Digital Commons Network^™

A Python Implementation Of The Quasi-Harmonic Approximation: Ab-Initio Study Of The Thermoelastic Properties Of Magnesium Oxide And Calcium Oxide, Adewumi Bakare

Dissertations, Theses, and Capstone Projects

When heated up, materials change volume, typically they expand, and they also change their elastic properties, typically by softening. Computational methods to calculate materials properties at finite temperature are needed to compensate for the lack of experimental data, as well as to predict materials properties at conditions difficult to be reached in experimental labs. In this research project, I designed a set of Python codes implementing a quasi-harmonic approximation (QHA) method to calculate thermodynamic functions at constant volume, equation of state, and the isothermal Bulk modulus of cubic materials. To validate the new computational tools, this implementation of QHA has …

Phase Transitions, Critical Phenomena, And Correlation Functions In The 2d Ising Model And Its Applications To Quantum Dynamics: A Tensor Network Approach, Sankhya Basu

Dissertations, Theses, and Capstone Projects

This thesis explores several aspects of the 2D Ising Model at both real and complex temperatures utilizing tensor network algorithms. We briefly discuss the importance of tensor networks in the context of forming efficient representations of wavefunctions and partition functions for quantum and classical many-body systems respectively, followed by a brief review of the tensor network renormalization algorithms to compute the one point and two point correlation functions. We use the Tensor Renormalization Group (TRG) to study critical phenomena and examine feasibility of accurate estimations of universal critical data for three critical points for three critical points in two dimensions …

Optical Studies Of Wide Bandgap Photonic Materials, Nikesh Maharjan

Dissertations, Theses, and Capstone Projects

In this dissertation work, optical properties of wide bandgap materials such as hexagonal Boron Nitride (h-BN) and Zinc Oxide (ZnO) have been studied. Deep UV photoluminescence spectroscopy was employed to study the optical properties of bulk h-BN and powder crystals using a laser of wavelength 200 nm, which is the fourth harmonic of Ti:Sapphire laser as excitation source. The properties and chemical compositions of annealed and unannealed bulk h-BN were investigated. The PL spectra from h-BN samples annealed at 900 ºC in ambient air, had strong phonon assisted band edge emissions along with a sharp atomic-like emission line at 4.09 …

The Application Of Electron Backscatter Diffraction To The Forensic Analysis Of Minerals, Tiffany J. Millett

Dissertations, Theses, and Capstone Projects

Electron Backscatter Diffraction has been largely used in the metallurgic and material sciences and until now, has found few applications in the forensic sciences. One of the few utilizations of this technique in forensic science is in firearm serial number restoration as a complementary technique to the time-consuming and tedious chemical etching methods. This research aims to expand the uses of Electron Backscatter Diffraction in the forensic sciences as it applies to other types of samples, specifically as it pertains to forensic mineral analysis.

Electron Backscatter Diffraction offers the analyst information regarding crystal structure of a material, so long as …

Because They Think They Can: A Memoir In History, Sarah Goodyear

Dissertations, Theses, and Capstone Projects

What’s in a name? How are we connected to our ancestral lines? What responsibility do we bear for our lineages? How did the American character form, and how can we understand our society better by reckoning with our individual family histories? These are some of the questions at the heart of this thesis. In it, I combine memoir and history by following the Goodyear name, which has been mine since the day I was born. I weave together personal memories, historical research, and exploration of place to attempt to answer these questions for myself.

I begin with an examination of …

A Machine Learning Approach To Text-Based Sarcasm Detection, Lara I. Novic

Dissertations, Theses, and Capstone Projects

Sarcasm and indirect language are commonplace for humans to produce and recognize but difficult for machines to detect. While artificial intelligence can accurately analyze sentiment and emotion in speech and text, it may struggle with insincere and sardonic content, although it is possible to train a machine to identify uttered and written sarcasm. This paper aims to detect sarcasm using logistic regression and a support vector machine (SVM) and compare their results to a baseline.

The models are trained on headlines from a Kaggle dataset containing headlines from the satirical news website The Onion and serious news website Huffpost (formerly …

A Comparison Of Machine Learning Techniques For Validating Students’ Proficiency In Mathematics, Alexander Avdeev

Dissertations, Theses, and Capstone Projects

A principal goal of this project was to compare several machine learning (ML) algorithms to explore and validate math proficiency classifications based on standardized test scores. The data used in these analyses came from the 6th-grade students’ mathematics assessment records of the New York State Education Department’s Testing Program (NYSTP). Our approach was to test a number of competing machine learning (ML) algorithms for classifying students’ as proficient based on their test scores and other demographic information. Our samples were drawn from the 2016 test-taking cohort of 6th-grade students (N=156,800). Five classifiers including multinominal logistic regression (MLR), XGBoost, Tree-As, Lagrangian …

Unraveling The Double-Bind: An Investigation Of Black And Latina Women In Stem, Katlyn L. Milless

Dissertations, Theses, and Capstone Projects

Civil rights activist Robert P. Moses was a driving force in defining equitable dissemination of quality science, technology, engineering, and math (STEM) education as an act of social justice. My work borrows this frame to highlight access to STEM education as a civil rights issue and to emphasize the importance of taking a social justice approach to interventions for those who experience intersecting systems of oppression (i.e., Black and Latina women), and for whom previous intervention efforts have not adequately addressed. Ameliorating racial and gender disparities through fostering psychological safety (e.g., belonging) in STEM fields has been a substantive focus …

Time-To-Degree: Bachelor’S Degree Completion For Latine First-Year And Transfer Students, Robert E. Kunicki

Dissertations, Theses, and Capstone Projects

Latine bachelor’s degree completion has grown in the last several decades but has not kept pace with other racial and ethnic groups. Millions of Latines have successfully navigated higher education, yet not enough is known about the conduits and barriers to timely degree completion. This dissertation utilizes LatCrit, Anti-Deficit Achievement, and Intersectionality as theoretical frameworks; employs secondary analysis of a City University of New York dataset; and utilizes hierarchical regression modeling to examine the relative impact of college completion programs, academic momentum, and key demographic variables on time-to-degree for Latine students. Further, to see how these relationships operate differently for …

Coded Distributed Function Computation, Pedro J. Soto

Dissertations, Theses, and Capstone Projects

A ubiquitous problem in computer science research is the optimization of computation on large data sets. Such computations are usually too large to be performed on one machine and therefore the task needs to be distributed amongst a network of machines. However, a common problem within distributed computing is the mitigation of delays caused by faulty machines. This can be performed by the use of coding theory to optimize the amount of redundancy needed to handle such faults. This problem differs from classical coding theory since it is concerned with the dynamic coded computation on data rather than just statically …

A Machine Learning Approach To Predicting The Onset Of Type Ii Diabetes In A Sample Of Pima Indian Women, Meriem Benarbia

Dissertations, Theses, and Capstone Projects

Type II diabetes is a disease that affects how the body regulates and uses sugar (glucose) as a fuel. This chronic disease results in too much sugar circulating in the bloodstream. High blood sugar levels can lead to circulatory, nervous, and immune systems disorders. Machine learning (ML) techniques have proven their strength in diabetes diagnosis. In this paper, we aimed to contribute to the literature on the use of ML methods by examining the value of a number of supervised machine learning algorithms such as logistic regression, decision tree classifiers, random forest classifiers, and support vector classifiers to identify factors …

Heating Fire Incidents In New York City, Merissa K. Lissade

Dissertations, Theses, and Capstone Projects

If you have ever had the Citizen app downloaded on your smart phone, then you know how many alerts you receive in a day living in New York City (NYC). Citizen is a mobile app that sends real-time safety alerts based on the location of its user. In my experience having the app, I have seen many notifications of fires caused by heaters during the winter. On the morning of January 9^th, 2022, I received a notification of an accidental blaze that took the lives of 17 people from the choking smoke of a 19-story residential building in …

Correlations Between The Rotations And Magnetospheres Of The Terrestrial Planets And The Sun's Formation In Our Solar System, Fred J. Cadieu

Publications and Research

Correlations between the rotations of the terrestrial planets in our solar system and the magnetic field of the Sun have been previously noted. These correlations account for the opposite rotation of Venus as a result of the magnetic field of the Sun being dragged across the conducting core of Venus. Currently the Sun’s magnetic field is not sufficiently strong to account for the proposed correlations. But recently meteorite paleomagnetism measurements have indicated that during the Sun’s formation the magnetic field of the Sun was of sufficient strength to have resulted in the observed correlations. As a part of these correlations …

A Course In Data Science: R And Prediction Modeling, Adam Kapelner

Open Educational Resources

This is a self-contained course in data science and machine learning using R. It covers philosophy of modeling with data, prediction via linear models, machine learning including support vector machines and random forests, probability estimation and asymmetric costs using logistic regression and probit regression, underfitting vs. overfitting, model validation, handling missingness and much more. There is formal instruction of data manipulation using dplyr and data.table, visualization using ggplot2 and statistical computing.

Inheritance, Katherin Machalek

Theses and Dissertations

Inheritance is a feature documentary that investigates the concept of spiritual inheritance, that which is passed from parent to child. More precisely, it examines how the experiences and struggles of an individual may be transferred and reprocessed by their children. Life experience is studied not as personal, but rather a continuous process that transcends the parent and projects onto the children. The film is a hybrid composed of experimental sequences and false starts, which all bring attention to the nuances of a not-so-straightforward story. The film begins as an essay focusing on an investigation into my parents’ divorce with the …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

The Personal Papers Of American Sailors, 1890s–1940s, Annie E. Tummino

Publications and Research

Personal papers in the archives at Maritime College, State University of New York, document the lives of alumni from the school’s founding in 1874 through the early decades of the 20th century. Journals, diaries, memoirs, and reminiscences located in these collections provide evidence of what it was like to work on a ship, far from home, travelling to foreign lands. In this article, I explore first-hand accounts of maritime life by Van Horne Morris, my maternal grandfather and a 1938 graduate of the Massachusetts Nautical School (now known as Massachusetts Maritime Academy), and several alumni of the New York Nautical …

Challenges In Migrating Imperative Deep Learning Programs To Graph Execution: An Empirical Study, Tatiana Castro Vélez, Raffi Khatchadourian, Mehdi Bagherzadeh, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code that supports symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development tends to produce DL code that is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, less error-prone imperative DL frameworks encouraging eager execution have emerged at the expense of run-time performance. While hybrid approaches aim for the "best of both worlds," the challenges in applying them in the real world are largely unknown. We conduct a data-driven analysis of challenges—and resultant bugs—involved …

Tailored Resonant Waveguide Gratings For Augmented Reality, Matt Markowitz, Michele Cotrufo, You Zhou, Karl Stensvad, Craig Schard, Adam C. Overvig, Andrea Alù

Advanced Science Research Center

We explore the use of tailored resonant waveguide gratings (RWG) embedded in a glass-like matrix as angularly tolerant tri-band reflection filters under oblique excitation. Through inverse design we optimize 1D grating structures to support multi-frequency narrow- band resonances in an otherwise transparent background, ideally suited for augmented reality applications. In particular, we show theoretically and experimentally that a single RWG can be tailored to provide reflection levels larger than 50% under p-polarized excitation at three distinct wavelengths of choice, over a narrow bandwidth and within a substantial angular range around 58° incidence, while simultaneously eliminating ghost reflections from the glass/air …

A Tool For Rejuvenating Feature Logging Levels Via Git Histories And Degree Of Interest, Yiming Tang, Allan Spektor, Raffi Khatchadourian, Mehdi Bagherzadeh

Publications and Research

Logging is a significant programming practice. Due to the highly transactional nature of modern software applications, a massive amount of logs are generated every day, which may overwhelm developers. Logging information overload can be dangerous to software applications. Using log levels, developers can print the useful information while hiding the verbose logs during software runtime. As software evolves, the log levels of logging statements associated with the surrounding software feature implementation may also need to be altered. Maintaining log levels necessitates a significant amount of manual effort. In this paper, we demonstrate an automated approach that can rejuvenate feature log …

Recent Advances In Bone Research 2022 Edition, Jean-Philippe Berteau, Laurent Pujo-Menjouet

Publications and Research

More and more scientific and engineering applications in bone research make pivotal advances in treating patients with orthopedics issues. Hence, bone research in the 21st century combines, inter alia, biology, chemistry, mathematics, and mechanics with complementary characteristics that help a holistic approach to bone-related pathologies. Nowadays, it is hard to connect new evidence when jargoning and money remain two significant obstacles to sharing knowledge. “Recent Advances In Bone Research” is a free book – no money involved at any stage - that combines the most recent efforts in bone research from several experts with different backgrounds, every expert seeks to …

The Significance Of Sonic Branding To Strategically Stimulate Consumer Behavior: Content Analysis Of Four Interviews From Jeanna Isham’S “Sound In Marketing” Podcast, Ina Beilina

Student Theses and Dissertations

Purpose:
Sonic branding is not just about composing jingles like McDonald’s “I’m Lovin’ It.” Sonic branding is an industry that strategically designs a cohesive auditory component of a brand’s corporate identity. This paper examines the psychological impact of music and sound on consumer behavior reviewing studies from the past 40 years and investigates the significance of stimulating auditory perception by infusing sound in consumer experience in the modern 2020s.

Design/methodology/approach:
Qualitative content analysis of audio media was used to test two hypotheses. Four archival oral interview recordings from Jeanna Isham’s podcast “Sound in Marketing” featuring the sonic branding experts …

Effectiveness And Safety Of Oral Anticoagulants In Non-Valvular Atrial Fibrillation Patients With Prior Bleeding Events: A Retrospective Analysis Of Administrative Claims Databases, G. Y. H. Lip, Allison V. Keshishian, Amiee Kang, Xuemei Luo, Nipun Atreja, Yan Zhang, Patricia Schuler, Jenny Jiang, Huseyin Yuce, Steve Deitelzweig

Publications and Research

Introduction

There are a paucity of real-world data examining effectiveness and safety of non-vitamin K antagonist oral anticoagulants (NOACs) and warfarin in nonvalvular atrial fibrillation (NVAF) patients with prior bleeding.

Methods

This retrospective analysis included data from 5 insurance claims databases and included NVAF patients prescribed OACs with prior bleeding. One-to-one propensity score matching was conducted between NOACs and warfarin and between NOACs in each database. Cox proportional hazards models were used to evaluate the risk of stroke/systemic embolism (SE) and MB.

Results

A total of 244,563 patients (mean age 77; 50% female) with prior bleeding included 55,094 (22.5%) treated …

Cell‑Controlled Dynamic Surfaces For Skeletal Stem Cell Growth And Differentiation, Hilary J. Anderson, Jugal Kishore Sahoo, Julia Wells, Sebastiaan Van Nuffel, Hala S. Dhowre, Richard O. C. Oreffo, Mischa Zelzer, Rein V. Ulijn, Matthew J. Dalby

Advanced Science Research Center

Skeletal stem cells (SSCs, or mesenchymal stromal cells typically referred to as mesenchymal stem cells from the bone marrow) are a dynamic progenitor population that can enter quiescence, self-renew or differentiate depending on regenerative demand and cues from their niche environment. However, ex vivo, in culture, they are grown typically on hard polystyrene surfaces, and this leads to rapid loss of the SSC phenotype. While materials are being developed that can control SSC growth and differentiation, very few examples of dynamic interfaces that reflect the plastic nature of the stem cells have, to date, been developed. Achieving such interfaces is …

Mapping The Covid-19 Pandemic In Staten Island, Vincenzo Mezzio

Student Theses

COVID-19 has had diverging effects in New York City. Out of the five boroughs, Staten Island has one of the largest percentages of COVID-19 cases relative to population. This research examines key social and spatial factors that contribute to the increase in COVID-19 cases in Staten Island). It asks: Which parts of Staten Island have higher rates of transmission of COVID-19? Which parts of the borough have higher population who are more vulnerable to COVID-19? What is the relationship between the location of vaccination centers with the rates of COVID-19 cases? Using Geographic Information Systems (GIS), this research examines the …

(1-12 All The Way Down), Amorelle Jacox

Theses and Dissertations

My paintings are born out of a profound sense of cosmic free-fall. Tables and black holes hover in a realm where slippage between figure, object and space are confused. Metaphor pries open depths of metaphysical inquiry. That, with a brushstroke, the sky’s stomach might fold into a plate, and slip between the days.

Dust, Mist, Haze, Michael C. Tracy

Theses and Dissertations

This paper explores painting through the ideas of dust, mist, and haze as specific atmospheric metaphors that could be used to describe ontologies of space, time, memory, and history.

T.R.A.S.H.:Trans-Relational-Affective-Stuff-Horde, Sg P

Theses and Dissertations

T.R.A.S.H. allies the moral confusion underlying (student) debt and the unregulated art market in order to establish a rigorous framework for “RED HOT SHAME”—an open edition contractual performance. In treating an art collector as a collections agency, the Debt Object becomes an Art Object.

Lake Satellite Temperature Data Validation, Mamadou Balde, Pascal Kouogang

Publications and Research

In environmental remote sensing, satellite data isn't absolutely conclusive, for that reason, there is a natural need to verify the data acquired from the satellite. The most suitable tool to achieve such verification is on ground sensors that have the advantage of proximity. Addressing any possible discrepancies between the satellite data and the ground sensor data is sure to yield ways to come up with improvements of satellite band calibration and sensing capabilities. This research focused on correlating temperature data from the MODIS satellite with the data obtained from the In Situ sensor located in Lake Sunapee. Doing the latter …

Pluto In Hand: Design And Implementation Of A Location-Based Mobile Augmented Reality Application For Viewing Open Data, Matthew O. Ward

Theses and Dissertations

Immersive mobile augmented reality (AR) technology has improved while geolocational data volume has grown. City governments can utilize this technology to share their geospatial data with the public, promoting smart city aims. This research describes the design and implementation of a novel open-source ARGIS application to view property tax lot information in New York City. This proof-of-technology demonstrates web-based AR can visualize location-based spatial data.