Digital Commons Network^™

Using Strainmeters To Characterize Enhanced Geothermal Systems, Clem Laffaille

All Theses

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Guardians Of The Data: Government Use Of Ai And Iot In The Digital Age, Jannat Saeed

Honors Theses

The exponential growth of technology, epitomized by Moore's Law – “the observation that the number of transistors on an integrated circuit will double every two years”– has propelled the swift evolution of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. This phenomenon has revolutionized various facets of daily life, from smart home devices to autonomous vehicles, reshaping how individuals interact with the world around them. However, as governments worldwide increasingly harness these innovations to monitor and collect personal data, profound privacy concerns have arisen among the general populace. Despite the ubiquity of AI and IoT in modern society, formal …

Best Practices For Offline Evaluation For Top-N Recommendation: Candidate Set Sampling And Statistical Inference, Ngozi Ihemelandu

Boise State University Theses and Dissertations

Evaluation of recommender systems is key to ensuring that we are making progress by only promoting proposed algorithms that actually outperform the state-of-the-art. Evaluation can be performed offline using logged historic data, or online such as A/B tests. Offline evaluation is the most popular evaluation paradigm used in recent research publications because of its accessibility. It has been an area of study since its earliest days, and is still currently an active area of research. Even though significant work has been done to improve the process and metrics of offline evaluation, it still faces fundamental difficulties. Given the significant role …

Developing A Suitability Model And Feasibility Report For The Tennessee Mesonet, Tristan Holmes

Electronic Theses and Dissertations

Mesoscale networks, also known as Mesonets, are advanced environmental monitoring systems that consist of multiple high-quality weather stations that collect meteorological data at frequent intervals (5 minutes or less). Tennessee currently lacks a Mesonet system, and this study identifies suitable and feasible locations for stations in all 95 counties. Layers needed to develop the suitability model included land cover, road centerlines, elevation, flood zones, building footprints, and hydrologic soil types. Geospatial analysis techniques were used to process and combine these layers to identify suitable areas. Once suitable areas were determined, a feasibility assessment that examined land ownership, accessibility, and cell …

Osint Research Studios: A Flexible Crowdsourcing Framework To Scale Up Open Source Intelligence Investigations, A. Mukhopadhyay, Sukrit Venkatagiri, K. Luther

Computer Science Faculty Works

Open Source Intelligence (OSINT) investigations, which rely entirely on publicly available data such as social media, play an increasingly important role in solving crimes and holding governments accountable. The growing volume of data and complex nature of tasks, however, means there is a pressing need to scale and speed up OSINT investigations. Expert-led crowdsourcing approaches show promise, but tend to either focus on narrow tasks or domains, or require resource-intense, long-term relationships between expert investigators and crowds. We address this gap by providing a flexible framework that enables investigators across domains to enlist crowdsourced support for discovery and verification of …

A Climatology Of North American Monsoon Precipitation Over Arizona From Mrms Data, Greta Graeler, Mark Sinclair, Curtis N. James

Publications

The North American Monsoon (NAM) is a seasonal shift in pressure and wind which accounts for over half of the southwest’s annual precipitation. North-central Arizona has variable terrain which influences the location and intensity of convective storms. Severe weather such as strong winds, lightning, and hail can cause loss of life, property, and fires. High spatial and temporal resolution data along with reanalysis data is used to identify convective cells and their motion for the 2015 to 2022 NAM seasons. The heaviest precipitation in north-central Arizona is found over the Bradshaw Mountains and is most active in July and August. …

Supply, Demand, And Fiscal Sustainability Of Outdoor Recreation In Utah, Jordan W. Smith, Chris Monz

Environment and Society Faculty Publications

Because Utah's outdoor recreation destinations are managed by several different federal and state agencies, there is no comprehensive and consistent information on the amount and types of outdoor recreation resources available within the state. Additionally, there has been no research to date on how state programs whose revenues are dependent on outdoor recreation activity, are likely to fare in the coming years. This report begins to address these limitations by: 1) compiling and synthesizing data that characterize the amount and location of outdoor recreation resources throughout the state; and 2) presenting the results of a suite of econometric forecasting models …

Modeling Metaverse Perceptions For Bolstering Traffic Safety Using Novel Trss-Based Owcm-Ram Mcdm Techniques: Purposes And Strategies, Mona Mohamed, Asmaa Elsayed, Marwa Sharawi

Neutrosophic Systems with Applications

The Metaverse has the potential to revolutionize various aspects of human life, including transportation systems. The integration of the Metaverse into intelligent transportation systems has the potential to significantly improve traffic safety in smart cities. By creating a virtual replica of the physical world, the Metaverse can provide a platform for testing new traffic management systems, road designs, and vehicle technologies in a controlled and safe environment before implementing them in the real world. One way to integrate the Metaverse into intelligent transportation systems (ITS) is by enhancing traffic safety. This can be achieved by developing an evaluation model that …

Network Level Detection Of Iot Attacks Via Time Series Shape Mining, Srijani Basu

Masters Theses

This research proposes a method, for detecting intrusions in the Internet of Things (IoT) realm. This approach was specifically tested using datasets containing both benign, and attacks on smart home devices like the Belkin Wemo Power Switch, Lifx Smart Bulb, Amazon Echo, and Netatmo Welcome Camera. These attacks consist of specification-compliant volumetric DDoS attacks, which can be both direct and reflective, with very low traffic volumes implemented in an ON-OFF pattern. Here, the ON-OFF pattern can be referred to as a pulse attack strategy.

We combined non-linear statistical moving averages, and Dynamic Time Warping into a single framework that can …

Cybersecurity Education And Continuous Learning Towards Uae Ncsp Fulfilment, Saleh Hamad Aldaajeh

Dissertations

This dissertation delves into enhancing cybersecurity education by aligning academic curricula with national cybersecurity strategic plan (NCSP) objectives, emphasizing the crucial role of Higher Education Institutions (HEIs) in developing a skilled cybersecurity workforce. Analyzing ten NCSPs, it identifies strategic themes and gaps between national goals and HEI offerings. The study reviews NCSP guidelines, international cybersecurity indices, and literature, including the NICE-NIST framework, to develop a framework that bridges the educational gap, improving learning outcomes and arming students with vital skills, knowledge, and competencies. Furthermore, it introduces a platform for continuous cybersecurity learning, employing micro-credentials, blockchain technology, and AI-driven systems. Based …

Multi-Aspect Rule-Based Ai: Methods, Taxonomy, Challenges And Directions Towards Automation, Intelligence And Transparent Cybersecurity Modeling For Critical Infrastructures, Iqbal H. Sarker, Helge Janicke, Mohamed A. Ferrag, Alsharif Abuadbba

Research outputs 2022 to 2026

Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets, and services that are vital for the functioning and well-being of a society, economy, or nation. However, the rapid proliferation and dynamism of today's cyber threats in digital environments may disrupt CI functionalities, which would have a debilitating impact on public safety, economic stability, and national security. This has led to much interest in effective cybersecurity solutions regarding automation and intelligent decision-making, where AI-based modeling is potentially significant. In this paper, we take into account “Rule-based AI” rather than other black-box solutions since model transparency, i.e., human …

Dynamic Soil-Structure Response And Failure Of Wood Utility Poles Under Hurricane-Force Wind And Non-Linear Cable Loads, Ramani Ayakannu

Civil & Environmental Engineering Theses & Dissertations

This dissertation presents the outcome of a study of the dynamic soil-structure interaction response of tapered wood utility poles embedded in various foundation soils subject to quasi-static and dynamic wind loads. The study includes the effects of nonlinear soil behavior with varying quantities of moisture and nonlinear cable tension loads on a class H1 wood pole. The natural frequency response of the pole is determined using a finite element formulation. The dynamic response in the presence of wind-induced forcing function is studied using a SAP2000 finite element scheme with wind speeds up to 220 mph. The natural frequency of the …

Intelligent Algorithm Safety: Concepts, Scientific Problems And Prospects, Xueqi Cheng, Wei Chen, Huawei Shen, Shiguang Shan, Xilin Chen, Guojie Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Intelligent algorithms refer to the methods embodied in the computational processes that realize intelligence. These methods are often characterized by being data-driven, involving uncertain computations, and with unexplainable model inferences. These characteristics simultaneously introduce potential safety risks to the application of intelligent algorithms and AI. This study firstly explores the concepts of intelligent algorithm safety. Specifically, intelligent algorithm safety, based on the degree of human-machine integration, extends from the univariate safety of the algorithm itself to the bivariate applicational safety when the algorithm serves humans, and finally evolves into the multivariate systemic safety arises within complex socio-technical systems of human-machine …

Yearly Population Data At Census Tract Level Revealed That More People Are Now Living In Highly Fire-Prone Zones In California, Usa, Slade Lazeweski, Shenyue Jia, Jessica E. Viner, Wesley Ho, Brian Hoover, Seung Hee Kim, Menas C. Kafatos

Institute for ECHO Articles and Research

In California (CA), the wildland-urban interface (WUI) faces escalating challenges due to surging population and real estate development. This study evaluates communities along CA's WUI that have witnessed substantial population growth from 2010 to 2021, utilizing demographic data and the 2020 WUI boundaries by the University of Wisconsin-Madison SILVIS Lab. Employing the Mann-Kendall test, we analyze yearly population trends for each census tract along the CA WUI and assess their significance. House ownership, affordability, and wildfire risk are examined as potential drivers of this demographic shift. Our findings indicate that 12.7% of CA's total population now resides in census tracts …

Artificial Intelligence And/Or Machine Learning (Ai &| Ml), George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

These slides are from an invited panel presentation at my home institution, Loyola University Chicago, organized by the Loyola University Chicago Retiree Association (LUCRA). I was asked to give a broad historical overview of AI and ML and speak about its societal impacts.

"The Loyola University Chicago Retiree Association embraces the Vision of Loyola University Chicago and will assist students, faculty, and administrators as they strive to serve humanity. The group values freedom of inquiry, the pursuit of truth, and care of others and embraces a commitment to excellence, service that promotes social justice, values based leadership, and global awareness."

Development Of An Empirical Ground-Motion Model For Post-Mining Induced Seismicity Near Gardanne, France, Pierre Gehl, Pascal Dominique, Hideo Aochi, Mickael Delatre, Jannes Kinscher, Isabelle Contrucci

Journal of Sustainable Mining

Since the closure of mining activities in 2003, the coal basin of Gardanne in South-East France has experienced thousands of small-magnitude earthquake events, mostly triggered by the flooding of mine workings. Some of these events have been powerful enough to be strongly felt by the population, generating nuisance and concern about potential damage to buildings. The aim of this study is to improve the characterisation of the level of ground motion at the surface, by developing a ground-motion model for post-mining induced seismicity, based on several years of recorded data. A Bayesian-based method is applied to the data in order …

Optimizing Medical Iot Disaster Management With Data Compression, Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

Journal of Informatics and Web Engineering

In today's technological landscape, the convergence of the Internet of Things (IoT) with various industries showcases the march of progress. This coming together involves combining diverse data streams from different sources and transmitting processed data in real-time. This empowers stakeholders to make quick and informed decisions, especially in areas like smart cities, healthcare, and industrial automation, where efficiency gains are evident. However, with this convergence comes a challenge – the large amount of data generated by IoT devices. This data overload makes processing and transmitting information efficiently a significant hurdle, potentially undermining the benefits of this union. To tackle this …

The Microverse: A Task-Oriented Edge-Scale Metaverse, Qian Qu, Mohsen Hatami, Ronghua Xu, Deeraj Nagothu, Yu Chen, Xiaohua Li, Erik Blasch, Erika Ardiles-Cruz, Genshe Chen

Michigan Tech Publications

Over the past decade, there has been a remarkable acceleration in the evolution of smart cities and intelligent spaces, driven by breakthroughs in technologies such as the Internet of Things (IoT), edge–fog–cloud computing, and machine learning (ML)/artificial intelligence (AI). As society begins to harness the full potential of these smart environments, the horizon brightens with the promise of an immersive, interconnected 3D world. The forthcoming paradigm shift in how we live, work, and interact owes much to groundbreaking innovations in augmented reality (AR), virtual reality (VR), extended reality (XR), blockchain, and digital twins (DTs). However, realizing the expansive digital vista …

Racism Detection In Tweets, Ndjeuha Gihane

All Graduate Projects

Since the advent of social networks in 1997, businesses and people’s lives have changed in a good way. From promoting companies to reaching out to friends and family, social networking has become a major element in our lives. X is a very popular platform that is used by many people, including celebrities and politicians, to communicate with their audience. Like other platforms, X is not spared by the racism contained in the tweets. We should be able to catch those racist comments on any social media and block the accounts of those responsible for them. To do so, we have …

Towards A Transparency-Based, Value-Sensitive Design Solution For Bias In Self-Driving Cars: An Ethical Violation Assessment And Risk Analysis Framework On Consumer-Held Values, Nada Ahmad Madkour

Master's Theses and Doctoral Dissertations

Background: The rapid growth of automated systems and artificial intelligence (AI), particularly, self-driving cars (SDCs), has attracted significant investments and can potentially contribute to humanity’s flourishing. However, before widespread adoption, it is important to address ethical violations such as bias in AI, highlighted by many real-world cases of bias in AI leading to unfair outcomes in tools like facial recognition, hiring software, and pedestrian detection. Bias in AI can lead to potentially fatal outcomes in SDCs, emphasizing the need for a thorough examination of bias in SDCs.

Purpose: To enhance AI ethics by providing tools to support transparency and value- …

Advancing Anti-Counterfeiting Approach Via The Development Of Functional Optical Materials, Zishen Yang

Dissertations and Theses

Counterfeiting poses a significant threat to public health and safety, necessitating robust measures to combat it. Addressing this challenge requires the development of advanced materials and techniques, coupled with a comprehensive understanding of the obstacles inherent in anti-counterfeiting endeavors. Our study delved into two approaches for crafting anti-counterfeiting technologies: plasmonic and luminescence materials. We thoroughly examined the challenges associated with each method and proposed viable solutions. Notably, we devised a streamlined process for producing inkjet printable Surface-enhanced Raman Scattering (SERS) ink, enabling the creation of low-cost covert quick response (QR) codes with a high storage capacity. Access to the encoded …

Crowdsourcing Geospatial Data For Earth And Human Observations: A Review, Xiao Huang, Siqin Wang, Di Yang, Tao Hu, Meixu Chen, Mengxi Zhang, Guiming Zhang, Filip Biljecki, Tianjun Lu, Lei Zou, Connor Y. H. Wu, Yoo Min Park, Xiao Li, Yunzhe Liu, Hongchao Fan, Jessica Mitchell, Zhenlong Li, Alexander Hohl

Earth and Environmental Sciences Faculty Publications

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between data producers and users. While previous literature has compartmentalized this subject into distinct platforms and application domains, this review offers a holistic examination of crowdsourced geospatial data. Employing a narrative review approach due to the interdisciplinary nature of the topic, we investigate both human and Earth observations through crowdsourced initiatives. This review categorizes the diverse applications of these data and …

Multi-Jurisdictional Hazard Mitigation Plan For Landslides For The Big Sandy Area Development District, Kentucky, Matt M. Crawford, Hudson J. Koch, Jason M. Dortch

Contract Reports--KGS

Landslides are a complex geologic hazard that occurs worldwide, impacting lives, infrastructure, and property. The Big Sandy Area Development District, Kentucky incurs high landslide activity impacting several municipalities. This hazard mitigation planning project includes landslide susceptibility and risk assessments for the Big Sandy Area Development District. We based the landslide susceptibility model on statistics of hillslope morphological features such as slope, curvature, roughness, aspect, and elevation. Using a dual machine learning approach, we modeled the probability of landslide occurrence, defined as an area that is occupied, or might be occupied in the future, by a landslide. We also developed the …

The Hip Ontology: A Formal Framework To Support Disaster Risk Reduction And Management, Shirly Stephen, Mark Schildhauer, Krzysztof Janowicz, Kitty Currier, Pascal Hitzler, Cogan Shimizu, Colby K. Fisher, Dean Rehberger

Computer Science and Engineering Faculty Publications

Open data initiatives and knowledge graphs, in synergy, have contributed to an increasing volume of disaster-related data in the Semantic Web. Synthesizing and enriching these data is critical to support all aspects of data-driven disaster risk reduction and management. A standard template that coherently defines, maps, and classifies the wide range of hazards to which communities are exposed is a key input for this task. The UNDRR-ISC Hazard Information Profiles (HIPs) provide evidence-informed standardization of hazard nomenclature and definitions and a “science-backed” classification. Unfortunately, they are not in a machine-readable format. This paper develops the HIP Ontology as its FAIR …

Investigating Inland Waterway Transport Through A Sustainable Development Perspective: A Case Study Of Magdalena River (Colombia), Natalia Calderón-Rivera

World Maritime University Ph.D. Dissertations

The development of transport systems significantly influences economies, growth, and welfare of populations. However, these systems can have negative consequences, such as water and air pollution, traffic congestion, noise, and biodiversity loss. To address these challenges, it is essential to implement strategies that mitigate negative effects while improving the environmental, social, and economic conditions of the population. In this regard, inland water transport (IWT) is globally recognized as a more sustainable transport alternative due to its high cargo load capacities and comparatively lower environmental and social impacts. In Colombia, the Magdalena River – the country’s most important river basin – …

The Hazard Prediction Problem, Mary E. Helander, Brendan Smith, Sylvia Charchut, Erika Swiatowy, Calvin Nau, Gregory Cavaretta, Timothy Schuler, Adam Schunk, Héctor Ortiz-Peña

Social Science - All Scholarship

This work formulates the hazard prediction problem while addressing the research question: Can machine learning create a model to automatically recognize patterns that correspond to hazard state conditions during a mission-critical operation? Supervised learning models were trained and tested on data observed from mission simulators, which allowed for safe observation of dynamic system states and undesirable casualty events. The prediction task was formulated as a binary classification problem, producing the probability of being in a hazard state at time t and providing situational awareness of a possible imminent loss. Several modeling architectures were investigated: neural networks, logistic regression, a support …

Strategy Overview For Cema, Lucas Bernicker, Sarah Biedron, Marcus Ding, Elianna Filivaa, Alister Paul, Rosie Swidler

Sustainability Exchange Projects

No abstract provided.

The Right To A Glass Box: Rethinking The Use Of Artificial Intelligence In Criminal Justice, Brandon L. Garrett, Cynthia Rudin

Faculty Scholarship

Artificial intelligence (“AI”) increasingly is used to make important decisions that affect individuals and society. As governments and corporations use AI more pervasively, one of the most troubling trends is that developers so often design it to be a “black box.” Designers create AI models too complex for people to understand or they conceal how AI functions. Policymakers and the public increasingly sound alarms about black box AI. A particularly pressing area of concern has been criminal cases, in which a person’s life, liberty, and public safety can be at stake. In the United States and globally, despite concerns that …

Evaluating Pre-Trial Programs Using Interpretable Machine Learning Matching Algorithms For Causal Inference, Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad, Brandon Garrett, Sudeepa Roy, Cynthia Rudin, Alexander Volfovsky

Faculty Scholarship

After a person is arrested and charged with a crime, they may be released on bail and required to participate in a community supervision program while awaiting trial. These ‘pretrial programs’ are common throughout the United States, but very little research has demonstrated their effectiveness. Researchers have emphasized the need for more rigorous program evaluation methods, which we introduce in this article. We describe a program evaluation pipeline that uses recent interpretable machine learning techniques for observational causal inference, and demonstrate these techniques in a study of a pre-trial program in Durham, North Carolina. Our findings show no evidence that …

Reducing Short-Chain Pfas Levels In California Water Supplies, Manu Prabandham

Pomona Senior Theses

This thesis proposes twelve specific policies based on precedents set by prior regulation of persistent organic pollutants (such as PCBs), the costs and benefits of short-chain PFAS, technologies available to remove and destroy short-chain PFAS, and the roles and limitations of California’s regulatory institutions. The twelve policies are chosen to be politically and financially feasible, effective at removing short-chain PFAS from water supplies, and equitable towards lower-income and minority Californians, who suffer the most from the consequences of PFAS and other environmental pollutants. The new definitions, education campaigns, studies, taxes, bans, standards, testing, and filtration systems proposed are intended to …