Physical Sciences and Mathematics Commons^™

Gouldian Finch Monitoring: Nesting Activity - Goomig Project 2021 To 2022, J Graff

Irrigated Agricultural Development in the North

The Goomig Project (Weaber Plains Development Project) is an irrigated agricultural development located approximately 30 km north of Kununurra, which involved clearing approximately 9,260 ha of vegetation for agriculture. Approximately 11,470 ha of native vegetation surrounding, or remaining between, the cleared areas has been designated as a buffer area (the study area) to be managed to protect surrounding conservation reserves and watercourses (Strategen 2014). Gouldian Finch monitoring in the buffer area during ongoing operation is required as a condition of the approval for the project, and is outlined in the Gouldian Finch Conservation Plan (GFCP; Strategen 2014). Item 7 of …

Numerical Analysis Of A Model For The Growth Of Microorganisms, Alexander Craig Montgomery, Braden J. Carlson

Rose-Hulman Undergraduate Mathematics Journal

A system of first-order differential equations that arises in a model for the growth of microorganisms in a chemostat with Monod kinetics is studied. A new, semi-implicit numerical scheme is proposed to approximate solutions to the system. It is shown that the scheme is uniquely solvable and unconditionally stable, and further properties of the scheme are analyzed. The convergence rate of the numerical solution to the true solution of the system is given, and it is shown convergence of the numerical solutions to the true solutions is uniform over any interval [0, T ] for T > 0.

Using Differential Equations To Model A Cockatoo On A Spinning Wheel As Part Of The Scudem V Modeling Challenge, Miles Pophal, Chenming Zhen, Henry Bae

Rose-Hulman Undergraduate Mathematics Journal

For the SCUDEM V 2020 virtual challenge, we received an outstanding distinction for modeling a bird perched on a bicycle wheel utilizing the appropriate physical equations of rotational motion. Our model includes both theoretical calculations and numerical results from applying the Heaviside function for the swing motion of the bird. We provide a discussion on: our model and its numerical results, the overall limitations and future work of the model we constructed, and the experience we had participating in SCUDEM V 2020.

One-Stage Blind Source Separation Via A Sparse Autoencoder Framework, Jason Anthony Dabin

Dissertations

Blind source separation (BSS) is the process of recovering individual source transmissions from a received mixture of co-channel signals without a priori knowledge of the channel mixing matrix or transmitted source signals. The received co-channel composite signal is considered to be captured across an antenna array or sensor network and is assumed to contain sparse transmissions, as users are active and inactive aperiodically over time. An unsupervised machine learning approach using an artificial feedforward neural network sparse autoencoder with one hidden layer is formulated for blindly recovering the channel matrix and source activity of co-channel transmissions. The BSS sparse autoencoder …

Planning Methodology For Alternative Intersection Design And Selection, Liran Chen

Dissertations

The recent publication of the 6th Edition of the Highway Capacity Manual included a chapter on Ramp Terminals and Alternative Intersections that introduces various alternative intersection designs and assesses the performance of Median U-turn, Restricted crossing U-turn and Displaced left-turn intersections. Missing from the literature is an alternative intersection selection tool for identifying whether an alternative intersection would be successful under local conditions. With limited information of organized alternative intersection research, most planners must rely heavily on their personal judgement while selecting the most suitable intersection designs. As appealing as alternative intersections are, there is no comprehensive methodology for planners …

Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai

Dissertations

Harmful content, such as hate speech, online abuses, harassment, and cyberbullying, proliferates across various online communities. Live streaming as a novel online community provides ways for thousands of users (viewers) to entertain and engage with a broadcaster (streamer) in real-time in the chatroom. While the streamer has the camera on and the screen shared, tens of thousands of viewers are watching and messaging in real-time, resulting in concerns about harassment and cyberbullying. To regulate harmful content—toxic messages in the chatroom, streamers rely on a combination of automated tools and volunteer human moderators (mods) to block users or remove content, which …

Waves And Oscillations In A Sunspot: Observations And Modeling Of Noaa Ar 12470, Yi Chai

Dissertations

Waves and oscillations are important solar phenomena not only because they can propagate and dissipate energy in the chromosphere, but also because they carry information about the structure of the atmosphere in which they propagate. Among these phenomena, the one of the most interesting ones occurs in the sunspot umbra. In this area, continuously propagating magnetohydrodynamic (MHD) waves generated from below the photosphere create the famous 3-minute sunspot umbral oscillations that affect the line profile of spectral lines due to temperature, density, and velocity changes of the plasma in the region. In the past decades, numerous observations and models have …

Nondestructive Evaluation Of 3d Printed, Extruded, And Natural Polymer Structures Using Terahertz Spectroscopy And Imaging, Alexander T. Clark

Dissertations

Terahertz (THz) spectroscopy and imaging are considered for the nondestructive evaluation (NDE) of various three-dimensional (3D) printed, extruded, and natural polymer structures. THz radiation is the prime candidate for many NDE challenges due to the added benefits of safety, increased contrast and depth resolution, and optical characteristic visualization when compared to other techniques. THz imaging, using a wide bandwidth pulse-based system, can evaluate the external and internal structure of most nonconductive and nonpolar materials without any permanent effects. NDE images can be created based on THz pulse attributes or a material’s spectroscopic characteristics such as refractive index, attenuation coefficient, or …

Investigation Of Topological Phonons In Acoustic Metamaterials, Wenting Cheng

Dissertations

Topological acoustics is a recent and intense area of research. It merges the knowledge of mathematical topology, condensed matter physics, and acoustics. At the same time, it has been pointed out that quasiperiodicity can greatly enhance the periodic table of topological systems. Because quasiperiodic patterns have an intrinsic global degree of freedom, which exists in the topological space called the hull of a pattern, where the shape traced in this topological space is called the phason. The hull augments the physical space, which opens a door to the physics of the integer quantum Hall effect (IQHE) in arbitrary dimensions. In …

A Self-Learning Intersection Control System For Connected And Automated Vehicles, Ardeshir Mirbakhsh

Dissertations

This study proposes a Decentralized Sparse Coordination Learning System (DSCLS) based on Deep Reinforcement Learning (DRL) to control intersections under the Connected and Automated Vehicles (CAVs) environment. In this approach, roadway sections are divided into small areas; vehicles try to reserve their desired area ahead of time, based on having a common desired area with other CAVs; the vehicles would be in an independent or coordinated state. Individual CAVs are set accountable for decision-making at each step in both coordinated and independent states. In the training process, CAVs learn to minimize the overall delay at the intersection. Due to the …

Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld

Dissertations

This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing paradigm more closely modeled after the biological brain in an effort to harness its low power processing capability. SNNs use an event based processing scheme which leads to significant power savings when implemented in dedicated neuromorphic hardware such as Intel’s Loihi chip.

This work …

Numerical Methods For Optimal Transport And Optimal Information Transport On The Sphere, Axel G. R. Turnquist

Dissertations

The primary contribution of this dissertation is in developing and analyzing efficient, provably convergent numerical schemes for solving fully nonlinear elliptic partial differential equation arising from Optimal Transport on the sphere, and then applying and adapting the methods to two specific engineering applications: the reflector antenna problem and the moving mesh methods problem. For these types of nonlinear partial differential equations, many numerical studies have been done in recent years, the vast majority in subsets of Euclidean space. In this dissertation, the first major goal is to develop convergent schemes for the sphere. However, another goal of this dissertation is …

Optimization Opportunities In Human In The Loop Computational Paradigm, Dong Wei

Dissertations

An emerging trend is to leverage human capabilities in the computational loop at different capacities, ranging from tapping knowledge from a richly heterogeneous pool of knowledge resident in the general population to soliciting expert opinions. These practices are, in general, termed human-in-the-loop (HITL) computations.

A HITL process requires holistic treatment and optimization from multiple standpoints considering all stakeholders: a. applications, b. platforms, c. humans. In application-centric optimization, the factors of interest usually are latency (how long it takes for a set of tasks to finish), cost (the monetary or computational expenses incurred in the process), and quality of the completed …

Towards Practicalization Of Blockchain-Based Decentralized Applications, Songlin He

Dissertations

Blockchain can be defined as an immutable ledger for recording transactions, maintained in a distributed network of mutually untrusting peers. Blockchain technology has been widely applied to various fields beyond its initial usage of cryptocurrency. However, blockchain itself is insufficient to meet all the desired security or efficiency requirements for diversified application scenarios. This dissertation focuses on two core functionalities that blockchain provides, i.e., robust storage and reliable computation. Three concrete application scenarios including Internet of Things (IoT), cybersecurity management (CSM), and peer-to-peer (P2P) content delivery network (CDN) are utilized to elaborate the general design principles for these two main …

Representation Learning In Finance, Ajim Uddin

Dissertations

Finance studies often employ heterogeneous datasets from different sources with different structures and frequencies. Some data are noisy, sparse, and unbalanced with missing values; some are unstructured, containing text or networks. Traditional techniques often struggle to combine and effectively extract information from these datasets. This work explores representation learning as a proven machine learning technique in learning informative embedding from complex, noisy, and dynamic financial data. This dissertation proposes novel factorization algorithms and network modeling techniques to learn the local and global representation of data in two specific financial applications: analysts’ earnings forecasts and asset pricing.

Financial analysts’ earnings forecast …

Periodic Fast Multipole Method, Ruqi Pei

Dissertations

Applications in electrostatics, magnetostatics, fluid mechanics, and elasticity often involve sources contained in a unit cell C, centered at the origin, on which periodic boundary condition are imposed. The free-space Green’s functions for many classical partial differential equations (PDE), such as the modified Helmholtz equation, are well-known. Among the existing schemes for imposing the periodicity, three common approaches are: direct discretization of the governing PDE including boundary conditions to yield a large sparse linear system of equations, spectral methods which solve the governing PDE using Fourier analysis, and the method of images based on tiling the plane with copies of …

Nystrom Methods For High-Order Cq Solutions Of The Wave Equation In Two Dimensions, Erli Wind-Andersen

Dissertations

An investigation of high order Convolution Quadratures (CQ) methods for the solution of the wave equation in unbounded domains in two dimensions is presented. These rely on Nystrom discretizations for the solution of the ensemble of associated Laplace domain modified Helmholtz problems. Two classes of CQ discretizations are considered: one based on linear multistep methods and the other based on Runge-Kutta methods. Both are used in conjunction with Nystrom discretizations based on Alpert and QBX quadratures of Boundary Integral Equation (BIE) formulations of the Laplace domain Helmholtz problems with complex wavenumbers. CQ in conjunction with BIE is an excellent candidate …

Atmospheric Mercury Chemistry: Detection, Kinetics, And Mechanism, Na Mao

Dissertations

The presence of mercury in the environment is of global concern due to its toxicity. The atmosphere is an important transient reservoir for mercury released by human activities and natural sources. The knowledge of atmospheric mercury chemistry is critical for understanding the global biogeochemical cycle. In the atmosphere, mercury primarily exists in three forms: gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM). Over the last decade, the existing knowledge of mercury cycle has dramatically changed: (1) There has been increasing evidence that current detection methods do not accurately quantify gaseous oxidized mercury and a technique which …

Nusax: Multilingual Parallel Sentiment Dataset For 10 Indonesian Local Languages, Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Rahmad Mahendra, Fajri Koto, Ade Romadhony, Kemal Kurniawan, David Moeljadi, Radityo Eko Prasojo, Pascale Fung, Timothy Baldwin, Jey Han Lau

Natural Language Processing Faculty Publications

Natural language processing (NLP) has a significant impact on society via technologies such as machine translation and search engines. Despite its success, NLP technology is only widely available for high-resource languages such as English and Chinese, while it remains inaccessible to many languages due to the unavailability of data resources and benchmarks. In this work, we focus on developing resources for languages in Indonesia. Despite being the second most linguistically diverse country, most languages in Indonesia are categorized as endangered and some are even extinct. We develop the first-ever parallel resource for 10 low-resource languages in Indonesia. Our resource includes …

Towards A Cross-Layer Coupled Design Framework For Big Data Workflows, Qianwen Ye

Dissertations

The processing and analysis of big data increasingly rely on workflow technologies for knowledge discovery and scientific innovation. The execution of such workflows goes far beyond the capability and capacity of single computers and is now commonly supported on reliable and scalable data storage and analysis platforms in distributed environments, such as the Hadoop ecosystem. Workflow performance largely depends on how big data systems are configured and used. For example, the makespan of a big data workflow is affected by multiple layers of big data systems, including the parallel computing engine it runs on, the resource manager that orchestrates various …

Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao

Dissertations

The world has never been more connected, led by the information technology revolution in the past decades that has fundamentally changed the way people interact with each other using social networks. Consequently, enormous human activity data are collected from the business world and machine learning techniques are widely adopted to aid our decision processes. Despite of the success of machine learning in various application scenarios, there are still many questions that need to be well answered, such as optimizing machine learning outcomes when desired knowledge cannot be extracted from the available data. This naturally drives us to ponder if one …

Reactive Iron Mineral Coatings In Redox Transition Zones Of A Site With Historical Contamination: Abiotic Attenuation, Xin Yin

Dissertations

Reactive iron mineral coatings are found throughout reduction-oxidation (redox) transition zones and play a significant role in contaminant transformation processes. In this study, an 18.3-meter core is collected, subsampled, and preserved under anoxic conditions to maintain its original redox state. Screening analyses are conducted at sampling increments of 5.08 cm in depth for the following: elemental concentrations with X-ray fluorescence (XRF), sediment pH, sediment oxidation-reduction potential (ORP), total volatile organic carbon (TVOC) in the sample headspace, and abundant bacteria (16S rRNA sequencing). Using the Fe and S gradients correlated with microbial data, five RTZs are delineated. To characterize iron mineral …

Development Of Novel Mass Spectrometric Methods For Reaction Screening, Oligosaccharide Detection, And Nitrosamine Quantitation, Qi Wang

Dissertations

Benefitting from its high detection sensitivity and specificity, mass spectrometry (MS) has become a powerful technique in academia and industry. The aim of this dissertation study is to develop new mass spectrometric methods for organic reaction screening, detection of oligosaccharide/glycan in complex matrices, and nitrosamine absolute quantitation.

First, an electrochemistry/mass spectrometry (EC/MS) platform is built to generate an N-cyclopropylaniline radical cation electrochemically and to monitor its reactivity toward alkenes, which leads to the discovery of a new redox neutral reaction of intermolecular [3 + 2] annulation of N-cyclopropylanilines and alkenes. Net redox neutral electrosynthesis is quite rare in synthetic organic …

Adversarially Robust And Accurate Machine Learning For Image Classification, Yanan Yang

Dissertations

Machine learning techniques in medical imaging systems are accurate, but minor perturbations in the data known as adversarial attacks can fool them. These attacks make the systems vulnerable to fraud and deception, and thus a significant challenge has been posed in practice. This dissertation presents the gradient-free trained sign activation networks to detect and deter adversarial attacks on medical imaging AI (Artificial Intelligence) systems. Experimental results show a higher distortion value is required to attack the proposed model than other state-of-the-art models on brain MRI (Magnetic resonance imaging), Chest X-ray, and histopathology image datasets. Moreover, the proposed models outperform the …

Private Information Retrieval And Function Computation For Noncolluding Coded Databases, Sarah A. Obead

Dissertations

The rapid development of information and communication technologies has motivated many data-centric paradigms such as big data and cloud computing. The resulting paradigmatic shift to cloud/network-centric applications and the accessibility of information over public networking platforms has brought information privacy to the focal point of current research challenges. Motivated by the emerging privacy concerns, the problem of private information retrieval (PIR), a standard problem of information privacy that originated in theoretical computer science, has recently attracted much attention in the information theory and coding communities. The goal of PIR is to allow a user to download a message from a …

Bodipy-Based Light-Responsive Materials, Zhaoxiong Wan

Dissertations

The energy required for life on our planet is provided by light. In science, light is an important and powerful tool for measuring and modifying substances. For example, under the effect of illumination, light-responsive materials can change their physical and chemical properties. Photochemistry is a branch of research to study the effects of light irradiation on chemical structures and reactions. Some photochemical changes could lead to chemical bond dissociation (such as in photosynthesis) and structure isomerization (such as in the retina). Photochemistry has a strong relationship with human lives and it is essential in many ways. Among photophysics, fluorescence emission …

Type I Error Rate Controlling Procedures For Multiple Hypotheses Testing, Beibei Li

Dissertations

This dissertation addresses several different but related topics arising in the field of multiple testing, including weighted procedures and graphical approaches for controlling the familywise error rate (FWER), and stepwise procedures with control of the false discovery rate (FDR) for discrete data. It consists of three major parts.

The first part investigates weighted procedures for controlling the FWER. In many statistical applications, hypotheses may be differentially weighted according to their different importance. Many weighted multiple testing procedures (wMTPs) have been developed for controlling the FWER. Among these procedures, two weighted Holm procedures are commonly used in practice: one is based …

Formation Of Gaseous Peptide Ions From Electrospray Droplets: Competition Between The Ion Evaporation Mechanism And Charged Residue Mechanism., Elnaz Aliyari, Lars Konermann

Chemistry Publications

The transfer of peptide ions from solution into the gas phase by electrospray ionization (ESI) is an integral component of mass spectrometry (MS)-based proteomics. The mechanisms whereby gaseous peptide ions are released from charged ESI nanodroplets remain unclear. This is in contrast to intact protein ESI, which has been the focus of detailed investigations using molecular dynamics (MD) simulations and other methods. Under acidic liquid chromatography/MS conditions, many peptides carry a solution charge of 3+ or 2+. Because of this pre-existing charge and their relatively small size, prevailing views suggest that peptides follow the ion evaporation mechanism (IEM). The IEM …

Language Learning Using Models Of Intentionality In Repeated Games With Cheap Talk, Jonathan Berry Skaggs

Theses and Dissertations

Language is critical to establishing long-term cooperative relationships among intelligent agents (including people), particularly when the agents' preferences are in conflict. In such scenarios, an agent uses speech to coordinate and negotiate behavior with its partner(s). While recent work has shown that neural language modeling can produce effective speech agents, such algorithms typically only accept previous text as input. However, in relationships among intelligent agents, not all relevant context is expressed in conversation. Thus, in this paper, we propose and analyze an algorithm, called Llumi, that incorporates other forms of context to learn to speak in long-term relationships modeled as …

Un-Fair Trojan: Targeted Backdoor Attacks Against Model Fairness, Nicholas Furth

Theses

Machine learning models have been shown to be vulnerable against various backdoor and data poisoning attacks that adversely affect model behavior. Additionally, these attacks have been shown to make unfair predictions with respect to certain protected features. In federated learning, multiple local models contribute to a single global model communicating only using local gradients, the issue of attacks become more prevalent and complex. Previously published works revolve around solving these issues both individually and jointly. However, there has been little study on the effects of attacks against model fairness. Demonstrated in this work, a flexible attack, which we call Un-Fair …