Social and Behavioral Sciences Commons^™

From Negative To Positive Algorithm Rights, Cary Coglianese, Kat Hefter

All Faculty Scholarship

Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we …

Smart Home Forensics: Identifying Ddos Attack Patterns On Iot Devices, Samuel Ho, Hope Greeson, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Smart homes are becoming more common as more people integrate IoT devices into their home environment. As such, these devices have access to personal data on their homeowners’ networks. One of the advantages of IoT devices is that they are compact. However, this limits the incorporation of security measures in their hardware. Misconfigured IoT devices are commonly the target of malicious attacks. Additionally, distributed denial-of-service attacks are becoming more common due to applications and software that provides users with easy-to-use user interfaces. Since one vulnerable device is all an attacker needs to launch an attack on a network, in regards …

Detection Of Overlapping Passive Manipulation Techniques In Image Forensics, Gianna S. Lint, Umit Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

With a growing number of images uploaded daily to social media sites, it is essential to understand if an image can be used to trace its origin. Forensic investigations are focusing on analyzing images that are uploaded to social media sites resulting in an emphasis on building and validating tools. There has been a strong focus on understanding active manipulation or tampering techniques and building tools for analysis. However, research on manipulation is often studied in a vacuum, involving only one technique at a time. Additionally, less focus has been placed on passive manipulation, which can occur by simply uploading …

A Low-Cost Machine Learning Based Network Intrusion Detection System With Data Privacy Preservation, Jyoti Fakirah, Lauhim Mahfuz Zishan, Roshni Mooruth, Michael L. Johnstone, Wencheng Yang

Annual ADFSL Conference on Digital Forensics, Security and Law

Network intrusion is a well-studied area of cyber security. Current machine learning-based network intrusion detection systems (NIDSs) monitor network data and the patterns within those data but at the cost of presenting significant issues in terms of privacy violations which may threaten end-user privacy. Therefore, to mitigate risk and preserve a balance between security and privacy, it is imperative to protect user privacy with respect to intrusion data. Moreover, cost is a driver of a machine learning-based NIDS because such systems are increasingly being deployed on resource-limited edge devices. To solve these issues, in this paper we propose a NIDS …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

Digital Searching: A Grounded Theory Study On The Modern Search Experience, Nicolas Armando Parés

Electronic Theses and Dissertations

This Grounded theory study explores US adults' modern information search process as they pursue information through digital search user interfaces and tools. To study the current search process, a systematic grounded theory methodology and two data collection methods, a think-aloud protocol and semi-structured interviews, are used to develop the theory. The emerging theory addressed two tightly connected research questions that asked, “What is the process by which humans search and discover information?” and “What is the process by which search and discovery interfaces and tools support the modern search process?”

The study collects participant data from US adults who have …

Forging Ahead And Adapting To Change: A Review Of The Initiatives Of The Isprs Student Consortium, Sheryl Rose C. Reyes, Charmaine A. Cruz

SOSE Affiliate: Manila Observatory

The International Society for Photogrammetry and Remote Sensing Student Consortium (ISPRS SC) is an international organization that represents a constituency of the students and the young professionals with common interests and goals within ISPRS in the areas of photogrammetry, remote sensing and spatial information science. The ISPRS SC Board of Directors strengthened the organization’s foundations and increased its engagement in the Society from 2016 to 2022. Given the current global health crisis, selected members of the Board of Directors continued to serve in the ISPRS SC for a two-year extension and developed creative strategies in navigating the new normal. Building …

Service Contracting As A Policy Response For Public Transport Recovery During The Covid-19 Pandemic: A Preliminary Evaluation, Varsolo Sunio, Wilhansen Joseph Li, Joemier Pontawe, Albert Dizon, Joel Bienne Valderrama, Agnes Robang

Department of Information Systems & Computer Science Faculty Publications

We examine and assess the service contracting (SC) program implemented for the first time in Metro Manila, Philippines as a response to the impact of the pandemic on road-based public transport sector. We develop an evaluation framework, consisting of three indicators: social amelioration, increase in transport supply and performance improvement. These indicators are the purported objectives of SC. Using a mix of qualitative and quantitative methods, our evaluation suggests that although SC has brought positive impact in terms of the first two indicators, there is no robust evidence so far that may suggest that SC has improved the performance of …

Mis-Specification Of Functional Forms In Growth Mixture Modeling: A Monte Carlo Simulation, Richa Ghevarghese

Electronic Theses and Dissertations

Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are distinct to each subgroup, and form the core assumptions of the model. Therefore, the accuracy of the assumed functional forms of growth strongly influences substantive research and theories of growth. While there is evidence of mis-specified functional forms of growth in GMM literature, the weight of this violation has been largely overlooked. Current solutions to circumvent …

Bicycles And Transit: Weather Or Not: A Study On The Effect Of Weather And Air Quality On Bicycle-Transit, Bicycle, Rail Transit Counts In Denver, Christiana M. Fairfield

Electronic Theses and Dissertations

The movement of people and goods within metropolitan areas is critically important to the operational efficiency and functionality of cities. This study explores the influence of local weather conditions and the air quality index on bicycle-transit user in Denver, Colorado. Based on bicycle-transit having two key components, bicycle and transit, the effect of local weather conditions and the air quality index is also explored with bicycle use and rail-transit usage. Key findings include: (1) the most significant variable across all three modes is temperature, (2) for bicycle-transit and bicycle use, there is a steady increase in ridership as temperatures increase …

A Lightweight Reliably Quantified Deepfake Detection Approach, Tianyi Wang, Kam Pui Chow

Annual ADFSL Conference on Digital Forensics, Security and Law

Deepfake has brought huge threats to society such that everyone can become a potential victim. Current Deepfake detection approaches have unsatisfactory performance in either accuracy or efficiency. Meanwhile, most models are only evaluated on different benchmark test datasets with different accuracies, which could not imitate the real-life Deepfake unknown population. As Deepfake cases have already been raised and brought challenges at the court, it is disappointed that no existing work has studied the model reliability and attempted to make the detection model act as the evidence at the court. We propose a lightweight Deepfake detection deep learning approach using the …

A Human-Centered Approach To Improving Adolescent Online Sexual Risk Detection Algorithms, Afsaneh Razi

Electronic Theses and Dissertations, 2020-2023

Computational risk detection has the potential to protect especially vulnerable populations from online victimization. Conducting a comprehensive literature review on computational approaches for online sexual risk detection led to the identification that the majority of this work has focused on identifying sexual predators after-the-fact. Also, many studies rely on public datasets and third-party annotators to establish ground truth and train their algorithms, which do not accurately represent young social media users and their perspectives to prevent victimization. To address these gaps, this dissertation integrated human-centered approaches to both creating representative datasets and developing sexual risk detection machine learning models to …

Reticular Design And Synthesis Of Metal-Organic Frameworks With Targeted Emergent Properties, David Fairchild

Electronic Theses and Dissertations, 2020-2023

The research presented in this dissertation describes the design and synthesis of substitutional-solid-solution-based multivariate metal-organic frameworks (SSS-based MTV MOFs) with functionalized organic linkers to study their emergent properties in the crystalline solid state. The synthetic versatility and tunability of organic chemistry coupled with the predictable organization of inorganic structures enables MTV MOF systems to further the fundamental understanding of structure-composition-property relationships for the targeted design of applied materials due to their ability to control the structure, composition, and property independently. To begin, a set of terphenyl linkers with varied steric and electronic properties were crystallized as a family of UiO-type …

Understanding The Impacts Of Urban Agriculture In Gentrifying Neighborhoods In Denver, Kate Johnson

Electronic Theses and Dissertations

Urban Agriculture is prominent in cities across the United States and has been studied in relation to food security, sustainability, and gentrification. Urban agriculture is context specific and can include individual gardens, community gardens, guerilla gardening, and urban farms. Urban agriculture is a product of the community it is based in, depending on politics, history, and social environments. For these reasons, the relationship between urban agriculture and the community is an area where more research is needed. This thesis explores the role visible gardens play in community building, sustainability, and food security in gentrifying neighborhoods in Denver. Through qualitative methods …

Exploring The Existing And Unknown Side Effects Of Privacy Preserving Data Mining Algorithms, Hima Bindu Sadashiva Reddy

CCE Theses and Dissertations

The data mining sanitization process involves converting the data by masking the sensitive data and then releasing it to public domain. During the sanitization process, side effects such as hiding failure, missing cost and artificial cost of the data were observed. Privacy Preserving Data Mining (PPDM) algorithms were developed for the sanitization process to overcome information loss and yet maintain data integrity. While these PPDM algorithms did provide benefits for privacy preservation, they also made sure to solve the side effects that occurred during the sanitization process. Many PPDM algorithms were developed to reduce these side effects. There are several …

The Global Impact Of Covid-19 And Tourism On Conservation Rangers' Guardianship Capabilities, Zachary Bockler

Honors Undergraduate Theses

This thesis explores how the COVID-19 pandemic has impacted wildlife rangers with an emphasis on the influences of tourism rates. Two sets of data are used: one is a survey of rangers around the world and the other looks at global governmental tourism data. While coming from a routine activities perspective, the problem of decreased capable guardianship becomes apparent in the form of massively decreased tourism arrivals and troubling ranger perceptions. This data allows for the establishment of tourism trends and changes during COVID. The findings of this thesis link the downturn in tourism with impacts on formal and informal …

Social Disorganisation Theory And Violent Crime: A Spatial-Econometric Analysis Of Chicago And Sydney, Anthony N. Greening

Theses: Doctorates and Masters

The spatialisation of violent crime is explored in two large case studies, Chicago and Sydney, using spatial econometric methods and macro-sociological variables derived from Social Disorganisation Theory.

Social Disorganisation Theory (SDT) is introduced in terms of its formulation in response to highly specific conditions arising in Chicago, as well as its adoption of methodological and theoretical developments from existing traditions. This specificity belies its breadth of application and enduring presence in criminology. With “Social Disorganisation Theory” hosting a wealth of highly nuanced academic dialogue conducted under its banner, current incarnations of SDT appear as branches on an evolutionary tree. This …

Exploring The Potential Of Online Education And College Students' Connection To Nature, Michael Weinstein

Antioch University Dissertations & Theses

There is limited research examining the efficacy of online delivery for experiential, field-based, interdisciplinary coursework in environmental education geared towards undergraduate students, and how connection to nature can be understood through the theory of emerging adulthood. This research employed a convergent mixed methods approach to explore the experiences of 11 undergraduate students enrolled in an online, introductory ecology course, and how their experience of connection to nature was influenced through the course, technology-mediated nature embedded within the course, and how their identities as emerging adults were impacted by their connection to nature. Quantitative methods employed included pre/post surveys, while qualitative …

Digital Forensic Investigation, Dejuan Green

Cybersecurity Undergraduate Research Showcase

Finding, acquiring, processing, analyzing, and reporting data on electronically stored data is the main goal of the forensic science discipline known as "digital forensics." Nearly all illegal acts include the use of electronic evidence, making digital forensics support essential for law enforcement investigations. Furthermore, digital forensics is very important to cases aiding in many cases and can lead to saving lives/ victims and locking up criminals. A wide range of devices, including laptops, cellphones, remote storage, unmanned aerial systems, shipborne equipment, and more, can be used to gather electronic evidence. [2] Digital forensics' major objective is to take data from …

Pathways Forward For Onshore Wind Energy In The State Of Maryland: A Gis Multi-Criteria Analysis, George Pisano

Geography and the Environment: Graduate Student Capstones

This study examines pathways forward for onshore wind energy in the State of Maryland. To meet its decarbonization goals, Maryland needs to quickly transition its electric grid away from fossil fuels. The state is currently in the process of developing offshore wind farms that have the potential to represent a significant source of renewable energy. However little progress has been made in expanding Maryland’s onshore wind energy production capacity. Using a multi-criteria GIS analysis, this study found that there is a limited but not inconsiderable area in the state that could be suitable for wind farms of varying scales that …

Civiic: Cybercrime In Virginia: Impacts On Industry And Citizens Final Report, Randy Gainey, Tancy Vandecar-Burdin, Jay Albanese, Thomas Dearden, James Hawdon, Katalin Parti

Sociology & Criminal Justice Faculty Publications

[First paragraph] Victimization from cybercrime is a major concern in Virginia, the US, and the world. As individuals and businesses spend more time online, it becomes increasingly important to understand cybercrime and how to protect against it. Such an understanding is dependent on valid and reliable baseline data that identifies the specific nature, extent, and outcomes of cybercrime activity. A better understanding of cybercrime activity is needed to target and prevent it more effectively, minimize its consequences, and provide support for both individual and corporate victims. Before that can occur, however, better baseline data are required, and this project was …

Frameless-Finding And Refining A Sampling Frame For Surveying Recreational Fisheries: Lessons From Estimating Swedish Harvest Of Western Baltic Cod, Hege Sande, Nuno Prista, Annica De Groote, Michele Casini, Cynthia Jones, Andreas Sundelöf

OES Faculty Publications

To achieve sustainable fisheries, advice to management should be based on reliable science and unbiased data. Attaining quality data (i.e. precise and unbiased) on recreational fishing can be challenging, particularly when prior knowledge of the sector is limited and a proper sample frame of recreational fishers or vessels does not exist. In this study, a registry of access points was constructed for the Swedish south–west coast and used as a spatial sample frame in determining both effort and catches of the private boat fishery. Sampling dates, times for sampling, and access points visited were selected using probabilistic methods, ensuring unbiased …

Microbial Labilization And Diversification Of Pyrogenic Dissolved Organic Matter, Aleksandar I. Goranov, Andrew S. Wozniak, Kyle W. Bostick, Andrew R. Zimmerman, Siddhartha Mitra, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the increased occurrence of wildfires around the world, interest in the chemistry of pyrogenic organic matter (pyOM) and its fate in the environment has increased. Upon leaching from soils by rain events, significant amounts of dissolved pyOM (pyDOM) enter the aquatic environment and interact with microbial communities that are essential for cycling organic matter within the different biogeochemical cycles. To evaluate the biodegradability of pyDOM, aqueous extracts of laboratory-produced biochars were incubated with soil microbes, and the molecular changes to the composition of pyDOM were probed using ultrahigh-resolution mass spectrometry (Fourier transform–ion cyclotron resonance–mass spectrometry). Given that solar irradiation …

Taming The Data In The Internet Of Vehicles, Shahab Tayeb

Mineta Transportation Institute

As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …

Impact Of Prairie Restoration On Geochemistry And Microbial Communities In Groundwater, Kayla Koenig

Graduate Research Theses & Dissertations

Prairie restoration is important for reversing the loss of biodiversity and repairing ecosystem functions humanity is dependent on diverse ecosystems. This study looks at the impact of the beginning phases of prairie restoration on groundwater geochemistry and microbial communities the relationship between them. This research project studied the geochemistry and microbial communities in five wells before, during, and after the beginning phases of the first year of a prairie restoration on the Northern Illinois University campus. Water samples were collected bimonthly for a year and analyzed on an Ion Chromatograph. Microbial samples were collected monthly and underwent DNA extraction, amplification, …

Comparison Of Topsoil Moisture In E3sm Model Simulations And In-Situ Observations Over Illinois, Jacinda Lee Mayer

Graduate Research Theses & Dissertations

Soil moisture stimulates land-atmosphere interactions by modifying energy and water fluxes in the boundary layer and it plays an important role in climate change studies. The objective of this research is to quantify the spatial and temporal variations of the Illinois Climate Network’s (ICN) observed topsoil moisture, as well as evaluate how accurately the new climate model, E3SM, is simulating soil moisture compared to the observed data during 2003-2014. Observed topsoil moisture averaged over growing season during the 12-year period indicates a general dry-north and wet-south pattern in Illinois, and northeast and southwest become drier with the progression of the …

A Historical Analysis Of The U.S. Federal Emergency Management Agencies (Fema) Response And Recovery To Gulf Coast Hurricane And Other Weather-Related Disasters, Lauren Marie Denning

Graduate Research Papers

The growing changes in our environment combined with the increased number of catastrophic climate and weather- related events are occurring more frequently and continuing to intensify in the United States and Worldwide. These events are resulting in mass destruction in our environment and infrastructure, significant loss in human lives, and costing billions of dollars in response and recovery. Although there is no way to prevent these events, governments and populations can take steps to adapt and prepare for these events. This will ultimately decrease the overall impacts that these events have on our environment and future generations to come.

This …

Attitudes About Cybersecurity Articulation Agreements And Transfer Students: A Statewide Survey Of Faculty Members And Advisors, Brian K. Payne, Tracy Vandecar-Burdin, Daniela Cigularova

Sociology & Criminal Justice Faculty Publications

In this study, cybersecurity faculty and academic advisors from community colleges and 4-year universities in the southeast region of the United States completed a survey assessing attitudes about and support for articulation agreements and related transfer policies. Hypothesizing that professional structures shape attitudes and experiences, the researchers conducted an exploratory quantitative study with primarily descriptive analyses. The results reveal differences in attitudes between community college and 4-year stakeholders and between faculty and academic advisors. The results of this study are discussed in relation to faculty and advisor training and communication.

A Synthetic Prediction Market For Estimating Confidence In Published Work, Sarah Rajtmajer, Christopher Griffin, Jian Wu, Robert Fraleigh, Laxmann Balaji, Anna Squicciarini, Anthony Kwasnica, David Pennock, Michael Mclaughlin, Timothy Fritton, Nishanth Nakshatri, Arjun Menon, Sai Ajay Modukuri, Rajal Nivargi, Xin Wei, Lee Giles

Computer Science Faculty Publications

[First paragraph] Concerns about the replicability, robustness and reproducibility of findings in scientific literature have gained widespread attention over the last decade in the social sciences and beyond. This attention has been catalyzed by and has likewise motivated a number of large-scale replication projects which have reported successful replication rates between 36% and 78%. Given the challenges and resources required to run high-powered replication studies, researchers have sought other approaches to assess confidence in published claims. Initial evidence has supported the promise of prediction markets in this context. However, they require the coordinated, sustained effort of collections of human experts …

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 …