Digital Commons Network^™

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Big Data Applications And Challenges In Giscience (Case Studies: Natural Disaster And Public Health Crisis Management), Amir Masoud Forati

Theses and Dissertations

This dissertation examines the application and significance of user-generated big data in Geographic Information Science (GIScience), with a focus on managing natural disasters and public health crises. It explores the role of social media data in understanding human-environment interactions and in informing disaster management and public health strategies. A scalable computational framework will be developed to model extensive unstructured geotagged data from social media, facilitating systematic spatiotemporal data analysis.The research investigates how individuals and communities respond to high-impact events like natural disasters and public health emergencies, employing both qualitative and quantitative methods. In particular, it assesses the impact of socio-economic-demographic …

Introductory Chemistry, Mona Muzammil

Chemistry Faculty Publications and Presentations

Introductory Chemistry, this edition is designed for a one-semester, introductory or preparatory chemistry course. Students taking this course need to develop problem-solving skills-but they also must see why these skills are important to them and to their world. Introductory Chemistry extends chemistry from the laboratory to the student's world. It motivates students to learn chemistry by demonstrating how it plays out in their daily lives.

This book draws students into the course through engagement and building their foundational knowledge – while introducing new content and resources to help students build critical thinking and problem-solving skills. allowing students flexibility and ensuring …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …

Like Treating The Symptom Rather Than The Cause - The Omission Of Courses Over Terrorism In Nsa Designated Institutions, Ida L. Oesteraas

Journal of Cybersecurity Education, Research and Practice

The National Security Agency (NSA) awards Center of Academic Excellence (CAE) designations to institutions that commit to producing cybersecurity professionals who will work in careers that reduce vulnerabilities in our national infrastructure. A review of the curricula in the 327 institutions and their degree programs reveal that only two programs offer a required course about terrorism. Given the fluid nature of terrorism and its threat to national infrastructure, the omission is concerning. It is recommended that NSA-certified cybersecurity programs begin implementing educational content that aim to teach about this emerging crime and justice issue. One suggestion is to embrace the …

Docker Technology For Small Scenario-Based Excercises In Cybersecurity, Zeinab Ahmed

Theses and Dissertations

This study aims to better prepare students for cybersecurity roles by providing practical tools that bridge the gap between theory and real-world applications. We investigate the role of small scenario-based exercises for students’ understanding of cybersecurity concepts. In particular, we assess the use of Docker technology to deliver training that includes a simple small scenario on html code injection. The effectiveness of scenario-based learning has long been defined and by using SBL, we are going to create hands-on activity that involves the fundamental topics in cybersecurity using Docker technology, allowing students to see the exploitation of the vulnerabilities and defense …

Catching Elusive Depression Via Facial Micro-Expression Recognition, Xiaohui Chen, Tony Tie (T.) Luo

Computer Science Faculty Research & Creative Works

Depression is a common mental health disorder that can cause consequential symptoms with continuously depressed mood that leads to emotional distress. One category of depression is Concealed Depression, where patients intentionally or unintentionally hide their genuine emotions through exterior optimism, thereby complicating and delaying diagnosis and treatment and leading to unexpected suicides. In this article, we propose to diagnose concealed depression by using facial micro-expressions (FMEs) to detect and recognize underlying true emotions. However, the extremely low intensity and subtle nature of FMEs make their recognition a tough task. We propose a facial landmark-based Region-of-Interest (ROI) approach to address the …

Harnessing Large Language Models To Simulate Realistic Human Responses To Social Engineering Attacks: A Case Study, Mohammad Asfour, Juan Carlos Murillo

International Journal of Cybersecurity Intelligence & Cybercrime

The research publication, “Generative Agents: Interactive Simulacra of Human Behavior,” by Stanford and Google in 2023 established that large language models (LLMs) such as GPT-4 can generate interactive agents with credible and emergent human-like behaviors. However, their application in simulating human responses in cybersecurity scenarios, particularly in social engineering attacks, remains unexplored. In addressing that gap, this study explores the potential of LLMs, specifically the Open AI GPT-4 model, to simulate a broad spectrum of human responses to social engineering attacks that exploit human social behaviors, framing our primary research question: How does the simulated behavior of human targets, based …

Understanding The Use Of Artificial Intelligence In Cybercrime, Katalin Parti, Thomas Dearden, Sinyong Choi

International Journal of Cybersecurity Intelligence & Cybercrime

Artificial intelligence is one of the newest innovations which offenders exploit to satisfy their criminal desires. Although understanding cybercrime that is associated with this relatively new technology is essential in developing proper preventive measures, little has been done to examine this area. Therefore, this paper provides an overview of the two articles featured in the special issue of the International Journal of Cybersecurity Intelligence and Cybercrime, one about deepfakes in the metaverse and the other about social engineering attacks. The articles were written by the winners of the student paper competition at the 2023 International White Hat Conference.

Victimization By Deepfake In The Metaverse: Building A Practical Management Framework, Julia Stavola, Kyung-Shick Choi

International Journal of Cybersecurity Intelligence & Cybercrime

Deepfake is digitally altered media aimed to deceive online users for political favor, monetary gain, extortion, and more. Deepfakes are the prevalent issues of impersonation, privacy, and fake news that cause substantial damage to individuals, groups, and organizations. The metaverse is an emerging 3-dimensional virtual platform led by AI and blockchain technology where users freely interact with each other. The purpose of this study is to identify the use of illicit deep fakes which can potentially contribute to cybercrime victimization in the metaverse. The data will be derived from expert interviews (n=8) and online open sources to design a framework …

On Computing Optimal Repairs For Conditional Independence, Alireza Pirhadi

Electronic Thesis and Dissertation Repository

This thesis focuses on the concept of Conditional Independence (CI) and its testing, which holds immense significance across various fields, including economics, social sciences, and biomedical research. Notably, within computer science, CI has become an integral part of building probabilistic and causal models. It aids efficient inference and plays a key role in uncovering causal relationships.

The primary aim of this thesis is to broaden the scope of CI beyond its testing aspect. We introduce the pioneering problem of data repair, designed to adhere to particular CI constraints. The value and pertinence of this problem are highlighted through two contrasting …

The Emergence Of Convergence, Shana M. Sundstrom, David G. Angeler, Jessica G. Ernakovich, Jorge H. Garcia, Joseph A. Hamm, Orville Huntington, Craig R. Allen

Faculty Publications

Science is increasingly a collaborative pursuit. Although the modern scientific enterprise owes much to individuals working at the core of their field, humanity is increasingly confronted by highly complex problems that require the integration of a variety of disciplinary and methodological expertise. In 2016, the U.S. National Science Foundation launched an initiative prioritizing support for convergence research as a means of “solving vexing research problems, in particular, complex problems focusing on societal needs.” We discuss our understanding of the objectives of convergence research and describe in detail the conditions and processes likely to generate successful convergence research. We use our …

Anonymity And Gender Effects On Online Trolling And Cybervictimization, Gang Lee, Annalyssia Soonah

Journal of Cybersecurity Education, Research and Practice

The purpose of this study was to investigate the effects of the anonymity of the internet and gender differences in online trolling and cybervictimization. A sample of 151 college students attending a southeastern university completed a survey to assess their internet activities and online trolling and cybervictimization. Multivariate analyses of logistic regression and ordinary least squares regression were used to analyze online trolling and cybervictimization. The results indicated that the anonymity measure was not a significant predictor of online trolling and cybervictimization. Female students were less likely than male students to engage in online trolling, but there was no gender …

An Ml Based Digital Forensics Software For Triage Analysis Through Face Recognition, Gaurav Gogia, Parag H. Rughani

Journal of Digital Forensics, Security and Law

Since the past few years, the complexity and heterogeneity of digital crimes has increased exponentially, which has made the digital evidence & digital forensics paramount for both criminal investigation and civil litigation cases. Some of the routine digital forensic analysis tasks are cumbersome and can increase the number of pending cases especially when there is a shortage of domain experts. While the work is not very complex, the sheer scale can be taxing. With the current scenarios and future predictions, crimes are only going to become more complex and the precedent of collecting and examining digital evidence is only going …

Institute For Global Health And Development : Issue 5 - July 2023, Institute For Global Health And Development

IGHD Newsletter

• Research Highlights
• Key Publications
• IGHD in the News
• Webinars, Academics & Conferences
• ‘Choice’ Programme - Technical Advisory Group
• Welcome New Team Members
• Mark your Calendars: Upcoming Event
• Congratulations Team IGHD
• Collaborate With Us

Designing Human-Centered Algorithms For The Public Sector: A Case Study Of The U.S. Child Welfare System, Devansh Saxena

Dissertations (1934 -)

Public sector agencies in the United States are increasingly seeking to emulate business models of the private sector centered in efficiency, cost reduction, and innovation through the adoption of algorithmic systems. These data-driven systems purportedly improve decision-making; however, the public sector poses its own unique challenges where policies, practices, and organizational constraints mediate all decisions. Algorithms that do not account for these pertinent aspects of professional practice frustrate practitioners, diminish the quality of human discretionary work, and amplify biases in decision-making. A human-centered research agenda can help us develop algorithms centered in social-ecological theories that support the decision-making processes of …

Crosssections, Summer 2023, University Of Northern Iowa. Department Of Physics.

CrossSections

Contents:

A Message from the Department Head --- 1
Department Happenings --- 2
Faculty Profile: Andrew Stollenwerk --- 7
Student Profile: Lukas Stuelke --- 8
Student Focus: Jenna Heinen --- 11
Physics Education --- 13
Alumni Profile: Sam Prophet --- 14
Alumni News: Shawn Poellet --- 15
New Physics: Quantum Mechanics Must Be Complex --- 17

Identification Of Different Hair Dyes In Dyed Hair Using Attenuated Total Reflectance (Atr Ft-Ir), Surface Enhancing Raman Spectroscopy (Sers) Techniques, Nicholas Lovera

Student Theses

This investigation compares the ability of Attenuated Total Reflection Fourier Transfer Infrared Spectroscopy (ATR FT-IR) and Surface Enhance Raman Spectroscopy (SERS) to identify and differentiate different hair dye brands on dyed hair samples. Hair is a common type of trace evidence found at crime scenes and can provide numerous information through forensic hair analysis. Cosmetic hair treatment such as dying the hair different colors has grown and became popular, thus it can be a very common type of trace evidence. This study can provide a forensic scientist an additional method for analyzing dyed hair samples. The goal was to compare …

Weird Winter Weather In The Anthropocene: How Volatile Temperatures Shape Violent Crime, Christopher Thomas, Kevin T. Wolff

Publications and Research

Purpose: Current evidence suggests volatile temperatures are becoming more common because of climate change and can be expected to become even more frequent in the future. By focusing on recent temperature variability, we attempt to estimate one important dimension of the impact of climate change on violent crime. We also explore whether sudden upward temperature anomalies have stronger positive impacts on violent crime in the coldest months of the year, as routine activities are likely to change more drastically during this period.

Methods: This study explores the association between sudden temperature anomalies (both upward and downward) and the daily incidence …

Analysis Of Polymer-Coated Bullets Using Spectroscopic Methods, Liana R. Albano

Student Theses

Polymer-coated bullets have gained popularity because they can reduce the user’s exposure to heavy metals in the ammunition. The synthetic jacket, which surrounds the lead core, is advantageous because it prevents metal-on-metal contact between the bullet and the bore. A challenge for firearms identification is that polymer-coated bullets do not retain unique markings that can be used to identify the gun, the way standard metal-coated bullets do. However, metal-coated bullets will result in a similar challenge if the bullet is too deformed once it is recovered. Another issue is that the composition of the polymer coating was never disclosed by …

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 …

Investigating English-Language Dialect-Adjusted Models, Samiha Datta

Computer Science Senior Theses

This thesis describes several approaches to better understand how large language models interpret different dialects of the English language. Our goal is to consider multiple contexts of textual data and to analyze how English-language dialects are realized in them, as well as how a variety of machine learning techniques handle these differences. We focus on two genres of text data: news and social media. In the news context, we establish a dataset covering news articles from five countries and four US states and consider language modeling analysis, topic and sentiment distributions, and manual analysis before performing nine experiments and evaluating …

Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie

Dissertations

Mental health is quickly becoming a major policy concern, with recent data reporting increasing and disproportionately worse mental health outcomes, including anxiety, depression, increased substance abuse, and elevated suicidal ideation. One specific population that is especially high risk for these issues is the military community because military conflict, deployment stressors, and combat exposure contribute to the risk of mental health problems.

Although several pharmacological approaches have been employed to combat this epidemic, their efficacy is mixed at best, which has led to novel nonpharmacological approaches. One such approach is Operation Surf, a nonprofit that provides nature-based programs advocating the restorative …

Modeling The Dynamics Of Alcohol-Marijuana Co-Abuse In Virginia, Ana L. Vivas-Barber, James Tipton, Sujan Pant, Anne Fernando

Biology and Medicine Through Mathematics Conference

No abstract provided.

Drug Ideologies Of The United States, Macy Montgomery

Helm's School of Government Conference - American Revival: Citizenship & Virtue

The United States has been increasingly creating lenient drug policies. Seventeen states and Washington, the District of Columbia, legalized marijuana, and Oregon decriminalized certain drugs, including methamphetamine, heroin, and cocaine. The medical community has proven that drugs, including marijuana, have myriad adverse health side effects. This leads to two questions: Why does the United States government continue to create lenient drug policies, and what reasons do citizens give for legalizing drugs when the medical community has proven them harmful? The paper hypothesizes that the disadvantages of drug legalization outweigh its benefits because of the numerous harms it causes, such as …

Rattus Norvegicus As A Biological Detector Of Clandestine Remains And The Use Of Ultrasonic Vocalizations As A Locating Mechanism, Gabrielle M. Johnston

Master's Theses

In investigations, locating missing persons and clandestine remains are imperative. One way that first responder and police agencies can search for the remains is by using cadaver dogs as biological detectors. Cadaver dogs are typically used due to their olfactory sensitivity and ability to detect low concentrations of volatile organic compounds produced by biological remains. Cadaver dogs are typically chosen for their stamina, agility, and olfactory sensitivity. However, what is not taken into account often is the size of the animal and the expense of maintaining and training the animal. Cadaver dogs are typically large breeds that cannot fit in …

Fair Enough: Standardizing Evaluation And Model Selection For Fairness Research In Nlp, Xudong Han, Timothy Baldwin, Trevor Cohn

Natural Language Processing Faculty Publications

Modern NLP systems exhibit a range of biases, which a growing literature on model debiasing attempts to correct. However, current progress is hampered by a plurality of definitions of bias, means of quantification, and oftentimes vague relation between debiasing algorithms and theoretical measures of bias. This paper seeks to clarify the current situation and plot a course for meaningful progress in fair learning, with two key contributions: (1) making clear inter-relations among the current gamut of methods, and their relation to fairness theory; and (2) addressing the practical problem of model selection, which involves a trade-off between fairness and accuracy …

Developing A Risk Assessment Instrument For Immigration Cases Under Federal Supervision, Mayra Eydie Pacheco

Open Access Theses & Dissertations

No abstract provided.

Gentrification And Crime In The Twin Cities: Insights And Challenges Through A Statistical Lens, Erin G. Franke

Mathematics, Statistics, and Computer Science Honors Projects

Gentrification is a complex process of urban redevelopment that typically involves an in-migration of educated people to neighborhoods experiencing a period of disinvestment. While gentrification is widely regarded for its potential to displace long-time businesses and residents of the neighborhood, its impact on crime is highly controversial. There is not a consensus on the relationship between gentrification and crime across criminological theory and past statistical studies have also shown contradictory results. Measuring gentrification on the tract level with census data, we seek to understand gentrification’s relationship with violent crime and theft in the Twin Cities. Using a Poisson model with …

Towards Explainable Ai: Predicting Linear And Nonlinear Feature Relations Of Datasets, Nimmy Chhaganbhai Patel

Theses and Dissertations

Artificial Intelligence (AI) makes critical decisions in an opaque way without explaining the reasoning behind them. Decision support systems are often built as black boxes. This has generated interest in Explainable AI (XAI), an area of research that explains AI algorithms and provides more insight into their internal decision-making process. Advancements in XAI have enhanced machine learning (ML) models’ interpretability, explainability, and transparency. Additionally, there has been speculation on whether it is possible to predict the type of dataset used in the model by analyzing the results. In this research, we proposed a methodology for determining the linearity or non-linearity …