Physical Sciences and Mathematics Commons^™

New Algorithmic Support For The Fundamental Theorem Of Algebra, Vitaly Zaderman

Dissertations, Theses, and Capstone Projects

Univariate polynomial root-finding is a venerated subjects of Mathematics and Computational Mathematics studied for four millenia. In 1924 Herman Weyl published a seminal root-finder and called it an algorithmic proof of the Fundamental Theorem of Algebra. Steve Smale in 1981 and Arnold Schonhage in 1982 proposed to classify such algorithmic proofs in terms of their computational complexity. This prompted extensive research in 1980s and 1990s, culminated in a divide-and-conquer polynomial root-finder by Victor Pan at ACM STOC 1995, which used a near optimal number of bit-operations. The algorithm approximates all roots of a polynomial p almost as fast as one …

The Early Late Miocene Cessation Of Deep And Intermediate Water Circulation Through The Central American Seaway, Benjamin Stanley Kwiatkowski

Dissertations, Theses, and Capstone Projects

The state of the middle late Miocene global ocean circulations which regulated climate and affected deep ocean chemical environments were impacted by geographic changes. During the Miocene, cirum-equatorial circulations slowly decreased, which included through the seaway between the Americas called the Central American Seaway (CAS). Its shoaling and ultimate closing led to the onset of modern day oceanic circulation as characterized by the global thermohaline circulation. However, this seaway has a long hotly debated history concerning the timing of its restriction and shallowing owing in part to the shifting of tectonic plates.

The goal of this research focuses on investigating …

Trees In Urban Environments: How Soil Quality Impacts Tree Performance, Saidan Qi

Dissertations, Theses, and Capstone Projects

Cities around the world are increasingly investing in reforestation and afforestation efforts to mitigate impacts from climate change and population growth. However, urban soil conditions can be unfavorable for tree growth. Street trees are widely known to suffer from poor soil quality, but there has been no comprehensive review of this topic so far. Clean soils can be transported from nonurban areas to support cities’ green projects, but this approach is not sustainable. Artificial (constructed) soils can be created from various materials and have been proposed as an alternative medium for urban tree growth, but no research has been done …

Containerization Of Seafarers In The International Shipping Industry: Contemporary Seamanship, Maritime Social Infrastructures, And Mobility Politics Of Global Logistics, Liang Wu

Dissertations, Theses, and Capstone Projects

This dissertation discusses the mobility politics of container shipping and argues that technological development, political-economic order, and social infrastructure co-produce one another. Containerization, the use of standardized containers to carry cargo across modes of transportation that is said to have revolutionized and globalized international trade since the late 1950s, has served to expand and extend the power of international coalitions of states and corporations to control the movements of commodities (shipments) and labor (seafarers). The advent and development of containerization was driven by a sociotechnical imaginary and international social contract of seamless shipping and cargo flows. In practice, this liberal, …

Evaluating The Reliability And Accuracy Of Alchemical Binding Free Energy Methods And Calculations, Fnu Sheenam

Dissertations, Theses, and Capstone Projects

Molecular recognition plays a crucial role in various biological processes, such as enzymatic reactions, signal transduction, and genetic information processing. Investigating how proteins selectively bind to their partners is an active research area, but there is a lack of experimental details on protein structures and interactions in molecular complexes. Computational techniques based on macromolecular structures offer a way to predict protein-ligand interactions and explore their recognition mechanisms. Estimating binding affinities, particularly through alchemical binding free energy calculations, has become valuable in supporting drug discovery. This work introduces new methodologies, utilizing the Alchemical Transfer Method, to address issues like poor convergence …

Deep Learning-Based Human Action Understanding In Videos, Elahe Vahdani

Dissertations, Theses, and Capstone Projects

The understanding of human actions in videos holds immense potential for technological advancement and societal betterment. This thesis explores fundamental aspects of this field, including action recognition in trimmed clips and action localization in untrimmed videos. Trimmed videos contain only one action instance, with moments before or after the action excluded from the video. However, the majority of videos captured in unconstrained environments, often referred to as untrimmed videos, are naturally unsegmented. Untrimmed videos are typically lengthy and may encompass multiple action instances, along with the moments preceding or following each action, as well as transitions between actions. In the …

Rational Design Of Peptide-Based Materials Informed By Multiscale Molecular Dynamics Simulations, Dhwanit Rahul Dave

Dissertations, Theses, and Capstone Projects

The challenge of establishing a sustainable and circular economy for materials in medicine and technology necessitates bioinspired design. Nature's intricate machinery, forged through evolution, relies on a finite set of biomolecular building blocks with through-bond and through-space interactions. Repurposing these molecular building blocks requires a seamless integration of computational modeling, design, and experimental validation. The tools and concepts developed in this thesis pioneer new directions in peptide-materials design, grounded in fundamental principles of physical chemistry. We present a synergistic approach that integrates experimental designs and computational methods, specifically molecular dynamics simulations, to gain in-depth molecular insights crucial for advancing the …

Clustering Of Patients With Heart Disease, Mukadder Cinar

Dissertations, Theses, and Capstone Projects

Heart disease, a leading cause of mortality worldwide, presents complex challenges in public health due to its varied manifestations. Accurate diagnosis and patient stratification are essential for effective management and improved outcomes. In response, this study employed machine learning techniques to analyze heart disease data obtained from UCI Machine Learning Repository, aiming to enhance patient care through advanced data analysis.

The study began with the application of K-Nearest Neighbors (KNN) classification, which categorized patients into 'Disease' and 'No Disease' groups. This preliminary step provided initial insights into the structure of the dataset. Subsequently, K-means clustering was applied in two rounds, …

Synthesis And Characterization Of Donor-Acceptor Fluorescent Conjugated Polymers By Acyclic Diene Metathesis (Admet) And Suzuki Polycondensation (Spc), Hamid Ardolic Jr.

Dissertations, Theses, and Capstone Projects

Conjugated polymers are useful in a wide variety of applications including production of Light Emitting Diodes (LEDs), Field Effect Transistors (FETs) and organic photovoltaics. Our work in the lab focuses on the development of materials for use in Polymer Solar Cells (PSCs) using various electron donating and electron accepting units to individually tune the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) respectively and produce a small but controlled band gap. This is accomplished through the synthesis of several precursors and their subsequent polymerization using Acyclic Diene Metathesis (ADMET) and Suzuki Polycondensation (SPC). Moderately strong electron donors, …

Examining The Health Risks Of Particulate Matter 2.5 In New York City: How It Affects Marginalized Groups And The Steps Needed To Reduce Air Pollution, Freddy Castro

Dissertations, Theses, and Capstone Projects

The following examines the impact of particulate matter 2.5 (PM2.5) on public health, focusing on its sources and effects on vulnerable populations in New York City. PM2.5 is a particle that is 2.5 micrometers or less in diameter and, because of its size, can enter the bloodstream affecting the respiratory and cardiovascular systems and further complicating the health of the immunocompromised. Recent studies have shown that PM2.5 can come from various sources, including transportation and industrial emissions, as well as indoor sources like cigarettes and gas-operated stoves. Despite reduced levels of PM2.5 due to recent policy changes and initiatives taken …

Making Sense Of Making Parole In New York, Alexandra Mcglinchy

Dissertations, Theses, and Capstone Projects

For many individuals incarcerated in New York, the initial step toward freedom begins with an interview with the Board of Parole. This process, however, is frequently a complex and challenging one, characterized by repeated denials and extended incarcerations. The disparity in outcomes – where one individual may receive over 20 denials and another is granted parole on their first attempt – highlights the ambiguity and inconsistency in the parole decision-making process. This project aims to clarify the factors that influence parole decisions by concentrating on measurable variables. These include age, race, duration of sentence served, proportion of sentence served, type …

Towards Sociobiogeochemistry: Critical Perspectives On Anthropogenic Alterations To Soil Nitrogen Chemistry Via U.S. Urban And Suburban Development, Christopher D. Ryan

Dissertations, Theses, and Capstone Projects

The ecological impacts of changes to land use are relevant to concerns about climate change, eutrophication of waterbodies, and reductions in biodiversity. As a foundational component of ecosystem functioning, changes to soil biogeochemistry have significant effects on overall ecosystem health. With cities continuing to grow and develop in extent, the impacts of urbanization and suburbanization on soils are of particular concern. Despite a wide range of natural climatic and geologic conditions, several factors have driven similar patterns of land transformation and management across the United States. In particular, federal initiatives including the Home Owners Loan Corporation, the Federal Housing Administration, …

What Does One Billion Dollars Look Like?: Visualizing Extreme Wealth, William Mahoney Luckman

Dissertations, Theses, and Capstone Projects

The word “billion” is a mathematical abstraction related to “big,” but it is difficult to understand the vast difference in value between one million and one billion; even harder to understand the vast difference in purchasing power between one billion dollars, and the average U.S. yearly income. Perhaps most difficult to conceive of is what that purchasing power and huge mass of capital translates to in terms of power. This project blends design, text, facts, and figures into an interactive narrative website that helps the user better understand their position in relation to extreme wealth: https://whatdoesonebilliondollarslooklike.website/

The site incorporates …

Integration Of Field- And Space-Based Observations Toward Assessing Drivers Of Biogeochemical Variability Across Vulnerable Coastal Ecosystems, Alana B. Menendez

Dissertations, Theses, and Capstone Projects

This thesis uses new field datasets and satellite ocean color products to quantify biogeochemical variability in three coastal regions: Long Island Sound estuary, the coastline of the Bay of Bengal extending east to the Mekong Delta, and the Yukon River Delta. These three study regions have vastly different size domains, climates, populations, and economies, but all require enhanced coastal water monitoring in the face of climate change. These regions are all naturally dynamic and experience strong seasonal phenomena but are also subject to changing hydrological forcings and direct anthropogenic perturbations. This leaves these coastal areas vulnerable to altered biogeochemical cycling, …

Studies Of Oxidopyrylium Ylide Dimers And Their Utility In The Synthesis Of Densely Functionalized Troponoids, Daniel V. Schiavone

Dissertations, Theses, and Capstone Projects

Herein, we describe our efforts to investigate mechanistic considerations of oxidopyrylium ylides and their use in cycloadditions to form complex bicyclic structures and the advancement of these cycloadducts to the synthesis of densely functionalized tropolones. This work also describes applications of tropolones as biologically relevant structures and dynamic fluorophores.

In Chapter 1, we expand upon previous studies done in the Murelli Lab describing the ability of 3-hydroxy-4-pyrone derived oxidopyrylium dimers to revert back to ylides in situ and as result can be used as a clean oxidopyrylium ylide source in accessing oxabicyclic compounds. Intermolecular cycloadditions of these ylides can be …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction-a measure of …

Low Shear In Short-Term Impacts Endothelial Cell Traction And Alignment In Long-Term, Mohanish K. Chandurkar, Nikhil Mittal, Shaina P. Royer-Weeden, Steven D. Lehmann, Yeonwoo Rho, Sangyoon J. Han

Michigan Tech Publications

Within the vascular system, endothelial cells (ECs) are exposed to fluid shear stress (FSS), a mechanical force exerted by blood flow that is critical for regulating cellular tension and maintaining vascular homeostasis. The way ECs react to FSS varies significantly; while high, laminar FSS supports vasodilation and suppresses inflammation, low or disturbed FSS can lead to endothelial dysfunction and increase the risk of cardiovascular diseases. Yet, the adaptation of ECs to dynamically varying FSS remains poorly understood. This study focuses on the dynamic responses of ECs to brief periods of low FSS, examining its impact on endothelial traction—a measure of …

Investigating The Mass Mortality Induced Factors Of Pearl Oyster (Pinctada Radiata) At Abu Dhabi Pearls Farm, Uae, Hamad Ahmed Almansoori

Theses

The aquaculture of shellfish plays a crucial role in enhancing maritime environments by mitigating algal blooms and improving water quality through the filtration of organic matter, nutrients, and bacteria. This study investigated the environmental factors influencing oyster (Pinctada radiata) mortalities through a comprehensive analysis of water quality in Al Mirfa and Al Mughirah farming sites of Abu Dhabi (UAE), from February 2021 to February 2022. To reach such understanding of the main factors led to mass mortalities of cultivated oysters, different monthly sampling and both chemical and biological analyses of the farm water, sediments as well as for both living …

Fast And Reliable Authentication Method For Indoor Constrained Drones, Fatima Ali Al Nuaimi

Theses

Over the last twenty years, the commercial sector of Unmanned Aerial Vehicles has been growing exponentially, owing to their rapid deployment, high mobility, and the number of applications in the industry field such as military, transportation, critical infrastructures, as well as in the academic field for research purposes. One of the main communication systems adopted by the UAVs relies on transmitting wireless signals.

In particular, UAVs are adopted for indoor use-case scenarios, such as warehouse inventory applications and indoor building inspections. They need to transmit control messages and sensitive data by leveraging an efficient, short-range, and secure communication channel to …

Accessing Reactive Metal Hydrides Through Designed Heterometallic Bridges, Fernando Gonzalez, Edgardo De Leon, Manar M. Shoshani

School of Integrative Biological & Chemical Sciences Faculty Publications

A methodology to access reactive hydride moieties is highly desirable, yet limited. Multimetallic hydride fragments are notable for their heightened reactivity and catalysis, but deliberate access to these species is lacking. In this highlight, we discuss recent developments by our group in the design of a new heterometallic complex that invokes an architecture designed to provide modular access to reactive hydride moieties by leveraging metal hydrides in combination with pendent donors to a model heterotrimetallic Ni–(Al–H)2 complex. An amplification of insertion-based reactivity has been examined in the hydrofunctionalization of quinolines, and our complex substantially outperformed the parent aluminum hydride LAlH …

Recommendations With Minimum Exposure Guarantees: A Post-Processing Framework, Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft

Research Collection School Of Computing and Information Systems

Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may favor some item groups over others. For instance, some items might receive lower ratings due to some sort of bias (e.g. gender bias). A fair ranking should balance the exposure of items from advantaged and disadvantaged groups. To this end, we propose a novel post-processing framework to produce fair, exposure-aware recommendations. Our approach is based on an integer linear programming model maximizing the expected utility while satisfying a minimum exposure constraint. The model has fewer variables than previous …

Foodmask: Real-Time Food Instance Counting, Segmentation And Recognition, Huu-Thanh Nguyen, Yu Cao, Chong-Wah Ngo, Wing-Kwong Chan

Research Collection School Of Computing and Information Systems

Food computing has long been studied and deployed to several applications. Understanding a food image at the instance level, including recognition, counting and segmentation, is essential to quantifying nutrition and calorie consumption. Nevertheless, existing techniques are limited to either category-specific instance detection, which does not reflect precisely the instance size at the pixel level, or category-agnostic instance segmentation, which is insufficient for dish recognition. This paper presents a compact and fast multi-task network, namely FoodMask, for clustering-based food instance counting, segmentation and recognition. The network learns a semantic space simultaneously encoding food category distribution and instance height at pixel basis. …

Better Pay Attention Whilst Fuzzing, Shunkai Zhu, Jingyi Wang, Jun Sun, Jie Yang, Xingwei Lin, Tianyi Wang, Liyi Zhang, Peng Cheng

Research Collection School Of Computing and Information Systems

Fuzzing is one of the prevailing methods for vulnerability detection. However, even state-of-the-art fuzzing methods become ineffective after some period of time, i.e., the coverage hardly improves as existing methods are ineffective to focus the attention of fuzzing on covering the hard-to-trigger program paths. In other words, they cannot generate inputs that can break the bottleneck due to the fundamental difficulty in capturing the complex relations between the test inputs and program coverage. In particular, existing fuzzers suffer from the following main limitations: 1) lacking an overall analysis of the program to identify the most “rewarding” seeds, and 2) lacking …

Machine Learning For Refining Knowledge Graphs: A Survey, Budhitama Subagdja, D. Shanthoshigaa, Zhaoxia Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Knowledge graph (KG) refinement refers to the process of filling in missing information, removing redundancies, and resolving inconsistencies in knowledge graphs. With the growing popularity of KG in various domains, many techniques involving machine learning have been applied, but there is no survey dedicated to machine learning-based KG refinement yet. Based on a novel framework following the KG refinement process, this paper presents a survey of machine learning approaches to KG refinement according to the kind of operations in KG refinement, the training datasets, mode of learning, and process multiplicity. Furthermore, the survey aims to provide broad practical insights into …

Imitate The Good And Avoid The Bad: An Incremental Approach To Safe Reinforcement Learning, Minh Huy Hoang, Mai Anh Tien, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

A popular framework for enforcing safe actions in Reinforcement Learning (RL) is Constrained RL, where trajectory based constraints on expected cost (or other cost measures) are employed to enforce safety and more importantly these constraints are enforced while maximizing expected reward. Most recent approaches for solving Constrained RL convert the trajectory based cost constraint into a surrogate problem that can be solved using minor modifications to RL methods. A key drawback with such approaches is an over or underestimation of the cost constraint at each state. Therefore, we provide an approach that does not modify the trajectory based cost constraint …

Catnet: Cross-Modal Fusion For Audio-Visual Speech Recognition, Xingmei Wang, Jianchen Mi, Boquan Li, Yixu Zhao, Jiaxiang Meng

Research Collection School Of Computing and Information Systems

Automatic speech recognition (ASR) is a typical pattern recognition technology that converts human speeches into texts. With the aid of advanced deep learning models, the performance of speech recognition is significantly improved. Especially, the emerging Audio–Visual Speech Recognition (AVSR) methods achieve satisfactory performance by combining audio-modal and visual-modal information. However, various complex environments, especially noises, limit the effectiveness of existing methods. In response to the noisy problem, in this paper, we propose a novel cross-modal audio–visual speech recognition model, named CATNet. First, we devise a cross-modal bidirectional fusion model to analyze the close relationship between audio and visual modalities. Second, …

When Evolutionary Computation Meets Privacy, Bowen Zhao, Wei-Neng Chen, Xiaoguo Li, Ximeng Liu, Qingqi Pei, Jun Zhang

Research Collection School Of Computing and Information Systems

Recently, evolutionary computation (EC) has experienced significant advancements due to the integration of machine learning, distributed computing, and big data technologies. These developments have led to new research avenues in EC, such as distributed EC and surrogate-assisted EC. While these advancements have greatly enhanced the performance and applicability of EC, they have also raised concerns regarding privacy leakages, specifically the disclosure of optimal results and surrogate models. Consequently, the combination of evolutionary computation and privacy protection becomes an increasing necessity. However, a comprehensive exploration of privacy concerns in evolutionary computation is currently lacking, particularly in terms of identifying the object, …

Hgprompt: Bridging Homogeneous And Heterogeneous Graphs For Few-Shot Prompt Learning, Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang

Research Collection School Of Computing and Information Systems

Graph neural networks (GNNs) and heterogeneous graph neural networks (HGNNs) are prominent techniques for homogeneous and heterogeneous graph representation learning, yet their performance in an end-to-end supervised framework greatly depends on the availability of task-specific supervision. To reduce the labeling cost, pre-training on selfsupervised pretext tasks has become a popular paradigm, but there is often a gap between the pre-trained model and downstream tasks, stemming from the divergence in their objectives. To bridge the gap, prompt learning has risen as a promising direction especially in few-shot settings, without the need to fully fine-tune the pre-trained model. While there has been …

Glop: Learning Global Partition And Local Construction For Solving Large-Scale Routing Problems In Real-Time, Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li

Research Collection School Of Computing and Information Systems

The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Global and Local Optimization Policies), a unified hierarchical framework that efficiently scales toward large-scale routing problems. GLOP partitions large routing problems into Travelling Salesman Problems (TSPs) and TSPs into Shortest Hamiltonian Path Problems. For the first time, we hybridize non-autoregressive neural heuristics for coarse-grained problem partitions and autoregressive neural heuristics for fine-grained route constructions, leveraging the scalability of the former and the meticulousness of the latter. Experimental results show that GLOP achieves competitive and state-of-the-art real-time performance …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …