Physical Sciences and Mathematics Commons^™

How Facial Features Convey Attention In Stationary Environments, Janelle Domantay, Brendan Morris

Spectra Undergraduate Research Journal

Awareness detection technologies have been gaining traction in a variety of enterprises; most often used for driver fatigue detection, recent research has shifted towards using computer vision technologies to analyze user attention in environments such as online classrooms. This paper aims to extend previous research on distraction detection by analyzing which visual features contribute most to predicting awareness and fatigue. We utilized the open-source facial analysis toolkit OpenFace in order to analyze visual data of subjects at varying levels of attentiveness. Then, using a Support-Vector Machine (SVM) we created several prediction models for user attention and identified the Histogram of …

Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virginia B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai

Electrical & Computer Engineering Faculty Research

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications …

Computational Approaches To Facilitate Automated Interchange Between Music And Art, Rao Hamza Ali

Computational and Data Sciences (PhD) Dissertations

Recently, there has been a tremendous increase in generating and synthesizing music and art using various computational techniques. An area that is still under-researched, however, is how one medium can be converted into the other, while maintaining the overall aesthetics. Over the last few centuries, artists, composers, and scholars, have attempted to use substitute one form of art for the other: by proposing techniques where music notes are synonymous to colors, by inventing instruments that combine the aesthetics of music and visual art, and by incorporating the two media in live performances. A widely accepted computational approach, for the conversion, …

Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen

Engineering Faculty Articles and Research

Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …

Communicating With Culture: How Humans And Machines Detect Narrative Elements, Wolfgang Victor H. Yarlott

FIU Electronic Theses and Dissertations

To understand how people communicate, we must understand how they leverage shared stories and all the knowledge, information, and associations contained within those stories. I examine three classes of narrative elements that convey a wealth of cultural knowledge: Propp's morphology, motifs, and discourse structure. Propp's morphology communicates how roles and actions drive a narrative forward; motifs fill those roles and actions with specific, remarkable events; discourse groups these into a coherent structure to convey a point.

My thesis has three aims: first, to demonstrate that people can reliably detect and identify all three of these narrative elements; second, to develop …

A High Precision Machine Learning-Enabled System For Predicting Idiopathic Ventricular Arrhythmia Origins, Jianwei Zheng, Guohua Fu, Daniele Struppa, Islam Abudayyeh, Tahmeed Contractor, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy.

Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, …

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 …

Classifying Blood Glucose Levels Through Noninvasive Features, Rishi Reddy

Graduate Theses, Dissertations, and Problem Reports

Blood glucose monitoring is a key process in the prevention and management of certain chronic diseases, such as diabetes. Currently, glucose monitoring for those interested in their blood glucose levels are confronted with options that are primarily invasive and relatively costly. A growing topic of note is the development of non-invasive monitoring methods for blood glucose. This development holds a significant promise for improvement to the quality of life of a significant portion of the population and is overall met with great enthusiasm from the scientific community as well as commercial interest. This work aims to develop a potential pipeline …