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Full-Text Articles in Social and Behavioral Sciences
Applying Data Science And Machine Learning To Understand Health Care Transition For Adolescents And Emerging Adults With Special Health Care Needs, Lisamarie Turk
Nursing ETDs
A problem of classification places adolescents and emerging adults with special health care needs among the most at risk for poor or life-threatening health outcomes. This preliminary proof-of-concept study was conducted to determine if phenotypes of health care transition (HCT) for this vulnerable population could be established. Such phenotypes could support development of future studies that require data classifications as input. Mining of electronic health record data and cluster analysis were implemented to identify phenotypes. Subsequently, a machine learning concept model was developed for predicting acute care and medical condition severity. Three clusters were identified and described (Cluster 1, n …
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Electrical & Computer Engineering Theses & Dissertations
Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …
Exploring The Effectiveness Of Multiple-Exemplar Training For Visual Analysis Of Ab-Design Graphs, Verena S. Bethke
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, …
Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny
Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny
Civil & Environmental Engineering Theses & Dissertations
Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …
A Remote Sensing And Machine Learning-Based Approach To Forecast The Onset Of Harmful Algal Bloom (Red Tides), Moein Izadi
A Remote Sensing And Machine Learning-Based Approach To Forecast The Onset Of Harmful Algal Bloom (Red Tides), Moein Izadi
Dissertations
In the last few decades, harmful algal blooms (HABs, also known as “red tides”) have become one of the most detrimental natural phenomena all around the world especially in Florida’s coastal areas due to local environmental factors and global warming in a larger scale. Karenia brevis produces toxins that have harmful effects on humans, fisheries, and ecosystems. In this study, I developed and compared the efficiency of state-of-the-art machine learning models (e.g., XGBoost, Random Forest, and Support Vector Machine) in predicting the occurrence of HABs. In the proposed models, the K. brevis abundance is used as the target, and 10 …
Predicting League Of Legends Ranked Games Outcome, Ngoc Linh Chi Nguyen
Predicting League Of Legends Ranked Games Outcome, Ngoc Linh Chi Nguyen
Senior Projects Spring 2022
League of Legends (LoL) is the one of most popular multiplayer online battle arena (MOBA) games in the world. For LoL, the most competitive way to evaluate a player’s skill level, below the professional Esports level, is competitive ranked games. These ranked games utilize a matchmaking system based on the player’s ranks to form a fair team for each game. However, a rank game's outcome cannot necessarily be predicted using just players’ ranks, there are a significant number of different variables impacting a rank game depending on how well each team plays. In this paper, I propose a method to …
Exploring Cyberterrorism, Topic Models And Social Networks Of Jihadists Dark Web Forums: A Computational Social Science Approach, Vivian Fiona Guetler
Exploring Cyberterrorism, Topic Models And Social Networks Of Jihadists Dark Web Forums: A Computational Social Science Approach, Vivian Fiona Guetler
Graduate Theses, Dissertations, and Problem Reports
This three-article dissertation focuses on cyber-related topics on terrorist groups, specifically Jihadists’ use of technology, the application of natural language processing, and social networks in analyzing text data derived from terrorists' Dark Web forums. The first article explores cybercrime and cyberterrorism. As technology progresses, it facilitates new forms of behavior, including tech-related crimes known as cybercrime and cyberterrorism. In this article, I provide an analysis of the problems of cybercrime and cyberterrorism within the field of criminology by reviewing existing literature focusing on (a) the issues in defining terrorism, cybercrime, and cyberterrorism, (b) ways that cybercriminals commit a crime in …