Physical Sciences and Mathematics Commons^™

Thermometry And Microstructural Analysis Imply Protracted Extensional Exhumation Of The Tso Morari Uhp Nappe, Northwestern Himalaya: Implications For Models Of Uhp Exhumation, Sean P. Long, Matthew J. Kohn, Buchanan C. Kerswell, Jesslyn K. Starnes, Kyle P. Larson, Nolan R. Blackford, Emmanuel Soignard

Geosciences Faculty Publications and Presentations

Documenting the processes that facilitate exhumation of ultrahigh‐pressure (UHP) rocks at convergent margins is critical for understanding orogen dynamics. Here, we present structural and temperature data from the Himalayan UHP Tso Morari nappe (TMN) and overlying nappes, which we integrate with published pressure‐temperature‐time constraints to refine interpretations for their structural evolution and exhumation history. Our data indicate that the 5.5‐km‐thick TMN is the upper portion of a penetratively deformed ductile slab, which was extruded via distributed, pure shear‐dominated, top‐down‐to‐east shearing. Strain in the TMN is recorded by high‐strength quartz fabrics (density norms between 1.74 and 2.86) and finite strain data …

Seasonal Variability Of Upwelling And Downwelling Surface Current Patterns Near A Small Coastal Embayment, Nicholas Trautman

Physics

Upwelling in coastal embayments is important to a variety of physical and biological processes. Despite their ubiquity, circulation patterns in small bays (width and length scales ≤ 20 km) in eastern boundary current upwelling systems are relatively understudied compared to their larger counterparts. In this study, we apply a conditional averaging technique to investigate upwelling- and downwelling-driven circulation in a small coastal embayment located in Central California [San Luis Obispo (SLO) Bay]. We also investigate intraseasonal differences in the current patterns in SLO Bay. Conditional averaging reveals distinct intraseasonal differences and features that are obscured by traditional seasonal averages when …

Monitoring 2019 Bonnet Carré Spillway Impacts - Final Report, J. Read Hendon, Jerry D. Wiggert, Jill Hendon

Faculty Publications

Due to the multiple and extended openings of the Bonnet Carré Spillway in 2019, the University of Southern Mississippi (USM) was tasked by the Mississippi Department of Marine Resources to conduct ecological sampling in the Mississippi Sound and adjacent waters. in an effort to better understand the impacts of the extensive freshwater diversion of Bonnet Carré Spillway operations on Mississippi's coastal and marine resources. The period of performance for this project was June 1, 2019, to August 31, 2019. This technical report summarizes the three months of weekly surveys and analyses, over June - August 2019, conducted by the University …

Setting Constraints On The Lunar Exosphere: A Comprehensive Analysis Of Velocity Resolved Sodium And Potassium Line Profile Measurements, Dona Chathuni P. Kuruppuaratchi

Doctoral Dissertations and Master's Theses

This dissertation outlines and presents the most comprehensive set of velocity-resolved measurements of sodium D2 (5889.9509 Å) lines taken over multiple lunations spanning seven years (2011 – 2017). These data are used to study the morphology and dynamics of the lunar exosphere. Additionally, potassium D1 (7698.9646 Å) is used as a complement to sodium. The two species approach, with sodium being the main attraction, provides constraints on the critical drivers of the lunar exosphere. Observations were made at the National Solar Observatory McMath – Pierce Telescope, Kitt Peak, Arizona where I personally collected both sodium and potassium data over about …

Higher Order Interactions In Complex Networks Of Phase Oscillators Promote Abrupt Synchronization Switching, Per Sebastian Skardal, Alex Arenas

Faculty Scholarship

© 2020, The Author(s). Synchronization processes play critical roles in the functionality of a wide range of both natural and man-made systems. Recent work in physics and neuroscience highlights the importance of higher-order interactions between dynamical units, i.e., three- and four-way interactions in addition to pairwise interactions, and their role in shaping collective behavior. Here we show that higher-order interactions between coupled phase oscillators, encoded microscopically in a simplicial complex, give rise to added nonlinearity in the macroscopic system dynamics that induces abrupt synchronization transitions via hysteresis and bistability of synchronized and incoherent states. Moreover, these higher-order interactions can stabilize …

A Predictive Analytics Approach To Building A Decision Support System For Improving Graduation Rates At A Four-Year College, Xuan Wang, Helmut Schneider, Kenneth R. Walsh

Information Systems Faculty Publications and Presentations

Although graduation rates have interested stakeholders, educational researchers, and policymakers for some time, little progress has been made on the overall graduation rate at four-year state colleges. Even though selective admission based on academic indicators such as high school GPA and ACT/ SAT have widely been used in the USA for years, and recent statistics show that less than 40% of students graduate from four-year state colleges in four years in the US. The authors propose using an ensemble of analytic models that considers cost as a better form of analysis that can be used as input to decision support …

Fractional Nonlinear Volterra–Fredholm Integral Equations Involving Atangana–Baleanu Fractional Derivative: Framelet Applications, Mutaz Mohammad, Alexander Trounev

All Works

© 2020, The Author(s). In this work, we propose a framelet method based on B-spline functions for solving nonlinear Volterra–Fredholm integro-differential equations and by involving Atangana–Baleanu fractional derivative, which can provide a reliable numerical approximation. The framelet systems are generated using the set of B-splines with high vanishing moments. We provide some numerical and graphical evidences to show the efficiency of the proposed method. The obtained numerical results of the proposed method compared with those obtained from CAS wavelets show a great agreement with the exact solution. We confirm that the method achieves accurate, efficient, and robust measurement.

Cross Dataset Evaluation For Iot Network Intrusion Detection, Anjum Farah

Theses and Dissertations

With the advent of Internet of Things (IOT) technology, the need to ensure the security of an IOT network has become important. There are several intrusion detection systems (IDS) that are available for analyzing and predicting network anomalies and threats. However, it is challenging to evaluate them to realistically estimate their performance when deployed. A lot of research has been conducted where the training and testing is done using the same simulated dataset. However, realistically, a network on which an intrusion detection model is deployed will be very different from the network on which it was trained. The aim of …

Novel Approaches To The Determination Of Toxic Metals In Industrial Waste And Soil Extracts, Garrett Bruce Finn

Theses and Dissertations

Abstract:Because of their environmental impact, the contamination and migration of heavy metals is an important field of study. In this thesis, two novel methods for measuring toxic metals over a broad concentration range in complex matrices were successfully developed and applied to authentic samples. This research focused on toxic metals in two disparate environments: industrial effluent and soil. The primary work reported in this research focused on developing a Sequential Injection Analysis (SIA) process monitor to measure metals in industrial process waste streams in near real-time. Molecular Absorption Spectroscopy was used to determine levels of Zn and several other metals. …

Effects Of Intercalation And Deintercalation In Layered Materials: From Topological Insulators To Battery Cathodes, Uma Garg

Theses and Dissertations

Topological insulators are quantum materials which have insulating bulk and conducting surface. The surface states in these materials is protected by time reversal symmetry and spin-orbit coupling. The fascinating quantum properties of these materials could lead to high speed electronics and quantum computing. To explore the transport properties of these systems, I synthesized single crystals of SnTe and Sb2Se3 which are potential topological insulators. SnTe is a topological crystalline insulator in which topological surface states are protected by time reversal symmetry and crystal symmetry, in particular mirror symmetry. My Shubnikov-de Haas (SdH) oscillation study on the (001) surface of SnTe …

Characterization Of Fiber Bragg Grating Based, Geometry-Dependent, Magnetostrictive Composite Sensors, Edward Lynch

Theses and Dissertations

Optical sensors based on geometry dependent magnetostrictive composite, having potential applications in current sensing and magnetic field sensing are modeled and evaluated experimentally with an emphasis on their thermal immunity from thermal disturbances. Two sensor geometries composed of a fiber Bragg grating (FBG) embedded in a shaped Terfenol-D/epoxy composite material, which were previously prototyped and tested for magnetic field response, were investigated. When sensing magnetic fields or currents, the primary function of the magnetostrictive composite geometry is to modulate the magnetic flux such that a magnetostrictive strain gradient is induced on the embedded FBG. Simulations and thermal experiments reveal the …

Trace: A Differentiable Approach To Line-Level Stroke Recovery For Offline Handwritten Text, Taylor Neil Archibald

Theses and Dissertations

Stroke order and velocity are helpful features in the fields of signature verification, handwriting recognition, and handwriting synthesis. Recovering these features from offline handwritten text is a challenging and well-studied problem. We propose a new model called TRACE (Trajectory Recovery by an Adaptively-trained Convolutional Encoder). TRACE is a differentiable approach using a convolutional recurrent neural network (CRNN) to infer temporal stroke information from long lines of offline handwritten text with many characters. TRACE is perhaps the first system to be trained end-to-end on entire lines of text of arbitrary width and does not require the use of dynamic exemplars. Moreover, …

Classification Of Jacobian Elliptic Fibrations On A Special Family Of K3 Surfaces Of Picard Rank Sixteen, Thomas Hill

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

K3 surfaces are an important tool used to understand the symmetries in physics that link different string theories, called string dualities. For example, heterotic string theory compactified on an elliptic curve describes a theory physically equivalent to (dual to) F-theory compactified on a K3 surface. In fact, M-theory, the type IIA string, the type IIB string, the Spin(32)/Z₂ heterotic string, and the E₈ x E₈ heterotic string are all related by compactification on Calabi-Yau manifolds.

We study a special family of K3 surfaces, namely a family of rank sixteen K3 surfaces polarized by the lattice H⊕E …

Environmental Controls On Didymosphenia Geminata Bloom Formation, Lindsay Capito

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Climate change is causing rapid glacial recession and earlier snowmelt, which alter the physical and chemical properties of rivers. As a result, organisms at the base of the food web are responding in unforeseen ways. We use the nuisance algae D. geminata (Didymo) as a case study for how climate induced shifts in the timing of glacial and snowmelt runoff are affecting river ecosystems. We evaluated how shifts in the timing of nutrient concentrations and light availability affect nuisance blooms of Didymo in three complementary ways. These are, field studies across streams in various stages of glacial recession, weekly measurements …

Deep Q Learning Applied To Stock Trading, Agnibh Dasgupta

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Developing a strategy for stock trading is a vital task for investors. However, it is challenging to obtain an optimal strategy, given the complex and dynamic nature of the stock market. This thesis aims to explore the applications of Reinforcement Learning with the goal of maximizing returns from market investment, keeping in mind the human aspect of trading by utilizing stock prices represented as candlestick graphs. Furthermore, the algorithm studies public interest patterns in form of graphs extracted from Google Trends to make predictions. Deep Q learning has been used to train an agent based on fused images of stock …

Development Of Hplc Stationary Phases With Unique Selectivities And Introduction Of Molecular Rotational Resonance Spectroscopy In Gas Chromatography, Nimisha Thakur

Chemistry & Biochemistry Dissertations

This thesis contributes to advancing liquid and gas chromatography by introducing new stationary phases for HPLC and a new hyphenated GC technique. In the first section, new pH stable stationary phases based on geopolymers are presented for applications in liquid chromatography. The first-ever synthesis of micron-sized spherical particles of geopolymers, customized to be used as HPLC stationary phases, is reported. Complete material characterization of geopolymers using X-ray diffraction, scanning electron microscopy, energy dispersive spectroscopy, laser diffraction, and porosimetry is shown. The chromatographic evaluation of geopolymers is done by comparing parameters such as hydrophilicity, ion exchange selectivity, efficiency, hydrolytic stability, and …

Investigation Of Clinoptilolite Zeolite As A Candidate System For Study By Positron Annihilation, Edward Perez

Physics Theses

This thesis reports on the characterization of a clinoptilolite zeolite (〖Na〗_3 [〖Al〗_3 〖Si〗_15 O_36 ]12H_2 O) using Energy-dispersive X-ray spectroscopy (EDX/EDS) for chemical analysis, low energy Secondary Electron (SE) analysis for three-dimensional imaging and topography, and Transmission Electron Microscopy (TEM) for two-dimensional imaging at the nanometer level. The goal of this work was to provide additional information that can aid in the interpretation of the data obtained using positron beam based spectroscopies. The measurements were performed using the Hitachi S-3000N Variable Pressure Scanning Electron Microscope (SEM) integrated with a NORAN 7 EDS/EBSD system, the Hitachi S-4800 II Field Emission Scanning …

Stable Isotope Composition Of Surface Water Across Central Mexico, Jordan Foote

Earth & Environmental Sciences Theses

Understanding the controlling factors of modern surface water stable isotope compositions is important for reconstructions of paleoclimate and paleoelevation. Few studies have attempted to understand patterns of surface water isotope compositions and their controlling factors in Mexico. Here I study the δ18O, δD and d-excess values of 124 modern river, lake and spring water samples across the Sierra Madre Occidental, Central Mexican Plateau and Sierra Madre Oriental to constrain the spatial pattern and lapse rate. These samples were collected at various elevations after the wet season in 2019. The isotope data were integrated with moisture back trajectory analysis and climatic …

Report On Icdp Deep Dust Workshops: Probing Continental Climate Of The Late Paleozoic Icehouse-Greenhouse Transition And Beyond, Gerilyn S. Soreghan, Laurent Beccaletto, Kathleen C. Benison, Sylvie Borquin, Georg Feulner, Natsuko Hamamura, Michael Hamilton, Nicholas G. Heavens, Linda Hinnov, Adam Huttenlocker, Cindy Looy, Lily Pfeifer, Stephane Pochat, Mehrdad Sarder Abadi, James Zambito

School of Earth & Environment Departmental Research

Chamberlin and Salisbury's assessment of the Permian a century ago captured the essence of the period: it is an interval of extremes yet one sufficiently recent to have affected a biosphere with near-modern complexity. The events of the Permian – the orogenic episodes, massive biospheric turnovers, both icehouse and greenhouse antitheses, and Mars-analog lithofacies – boggle the imagination and present us with great opportunities to explore Earth system behavior. The ICDP-funded workshops dubbed “Deep Dust,” held in Oklahoma (USA) in March 2019 (67 participants from nine countries) and Paris (France) in January 2020 (33 participants from eight countries), focused on …

Data Processing & Analysis For Atomic Force Microscopy (Afm), Molly Mcdonough, Polievkt Perov, Walter Johnson, Stevan Radojev

Undergraduate Theses and Capstone Projects

Scanning Probe Microscopy (SPM) has become a critical tool for characterization of materials in fields such as physics, material science, chemistry, and biology. Atomic Force Microscopy (AFM) is an increasingly useful technique because of its high resolution in three dimensions, the sample does not need to be conductive, and the technique does not need to take place in vacuum. AFM can image a wide variety of topographies and many different types of materials. AFM can deliver 3D topography information from the angstrom level to the micron scale with high resolution. One of the most important aspects of Atomic Force Microscopy …

Approaching Hanabi With Q-Learning And Evolutionary Algorithm, Joseph Palmersten

Culminating Projects in Computer Science and Information Technology

Hanabi is a cooperative card game with hidden information that requires cooperation and communication between the players. For a machine learning agent to be successful at the Hanabi, it will have to learn how to communicate and infer information from the communication of other players. To approach the problem of Hanabi the machine learning methods of Q-learning and Evolutionary algorithm are proposed as potential solutions. The agents that were created using the method are shown to not achieve human levels of communication.

Devops Impact On Software Testing Life Cycle, Jigar Singh

Culminating Projects in Computer Science and Information Technology

DevOps is a software development practice where the focus is on automating repetitive processes [1]. It has brought a change in the way organizations develop and deliver software products. The main purpose of this paper is to investigate the impact of DevOps on the Software Testing Life Cycle (STLC). There is a lot of ambiguity and confusion as to what is DevOps and how it is practiced and implemented and what change it has brought to the software development and the testing process. In this paper, I have investigated how DevOps has benefited the testing process through automated execution of …

Towards Development Of A Remote Charting System For Connected Healthcare, Alex Bodurka

Masters Theses

Health Care Providers play a crucial role in a patients well-being. While their primary role is to treat the patient, it is also vital to ensure that they can spend adequate time with the patient to create a unique treatment plan and build a personal relationship with their patients to help them feel comfortable during their treatment. Health Care Providers are frequently required to manually record patient data to track their healthcare progress during their hospital stay. However, with hospitals continuously trying to optimize their workflows, this crucial one-on-one time with the patient is often not practical.

As a solution, …

Enabling Collaborative Video Sensing At The Edge Through Convolutional Sharing, Kasthuri Jayarajah, Wanniarachchige Dhanuja Tharith Wanniarachchi, Archan Misra

Research Collection School Of Computing and Information Systems

While Deep Neural Network (DNN) models have provided remarkable advances in machine vision capabilities, their high computational complexity and model sizes present a formidable roadblock to deployment in AIoT-based sensing applications. In this paper, we propose a novel paradigm by which peer nodes in a network can collaborate to improve their accuracy on person detection, an exemplar machine vision task. The proposed methodology requires no re-training of the DNNs and incurs minimal processing latency as it extracts scene summaries from the collaborators and injects back into DNNs of the reference cameras, on-the-fly. Early results show promise with improvements in recall …

Learning To Dispatch For Job Shop Scheduling Via Deep Reinforcement Learning, Cong Zhang, Wen Song, Zhiguang Cao, Jie Zhang, Puay Siew Tan, Xu Chi

Research Collection School Of Computing and Information Systems

Priority dispatching rule (PDR) is widely used for solving real-world Job-shop scheduling problem (JSSP). However, the design of effective PDRs is a tedious task, requiring a myriad of specialized knowledge and often delivering limited performance. In this paper, we propose to automatically learn PDRs via an end-to-end deep reinforcement learning agent. We exploit the disjunctive graph representation of JSSP, and propose a Graph Neural Network based scheme to embed the states encountered during solving. The resulting policy network is size-agnostic, effectively enabling generalization on large-scale instances. Experiments show that the agent can learn high-quality PDRs from scratch with elementary raw …

A Study Of Multi-Task And Region-Wise Deep Learning For Food Ingredient Recognition, Jingjing Chen, Bin Zhu, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the categorization of food according to dish names, while ignoring the underlying ingredient composition. In reality, two dishes with the same name do not necessarily share the exact list of ingredients. Therefore, the dishes under the same food category are not mandatorily equal in nutrition content. Nevertheless, due to limited datasets available with ingredient labels, the problem of ingredient recognition is often overlooked. Furthermore, as the number of ingredients is expected to be much less than the number of food categories, …

Smartfuzz: An Automated Smart Fuzzing Approach For Testing Smartthings Apps, Lwin Khin Shar, Nguyen Binh Duong Ta, Lingxiao Jiang, David Lo, Wei Minn, Kiah Yong Glenn Yeo, Eugene Kim

Research Collection School Of Computing and Information Systems

As IoT ecosystem has been fast-growing recently, there have been various security concerns of this new computing paradigm. Malicious IoT apps gaining access to IoT devices and capabilities to execute sensitive operations (sinks), e.g., controlling door locks and switches, may cause serious security and safety issues. Unlike traditional mobile/web apps, IoT apps highly interact with a wide variety of physical IoT devices and respond to environmental events, in addition to user inputs. It is therefore important to conduct comprehensive testing of IoT apps to identify possible anomalous behaviours. On the other hand, it is also important to optimize the number …

Prediction Of Nocturia In Live Alone Elderly Using Unobtrusive In-Home Sensors, Barry Nuqoba, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

Nocturia, or the need to void (or urinate) one or more times in the middle of night time sleeping, represents a significant economic burden for individuals and healthcare systems. Although it can be diagnosed in the hospital, most people tend to regard nocturia as a usual event, resulting in underreported diagnosis and treatment. Data from self-reporting via a voiding diary may be irregular and subjective especially among the elderly due to memory problems. This study aims to detect the presence of nocturia through passive in-home monitoring to inform intervention (e.g., seeking diagnosis and treatment) to improve the physical and mental …

Analysis Of Online Posts To Discover Student Learning Challenges And Inform Targeted Curriculum Improvement Actions, Michelle L. F. Cheong, Jean Y. C. Chen, Bingtian Dai

Research Collection School Of Computing and Information Systems

Past research on analysing end-of-term student feedback tend to result in only high-level course improvement suggestions, and some recent research even argued that student feedback is a poor indicator of teaching effectiveness and student learning. Our intelligent Q&A platform with machine learning prediction and engagement features allow students to ask self-directed questions and provide answers in an out-of-class informal setting. By analysing such high quality and truthful posts which represent the students’ queries and knowledge about the course content, we can better identify the exact course topics which the students face learning challenges. We have implemented our Q&A platform for …

Co-Embedding Attributed Networks With External Knowledge, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Attributed network embedding aims to learn representations of nodes and their attributes in a low-dimensional space that preserves their semantics. The existing embedding models, however, consider node connectivity and node attributes only while ignoring external knowledge that can enhance node representations for downstream applications. In this paper, we propose a set of new VAE-based embedding models called External Knowledge-Aware Co-Embedding Attributed Network (ECAN) Embeddings to incorporate associations among attributes from relevant external knowledge. Such external knowledge can be extracted from text corpus and knowledge graphs. We use multi-VAE structures to model the attribute associations. To cope with joint encoding of …