Digital Commons Network^™

Characterizing The Demographic Effects Relative To Race, Gender, And Skin Tone On The Accuracy Of Deep Convolutional Neural Network Based Face Recognition Systems, Krishnapriya Kottakkal Sugathan

Theses and Dissertations

Automated face recognition (AFR) is an important tool used in national security and public safety operations. Numerous cases exist in which AFR was successfully used to search large repositories containing millions of face images, such as identifying a suspect in a mass shooting, a victim of a crime, or even a person attempting to acquire a driver’s license under an assumed identity fraudulently. However, concerns have been raised about how this technology impacts privacy and civil liberty. The studies from the Georgetown Law Center on Privacy and Technology and the American Civil Liberties Union (ACLU) have noted different rates of …

Decisions Cards, Center For Urban Resilience

Module 02: Land Use

No abstract provided.

Control Over Skies: Survivability, Coverage, And Mobility Laws For Hierarchical Aerial Base Stations, Vishal Sharma, Navuday Sharma, Mubashir Husain Rehmani, Haris Pervaiz

Publications

Aerial Base Stations (ABSs) have gained significant importance in the next generation of wireless networks for accommodating mobile ground users and flash crowds with high convenience and quality. However, to achieve an efficient ABS network, many factors pertaining to ABS flight, governing laws and information transmissions must be studied. In this article, multi-drone communications are studied in three major aspects, survivability, coverage, and mobility laws, which optimize the multitier ABS network to avoid issues related to inter-cell interference, deficient energy, frequent handovers, and lifetime. The article includes simulation results of hierarchical ABS allocations for handling a set of users over …

Analysis Of Winter Weather Conditions And Their Relationship To Crashes In Nebraska, John Cecava

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Adverse weather conditions: such as changes in visibility, precipitation, wind speed, temperature, and road surface conditions, substantially impact highway and interstate safety. Therefore, an investigation into the winter weather conditions during highway and interstate crashes in Nebraska was conducted. Crash data were obtained from the Nebraska Department of Transportation (NDOT) for the years 2008 to 2018. In order to separate the non-winter weather related crashes and the winter weather related crashes, six filtrations were applied to make this possible. These filters were based on a few crash parameters: road classification, alcohol, and crash severity, and weather parameters within the crash …

Cyber-Victimization Trends In Trinidad & Tobago: The Results Of An Empirical Research, Troy Smith, Nikolaos Stamatakis

International Journal of Cybersecurity Intelligence & Cybercrime

Cybertechnology has brought benefits to the Caribbean in the form of new regional economic and social growth. In the last years, Caribbean countries have also become attractive targets for cybercrime due to increased economic success and online presence with a low level of cyber resilience. This study examines the online-related activities that affect cybercrime victimization by using the Routine Activity Theory (RAT). The present study seeks to identify activities that contribute to different forms of cybercrime victimization and develop risk models for these crimes, particularly the understudied cyber-dependent crimes of Hacking and Malware. It also aims to explore if there …

South Carolina Biomass Council Project, Samantha Balough, Taryn Long

Goal 1: No Poverty

No abstract provided.

Technological Tethereds: Potential Impact Of Untrustworthy Artificial Intelligence In Criminal Justice Risk Assessment Instruments, Sonia M. Gipson Rankin

Faculty Scholarship

Issues of racial inequality and violence are front and center in today’s society, as are issues surrounding artificial intelligence (AI). This Article, written by a law professor who is also a computer scientist, takes a deep dive into understanding how and why hacked and rogue AI creates unlawful and unfair outcomes, particularly for persons of color.

Black Americans are disproportionally featured in criminal justice, and their stories are obfuscated. The seemingly endless back-to-back murders of George Floyd, Breonna Taylor, and Ahmaud Arbery, and heartbreakingly countless others have finally shaken the United States from its slumbering journey towards intentional criminal justice …

Cybersecurity Legislation And Ransomware Attacks In The United States, 2015-2019, Joseph Skertic

Graduate Program in International Studies Theses & Dissertations

Ransomware has rapidly emerged as a cyber threat which costs the global economy billions of dollars a year. Since 2015, ransomware criminals have increasingly targeted state and local government institutions. These institutions provide critical infrastructure – e.g., emergency services, water, and tax collection – yet they often operate using outdated technology due to limited budgets. This vulnerability makes state and local institutions prime targets for ransomware attacks. Many states have begun to realize the growing threat from ransomware and other cyber threats and have responded through legislative action. When and how is this legislation effective in preventing ransomware attacks? This …

Socastee Interview, Participant #03, March 26, 2021, Jennifer Mokos, Jaime Mccauley

Flood Survivor Interviews

A community member of the Rosewood neighborhood in Socastee is interviewed by a CCU student.

Evaluation Of Manual And Semi-Automated Deep-Seated Landslide Inventory Processes: Willapa Hills, Washington, Tiffany E. Justice

Dissertations and Theses

Recent advances in remote sensing data and technology have allowed for computational models to be designed that successfully extract landforms from the landscape. The goal of this work is to create one such semi-automated model to extract deep-seated landslides located in complex geomorphic terrain. This is accomplished using geographic object-based image analysis (GEOBIA) techniques, considered by leaders in the field of image analysis to have an advantage over traditional automated classification methods. GEOBIA methods can mimic human visual interpretation by including more characteristic features used to assess the relationship between image data and the ground surface such as color reflectance …

The Communicative Effects Of Anonymity Online: A Natural Language Analysis Of The Faceless, Caleb Johnson

Undergraduate Honors Theses

An ever-increasing number of Americans have an active social media

presence online. As of March 2020, an estimated 79% of Americans were active

monthly users of some sort. Many of these online platforms allow users to

operate anonymously which could potentially lead to shifts in communicative

behavior. I first discuss my compilation process of the Twitter Anonymity

Dataset (TAD), a human-classified dataset of 100,000 Twitter accounts that are

categorized by their level of identifiability to their real-world agent. Next, I

investigate some of the structural differences between the classification levels

and employ a variety of Natural Language Processing models and …

A Constructive Direst Security Threat Modeling For Drone As A Service, Fahad E. Salamh, Umit Karabiyik, Marcus Rogers

Journal of Digital Forensics, Security and Law

The technology used in drones is similar or identical across drone types and components, with many common risks and opportunities. The purpose of this study is to enhance the risk assessment procedures for Drone as a Service (DaaS) capabilities. STRIDE is an acronym that includes the following security risks: Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, and Elevation of Privileges. The paper presents a modified STRIDE threat model and prioritize its desired properties (i.e., authenticity, integrity, non-reputability, confidentiality, availability, and authorization) to generate an appropriate DaaS threat model. To this end, the proposed DIREST threat model better meets the …

Improving Text Classification With Semantic Information, Joshua H. White

Theses and Dissertations

The Air Force contracts a variety of positions, from Information Technology to maintenance services. There is currently no automated way to verify that quotes for services are reasonably priced. Small training data sets and word sense ambiguity are challenges that such a tool would encounter, and additional semantic information could help. This thesis hypothesizes that leveraging a semantic network could improve text-based classification. This thesis uses information from ConceptNet to augment a Naive Bayes Classifier. The leveraged semantic information would add relevant words from the category domain to the model that did not appear in the training data. The experiment …

Climate-Informed Prediction And Forecast Modeling Of Installation Total Energy Consumption, Scott C. Weiss

Theses and Dissertations

Climate variability is an external and stochastic factor that causes energy demand uncertainty. Energy managers can use climate-based models to understand future trends of energy demand and to adjust operations, policy, and budgets accordingly. This research focuses on 1) identifying how climate attributes impact energy use, 2) creating a historically informed statistical modeling framework to skillfully predict energy use, and 3) forecasting future changes to energy use and costs, using CMIP5 temperature projections, at the campus level. After synthesizing the existing breadth of research on climate-informed energy modeling, a skillful, unbiased, climate-informed total energy consumption prediction model is developed for …

Ghosts Of Landuse Past: Legacy Effects Of Milldams For Riparian Nitrogen (N) Processing And Water Quality Functions, Shreeram Inamdar, Marc Peipoch, Arthur J. Gold, Evan Lewis, Johanna Hripto, Melissa Sherman, Kelly Addy, Dorothy Merritts, Jinjun Kan, Peter M. Groffman, Robert Walter, Tara L E Trammel

Advanced Science Research Center

Milldams and their legacies have significantly influenced fluvial processes and geomorphology. However, less is known about their effects on riparian zone hydrology, biogeochemistry, and water quality. Here, we discuss the potential effects of existing and breached milldams on riparian nitrogen (N) processing through multiple competing hypotheses and observations from complementary studies. Competing hypotheses characterize riparian zone processes that remove (sink) or release (source) N. Elevated groundwater levels and reducing soil conditions upstream of milldams suggest that riparian zones above dams could be hotspots for N removal via denitrification and plant N uptake. On the other hand, dam removals and subsequent …

A First Look Into Users’ Perceptions Of Facial Recognition In The Physical World, Sovantharith Seng, Mahdi Nasrullah Al-Ameen, Matthew Wright

Computer Science Faculty and Staff Publications

Facial recognition (FR) technology is being adopted in both private and public spheres for a wide range of reasons, from ensuring physical safety to providing personalized shopping experiences. It is not clear yet, though, how users perceive this emerging technology in terms of usefulness, risks, and comfort. We begin to address these questions in this paper. In particular, we conducted a vignette-based study with 314 participants on Amazon Mechanical Turk to investigate their perceptions of facial recognition in the physical world, based on thirty-five scenarios across eight different contexts of FR use. We found that users do not have a …

Csci 40500/77100: Software Engineering, Raffi Khatchadourian

Open Educational Resources

This course is intended to be an introductory survey on the fundamental concepts and principles that underlie current and emerging methods, tools, and techniques for the efficient engineering of high-quality software systems. This may include understanding and appreciating problems in large-scale software development such as functional analysis of information processing systems, system design concepts, timing estimates, documentation, and system testing.

Best Management Practices For Firefighting In The Karstic Edwards (Balcones Fault Zone) Aquifer Of South-Central Texas, Geary M. Schindel, Rudolph A. Rosen

Water Resources Science and Technology Faculty Publications (Archived)

Karst aquifers are vulnerable to contamination from hazardous pollutants that can harm drinking water supplies, species inhabiting aquifers and springs, and other karst water resources. This paper presents best management practices (BMPs) designed for use by first responders, and for use in developing training curricula and tools to assist first responders in protecting karst water resources. Training and tools based on the BMPs will help first responders prevent or reduce runoff of potentially hazardous materials that can rapidly enter an aquifer during firefighting and other responses to emergencies in locations where hazardous materials are stored, such as in retail centers, …

Exploiting Common Senses: Sensory Ecology Meets Wildlife Conservation And Management, Laura K. Elmer, Christine L. Madliger, Daniel T. Blumstein, Chris K. Elvidge, Esteban Ernández-Juricic, Andrij Z. Horodysky, Nicholas S. Johnson, Liam P. Mcguire, Ronald R. Swaisgood, Steven J. Cooke

United States Geological Survey: Staff Publications

Multidisciplinary approaches to conservation and wildlife management are often effective in addressing complex, multi-factor problems. Emerging fields such as conservation physiology and conservation behaviour can provide innovative solutions and management strategies for target species and systems. Sensory ecology combines the study of ‘how animals acquire’ and process sensory stimuli from their environments, and the ecological and evolutionary significance of ‘how animals respond’ to this information. We review the benefits that sensory ecology can bring to wildlife conservation and management by discussing case studies across major taxa and sensory modalities. Conservation practices informed by a sensory ecology approach include the amelioration …

Elaboration And The Logical And Affective Responses To Flood Risk Messages: Elaboration Likelihood Model And Information Processing Perspectives, Ayanna Eastman

Faculty Works

The loss of property and life following tragic events, such as flooding in the United States, demonstrate the frequent ineffectiveness of official risk communication strategies. Few studies have focused on the cognitive processes that impact individuals’ decisions upon receiving risk messages prior to flooding events. This study focuses specifically on the content of public service announcements (PSAs), elaboration and the logical and affective responses elicited by flooding and assesses individualized responses to varying message formats. It does so through the frameworks of the Information Processing Theory (IPT) and Elaboration Likelihood Model (ELM) by examining the impact of flood risk messages …

Evaluating Nuclear Energy As A Component Of U.S. Energy Innovation Systems, Bryce Jones

Electronic Theses and Dissertations

Nuclear energy is contentious in policy discussions that evaluate its role in the current U.S. clean energy innovation system. OECD nations, on average, have begun to reduce their dependence on nuclear energy. However, the United States has remained invested in its nuclear energy infrastructure and the role that it plays within federal research and development. This thesis examines the Neo-Schumpeterian perspective and the National Innovation System’s approach, the economic history of nuclear energy in the United States, and given insight from these factors, discusses the current role of nuclear energy in the U.S. energy innovation system. The objective is to …

Interdisciplinary Thinking: Financial Literacy Crosses Disciplinary Boundaries, Marla A. Sole

Publications and Research

Financial literacy is ideally suited to be integrated into mathematics courses and taught in an interdisciplinary manner. Students learn best and are motivated when tackling real-world meaningful questions. This article shares how elementary mathematics was applied to better understand the debate about raising the minimum wage and the United States National Debt. To serve as a guide for other teachers who wish to incorporate financial literacy into their mathematics courses and take an interdisciplinary approach, this article suggests readings, data sets, and pedagogical practices. Students were engaged and enthusiastic to work on problems that challenged their thinking about financial issues.

Interdisciplinary Thinking: Financial Literacy Crosses Disciplinary Boundaries, Marla A. Sole

Publications and Research

Financial literacy is ideally suited to be integrated into mathematics courses and taught in an interdisciplinary manner. Students learn best and are motivated when tackling real-world meaningful questions. This article shares how elementary mathematics was applied to better understand the debate about raising the minimum wage and the United States National Debt. To serve as a guide for other teachers who wish to incorporate financial literacy into their mathematics courses and take an interdisciplinary approach, this article suggests readings, data sets, and pedagogical practices. Students were engaged and enthusiastic to work on problems that challenged their thinking about financial issues.

Blockchain For A Resilient, Efficient, And Effective Supply Chain, Evidence From Cases, Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …

Emergency Communications Deficiency Locator, Austin Collins

Undergraduate Journal of Mathematical Modeling: One + Two

The Bi-Directional Amplifier (BDA) is the newest edition to Life Safety in the state of Florida. The Florida Fire Prevention Code (NFPA 1) section 11.10.1 states that “In all new and existing buildings, minimum radio signal strength for fire department communications shall be maintained at a level determined by the authority having jurisdiction (Committee NFPA 1: Fire Code 2018). That authority having jurisdiction for our local Tampa Bay area is the Hillsborough County Fire Rescue department and they have posted their own requirements along with the Florida Senate for emergency communication standards. All existing “Hi-rise” buildings, 75 feet tall …

Consumer Preferences And Policy Assessment On Electric Vehicle Adoption In Thailand, Phasiri Manutworakit

Chulalongkorn University Theses and Dissertations (Chula ETD)

Thailand faces a problem about energy consumption and air pollution because of increasing the number of consumption cars. The replacement of combustion cars with battery electric cars can help support sustainable transport and renewable energy on the green transportation in Thailand, but diffusion rates of battery electric cars are still low. Thailand requires efficient policies to increasing electric vehicles adoption. The objectives of the study are to study the current situation of EVs in Thailand, to identify factors affecting purchasing intention of BEVs in Thailand and to propose policy recommendations to stimulate BEV adoption in Thailand. This research was designed …

The Impact Of Covid-19 On Volunteering:Results Of A Survey Of Maine Non-Profits, Sarah Goan

Publications

In response to the disruptions caused by the COVID-19 pandemic, particularly within the nonprofit sector that relies heavily on volunteers, Volunteer Maine sought to assess how volunteer capacity had been affected and what types of support organizations needed to rebuild. To accomplish this, the organization partnered with DIP and SRC to design and administer a statewide survey of nonprofit organizations. The purpose of the study was to understand the pandemic’s impact on the volunteer base, document organizational adjustments to changing conditions, identify innovative responses, and determine how Volunteer Maine and its affiliates could best assist in community recovery efforts. The …

Mining Learner-Friendly Security Patterns From Huge Published Histories Of Software Applications For An Intelligent Tutoring System In Secure Coding, Xu Du, Aparna S. Varde

Department of Computer Science Faculty Scholarship and Creative Works

Security patterns are proven solutions to recurring problems in software development. The growing importance of secure software development has introduced diverse research efforts on security patterns that mostly focused on classification schemes, evolution and evaluation of the patterns. Despite a huge mature history of research and popularity among researchers, security patterns have not fully penetrated software development practices. Besides, software security education has not been benefited by these patterns though a commonly stated motivation is the dissemination of expert knowledge and experience. This is because the patterns lack a simple embodiment to help students learn about vulnerable code, and to …

Deep Learning For Electricity Forecasting Using Time Series Data, Hanan Abdullah Alshehri

Theses, Dissertations and Culminating Projects

The complexity and nonlinearities of the modern power grid render traditional physical modeling and mathematical computation unrealistic. AI and predictive machine learning techniques allow for accurate and efficient system modeling and analysis. Electricity consumption forecasting is highly valuable in energy management and sustainability research. Furthermore, accurate energy forecasting can be used to optimize energy allocation. This thesis introduces Deep Learning models including the Convolutional Neural Network (CNN), the Recurrent neural network (RNN), and Long Short-Term memory (LSTM). The Hourly Usage of Energy (HUE) dataset for buildings in British Columbia is used as an example for our investigation, as the dataset …

Learning Graphs For Object Tracking And Counting, Shengkun Li

Legacy Theses & Dissertations (2009 - 2024)

As important problems in computer vision, object tracking and counting attract increasing amounts of attention in recent years due to its wide range of applications, such as video surveillance, human- computer interaction, smart city. Despite much progress has been made in object tracking and counting with the arriving of deep neural networks (DNN), there still remains much room for improvement to satisfy the real-world applications.