Physical Sciences and Mathematics Commons^™

The Empathetic Car: Exploring Emotion Inference Via Driver Behaviour And Traffic Context, Shu Liu, Kevin Koch, Zimu Zhou, Simon Foll, Xiaoxi He, Tina Menke, Elgar Fleisch, Felix Wortmann

Research Collection School Of Computing and Information Systems

An empathetic car that is capable of reading the driver’s emotions has been envisioned by many car manufacturers. Emotion inference enables in-vehicle applications to improve driver comfort, well-being, and safety. Available emotion inference approaches use physiological, facial, and speech-related data to infer emotions during driving trips. However, existing solutions have two major limitations: Relying on sensors that are not built into the vehicle restricts emotion inference to those people leveraging corresponding devices (e.g., smartwatches). Relying on modalities such as facial expressions and speech raises privacy concerns. By contrast, researchers in mobile health have been able to infer affective states (e.g., …

Galaxy And Mass Assembly (Gama), U. Sureshkumar, A. Durkalec, A. Pollo, M. Bilicki, J. Loveday, D. J. Farrow, Benne Holwerda, A. M. Hopkins, J. Liske, K. A. Pimbblet, E. N. Taylor, A. H. Wright

Faculty and Staff Scholarship

Context. Galaxies are biased tracers of the underlying network of dark matter. The strength of this bias depends on various galaxy properties and on redshift. One of the methods used to study these dependences of the bias is measurement of galaxy clustering. Such studies are made using galaxy samples from various catalogues, which frequently bear their own problems related to sample selection methods. It is therefore crucial to understand how sample choice influences clustering measurements and which galaxy property is the most direct tracer of the galaxy environment.

Aims. We investigate how different galaxy properties, such as luminosities in the …

Piecewise Linear Manifold Clustering, Artyom Diky

Dissertations, Theses, and Capstone Projects

This work studies the application of topological analysis to non-linear manifold clustering. A novel method, that exploits the data clustering structure, allows to generate a topological representation of the point dataset. An analysis of topological construction under different simulated conditions is performed to explore the capabilities and limitations of the method, and demonstrated statistically significant improvements in performance. Furthermore, we introduce a new information-theoretical validation measure for clustering, that exploits geometrical properties of clusters to estimate clustering compressibility, for evaluation of the clustering goodness-of-fit without any prior information about true class assignments. We show how the new validation measure, when …

Developing Dynamical Probes Of Quantum Spin Liquids Inspired By Techniques From Spintronics, Joshua Aftergood

Dissertations, Theses, and Capstone Projects

We theoretically study low dimensional insulating spin systems using spin fluctuations as a probe of the spin dynamics. In some systems, low dimensionality in conjunction with other quantum fluctuation enhancing effects impedes spontaneous generation of long range magnetic ordering down to zero absolute temperature. In particular, we focus on exotic spin systems hosting mobile, fractionalized spin excitations above their ground state, and ultimately show that techniques already commonplace in spintronics can be utilized in the context of quantum magnetism to develop probes of exotic ground states.

We initially consider quantum spin chains (QSCs), and examine a system of two exchange-coupled …

Molecular Dynamics Simulations Of Self-Assemblies In Nature And Nanotechnology, Phu Khanh Tang

Dissertations, Theses, and Capstone Projects

Nature usually divides complex systems into smaller building blocks specializing in a few tasks since one entity cannot achieve everything. Therefore, self-assembly is a robust tool exploited by Nature to build hierarchical systems that accomplish unique functions. The cell membrane distinguishes itself as an example of Nature’s self-assembly, defining and protecting the cell. By mimicking Nature’s designs using synthetically designed self-assemblies, researchers with advanced nanotechnological comprehension can manipulate these synthetic self-assemblies to improve many aspects of modern medicine and materials science. Understanding the competing underlying molecular interactions in self-assembly is always of interest to the academic scientific community and industry. …

Monte Carlo, Molecular Dynamics And Network Analysis Of The Gramicidin Water Channel And Proton Transfer Pathways To Qb In Photosynthetic Reaction Centers, Yingying Zhang

Dissertations, Theses, and Capstone Projects

Water molecules play a key role in all biochemical processes. They help define the shape of proteins, and they are reactant or product in many reactions and are released as ligands are bound. They facilitate transfer of protons through transmembrane proton channel, pump and transporter proteins. Continuum electrostatics (CE) force fields such as used in MCCE (Multi-Conformation Continuum Electrostatics) capture electrostatic interactions in biomolecules with an implicit solvent, to give the averaged solvent water equilibrium properties. Hybrid CE methods can use explicit water molecules within the protein surrounded by implicit solvent. These hybrid methods permit the study of explicit hydrogen …

A Unified Approach To M Dwarf Ages, Rocio Kiman

Dissertations, Theses, and Capstone Projects

Estimating ages of M dwarfs, the lowest mass stars in the Galaxy, is a current unresolved problem in Astrophysics. This dissertation focuses on developing a method to estimate ages for M dwarfs. This method consists of combining different age indicators in a Bayesian framework to achieve a precise age measurement. The age indicators I use are: 1) position in the color-magnitude diagram which is a proxy for effective temperature and luminosity, 2) movement of the stars in the Galaxy, or its 3D kinematics, 3) magnetic activity, measured by the Halpha emission line of the spectrum. In this dissertation I analyze …

Carbon And Nitrogen Dynamics Of A Lagoon Salt Marsh In Davenport, California, Mark D. Gormley

Dissertations, Theses, and Capstone Projects

Wetlands are complex environments that play a critical role in regulating the global biogeochemical cycle of carbon (C) and nitrogen (N). Wetlands are critical contributors to global climate change and atmospheric chemistry since they store as much as 33% of the world’s soil organic carbon (SOC), release more than 20% of the atmospheric methane (CH₄), and produce nitrous oxide (N₂O), an extremely potent greenhouse gas (GHG). Despite the enormous radiative forcing potential of carbon dioxide (CO₂), CH₄ and N₂O derived from wetlands, uncertainties over the rates of C sequestration and GHG …

Solving Multiple Inference In Graphical Models, Cong Chen

Dissertations, Theses, and Capstone Projects

For inference problems in graphical models, much effort has been directed at algorithms for obtaining one single optimal prediction. In practice, the data is often noisy or incomplete, which makes one single optimal solution unreliable. To address this problem, multiple Inference is proposed to find several best solutions, M-Best, where multiple hypotheses are preferred for advanced reasoning. People use oracle accuracy as an evaluation criterion expecting one of the solutions has high accuracy with the ground truth. It has been shown that it is beneficial for the top solutions to be diverse. Approaches for solving diverse multiple inference are proposed …

Evaluation Of The Potential Of Automated Sem-Eds Analysis For The Discrimination Of Inorganic Soil Particles, Anna S. Duggar

Dissertations, Theses, and Capstone Projects

Soil, that complex mixture of minerals, organic particles, chemicals, and anthropogenic materials, is ubiquitous and easily transferred, which gives it forensic relevance. Forensic soil analysis has traditionally included the identification and comparison of both organic and inorganic components, the inorganic portion being most commonly examined by light microscopy and other instrumental techniques. Predominantly, the inorganic materials in soil are naturally-occurring minerals, contributed as grains from the surrounding bedrock, which gives a soil its regional character. That parent material then undergoes physical, chemical, and anthropogenic changes producing wide geographic variation within a single region. This variation forms the basis for potential …

Representing The Derivative Of Trace Of Holonomy, Jeffrey Peter Kroll

Dissertations, Theses, and Capstone Projects

Trace of holonomy around a fixed loop defines a function on the space of unitary connections on a hermitian vector bundle over a Riemannian manifold. Using the derivative of trace of holonomy, the loop, and a flat unitary connection, a functional is defined on the vector space of twisted degree 1 cohomology classes with coefficients in skew-hermitian bundle endomorphisms. It is shown that this functional is obtained by pairing elements of cohomology with a degree 1 homology class built directly from the loop and equipped with a flat section obtained from the variation of holonomy around the loop. When the …

Don't Sell Them Short, There's More To Bacterial Natural Products Than Antibiotics, Alison Clare Domzalski

Dissertations, Theses, and Capstone Projects

Recent genomic studies of microbiomes have revealed an overwhelming number of biosynthetic genes of unknown function. Most of these “cryptic” biosynthetic genes are not expressed in laboratory monocultures of individual microbes. Thus, there remains tremendous untapped potential for natural products discovery. Here we employ mixed microbial culture (MMC) as a simple yet powerful approach to awaken cryptic biosynthetic gene clusters. Our preliminary studies demonstrated that arrays of metabolites could be induced in MMCs upon environmental cues, such as surface adhesion. Using this system, we have screened, identified, and isolated bioactive bacterial metabolites, which were characterized structurally and biologically. Of the …

Connecting Communities To Coastal Resilience: Enhancing Sustainability Through Public Participation In Salt Marsh Management And Restoration In Suffolk County, Ny, Jennifer L. Mcgivern

Dissertations, Theses, and Capstone Projects

Coastal resiliency is becoming significantly more critical to the livelihood of coastal communities as the frequency and intensity of storm events increases and is exacerbated by rising sea levels due to climate change. In October 2012 Superstorm Sandy impacted the New York-New Jersey area costing over $70 billion in storm damages and 147 lives lost, as storm surges surpassed record highs for the region. Protruding more than 100 miles into the Atlantic Ocean with over 1,000 miles of shoreline, Long Island is particularly vulnerable to the increasingly ferocious and numerous storms as well as the rising sea levels that climate …

Wave Excitation And Dynamics In Disordered Systems, Yiming Huang

Dissertations, Theses, and Capstone Projects

This thesis presents studies of the field and energy excited in disordered systems as well as the dynamics of scattering.

Dynamic and steady state aspects of wave propagation are deeply connected in lossless open systems in which the scattering matrix is unitary. There is then an equivalence among the energy excited within the medium through all channels, the Wigner time delay, which is the sum of dwell times in all channels coupled to the medium, and the density of states. But these equivalences fall away in the presence of material loss or gain. In this paper, we use microwave measurements, …

Linear And Non Linear Properties Of Two-Dimensional Exciton-Polaritons, Mandeep Khatoniar

Dissertations, Theses, and Capstone Projects

Technology has been accelerating at breakneck speed since the first quantum revolution, an era that ushered transistors and lasers in the late 1940s and early 1960s. Both of these technologies relied on a matured understanding of quantum theories and since their inception has propelled innovation and development in various sectors like communications, metrology, and sensing. Optical technologies were thought to be the game changers in terms of logic and computing operations, with the elevator pitch being "computing at speed of light", a fundamental speed limit imposed by this universe’s legal system (a.k.a physics). However, it was soon realized that that …

Synthesis, Characterization And Applications Of Europium Based Perovskite Oxide Nanoparticles, Nasim Farahmand

Dissertations, Theses, and Capstone Projects

The synthesis and characterization of nanocrystalline transition and rare-earth metal oxides have been studied widely over the past years. These materials possess unique physical, chemical, magnetic and dielectric properties which make them potential candidates for a wide range of applications such as electronics, energy storage and photocatalysis. There are a number of synthesis methods for preparing these materials, where most of them require stringent conditions such as high pressure and high temperature. However, in this study, a modified sol-gel synthesis has been used with a lower calcination temperature to make uniform nanocrystals of the transition/rare-earth metal oxide family. The focus …

Adversarial Training For Skill Learning In A Mobile Robot, Todd W. Flyr

Dissertations, Theses, and Capstone Projects

Machine Learning in mobile robotics is sometimes hampered by the difficulties associated with the creation of a large corpus of labeled data that most neural network based learning algorithms demand. In recent years, advances in the field of machine learning have been facilitated via the creation of large collaboratively-created labeled training datasets that researchers can use as the basis for experiments to validate and improve their candidate neural network architectures. For the field of robotics, however, tasks are so disparate and the physical devices so varied that in most cases the creation of collaborative benchmark datasets are impractical. Obtaining data …

Development Of An Lcms Analytical Method With Applicability To Determination Of Trace Level Explosives In Environmental Waters, Cristina I. Veresmortean

Dissertations, Theses, and Capstone Projects

Traces of explosives and their degradation products present in explosives contaminated sites from military sources, such as training facilities, impose a great concern over the public health and our eco-system. This work is centered around finding an efficient way to extraction of these chemicals from water samples and their analysis using advanced separation technology: LC-MS/MS Shimadzu Prominence 8050 and AB Sciex Trap 4000 LC-MS/MS. Different extraction methods will be proposed, along with chromatographic and mass spectroscopy method development. Dependent on the target analyte polarity, thermal degradation, solubility and type of matrix, an appropriate method of analysis will be established. The …

Automated Code Engine For Tensor Hypercontraction: Derivation, Optimization And Implementation Of Rank-Reduced Coupled Cluster Theories, Yao Zhao

Dissertations, Theses, and Capstone Projects

The ultimate goal of electronic structure theory is solving the electronic Schr¨odinger Equation. However, even accurate approximations of solving Schr¨odinger Equation, such as high order coupled cluster theories, require computational efforts that are too demanding to be applied on large chemical systems. This thesis tackles the problem of curse of dimensionality: how to reduce the time complexity of high-accuracy coupled cluster methods in order to accelerate computations of molecular energy. On one hand, we believe that low-rank approximation (i.e. Tensor HyperContraction) of high-order tensors appearing in coupled cluster theory is a promising way to achieve rank-reduced coupled cluster theory. On …

Making Space For Unquantifiable Data: Hand-Drawn Data Visualization, Eva Sibinga

Dissertations, Theses, and Capstone Projects

This project makes space for personal “data” around labor and care, prompting users to consider the concrete and abstract (quantifiable and unquantifiable) forms labor and care take in their lives. The interactive, subjective data visualization uses hand-drawn visual elements to foreground that data about care and human interaction will always be ambiguous and complex, that they may never be satisfactorily or universally quantified, and that they will always be out of reach of perfect categorization.

The project provides an alternative to prescriptive truth-telling with data. Instead of using a dataset to provide data-driven answers and insights to users, the interactive …

Detecting Stance On Covid-19 Vaccine In A Polarized Media, Rodica Ceslov

Dissertations, Theses, and Capstone Projects

The growing polarization in the United States has been widely reported. Media coverage plays an important role in shaping public opinion and influences public debates on complex and unfamiliar topics. There are some benefits to individuals and society from political polarization and conflict between opposing viewpoints. However, recent research has primarily highlighted the negative consequences of polarization which reached an all-time high. One such topic is the Covid-19 vaccine which was developed in record time, and the public learned about its safety and possible risks through the media coverage.

In this capstone, we examine U.S. news media coverage on the …

Enhanced Platinum (Ii) Drug Delivery For Anti-Cancer Therapy, Marek T. Wlodarczyk

Dissertations, Theses, and Capstone Projects

Over the years, anti-cancer therapies have improved the overall survival rate of patients. Nevertheless, the traditional free drug therapies still suffer from side effects and systemic toxicity, resulting in low drug dosages in the clinic. This often leads to suboptimal drug concentrations reaching cancer cells, contributing to treatment failure and drug resistance. Among available anti-cancer therapies, metallodrugs are of great interest. Platinum (II)-based agents are highly potent and are used to treat many cancers, including ovarian cancer (OC). Cisplatin (cis-diaminedichloroplatinum (II)) is the first Food and Drug Administration (FDA)-approved metallodrug for treatment of solid tumors, and its mechanism …

Environmental Assessment Of The Impact Of Land-Based Discharges On Marine Water And Sediment Quality In Dubai, Uae, Ayman Fathy Halawa

Theses

The current seawater and Creek – Canal waterway in the Emirate of Dubai, UAE, is under tremendous pressure because of continuous urban water discharges from land-based sources. Therefore, the impact of urban water discharges on marine water and sediment quality in the Emirate requires a thorough assessment. The main objective of this study is to assess the impacts of effluent discharges on the quality of water and sediment in the open sea and Dubai Creek. The land-based sources include the power and desalination plants, industrial sector, sewage treatment plant, and stormwater runoff. To achieve the stated objective, relevant data on …

Unified And Incremental Simrank: Index-Free Approximation With Scheduled Principle, Fanwei Zhu, Yuan Fang, Kai Zhang, Kevin C.-C. Chang, Hongtai Cao, Zhen Jiang, Minghui Wu

Research Collection School Of Computing and Information Systems

SimRank is a popular link-based similarity measure on graphs. It enables a variety of applications with different modes of querying (e.g., single-pair, single-source and all-pair modes). In this paper, we propose UISim, a unified and incremental framework for all SimRank modes based on a scheduled approximation principle. UISim processes queries with incremental and prioritized exploration of the entire computation space, and thus allows flexible tradeoff of time and accuracy. On the other hand, it creates and shares common “building blocks” for online computation without relying on indexes, and thus is efficient to handle both static and dynamic graphs. Our experiments …

Quantum Computing For Supply Chain Finance, Paul R. Griffin, Ritesh Sampat

Research Collection School Of Computing and Information Systems

Applying quantum computing to real world applications to assess the potential efficacy is a daunting task for non-quantum specialists. This paper shows an implementation of two quantum optimization algorithms applied to portfolios of trade finance portfolios and compares the selections to those chosen by experienced underwriters and a classical optimizer. The method used is to map the financial risk and returns for a trade finance portfolio to an optimization function of a quantum algorithm developed in a Qiskit tutorial. The results show that whilst there is no advantage seen by using the quantum algorithms, the performance of the quantum algorithms …

Orthogonal Inductive Matrix Completion, Antoine Ledent, Rrodrigo Alves, Marius Kloft

Research Collection School Of Computing and Information Systems

We propose orthogonal inductive matrix completion (OMIC), an interpretable approach to matrix completion based on a sum of multiple orthonormal side information terms, together with nuclear-norm regularization. The approach allows us to inject prior knowledge about the singular vectors of the ground-truth matrix. We optimize the approach by a provably converging algorithm, which optimizes all components of the model simultaneously. We study the generalization capabilities of our method in both the distribution-free setting and in the case where the sampling distribution admits uniform marginals, yielding learning guarantees that improve with the quality of the injected knowledge in both cases. As …

Routing Policy Choice Prediction In A Stochastic Network: Recursive Model And Solution Algorithm, Tien Mai, Xinlian Yu, Song Gao, Emma Frejinger

Research Collection School Of Computing and Information Systems

We propose a Recursive Logit (STD-RL) model for routing policy choice in a stochastic time-dependent (STD) network, where a routing policy is a mapping from states to actions on which link to take next, and a state is defined by node, time and information. A routing policy encapsulates travelers’ adaptation to revealed traffic conditions when making route choices. The STD-RL model circumvents choice set generation, a procedure with known issues related to estimation and prediction. In a given state, travelers make their link choice maximizing the sum of the utility of the outgoing link and the expected maximum utility until …

A Learning And Optimization Framework For Collaborative Urban Delivery Problems With Alliances, Jingfeng Yang, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

The emergence of e-Commerce imposes a tremendous strain on urban logistics which in turn raises concerns on environmental sustainability if not performed efficiently. While large logistics service providers (LSPs) can perform fulfillment sustainably as they operate extensive logistic networks, last-mile logistics are typically performed by small LSPs who need to form alliances to reduce delivery costs and improve efficiency, and to compete with large players. In this paper, we consider a multi-alliance multi-depot pickup and delivery problem with time windows (MAD-PDPTW) and formulate it as a mixed-integer programming (MIP) model. To cope with large-scale problem instances, we propose a two-stage …

Injecting Descriptive Meta-Information Into Pre-Trained Language Models With Hypernetworks, Wenying Duan, Xiaoxi He, Zimu Zhou, Hong Rao, Lothar Thiele

Research Collection School Of Computing and Information Systems

Pre-trained language models have been widely adopted as backbones in various natural language processing tasks. However, existing pre-trained language models ignore the descriptive meta-information in the text such as the distinction between the title and the mainbody, leading to over-weighted attention to insignificant text. In this paper, we propose a hypernetwork-based architecture to model the descriptive meta-information and integrate it into pre-trained language models. Evaluations on three natural language processing tasks show that our method notably improves the performance of pre-trained language models and achieves the state-of-the-art results on keyphrase extraction.

Feeder Vessel Routing And Transshipment Coordination At A Congested Hub Port, Jiangang Jin, Qiang Meng, Hai Wang

Research Collection School Of Computing and Information Systems

With increasing container-shipping traffic, congestion at transshipment hub ports happens from time to time incurring longer-than-expected waiting time for vessels and loss of transshipment connections. This situation is even worse for feeder companies, due to their relatively lower berthing priority. It is essential to design the feeder vessel routes and schedules in response to hub port congestion while ensuring efficient transshipment connection with their connecting long-haul services. In this paper, we study the vessel routing and transshipment coordination problem for a feeder liner company where only limited choices of berthing time slots are available at the hub port. We proposed …