Physical Sciences and Mathematics Commons^™

Natural Language Processing For Disaster Tweets, Akinyemi D. Apampa, Nan Li

Publications and Research

Our goal is to establish an automatic model that identifies which tweets are about natural disasters based on the content of the tweets. Our method is to construct a decision tree based on keyword searching. We will construct the model using 7,645 tweets and test our model on 3,465 tweets as an assessment of the performance.

Finite Gaussian Neurons: Defending Against Adversarial Attacks By Making Neural Networks Say "I Don’T Know", Felix Grezes

Dissertations, Theses, and Capstone Projects

In this work, I introduce the Finite Gaussian Neuron (FGN), a novel neuron architecture for artificial neural networks aimed at protecting against adversarial attacks.
Since 2014, artificial neural networks have been known to be vulnerable to adversarial attacks, which can fool the network into producing wrong or nonsensical outputs by making humanly imperceptible alterations to inputs. While defenses against adversarial attacks have been proposed, they usually involve retraining a new neural network from scratch, a costly task.

My works aims to:
- easily convert existing models to Finite Gaussian Neuron architecture,
- while preserving the existing model's behavior on real …

Data-Centric Machine Learning For Speech And Audio, Ali Raza Syed

Dissertations, Theses, and Capstone Projects

There is growing recognition of the importance of data-centric methods for building machine learning systems. Data-centric methods assume a fixed model and iterate over the data to improve system performance. This is in contrast to traditional model-centric approaches, which assume a fixed dataset and iterate over models for the same ends. Data-centric machine learning is driven by the observation that, beyond the size of the training data, model performance depends on factors such as the quality of the annotations, and whether the data are representative of conditions in which models will be deployed. This is particularly of interest in the …

The Interaction Of Different Primary Producers And Physical And Chemical Dynamics Of An Urban Shallow Lake, Majid Sahin

Dissertations, Theses, and Capstone Projects

An artificial urban shallow lake, Prospect Park Lake (PPL), is situated on a terminal moraine in Brooklyn New York, and supplied with municipal water treated with ortho-phosphates. The constant input of the phosphate nutrient is the primary source of eutrophication in the lake. The numerous pools along the water course houses various aquatic phototrophs, which influence the water quality and the state of the system, driving conditions into favoring the survival of their species. In the first half of the dissertation, the focus of the project is on analyzing how the different primary producers in different regions of PPL affect …

Quantifying Aboveground Biomass In A Tropical Forest Using A Lidar Waveform Weighted Allometric Model, Alejandro Rojas

Theses and Dissertations

Our knowledge of the distribution and amount of terrestrial above ground biomass (AGB) has increased using lidar technology. Recent advancements in satellite lidar has enabled global mapping of forest biomass and structure. However, there are large biases in satellite lidar estimates which impacts our understanding of carbon dynamics, particularly in tropical forests.

Ni-Meister et al. (2022) developed a lidar full waveform weighted height-based allometric model which produced very good results in temperate deciduous/conifer forest in the continental US. The purpose of this study was to evaluate this biomass model in an African tropical forest using the Land Vegetation and Ice …

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 …

Exploring The Effectiveness Of Multiple-Exemplar Training For Visual Analysis Of Ab-Design Graphs, Verena S. Bethke

Dissertations, Theses, and Capstone Projects

In behavior analysis, data are usually analyzed using visual analysis of the graphed data. There are a wide range of methods used to visually analyze data, from a basic ‘textbook’ style approach to the use of visual aids, decision-rubrics, and computer-based approaches. In the literature, there have been some comparisons of the efficacy of different approaches. Visual analysis as a behavior can be taught using a variety of methods, independent of how the skill itself is to be performed. Teaching methods include lecture, online instruction, and equivalence-based instruction. There is not much research on the teaching of visual analysis specifically, …

Why, New York City? Gauging The Quality Of Life Through The Thoughts Of Tweeters, Sheryl Williams

Dissertations, Theses, and Capstone Projects

As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic modeling and sentiment analysis. Using this approach, the analysis reveals social and cultural differences, the overall sentiment of tweets, and subjects of interest to tweeters.

GitHub Repository for all …

Symmetry-Inspired Analysis Of Biological Networks, Ian Leifer

Dissertations, Theses, and Capstone Projects

The description of a complex system like gene regulation of a cell or a brain of an animal in terms of the dynamics of each individual element is an insurmountable task due to the complexity of interactions and the scores of associated parameters. Recent decades brought about the description of these systems that employs network models. In such models the entire system is represented by a graph encapsulating a set of independently functioning objects and their interactions. This creates a level of abstraction that makes the analysis of such large scale system possible. Common practice is to draw conclusions about …

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 …

Air Pollution, Climate Change, And Our Health, Kathia Vargas Feliz

Dissertations, Theses, and Capstone Projects

Climate change is a subject that is creating a lot of controversies nowadays. From newspapers to researchers, there are big efforts going on trying to bring awareness about the effects of air pollution and climate change over time. It is recommended that governments all over the world, and people from all communities act by taking care of the environment because the situation might turn out to be irremediable. There is a quote by Leonardo Dicaprio stating, “Climate change is real. It is happening right now; it is the most urgent threat facing our entire species and we need to …

Blockchain: Key Principles, Nadezda Chikurova

Dissertations, Theses, and Capstone Projects

“Blockchain: Key Principles” is an interactive visual project that explains the importance of data privacy and security, decentralized computing, and open-source software in the modern digital world through the history of the underlying principles of blockchain technology. Some of these key concepts have their roots in the time before the Information Age. By explaining the history of these principles, I want to present the fact that over the past centuries, humanity has been fighting for their privacy, security, and the ability to efficiently express themselves one way or another. Blockchain technology, which was introduced to the public in 2008 through …

Liquidity Commonality With Factor Models, Ernesto Garcia Iii

Dissertations, Theses, and Capstone Projects

Market microstructure research has recently devoted attention to a phenomenon called commonality in liquidity. In this dissertation, I will analyze commonality in liquidity using a novel factor model approach and a generalized definition of commonality in liquidity. This analysis will show that commonality in liquidity is rarely a marketwide phenomenon and is mostly restricted to stocks with a large market capitalization. Additionally, commonality in liquidity is a very recent phenomenon whose appearance coincides with a rise in passive investing after the Dotcom Bubble burst and, more so, after the 2008 Financial Crisis. I will present evidence that suggests commonality in …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

A Citizen-Science Approach For Urban Flood Risk Analysis Using Data Science And Machine Learning, Candace Agonafir

Dissertations and Theses

Street flooding is problematic in urban areas, where impervious surfaces, such as concrete, brick, and asphalt prevail, impeding the infiltration of water into the ground. During rain events, water ponds and rise to levels that cause considerable economic damage and physical harm. The main goal of this dissertation is to develop novel approaches toward the comprehension of urban flood risk using data science techniques on crowd-sourced data. This is accomplished by developing a series of data-driven models to identify flood factors of significance and localized areas of flood vulnerability in New York City (NYC). First, the infrastructural (catch basin clogs, …