Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Keyword
-
- Machine learning (4)
- Deep learning (3)
- Machine Learning (2)
- Mental health (2)
- Natural language processing (2)
-
- Sentiment analysis (2)
- Adaptive sampling (1)
- Artificial Intelligence (AI) (1)
- BPL (1)
- Bias (1)
- Biology (1)
- COMPAS (1)
- ChatGPT (1)
- Chord Progression (1)
- Classification (1)
- Computational Complexity (1)
- Computational biology (1)
- Computer science (1)
- Computer vision (1)
- Convolutional Neural Network (1)
- Data (1)
- Derandomization (1)
- Dermatology (1)
- Discrimination (1)
- EBIC (1)
- EPS (1)
- Encoder Decoder (1)
- Explainability (1)
- Extended Bayesian information criterion (1)
- Fairness (1)
Articles 1 - 16 of 16
Full-Text Articles in Physical Sciences and Mathematics
Predictive Ai For The S&P 500 Index, Jacqueline Rose Perry
Predictive Ai For The S&P 500 Index, Jacqueline Rose Perry
Computer Science Senior Theses
Artificial intelligence has powerful applications in virtually every field, and the financial world is no exception. Utilizing various elements of artificial intelligence, this research aims to predict the future value of the S&P 500 index using numerous models, and in doing so, identify relevant features. More specifically, models that include combinations of historical data, public sentiment, and technical indicators were employed to predict the stock price one day and three days forward. To account for public opinion, the sentiment of tweets and news headlines from the beginning of 2015 through the end of 2019 was calculated using FinBERT, a pre-trained …
The Dilemma Of Disclosure: Designing Interpersonal Informatics Tools For Mood Tracking, Daniel Earl Westphal
The Dilemma Of Disclosure: Designing Interpersonal Informatics Tools For Mood Tracking, Daniel Earl Westphal
Computer Science Senior Theses
Mental health is a serious issue that affects people of all ages, but is especially prevalent amongst college age youth. In the 2020-2021 school year, researchers found that around 60% of college students met the criteria for at least one mental health condition, such as major depression or generalized anxiety disorder. Many digital interventions have been innovated in order to help address this issue. These range in type and functionality from teletherapy to medication tracking applications. Some of these digital interventions include social features that allow users to interact with other users, friends, family, or doctors; however, having social features …
Stereotypes And Language Models: Understanding How Language Models Encode Stereotypes, Debiasing Language Models, And Examining How Stereotypes Affect Conversations, Brian C. Wang
Computer Science Senior Theses
This thesis describes a variety of approaches in examining how language models encode stereotypes (understanding stereotypes from a model point-of-view), debiasing language models, and using language models to understand how stereotypes affect conversations (understanding stereotypes from a conversational point-of-view). We present a novel approach for textual clues analysis that makes language models more interpretable, combining the understanding of what stereotypes the internal structures of language models have encoded during their initial training (via attention-based analysis) and understanding what textual clues are most relevant to identifying stereotypes for models trained to detect stereotypes (via SHAP-based analysis). We find that different pre-trained …
Sarcasm Detection In English And Arabic Tweets Using Transformer Models, Rishik Lad
Sarcasm Detection In English And Arabic Tweets Using Transformer Models, Rishik Lad
Computer Science Senior Theses
This thesis describes our approach toward the detection of sarcasm and its various types in English and Arabic Tweets through methods in deep learning. There are five problems we attempted: (1) detection of sarcasm in English Tweets, (2) detection of sarcasm in Arabic Tweets, (3) determining the type of sarcastic speech subcategory for English Tweets, (4) determining which of two semantically equivalent English Tweets is sarcastic, and (5) determining which of two semantically equivalent Arabic Tweets is sarcastic. All tasks were framed as classification problems, and our contributions are threefold: (a) we developed an English binary classifier system with RoBERTa, …
Counterfactual Replacement Analysis For Interpretation Of Blackbox Sexism Classification Models, Anders Knospe
Counterfactual Replacement Analysis For Interpretation Of Blackbox Sexism Classification Models, Anders Knospe
Computer Science Senior Theses
This paper describes the AKD team’s system designed for SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). We implement a simple fine-tuned GPT-3 model, ranking 26 on the leaderboard for task A. We also discuss different approaches to interpretability in the context of critiquing the EDOS task’s sub-category oriented approach. Finally, we propose counterfactual replacement analysis, a novel prototype technique for approaching explainability.
Utilizing Mixed Graphical Network Models To Explore Parent Psychological Symptoms And Their Centrality To Parent Mental Health In Households With High Child Screen Usage, Piper F. Stacey, Nicholas C. Jacobson, Damien Lekkas
Utilizing Mixed Graphical Network Models To Explore Parent Psychological Symptoms And Their Centrality To Parent Mental Health In Households With High Child Screen Usage, Piper F. Stacey, Nicholas C. Jacobson, Damien Lekkas
Computer Science Senior Theses
Especially among adolescents, screens are being used more than ever. In conjunction with this trend, mental illness is increasingly prevalent among both adults and children, and parental psychological problems are shown to be associated with children's TV watching, video watching, and gaming (Pulkki-Råback et al., 2022). This study aims to approach parent mental illness symptom by symptom to explore which specific symptoms are most central to parent psychological problems in households where children show high screen time behaviors. We draw from the Adolescent Brain Cognitive Development Study (ABCD Study®), a nationwide sample of 11,875 children aged 10-13 collected by …
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Computer Science Senior Theses
We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …
Exploring Improvements To Space-Bounded Derandomization From Better Pseudorandom Generators, Boxian Wang
Exploring Improvements To Space-Bounded Derandomization From Better Pseudorandom Generators, Boxian Wang
Computer Science Senior Theses
Saks and Zhou used Nisan’s PRG in a recursive manner to obtain BPL ⊆ L^(3/2). We describe how this framework could be generalized to use arbitrary PRGs following Armoni’s sampler idea. We then give a theorem relating the seed length of a better PRG to the implied improvements in derandomizing BPL. Recently, Hoza used Armoni’s PRG in the Saks-Zhou framework to obtain an even better derandomization. We describe the construction of Armoni’s PRG and conjecture that by using basic components other than extractors, parameters in that construction could be improved. Under some assumptions, we calculate the extent to which such …
Deep Learning For Skin Photoaging, Gokul Srinivasan
Deep Learning For Skin Photoaging, Gokul Srinivasan
Computer Science Senior Theses
Skin photoaging is the premature aging of skin that results from ultraviolet light exposure. It is a major risk factor for the development of skin cancer, among other malignant skin pathologies. Accordingly, understanding its etiology is important for both preventative and reparative clinical action. In this study, skin samples obtained from patients with ranging solar elastosis grades – a proxy for skin photoaging – were sequenced using next-generation sequencing techniques to further understand the genomic, epigenomic, and histological signs and signals of skin photoaging. The results of this study suggest that tissues with severe photoaging exhibit increases in the frequency …
Interpreting Business Strategy And Market Dynamics: A Multi-Method Ai Approach, Lobna Jbeniani
Interpreting Business Strategy And Market Dynamics: A Multi-Method Ai Approach, Lobna Jbeniani
Computer Science Senior Theses
This research paper presents an integrated approach that combines Long Short-Term Memory (LSTM), Q-Learning, Monte Carlo methods, and Text-to-Text Transfer Transformer (T5) to analyze and evaluate the business strategies of public companies. Leveraging a large and diverse dataset sourced from multiple reliable sources, the study examines corporate strategies and their impact on market dynamics. LSTM and Q-Learning are employed to process sequential data, enabling informed decision-making in simulated market environments and providing insights into potential outcomes of different strategies. The Monte Carlo method manages uncertainty, allowing for a comprehensive analysis of risks and rewards associated with specific strategies. T5 interprets …
Unmasking Bias: Investigating Strategies For Minimizing Discrimination In Ai Models, Julia L. Martin
Unmasking Bias: Investigating Strategies For Minimizing Discrimination In Ai Models, Julia L. Martin
Computer Science Senior Theses
Artificial Intelligence (AI) models are increasingly used as predictive tools with real-world applications occurring in diverse fields ranging from the healthcare industry to the criminal justice system. While AI often offers efficient and relatively effective solutions, there are growing concerns regarding AI’s role in decision-making processes due to potential biases embedded in these models. In many cases, bias in AI models can produce unfair outcomes, perpetuate social inequities, and undermine the trustworthiness of AI systems. This thesis explores this problem and spotlights certain biased models that are currently utilized in real-world situations. One such example is a highly biased AI …
Connecting Linguistic Expressions And Pain Relief Through Transformer Model Construction And Analysis, Sarah M. Chacko
Connecting Linguistic Expressions And Pain Relief Through Transformer Model Construction And Analysis, Sarah M. Chacko
Computer Science Senior Theses
Chronic pain is a widespread problem that significantly impacts quality of life. Overprescription and abuse of pain medication continues to be a major public health issue and can further burden patients due to a fragmented health care system. Previous research has suggested a possible psychological basis to pain and the potential for safer, non-pharmacological alternatives for pain relief. This project leverages language models to study chronic pain development and relief through psychological treatments, which will be assessed through responses to post-treatment interviews. A transformer-based natural language processing model is employed to identify connections between language expressions and pain on a …
An Algorithmic Approach To Jazz Guitar Voice-Leading Chord Fingerings, Matthew B. Keating
An Algorithmic Approach To Jazz Guitar Voice-Leading Chord Fingerings, Matthew B. Keating
Computer Science Senior Theses
A problem in guitar practice is choosing chord voicings that fit together in sequence, a process known as voice leading. In jazz, a guitarist follows voice leading by maintaining stepwise or limited motion for smoother harmony. The main avenues to learn jazz guitar voice leading theory are through a guitar instructor or chord books. To our knowledge, no computational method of generating voice-leading given chord labels exists. First, we demonstrate the complexity of this problem by presenting a graph search algorithm to optimize for a simplified version of voice leading. Then, we present a novel approach to algorithmically derive tablature …
Georcf-Gn: Geography-Aware State Prediction In Dynamic Networks, Barkin Cavdaroglu
Georcf-Gn: Geography-Aware State Prediction In Dynamic Networks, Barkin Cavdaroglu
Computer Science Senior Theses
No abstract provided.
An Empirical Study Of Locality-Sensitive Hashing To Approximate The Minimum Spanning Tree, Elizabeth Crocker
An Empirical Study Of Locality-Sensitive Hashing To Approximate The Minimum Spanning Tree, Elizabeth Crocker
Computer Science Senior Theses
The minimum spanning tree is a problem with important applications but for which there are no known efficient algorithms for large data sets. Locality-sensitive hashing has been used to solve the near-neighbor problem and further applications in clustering, which indicates its potential for approximating the minimum spanning tree as well. An algorithm by Sariel Har-Peled, Piotr Indyk, and Rajeev Motwani utilizes locality-sensitive hashing to provide a c-approximation of the minimum spanning tree in O(dn1+1/c log2 n) time. In this thesis, we implement and test this algorithm. We determine that the algorithm is suited to provide a better-than-random approximation …
Cyclic Mixed-Radix Dense Gray Codes, Jessica Cheng
Cyclic Mixed-Radix Dense Gray Codes, Jessica Cheng
Computer Science Senior Theses
A Gray code is a sequence of n binary integers in the range 0 to n-1 that has the Gray-code property: each integer in the sequence differs from the integer before it in a single digit. Gray codes have many applications, ranging from rotary encoders to Boolean circuit minimization. We refer to Gray codes where the first and last
codewords in the sequence fulfill the Gray-code property as cyclic. Additionally, we refer to a Gray code as dense if the sequence of n numbers consists of a permutation of ⟨0, 1, . . . , n − 1⟩. This thesis …