Digital Commons Network^™

Why Is Grade Distribution Often Bimodal? Why Individualized Teaching Adds Two Sigmas To The Average Grade? And How Are These Facts Related?, Christian Servin, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To make education more effective, to better use emerging technologies in education, we need to better understand the education process, to gain insights on this process. How can we check whether a new idea is indeed a useful insight? A natural criterion is that the new idea should explain some previously-difficult-to-explain empirical phenomenon. Since one of the main advantages of emerging educational technologies -- such as AI -- is the possibility of individualized education, a natural phenomenon to explain is the fact -- discovered by Benjamin Bloom -- that individualization adds two sigmas to the average grade. In this paper, …

Architectural Elements Contributing To Interpretability Of Deep Neural Networks (Dnns), Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of Deep Neural Networks (DNNs) has become a critical focus in artificial intelligence and machine learning, particularly as DNNs are increasingly used in high-stakes applications like healthcare, finance, and autonomous driving. Interpretability refers to the extent to which humans can understand the reasons behind a model's decisions, which is essential for trust, accountability, and transparency. However, the complexity and depth of DNN architectures often compromise interpretability as these models function as "black boxes." This article reviews key architectural elements of DNNs that affect their interpretability, aiming to guide the design of more transparent and trustworthy models. The primary …

On Coresets For Fair Clustering In Metric And Euclidean Spaces And Their Applications, Sayan Bandyapadhyay, Fedor V. Fomin, Kirill Simonov

Computer Science Faculty Publications and Presentations

Fair clustering is a constrained clustering problem where we need to partition a set of colored points. The fraction of points of each color in every cluster should be more or less equal to the fraction of points of this color in the dataset. The problem was recently introduced by Chierichetti et al. (2017) [1]. We propose a new construction of coresets for fair clustering for Euclidean and general metrics based on random sampling. For the Euclidean space Rd, we provide the first coreset whose size does not depend exponentially on the dimension d. The question of whether such constructions …

Matching The Scales Of Planning And Environmental Risk: An Evaluation Of Community Wildfire Protection Plans In The Western Us, Matthew Hamilton, Cody Evers, Max Nielsen-Pincus, Alan Ager

Environmental Science and Management Faculty Publications and Presentations

Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community …

A Sentiment Analysis Approach For Understanding Users’ Perception Of Metaverse Marketplace, Ahmed Al-Adaileh, Mousa Al-Kfairy, Mohammad Tubishat, Omar Alfandi

All Works

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace's revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding …

Assessing The Impact Of Hurricane Fiona On The Coast Of Pei National Park And Implications For The Effectiveness Of Beach-Dune Management Policies, Robin Davidson-Arnott, Jeff Ollerhead, Elizabeth George, Chris Houser, Bernard Bauer, Patrick Hesp, Ian Walker, Irene Delagado-Fernandez, Danika Van Proosdij

Earth & Environmental Sciences Publications

The impact of waves, storm surge, and aeolian transport associated with Post-tropical Storm Fiona (offshore significant wave height ∽ 8 m, storm surge up to 2 m) on the sandy beaches and foredunes of the north shore of Prince Edward Island National Park (PEINP), Canada, are assessed. Management policies and practices, as they apply to sandy beach systems within PEINP, are reviewed in the context of the shoreline changes attributed to Fiona. The effectiveness of these policies and practices are evaluated to inform the potential performance of beach-foredune systems as natural protection measures that mitigate the impacts of large-magnitude storms …

Western Kentucky University Stormwater Utility Survey 2024, Warren Campbell

SEAS Faculty Publications

The main goal of this survey is to identify as many U.S. Stormwater Utilities (SWUs) as possible. Because many stormwater professionals do not have the time to respond to questionnaires, our primary method of identification was Internet searches. We searched key terms such as “stormwater utility,” “stormwater fee,” and “drainage fee.” We scoured online municipal codes such as Municode, AmLegal, Sterling, LexisNexis, General Code, and others. We searched through many city web websites to find utilities. We have also had many people contact me to update fees and identify new utilities. However, the data primarily comes from Internet sources and …

Assessing Impact Of Urban Densification On Outdoor Microclimate And Thermal Comfort Using Envi-Met Simulations For Combined Spatial-Climatic Design (Cscd) Approach, Shreya Banerjee, Rachel X.Y. Pek, Sin Kang Yik, Graces N. Ching, Xiang Tian Ho, Dzyuban Yuliya, Peter J. Crank, Juan A. Acero, Winston T. L. Chow

Research Collection College of Integrative Studies

Future urban planning requires context-specific integration of spatial design and microclimate especially for tropical cities with extreme weather conditions. Thus, we propose a Combined Spatial-Climatic Design approach to assess impact of urban densification on annual outdoor thermal comfort performance employing ENVI-met simulations for Singapore. We first consider building bylaws and residential site guidelines to develop eight urban-density site options for a target population range. We further classify annual weather data into seven weather-types and use them as boundary conditions for the simulations. Comparing such fifty-six combined spatial-climatic simulation outputs by analyzing Outdoor Thermal Comfort Autonomy, we report the influence of …

Understanding The Impact Of Microplastic Contamination On Soil Quality And Eco-Toxicological Risks In Horticulture: A Comprehensive Review, N. P. Gayathri, Geena Prasad, Vaishna Prabhakaran, Vishnu Priya

Research outputs 2022 to 2026

The horticulture sector, essential for global food production, confronts significant challenges with prevalent pollutants, mainly microplastics. The presence of microplastics in the food chain has induced physiological stress and a multifactorial food safety concern. The complexity of the problem, arising from intricate interactions among microplastics, organisms, and ecosystems, poses a substantial challenge to food safety, necessitating an immediate strategic perspective due to the associated risks to human health and eco-toxicology. Significant knowledge gaps persist regarding their impact on terrestrial ecosystems, especially in horticulture. This study addresses the urgent need to comprehend the implications of microplastics on soil health, eco-toxicological risks, …

College Of Saint Benedict And Saint John's University Fy2023 Greenhouse Gas Emissions Inventory, Csb+Sju Office Of Sustainability

Sustainability Office Publications

The College of Saint Benedict (CSB) and Saint John’s University (SJU) Office of Sustainability conducted a comprehensive Greenhouse Gas (GHG) Inventory that includes emissions from both CSB and SJU campuses. This report details GHG emissions for Fiscal Year (FY) 2023 (July 1, 2022-June 30, 2023) in Metric Tons of Carbon Dioxide Equivalents (MTCO2e), the standard unit of measurement used to track and report GHG emissions based on their global warming potential. Data was collected, organized, and analyzed by staff in the CSB and SJU Sustainability Office.

Using Bayesian Multispecies Models To Evaluate Fish And Invertebrate Detection Probability And Distribution In The Hypersaline Bahia Grande Tidal Basin, Roy M. Ulibarri, Catherine M. Eckert, David Hicks, David Montagne, Brandon Jones, David R. Stewart

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Objective

In 2000, the Laguna Atascosa National Wildlife Refuge acquired the Bahia Grande (Texas) management unit, a space that had lain barren and arid for 70 years. A large cooperative partnership launched a restoration project to replenish the basin and recover its original tidal hydrology. In 2005, the construction of a pilot channel successfully restored water throughout the basin, and plans to eventually widen the channel were developed. Our study aims to evaluate an estuarine habitat restoration by assessing ecological drivers and the impacts on species diversity.

Methods

We evaluated species richness, detection/occupancy rates, and species–habitat relationships, and we estimated …

Spectroscopic Characterization, Dft Calculations, In Vitro Pharmacological Potentials, And Molecular Docking Studies Of N, N, O-Schiff Base And Its Trivalent Metal Complexes, Ikechukwu P. Ejidike, Amani Direm, Cemal Parlak, Adebayo A. Adeniyi, Mohammad Azam, Athar Ata, Michael O. Eze, Joshua W. Hollett, Hadley S. Clayton

Michigan Tech Publications, Part 2

In this study, trivalent metal complexes of the category: [M(L)(H2O)nCly] obtained from the interaction of metal3+ ion salts with organic N, N, O-Schiff base (HL) (where: HL = 4-{(Z)-((2-{(E)-((2-hydroxyphenyl)methylidene)amino}ethyl)imino)methyl}-2-methoxyphenol; n, y = 1 or 2 and M = Ti(III), Fe(III), Ru(III), Cr(III) and Al(III)) were synthesized and characterized viz molar conductance, FT-IR, and UV–Vis spectroscopies, elemental analyses, thermal analyses (TGA and DTA), and UV–Vis spectroscopy, theoretical calculations. A distorted octahedral structure around the metal ions was proposed based on the obtained experimental and calculated data. Thermal examination of the complexes signposts the step-by-step disintegration to give the final decomposition product …

Agricultural Groundcover Update May 2024, Justin Laycock

Natural resources published reports

• In May, over 9% (1,410,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.3% (208,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%. Half of this land was in the West Midlands Ag Soil Zone.

Agricultural Groundcover Update April 2024, Justin Laycock

Natural resources published reports

• In April, over 12% (1,876,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.5% (238,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

Mega-Projects, Cumulative Impacts, & Indigenous Nationhood On The Multinational Salish Sea, Natalie J.K. Baloy, Isabella Pipp

Institute Publications

In the Salish Sea, one of the major ports for today’s ships is Roberts Bank Superport, named for Henry Roberts (Vancouver’s predecessor), run by the Vancouver Fraser Port Authority, and located just north of the Canada-US border. In 2023, the Government of Canada and the Province of BC approved the Roberts Bank Terminal 2 (RBT2) project which will expand the port by building a second artificial island, adding three berths to accommodate increased capacity for container cargo.

Two court cases this year will challenge the Government of Canada RBT2 approval. One, issued by Ecojustice in alliance with several environmental organizations, …

A Pilot Study On Particulate Matter Concentrations From Cooking And Its Effects On Indoor Air Pollution In A Mexican American Household In Mission, South Texas, Usa, Sai Deepak Pinakana, Carlos Garcia Patlan, Esmeralda Mendez, Amit U. Raysoni

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

This pilot study focuses on particulate matter (PM) while cooking in a South Texan household. Dishes such as Beef, Burger, Fish, Chicken, Egg Sandwich, and Hotdog were prepared. Indoor PM levels were compared with outdoor PM levels. A DustTrak DRX was used to monitor the PM released during the cooking process. PM2.5 levels were highest while cooking beef, 162.79 + 209.62 μg m−3. Hot Dog preparation resulted in the lowest PM2.5 concentration of 27.72 + 5.58 μg m−3. Indoor PM2.5 levels were observed to be greater in contrast to outdoor levels when compared to the outdoor levels (96 words).

New Examples Of Self-Dual Near-Extremal Ternary Codes Of Length 48 Derived From 2-(47,23,11) Designs, Sanja Rukavina, Vladimir Tonchev

Michigan Tech Publications, Part 2

In a recent paper (Araya and Harada, 2023), Araya and Harada gave examples of self-dual near-extremal ternary codes of length 48 for 145 distinct values of the number A12 of codewords of minimum weight 12, and raised the question about the existence of codes for other values of A12. In this note, we use symmetric 2-(47,23,11) designs with an automorphism group of order 6 to construct self-dual near-extremal ternary codes of length 48 for 150 new values of A12.

Perceptions And Aspirations Of Undergraduate Computer Science Students Towards Generative Ai: A Qualitative Inquiry, James Hutson, Theresa Jeevanjee

Faculty Scholarship

This article presents a comprehensive study conducted during the spring semester of 2024, aimed at exploring undergraduate computer science students’ perceptions, awareness, and understanding of generative artificial intelligence (GAI) tools within the context of their Artificial Intelligence (AI) courses. The research methodology employed qualitative techniques, including human-subject research and focus groups, to delve into students’ insights on the evolution of AI as delineated in the seminal textbook by Russell and Norvig. The study-initiated discussions on the historical development of AI, prompting students to reflect on the aspects that intrigued them the most, and to identify which historical concepts and methodologies, …

Present Case Studies Highlighting Practical Implications Of Architectural Design Choices, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) has become a crucial focus within artificial intelligence and machine learning, particularly as these models are increasingly used in high-stakes applications such as healthcare, finance, and autonomous driving. This article explores the impact of architectural design choices on the interpretability of DNNs, emphasizing the importance of transparency, trust, and accountability in AI systems. By presenting case studies and experimental results, the article highlights how different architectural elements—such as layer types, network depth, connectivity patterns, and attention mechanisms—affect model interpretability and performance. The discussion is structured into three main sections: real-world applications, architectural trade-offs, …

Evaluating Methods For Assessing Interpretability Of Deep Neural Networks (Dnns), Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) is a critical focus in artificial intelligence (AI) and machine learning (ML), particularly as these models are increasingly deployed in high-stakes applications such as healthcare, finance, and autonomous systems. In the context of these technologies, interpretability refers to the extent to which a human can understand the cause of a decision made by a model. This article evaluates various methods for assessing the interpretability of DNNs, recognizing the significant challenges posed by their complex and opaque nature. The review encompasses both quantitative metrics and qualitative evaluations, aiming to identify effective strategies that enhance …

Navigating The Complexities Of Ai: The Critical Role Of Interpretability And Explainability In Ensuring Transparency And Trust, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability and explainability of deep neural networks (DNNs) are paramount in artificial intelligence (AI), especially when applied to high-stakes fields such as healthcare, finance, and autonomous driving. The need for this study arises from the growing integration of AI into critical areas where transparency, trust, and ethical decision-making are essential. This paper explores the impact of architectural design choices on DNN interpretability, focusing on how different architectural elements like layer types, network depth, connectivity patterns, and attention mechanisms affect model transparency. Methodologically, the study employs a comprehensive review of case studies and experimental results to analyze the balance between …

Navigating The Ethical Terrain Of Ai In Higher Education: Strategies For Mitigating Bias And Promoting Fairness, Emily Barnes, James Hutson

Faculty Scholarship

Artificial intelligence (AI) and machine learning (ML) are transforming higher education by enhancing personalized learning and academic support, yet they pose significant ethical challenges, particularly in terms of inherent biases. This review critically examines the integration of AI in higher education, underscoring the dual aspects of its potential to innovate educational paradigms and the essential need to address ethical implications to avoid perpetuating existing inequalities. The researchers employed a methodological approach that analyzed case studies and literature as primary data collection methods, focusing on strategies to mitigate biases through technical solutions, diverse datasets, and strict adherence to ethical guidelines. Their …

The Characteristics Of Digital Transformation Leadership: Theorizing The Practitioner Voice, Pat Mccarthy, David Sammon, Ibrahim Alhassan

Department of Computer Science Publications

Digital Transformation (DT) is more than simply integrating a new digital technology into the organization. Despite a growing volume of research, however, there is little coverage of the characteristics of DT leadership. Using a grounded approach, where 16 practitioner voices are central to the theorizing output, we present 10 DT leadership characteristics. Each characteristic links what action a DT leader needs to take and how a DT leader enables that action. We also asked 30 DT leaders to evaluate the importance of each of the 10 DT leadership characteristics. Our approach strengthens the relevance for practitioners striving for the best …

Decentralized Optimization Over Slowly Time-Varying Graphs: Algorithms And Lower Bounds, Dmitry Metelev, Aleksandr Beznosikov, Alexander Rogozin, Alexander Gasnikov, Anton Proskurnikov

Machine Learning Faculty Publications

We consider a decentralized convex unconstrained optimization problem, where the cost function can be decomposed into a sum of strongly convex and smooth functions, associated with individual agents, interacting over a static or time-varying network. Our main concern is the convergence rate of first-order optimization algorithms as a function of the network’s graph, more specifically, of the condition numbers of gossip matrices. We are interested in the case when the network is time-varying but the rate of changes is restricted. We study two cases: randomly changing network satisfying Markov property and a network changing in a deterministic manner. For the …

Boring But Demanding: Using Secondary Tasks To Counter The Driver Vigilance Decrement For Partially Automated Driving, Scott Mishler, Jing Chen

Psychology Faculty Publications

Objective

We investigated secondary–task–based countermeasures to the vigilance decrement during a simulated partially automated driving (PAD) task, with the goal of understanding the underlying mechanism of the vigilance decrement and maintaining driver vigilance in PAD.

Background

Partial driving automation requires a human driver to monitor the roadway, but humans are notoriously bad at monitoring tasks over long periods of time, demonstrating the vigilance decrement in such tasks. The overload explanations of the vigilance decrement predict the decrement to be worse with added secondary tasks due to increased task demands and depleted attentional resources, whereas the underload explanations predict the vigilance …

Trace Element Contamination In Urban Soils: Testing And Management, Melissa Chilinski, Melanie Stock, Paul R. Grossl, Eli Oliver

All Current Publications

Trace elements, often referred to as heavy metals, naturally occur in the soil at low levels. Certain land use histories can elevate the concentrations of trace elements to levels that present health risks. Understanding which elements and soil test values may impact human or crop health is an important aspect of gardening and micro-farming, particularly in urban environments that are at increased risk of soil contamination. This fact sheet provides instructions on interpreting soil test results for trace elements through the Total Element Composition EPA 3050B Soil Test (#S19) at Utah State University Analytical Laboratory.

Ethical Considerations Toward Protestware, Marc Cheong, Raula Kula, Christoph Treude

Research Collection School Of Computing and Information Systems

This article looks into possible scenarios where developers might consider turning their free and open source software into protestware. Using different frameworks commonly used in artificial intelligence (AI) ethics, we extend the applications of AI ethics to the study of protestware.

Network-Based Representations And Dynamic Discrete Choice Models For Multiple Discrete Choice Analysis, Huy Hung Tran, Tien Mai

Research Collection School Of Computing and Information Systems

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application …

Predictive Power Of Machine Learning Models On Degree Completion Among Adult Learners, Emily Barnes, James Hutson, Karriem Perry

Faculty Scholarship

The integration of machine learning (ML) into higher education has been recognized as a transformative force for adult learners, a growing demographic facing unique educational challenges. This study evaluates the predictive power of three ML models—Random Forest, Gradient-Boosting Machine, and Decision Trees—in forecasting degree completion among this group. Utilizing a dataset from the academic years 2013-14 to 2021-22, which includes demographic and academic performance metrics, the study employs accuracy, precision, recall, and F1 score to assess the efficacy of these models. The results indicate that the Gradient-Boosting Machine model outperforms others in predicting degree completion, suggesting that ML can significantly …

Strategic Integration Of Ai In Higher Education And Industry: The Ai8-Point Model, Emily Barnes, James Hutson

Faculty Scholarship

The AI8-Point Model, derived from extensive experience in technology, AI, and higher education administration, addresses the critical need for cost-effective, high-impact strategies tailored to higher education. Despite the transformative potential of AI in enhancing student engagement, optimizing processes, and improving educational outcomes, institutions often struggle with practical implementation. The AI8-Point Model fills this gap by offering strategies that balance cost and impact. Visualized as a circle divided into four quadrants, the model encompasses phases of student engagement and institutional interaction: pre-enrollment beyond institutional control, pre-enrollment within institutional control, post-enrollment within institutional control, and post-enrollment beyond institutional control. Each quadrant contains …