Physical Sciences and Mathematics Commons^™

Adapting Single-View View Synthesis With Multiplane Images For 3d Video Chat, Anurag Venkata Uppuluri

Master's Theses

Activities like one-on-one video chatting and video conferencing with multiple participants are more prevalent than ever today as we continue to tackle the pandemic. Bringing a 3D feel to video chat has always been a hot topic in Vision and Graphics communities. In this thesis, we have employed novel view synthesis in attempting to turn one-on-one video chatting into 3D. We have tuned the learning pipeline of Tucker and Snavely's single-view view synthesis paper — by retraining it on MannequinChallenge dataset — to better predict a layered representation of the scene viewed by either video chat participant at any given …

Space Charge Effects In Low Energy Magnetized Electron Beams, W. M. Sajini Anushika Kumari Wijethunga

Physics Theses & Dissertations

Magnetized electron cooling of the ion beam is one of the major approaches towards obtaining the required high luminosity in the proposed Electron-Ion Collider (EIC). To increase the cooling efficiency, a bunched electron beam with a high bunch charge and high repetition rate is required. However, these features can combine to enhance the collective interactions, such as the space charge effect. A magnetized electron beam was successfully generated at the Thomas Jefferson National Accelerator Facility (JLab) using a compact, 300 kV DC high voltage photo-gun with an inverted insulator geometry and bi-alkali antimonide photocathode. The beam magnetization was characterized using …

Combined Amplification And Sound Therapy For Individuals With Tinnitus And Coexisting Hearing Loss: A Retrospective Cohort Study, Purushothaman Ganesan, Hansapani Rodrigo, Jason Schmiedge, Rob Reiter, Simham Swapna, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

BACKGROUND: The heterogeneity of tinnitus perception and its impact necessitates a tailor-made management approach in everyone. The current study examined the effects of residual inhibition in combined amplification and sound therapy in individuals with tinnitus and coexisting hearing loss.

METHODS: A retrospective analysis was performed on patients with tinnitus and coexisting hearing loss between 2016 and 2019. A total of 72 patients provided with combined amplification and sound therapy were divided into 3 groups based on residual inhibition: (i) complete residual inhibition, (ii) partial residual inhibition, and (iii) negative residual inhibition. Tinnitus severity was measured using the Tinnitus …

On Combinatorics Of Voronoi Polytopes For Perturbations Of The Dual Root Lattices, Alexey Garber

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

The Voronoi conjecture on parallelohedra claims that for every convex polytope P that tiles Euclidean d-dimensional space with translations there exists a d-dimensional lattice such that P and the Voronoi polytope of this lattice are affinely equivalent. The Voronoi conjecture is still open for the general case but it is known that some combinatorial restrictions for the face structure of P ensure that the Voronoi conjecture holds for P. In this article, we prove that if P is the Voronoi polytope of one of the dual root lattices Dd*, E6*, E7* or E8*=E8 or their small perturbations, then every parallelohedron …

Accelerating Dynamical Density Response Code On Summit And Its Application For Computing The Density Response Function Of Vanadium Sesquioxide, Wileam Y. Phan

Masters Theses

This thesis details the process of porting the Eguiluz group dynamical density response computational platform to the hybrid CPU+GPU environment at the Summit supercomputer at Oak Ridge National Laboratory (ORNL) Leadership Computing Center. The baseline CPU-only version is a Gordon Bell-winning platform within the formally-exact time-dependent density functional theory (TD-DFT) framework using the linearly augmented plane wave (LAPW) basis set. The code is accelerated using a combination of the OpenACC programming model and GPU libraries -- namely, the Matrix Algebra for GPU and Multicore Architectures (MAGMA) library -- as well as exploiting the sparsity pattern of the matrices involved in …

Design, Assembly, And Testing Of A Small 3d-Printed Thick-Gem, Jerry Lamar Collins Ii

Theses and Dissertations

Thick GEMs are a type of gas electron multiplier, a micropattern gaseous detector, with many applications in research. The subject of this study is whether or not a small 3D printed thick GEM board can be used to form a well-functioning detector. A Thick GEM having three separate board sectors, each having different sized clearance rim annuli around their holes, was designed, printed, and assembled. Several studies to quantify its behavior over both short and long time intervals were conducted, and the results calculated. The THGEM sector with 0.1 mm annulus rims was able to achieve primarily 102 gain, whereas …

Arion 33: A Prospective Mission To Near-Earth Asteroids, Alita Regi

Theses and Dissertations

Near-Earth asteroids will become primary targets for space industrialization in the future as humanity becomes a multi-planetary species. But before such missions, it is necessary to survey these asteroids for their intrinsic scientific value. Exploring asteroids via orbiter missions can help us understand the asteroid's surface composition while providing us a cost and power model required for future missions. Therefore, it is beneficial to study asteroids to pave the way for future mining operations or more comprehensive scientific explorations. Hence, in this thesis, the target asteroids 2011 UW158 and 65803 Didymos are selected as case studies for the hypothetical mission …

Intermittency Scaling Laws In Magnetohydrodynamic Turbulence: Theory, Simulations And Observations, Juan Carlos Palacios Caicedo

Theses and Dissertations

The main objective of this dissertation is to investigate intermittency of Magnetohydrodynamic (MHD) plasmas by means of high-resolution numerical simulations and large sets of solar wind data. Understanding intermittency scaling laws is a significant step forward towards understanding the fundamental properties of plasma turbulence and how spatial structures influence dissipation, heating, transport and acceleration of charged particles, which is important in a wide range of laboratory, space and astrophysical plasmas. The current stateof- the art in the theoretical understanding of intermittency in MHD turbulence is based on phenomenological (non-exact) models, numerical simulations and solar wind observations of structure functions of …

Synthesis, Isolation And Structural Elucidation Of Cage-Shaped Aluminum And Gallium Phosphorous Aryloxide Complexes As Highly Reactive Lewis Acids And Carboxyboranes As Carbon Monoxide Releasing Molecules (Corms), Hussam Wannas Shinawa Alhamza

Theses and Dissertations

Group 13 Lewis acids have gained a lot of interest in over the years due to their reactivity, potency, and applications in the field of catalysis. Generally, there is a direct relationship between the catalytic activity of the organometallic Lewis acid and its acidity. However, this gives rise to a bigger challenge which is related to the stability of the catalyst. Our preliminary results from working on the catalytic reduction of CO2 have shown catalytic deactivation after one or two cycles. Utilizing bulkier substituents such as monodentate phenolates have shown promising increased stability and reactivity. The structural optimization (i.e., open-shape …

An Assessment Of Image-Cloaking Techniques Against Automated Face Recognition For Biometric Privacy, Brandon Scott Ledford

Theses and Dissertations

Over the past two decades, Americans have aggressively increased the amount of facial data uploaded to the internet primarily via social media. This data is largely unprotected due to the dire lack of existing regulations protecting users from large scale face recognition in the United States, where the value of data trade is in the tens of billions. In its current state, facial privacy in the United States depends on American corporations opting not to collect the public data, an option rarely chosen. Much research has been done in the area of suppressing recognition abilities, giving users the ability to …

Unveiling Migration Patterns Using Data And Network Science, Firas Aswad

Theses and Dissertations

Many real-world phenomena have recently been witnessed, motivating scientists to provide a comprehensive understanding of worldwide networks, such as the human migration phenomenon. Human migration research is multidisciplinary and has yielded work in social sciences, physics, and the new field of smart city designing and planning based on big data analytics. The importance of the research comes from the impacts on both countries, sources, and distention. Impacts occur at several levels such as economy, city planning, politics, and law enforcement, leading to changes in demographics. Thus, studies on human migration help policymakers prepare and handle crises when they occur in …

On A Class Of Critical N-Laplacian Problems, Tsz Chung Ho

Theses and Dissertations

We establish some existence results for a class of critical N-Laplacian problems in a bounded domain in R^N. In the absence of a suitable direct sum decomposition, we use an abstract linking theorem based on the Z₂-cohomological index to obtain a nontrivial critical point.

Changes In The Abundance And Distribution Of Benthic Mollusks In Polluted Sediments Of A Shallow Subtropical Estuary, Rachael Holtsberg Stark

Theses and Dissertations

The Indian River Lagoon (IRL) has been degraded by decades of eutrophication, and has accumulated an abundance of fine-grained, organic-rich sediments (muck). To quantify the impacts of organic sediments and environmental dredging, benthic mollusks were chosen to serve as bioindicators of environmental change, sediment health, and water quality. Data on species richness, biodiversity, and abundances was collected alongside sediment and water quality data before, during and after dredging. Organic sediment content was found to have an inverse logarithmic relationship benthic mollusk biodiversity, species richness, and abundance. Sediments low in percent organic content (0.7% to 6.1%) were located near the adjacent …

Development And Optimization Of A Denitrification System To Promote Biological Nutrient Removal In A Subtropical Estuary, Abigail Gering

Theses and Dissertations

Eutrophication impacts coastal ecosystems globally and triggers phytoplankton and algal blooms, leading to an increase in oxygen demand in the water column and sediments due to various biogeochemical processes. Naturally, biological nitrification, denitrification and anammox processes help to remove nitrogen predominately by nitrifying and denitrifying bacteria in the sediments. Eutrophic systems have increased nutrient and organic matter loading and are prone to the accumulation of ‘muddy’, fine-grained, organic-rich sediments (locally termed ‘muck’) that may not be able to support high enough populations of these bacteria, and therefore, may not adequately support nitrification/denitrification processes that would otherwise remove nitrogen. To decrease …

Investigation Of N-Sulfonyliminium Ion Triggered Cyclizations For The Synthesis Of Piperidine Scaffolds, Kaitlyn Birkhoff

Honors Theses

In consideration of the on-going global pandemic, immediate access to Food and Drug Administration approved pharmaceutical medications and vaccines is a matter of utmost priority to our national healthcare system. One significant modality in managed care is the dispensation of prescription drugs for the prevention or treatment of illnesses and diseases. According to the Centers for Disease Control and Prevention, physicians order and provide over 2.9 billion prescriptions each year with analgesics, antihyperlipidemics, and dermatological agents being the most prescribed therapeutic classes. Within those classes exists a disparate variety of chemical structures that must be prepared on a metric ton …

Techniques For The Enantioselective Asymmetric Synthesis Of Benzyl Substituted Malonic Acid Esters, Madison Hansen

Honors Theses

A popular method for the enantioselective synthesis of substituted malonic half esters is hydrolysis via Pig Liver Esterase (PLE), however some substrates produce low enantiomeric excess, namely benzyl-substituted malonic esters. Presented here are alternative methods explored for this synthesis, the first being phase-transfer catalyzed hydrolysis via N-benzyl quaternary ammonium salts derived from cinchona alkaloids. The second method utilized chiral auxiliary directed benzylation with auxiliaries including menthol and oxazolidinones. Though unsuccessful, this research provided valuable groundwork in the investigation for the enantioselective asymmetric synthesis of benzyl-substituted malonic acid esters.

Keywords: Pig Liver Esterase, Enantioselectivity, Phase-Transfer Catalysis, Cinchona Alkaloids, Quaternary Ammonium …

Joint Linear And Nonlinear Computation With Data Encryption For Efficient Privacy-Preserving Deep Learning, Qiao Zhang

Electrical & Computer Engineering Theses & Dissertations

Deep Learning (DL) has shown unrivalled performance in many applications such as image classification, speech recognition, anomalous detection, and business analytics. While end users and enterprises own enormous data, DL talents and computing power are mostly gathered in technology giants having cloud servers. Thus, data owners, i.e., the clients, are motivated to outsource their data, along with computationally-intensive tasks, to the server in order to leverage the server’s abundant computation resources and DL talents for developing cost-effective DL solutions. However, trust is required between the server and the client to finish the computation tasks (e.g., conducting inference for the newly-input …

Polynomial Embeddings Of Unilateral Weighted Shifts In 2-Variable Weighted Shifts, Raul E. Curto, Sang H. Lee, Jasang Yoon

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Given a bounded sequence omega of positive numbers, and its associated unilateral weighted shift W-omega, acting on the Hilbert space l(2) (Z+), we consider natural representations of W-omega as a 2-variable weighted shift, acting on the Hilbert space l(2)(Z(+)(2)). Alternatively, we seek to examine the various ways in which the sequence omega can give rise to a 2-variable weight diagram, corresponding to a 2-variable weighted shift. Our best (and more general) embedding arises from looking at two polynomials p and q nonnegative on a closed interval I subset of R+ and the double-indexed moment sequence {integral p(r)(k) q(r)(l) d sigma(r)}(k,l …

Smooth Loops And Loop Bundles, Sergey Grigorian

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

A loop is a rather general algebraic structure that has an identity element and division, but is not necessarily associative. Smooth loops are a direct generalization of Lie groups. A key example of a non-Lie smooth loop is the loop of unit octonions. In this paper, we study properties of smooth loops and their associated tangent algebras, including a loop analog of the Maurer-Cartan equation. Then, given a manifold, we introduce a loop bundle as an associated bundle to a particular principal bundle. Given a connection on the principal bundle, we define the torsion of a loop bundle structure and …

Synthesis And Characterization Of 4,6-Protected Glucosamine Derivatives And Branched Glycoconjugates, Jonathan Bietsch

Chemistry & Biochemistry Theses & Dissertations

Low molecular weight gelators (LMWGs) are small molecules that self-assemble in appropriate solvents to form three dimensional networks that immobilize the solvent, creating a supramolecular gel. The self-assembly of LMWGs occurs through non-covalent interactions such as hydrogen bonding, aromatic interactions, donor-acceptor interactions, Van der Waals interactions, hydrophobic forces, halogen bonding, etc. Due to self-assembly occurring through reversible non-covalent interactions, supramolecular gels can undergo a gel to solution transformation. Because of this, these materials can be sensitive to external stimuli such as temperature changes, pH changes, and other stimuli that effect non-covalent interactions. This makes the synthesis of LMWG’s an appealing …

Genetically Engineered Thermosynechococcus Elongatus Bp1: Assessment Of Potential Biorisks And Biofuel Production, Thu Ho Anh Nguyen-Jones

Chemistry & Biochemistry Theses & Dissertations

According to the International Energy Outlook 2019, released by the U.S. Energy Information Administration, it is projected that the energy consumption will increase up to 50% between 2018 and 2050 worldwide. As fossil fuel being a finite source of energy with the risk of depletion, many countries are now facing an energy security crisis. Therefore, it is important to develop other renewable and sustainable energy sources that will allow countries to shift away from depending on fossil fuels. Among several types of renewable energy, biofuel production using genetically engineered cyanobacteria is capturing much interest due to its many advantages. Different …

Graph Learning Assisted Multi-Objective Integer Programming, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang, Abhishek Gupta, Mingyan Simon Lin

Research Collection School Of Computing and Information Systems

Objective-space decomposition algorithms (ODAs) are widely studied for solvingmulti-objective integer programs. However, they often encounter difficulties inhandling scalarized problems, which could cause infeasibility or repetitive nondominatedpoints and thus induce redundant runtime. To mitigate the issue, we presenta graph neural network (GNN) based method to learn the reduction rule in the ODA.We formulate the algorithmic procedure of generic ODAs as a Markov decisionprocess, and parameterize the policy (reduction rule) with a novel two-stage GNNto fuse information from variables, constraints and especially objectives for betterstate representation. We train our model with imitation learning and deploy it ona state-of-the-art ODA. Results show that …

Neurolkh: Combining Deep Learning Model With Lin-Kernighan-Helsgaun Heuristic For Solving The Traveling Salesman Problem, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

We present NeuroLKH, a novel algorithm that combines deep learning with the strong traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem. Specifically, we train a Sparse Graph Network (SGN) with supervised learning for edge scores and unsupervised learning for node penalties, both of which are critical for improving the performance of LKH. Based on the output of SGN, NeuroLKH creates the edge candidate set and transforms edge distances to guide the searching process of LKH. Extensive experiments firmly demonstrate that, by training one model on a wide range of problem sizes, NeuroLKH significantly outperforms LKH and generalizes well to …

Learning To Iteratively Solve Routing Problems With Dual-Aspect Collaborative Transformer, Yining Ma, Jingwen Li, Zhiguang Cao, Wen Song, Le Zhang, Zhenghua Chen, Jing Tang

Research Collection School Of Computing and Information Systems

Recently, Transformer has become a prevailing deep architecture for solving vehicle routing problems (VRPs). However, it is less effective in learning improvement models for VRP because its positional encoding (PE) method is not suitable in representing VRP solutions. This paper presents a novel Dual-Aspect Collaborative Transformer (DACT) to learn embeddings for the node and positional features separately, instead of fusing them together as done in existing ones, so as to avoid potential noises and incompatible correlations. Moreover, the positional features are embedded through a novel cyclic positional encoding (CPE) method to allow Transformer to effectively capture the circularity and symmetry …

Integration Of Information Technology Certifications Into Undergraduate Computing Curriculum, Eng Lieh Ouh, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

This innovative practice full paper describes our experiences of integrating information technology certifications into an undergraduate computing curriculum. As the technology landscape evolves, a common challenge for educators in computing programs is designing an industry-relevant curriculum. Over the years, industry practitioners have taken technology certifications to validate themselves against a base level of technical knowledge currently in demand in industry. Information technology (IT) certifications can also offer paths for academic computing programs to stay relevant to industry needs. However, identifying relevant IT certifications and integrating it into an academic curriculum requires a careful design approach as substantial efforts are needed …

Towards Non-Intrusive Camera-Based Heart Rate Variability Estimation In The Car Under Naturalistic Condition, Shu Liu, Kevin Koch, Zimu Zhou, Martin Maritsch, Xiaoxi He, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

Driver status monitoring systems are a vital component of smart cars in the future, especially in the era when an increasing amount of time is spent in the vehicle. The heart rate (HR) is one of the most important physiological signals of driver status. To infer HR of drivers, the mainstream of existing research focused on capturing subtle heartbeat-induced vibration of the torso or leveraged photoplethysmography (PPG) that detects cardiac cycle-related blood volume changes in the microvascular. However, existing approaches rely on dedicated sensors that are expensive and cumbersome to be integrated or are vulnerable to ambient noise. Moreover, their …

On Analysing Student Resilience In Higher Education Programs Using A Data-Driven Approach, Audrey Tedja Widjaja, Ee-Peng Lim, Aldy Gunawan

Research Collection School Of Computing and Information Systems

Analysing student resilience is important as research has shown that resilience is related to students’ academic performance and their persistence through academic setbacks. While questionnaires can be conducted to assess student resilience directly, they suffer from human recall errors and deliberate suppression of true responses. In this paper, we propose ACREA, ACademic REsilience Analytics framework which adopts a data-driven approach to analyse student resilient behavior with the use of student-course data. ACREA defines academic setbacks experienced by students and measures how well students overcome such setbacks using a quasi-experimental design. By applying ACREA on a real world student-course dataset, we …

Empirical Evaluation Of Minority Oversampling Techniques In The Context Of Android Malware Detection, Lwin Khin Shar, Nguyen Binh Duong Ta, David Lo

Research Collection School Of Computing and Information Systems

In Android malware classification, the distribution of training data among classes is often imbalanced. This causes the learning algorithm to bias towards the dominant classes, resulting in mis-classification of minority classes. One effective way to improve the performance of classifiers is the synthetic generation of minority instances. One pioneer technique in this area is Synthetic Minority Oversampling Technique (SMOTE) and since its publication in 2002, several variants of SMOTE have been proposed and evaluated on various imbalanced datasets. However, these techniques have not been evaluated in the context of Android malware detection. Studies have shown that the performance of SMOTE …

Statistical Moderation: A Case Study In Grading On A Curve, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

There is a negative perception about “grading on a curve,” because of the feeling that the cohort strength may skew the final grades one way or another. However, given the difficulties in ensuring absolute uniformity in assessment across the years, especially when taught and assessed by different instructors under different settings, grading on a curve may be a necessary evil. Once we accept this type of statistical moderation as the last line of defense in standardizing the final scores so that student cohorts from different terms or sections or schools may be compared, we have to implement it well. In …

Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng

Research Collection School Of Computing and Information Systems

A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.