Undergraduate Research Posters 2024

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  The Origin of ISIS and its Founding Father

  Nadia Cruz

  This paper examines the life of Abu Musab al-Zarqawi, the founder of ISIS, and the events that led up to him becoming a terrorist. United States officials have implicated al-Zarqawi for 700 deaths during the invasion of Iraq in 2004, the number rising to the thousands since. There is no denying the violent nature of his acts of terror, but one must look at his history and rise to infamy to determine why he went down this path of radicalism. The methods used to delve into al-Zarqawi’s history and feats consist mainly of intensive research, reading texts such as ‘The New Face of Al-Qaeda’ by Jean-Charles Brisard, utilizing articles and scholarly journals, and watching multiple documentaries retelling the history of ISIS and how his actions impacted the world. It has been found that a part of al-Zarqawi’s dramatic lifestyle was ultimately a result of religious radicalism, political instability in the region, and being raised in war zones under oppressive governments. Al-Zarqawi was raised in an area and in a time of intense conflict between the Islamic and Western worlds, on top of civil wars and regional instability. His rise started with him abandoning his old religious views of Salafi Islam, then climbing the ranks of Al-Qaeda under Osama Bin Laden. He finally became an independent force and contributed to some of the worst acts of terror the world has seen. There are multiple circumstances that contributed to al-Zarqawi’s rise to power and modes of violence including political instability, civil war, the conflict between the West and the Islamic world, and the rampant religious radicalism in the region.

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  Generating a Dataset for Deep Reinforcement Learning

  Lewis Davis

  Reinforcement Learning (RL), is a subfield of Machine Learning where a computational agent interacts with the environment, learning an optimal course of action by trial and error. Deep Reinforcement Learning (Deep RL) uses neural networks to learn to perform tasks directly from raw data, such as images or text, without hard-coding task-specific knowledge. In this context, datasets are collections of data used as a single unit for analytic and prediction purposes. Datasets are made for specific tasks with raw data specific to the task or machine being used. There is a need for increasingly robust datasets to increase the use and effectiveness of these tasks. The purpose of this work is to generate a dataset designed specifically for Opentrons Flex, a pipetting robot designed for high throughput and laboratory experiments. For this purpose, an attempt to generate a dataset using Opentrons API, and its protocols was done. Gazebo was utilized to simulate and acquire image data for Deep RL. However, this action was limited by the lack of documentation and files available to run gazebo simulations with. Opentrons API has no documentation that works to recreate its machines in gazebo’s virtual environment; without this, simulations for which data can be extracted cannot be done.

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  A Guide to Ensemble Styled Machine Learning with JavaScript and Brain.js

  Michael Angelo De La Cruz Ortiz

  Currently, there are few comprehensive guides with detailed development procedures by which brain.js is used for creating ANNs (Artificial Neural Networks) that can recognize patterns in large amounts of data (big data) in sequential and multi-dimensional form.This work is a guide detailing the development of AI (Artificial Intelligence) using brain.js, a library of features which allow for the high-level development of ANNs, all purely written in the JavaScript programing language. It details an Ensemble Styled ML (Machine Learning) procedure with brain.js. The methods in this guide include: the creation of a set of sequential eight-digit binary patterns, its conversion into a JSON format dataset, the partitioning of the dataset, the set-up of a server side node.js JavaScript environment with the ES6 modules importing system - including the brain.js library in the environment - using brain.js to implement LSTM Time Step ANN models in JavaScript, individually training the models on each dataset partition, serializing the models, creating an averaging and voting algorithm which groups and analyzes the collective output of all serialized models upon input and lastly analyzing the model’s performance upon input of trained and untrained data. The goal of this guide is to provide useful basic technical information that is accessible to the inexperienced and yet provide a scalable procedure which the experienced can leverage for more complex ML applications.

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  Thought Quantification with a Single-Channel EEG BCI System

  Michael Angelo De La Cruz Ortiz

  BCI (Brain-Computer Interfaces) implement various aspects of brain activity monitoring and analysis technologies. EEG (electroencephalogram) has proven to be a viable way to safely probe electromagnetic brain activity through non-surgical means. However, these devices are not viable for everyday consumer use, specifically amongst people with disabilities. This project aims to develop a means of processing data to optimize the use of a single-channel EEG. For this purpose, the output of a mind flex headset by Mattel was processed to quantify six different thought commands (up, down, left, right, forward, backward) from one subject. The data was analyzed via a computational PCA (Principal Component Analysis) method to render scatter graphs. It was found that each thought created different patterns. Further analysis would be needed to further characterize the difference in patterns.

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  Examining the Relationship Between Intimate Partner Violence, Trauma, Attachment, and Help-seeking Self-Efficacy

  Dalton Hundt

  Intimate partner violence (IPV) negatively affects victims. However, traumatic experiences and anxious attachment are often overlooked in IPV studies. This study examined effectiveness of relationship perpetration between various types of IPV victimization, the perception of one’s ability to help-seek as a victim and a bystander, and how traumatic experiences and anxious attachment can play a role in the ability to help-seek. The data for this project was obtained from the Dating in Young Adults Study (studies 1 and 2). This secondary, archival dataset that examined relationships in young adults ages 18-30, contained questionnaires, self-report measures of IPV, and a qualitative interview. The total sample was 190 participants, 92 individuals from the DYAD 1 study and 98 individuals from the DYAD 2 study. Results indicated that when individuals report being less capable of help-seeking as a victim or as a bystander, the overall and all subtypes of IPV victimization scores were reported as the same. Secondly, based on existing studies of help-seeking, regardless of gender, individuals report the same levels of self-efficacy to engage in help-seeking as both a victim and a bystander. Lastly, in consideration of trauma, anxious attachment, and IPV victimization, each factor uniquely impacted help-seeking behavior above and beyond other subtypes.

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  The Impact of Adverse Childhood Experiences on Child Development and Communication: A Systematic Review of the Literature

  Tyler Johnson

  Adverse childhood experiences (ACEs) can be defined as possible early childhood traumatic and stressful events that could result from a variety of sources including abuse, neglect, toxic stress, or household dysfunction. The original ACE study described ten ACEs. In the United States, 34.8 million children are estimated to have been exposed to more than one adverse childhood experience. ACEs have been studied by several healthcare professionals. However, there is very little work investigating ACEs in the Communication Sciences and Disorders (CSD; Speech and Hearing) literature. This study sought to explore the impact of ACEs on communication development, and behavior, and whether or not culturally and linguistically diverse children are at higher risk of experiencing ACEs. It was conducted using a systematic review of the literature of over 40 articles. It was concluded that while ACEs occur in all tiers of society, culturally and linguistically diverse children do appear to be at a higher risk of experiencing ACEs. ACEs are also associated with emotional problems such as depression and anxiety as well as aggression and bullying. Children who experience ACEs are at a higher risk of social language delay and reduced vocabulary development. Additional research is needed to understand how to help clients who have experienced ACEs and are being treated for a communication disorder.

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  The Examination of the Forbidden Fruit

  Dominique Ryder

  The dominant subculture in each region significantly influences long-term behavioral changes. Strict social norms can result in deeply internalized punishment. Since enculturation and acculturation play a significant role in shaping established and accepted social norms, a complex interplay of sociocultural phenomena can be held accountable. Anthropology, sociology, and religious studies provide an interdisciplinary framework that can help explain how religion influences systemic discrimination. This study utilized interview techniques, short-term ethnography, and grounded theory methodology to collect data for an innovative framework and form a coherent theory to support this framework. The study focused on transgender and non-binary individuals in Northeast Ohio and their perspectives on how their religion, the religious views of the dominant culture, and their upbringing influence different aspects of their lives and identities. These findings will be analyzed in the context of a local case study on the legislative process affecting historically marginalized populations, specifically those surrounding the HB 68 issue. This research aims to promote interdisciplinary perspectives, establish an innovative framework with a cohesive, unifying theory for future research, and emphasize the relationship between social norms and systemic discrimination.

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  Assessment of the Intersectionality of Muslim and Queer Identities

  Elisha Sledge

  Queerness can be a taboo subject in many Muslim communities. However, little academic research explores the intersection between queer and Muslim identities. This project employs an audio-ethnographic approach to explore the intersections of familial judgment and sexual identity among Queer Muslims. We believe that familial judgment plays a critical role in shaping the experiences of Queer Muslims, potentially leading to heightened levels of anxiety, depression, and suicidal thoughts and attempts because of anticipated familial rejection. By integrating ethnographic methods with audio recordings, this study seeks to capture the nuanced personal narratives and lived experiences of individuals identifying as both Queer and Muslim. Through in-depth interviews and reflective audio documentation, the study aims to address the research question: Are Queer Muslims hesitant to embrace their sexual identities due to judgment from families rather than societal disapproval? Preliminary findings indicate that the fear of familial rejection significantly contributes to internalized stigma and emotional turmoil within this community. They also suggest that the psychological burden associated with familial expectations may be more impactful than societal or communal scrutiny. This work highlights the necessity of creating supportive networks that address the challenges faced by Queer Muslims, ultimately advocating for greater awareness and understanding within both familial and broader societal contexts. It also showcases the necessity of creating supportive networks that address the challenges faced by Queer Muslims, ultimately advocating for greater awareness and understanding within both familial and broader societal contexts.