential risks of various off-the-shelf LLMs.Our findings indicate the limited practical utility of current LLMs in identifying and clarifying ambiguous user queries, even enhanced by chain-of-thought (CoT) and few-shot prompting. These techniques may result in overconfidence …

Self-Chats From Large Language Models Make Small Emotional Support Chatbot Better, Zhonghua Zheng, Lizi Liao, Yang Deng, Libo Qin, Liqiang Nie

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) have shown strong generalization abilities to excel in various tasks, including emotion support conversations. However, deploying such LLMs like GPT-3 (175B parameters) is resource-intensive and challenging at scale. In this study, we utilize LLMs as “Counseling Teacher” to enhance smaller models’ emotion support response abilities, significantly reducing the necessity of scaling up model size. To this end, we first introduce an iterative expansion framework, aiming to prompt the large teacher model to curate an expansive emotion support dialogue dataset. This curated dataset, termed ExTES, encompasses a broad spectrum of scenarios and is crafted with meticulous strategies …

Exponential Qubit Reduction In Optimization For Financial Transaction Settlement, Elias X. Huber, Benjamin Y. L. Tan, Paul Robert Griffin, Dimitris G. Angelakis

Research Collection School Of Computing and Information Systems

We extend the qubit-efficient encoding presented in (Tan et al. in Quantum 5:454, 2021) and apply it to instances of the financial transaction settlement problem constructed from data provided by a regulated financial exchange. Our methods are directly applicable to any QUBO problem with linear inequality constraints. Our extension of previously proposed methods consists of a simplification in varying the number of qubits used to encode correlations as well as a new class of variational circuits which incorporate symmetries thereby reducing sampling overhead, improving numerical stability and recovering the expression of the cost objective as a Hermitian observable. We also …

Solving Long-Run Average Reward Robust Mdps Via Stochastic Games, Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Mehrdad Karrabi, Petr Novotný, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities into account. Robust Markov decision processes (RMDPs) address this shortcoming of MDPs by assigning to each transition an uncertainty set rather than a single probability value. In this work, we consider polytopic RMDPs in which all uncertainty sets are polytopes and study the problem of solving long-run average reward polytopic RMDPs. We present a novel perspective on this problem and show that it can be reduced to solving long-run average reward turn-based stochastic games with finite state …

Task Scheduling Strategy For 3dpcp Considering Multidynamic Information Perturbation In Green Scene, Jianjia He, Jian Wu, Keng Siau

Research Collection School Of Computing and Information Systems

The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for …

Palynostratigraphy And Bayesian Age Stratigraphic Model Of New Ca-Id-Tims Zircon Ages From The Walloon Coal Measures, Surat Basin, Australia, K. Sobczak, J. Cooling, T. Crossingham, H. G. Holl, M. Reilly, J. Esterle, J. L. Crowley, C. Hannaford, M. T. Mohr, Z. Hamerli, S. Hurter

Geosciences Faculty Publications and Presentations

The Surat Basin hosts significant coal and coal seam gas resources. New high-precision CA-TIMS U/Pb zircon ages from tuffs and Bayesian age stratigraphic models are combined with palynology from fine-grained sedimentary rocks and zircon trace elements to provide further chronostratigraphic and biostratigraphic constrains on the Walloon Coal Measures in the eastern margin of the Surat Basin and infer the palaeoenvironment and tectonic setting. The tuff ages range from 165.88 ± 0.11 Ma to 158.84 ± 0.05 Ma, with those from the stratigraphically lower Taroom Coal Measures ranging from 165.88 ± 0.11 to 163.05 ± 0.08 Ma and Juandah Coal Measures …

Assessing Gtfs Accuracy, Gregory L. Newmark

Mineta Transportation Institute

The promised benefits of the General Transit Feed Specification (GTFS) Schedule and Realtime standards are dependent on the underlying quality of the data. Despite this fundamental reliance, there has been relatively little research on techniques and strategies to assess GTFS accuracy. The need for such assessment is growing as federal and state governments increasingly require transit agencies to make these data available to the public. This research fills this gap by presenting a suite of methods and metrics to assess the temporal accuracy of GTFS Realtime and the spatial accuracy of GTFS Schedule feeds. The temporal assessment demonstrates an approach …

Forecasting Commercial Vehicle Miles Traveled (Vmt) In Urban California Areas, Steve Chung, Jaymin Kwon, Yushin Ahn

Mineta Transportation Institute

This study investigates commercial truck vehicle miles traveled (VMT) across six diverse California counties from 2000 to 2020. The counties—Imperial, Los Angeles, Riverside, San Bernardino, San Diego, and San Francisco—represent a broad spectrum of California’s demographics, economies, and landscapes. Using a rich dataset spanning demographics, economics, and pollution variables, we aim to understand the factors influencing commercial VMT. We first visually represent the geographic distribution of the counties, highlighting their unique characteristics. Linear regression models, particularly the least absolute shrinkage and selection operator (LASSO) and elastic net regressions are employed to identify key predictors of total commercial VMT. LASSO regression …