Digital Commons Network^™

Fetal Alcohol Spectrum Disorders (Fasd) And Sexually Inappropriate Behaviors: Important Reminders For Criminal Justice And Forensic Mental Health Professionals, Jerrod Brown, Cody Charette, Jodee Kulp, Diane Neal, Anne Russell, Aaron Trnka, Ryan Chukuske

Forensic Scholars Today

No abstract provided.

Course Correction: Examining 2020’S Middle Level Teacher Education Through A Critical, Antiracist Lens-A Collaborative Self-Study Of Teacher Education Practices, Kristie W. Smith, Kristina N. Falbe

Current Issues in Middle Level Education

The work of teacher education in a 2020’s context is challenging and filled with opportunity. With a diversifying P-12 student body (Love, 2020; Pitts, 2019) and the confluence of social, political, and educational factors (Nieto & Bode, 2018), the complexities of teacher education are vast and fluid. In a historical moment that has included teaching in a time of pandemic, national reckonings over race and injustice, and explicit legislation to guide teaching about social history (Kelly et al, 2023), effective middle level teacher education is multifaceted. It calls for the development of teacher candidates skilled in creating school environments that …

Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks on control systems can create unprofitable and unsafe operating conditions. To enhance safety and attack resiliency of control systems, cyberattack detection strategies can be developed. Prior work in our group has sought to develop cyberattack detection strategies that are integrated with an advanced control formulation known as Lyapunov-based economic model predictive control (LEMPC), in the sense that the controller properties can be used to analyze closed-loop stability in the presence or absence of undetected attacks. In this work, we consider neural network-approximated control laws, concepts for mitigating cyberattacks on such control laws, and how these ideas elucidate concepts in …

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

Study Of The Application Of Blender For Simulation Of A Closed-Loop Image-Based Greenhouse Supplemental Lighting Control, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Image-based control and sensing has been applied in a wide variety of next generation manufacturing fields. Utilizing methods of simulating closed-loop image-based control may be advantageous for improving control performance and design without the need for an experimental setup. One software capable of these simulations is the open-source 3D modeling software Blender, which has many capabilities aided by a Python API. This work explores the use of Blender as an image-based control test bed, where both the process and the controller are simulated, in the context of a greenhouse supplemental lighting control system.

Upcoming Career Fairs Offer Employment, Networking Chances For Students, Jeffery Woodard

News and Events (Discontinued Series)

No abstract provided.

Scientific History, Sampling Approach, And Physical Characterization Of The Camp Century Subglacial Material, A Rare Archive From Beneath The Greenland Ice Sheet, Paul R. Bierman, Andrew J. Christ, Catherine M. Collins, Halley M. Mastro, Juliana Souza, Pierre Henri Blard, Stefanie Brachfeld, Zoe R. Courville, Tammy M. Rittenour, Elizabeth K. Thomas, Jean Louis Tison, François Fripiat

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Basal materials in ice cores hold information about paleoclimate conditions, glacial processes, and the timing of past ice-free intervals, all of which aid understanding of ice sheet stability and its contribution to sea level rise in a warming climate. Only a few cores have been drilled through ice sheets into the underlying sediment and bedrock, producing limited material for analysis. The last of three Camp Century ice cores, which the U.S. Army collected in northwestern Greenland from 1963-1966 CE, recovered about 3.5 m of subglacial material, including ice and sediment. Here, we document the scientific history of the Camp Century …

Regulating Algorithmic Harms, Sylvia Lu

Law & Economics Working Papers

In recent years, the rapid expansion of artificial intelligence (AI) innovations has led to a rise in algorithmic harms—harms emerging from AI operations that pose significant threats to civil rights and democratic values in today’s technological landscape. A facial recognition system for improving criminal detection wrongly collected sensitive personal data and flagged racial minorities as shoplifters. A risk-prediction algorithm adopted to identify patients denied medical treatment to Black individuals with poor health conditions. A social media algorithm intended to boost social engagement exacerbated addictive behavior and mental illness in teenagers. These harms are becoming increasingly ubiquitous yet often manifest in …

Profit Considerations For Nonlinear Control-Integrated Cyberattack Detection On Process Actuators, Keshav Kasturi Rangan, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Prior research from our group developed a control-integrated active actuator cyberattack detection strategy. This strategy continuously probed for cyberattacks by updating target steady-states at every sampling time and then moving the process state toward these over the subsequent sampling period. Attacks were fagged if a Lyapunov function around the target steady-state did not decrease over a sampling period. This strategy had the benefit of ensuring safety of the process until an attack was detected. However, the continuous probing for attacks could decrease profit from the process compared to not probing for the attacks, which could limit the attractiveness of the …

Successful Economic Crisis Management Strategies Used By Small- And Medium-Size Enterprise Food Service Business Managers In The British West Indies, Lancelott Barnes

Walden Dissertations and Doctoral Studies

Poor crisis management strategies caused small and medium-sized food service enterprise leaders to permanently close business operations during the COVID-19 pandemic. These closures resulted in significant economic losses and reduced employment opportunities in the industry. Grounded in the relational crisis management model, this qualitative pragmatic inquiry aimed to understand the economic crisis management strategies used by business managers in the food services industries to prevent business closures in the British West Indies. Data were collected from semistructured interviews with six business managers in the food services industry who successfully navigated their businesses through the COVID-19 pandemic. Four themes that emerged …

Curriculum Minutes 09/05/2024, Curriculum Committee

Curriculum Committee Minutes

No abstract provided.

Supplementary Files For: Quantifying The Impact Of Rain-On-Snow Induced Flooding In The Western United States, Emma Watts, Brennan Bean

Browse all Datasets

Serious flooding can happen when rain falls on snow, which we call a rain-on-snow (ROS) event. Increasing our understanding of the behavior of floods resulting from ROS events can help us design better systems to manage flood water and prevent it from causing damage. This thesis explores how ROS events affect streamflow in the Western United States by examining the weather conditions that precede a streamflow surge. We classify stream surges as ROS or non-ROS induced based on these weather conditions, which helps us separate floods caused by ROS events from those caused by other factors. By comparing these different …

Tracing Atlantic Sea Scallops Using Radio Frequency Identification (Rfid) Technology, Will Shoup, David Rudders, Jonathon Peros

Journal of Extension

Radio Frequency Identification (RFID) represents a technology that has the potential to enhance many aspects of the Atlantic sea scallop fishery. Driven by fishery management and market forces, fishery product traceability benefits fisheries managers, consumers, and fishermen. In order to demonstrate the capabilities of RFID technology in the scallop fishery, a solution is proposed that would help establish clear Chain of Custody (CoC) so that the scallop supply chain can be better documented. Implementation and acceptance of any new technology will hinge on effective communication and extension efforts that can leverage the multi-benefit aspects of adopting RFID into the fishery.

Secondary Educators’ Perspectives On Implementing Culturally Responsive Teaching Practices, Quiana Brooks-Curry

Walden Dissertations and Doctoral Studies

The problem addressed in this study was the struggle that U.S. secondary teachers experience when implementing culturally responsive teaching (CRT) strategies. Guided by the culturally responsive education model as the conceptual framework, the purpose of this basic qualitative study was to explore secondary teachers’ perceptions of their successes, challenges, and needs in implementing CRT to support student achievement and foster a sense of belonging. Data were collected via semistructured interviews with 10 participants who (a) taught in Grades 6–12, (b) had a minimum of 2 years of teaching experience, and (c) had knowledge of and experience using CRT strategies. Data …

Intra- And Inter-Host Evolution Of Human Norovirus In Healthy Adults, Sasirekha Ramani, Sara J Javornik Cregeen, Anil Surathu, Frederick H Neill, Donna M Muzny, Harsha Doddapaneni, Vipin K Menon, Kristi L Hoffman, Matthew C Ross, Ginger Metcalf, Antone R Opekun, David Y Graham, Richard A Gibbs, Joseph F Petrosino, Mary K Estes, Robert L Atmar

Faculty, Staff and Students Publications

Background: Human noroviruses are a leading cause of acute and sporadic gastroenteritis worldwide. The evolution of human noroviruses in immunocompromised persons has been evaluated in many studies. Much less is known about the evolutionary dynamics of human norovirus in healthy adults.

Methods: We used sequential samples collected from a controlled human infection study with GI.1/Norwalk/US/68 virus to evaluate intra- and inter-host evolution of a human norovirus in healthy adults. Up to 12 samples from day 1 to day 56 post-challenge were sequenced using a norovirus-specific capture probe method.

Results: Complete genomes were assembled, even in samples that were below the …

Improving Ligand Pharmacokinetics Via Bioisosteric Substitution Of Amides With 1, 2, 3-Triazoles While Maintaining Dopamine D4 Receptor Selectivity And Potency, Mohammad Alkhatib

Theses and Dissertations

Several neurophysiological functions, such as attention, cognition, and emotional regulation, are regulated by the binding of dopamine on G-Protein coupled receptors. D4Rs are mainly located in the prefrontal cortex and the hippocampus and are known to have a key role in decision-making, memory formation, cognition, and attention. Administration of D4Rs- selective ligands during the preclinical studies enhance the outcomes and the results in animal models suffering from neuropsychiatric disorders, including ADHD, substance use disorders (SUD), and Alzheimer's disease. Recently, we reported a group of D4R-selective ligands with different efficacies depending on their phenylpiperazine ring scaffold to illustrate D4R function during …

Exploring The Experiences Of African American Women Parents’ Role Regarding Financial Socialization In Sacramento, California., Anita Renee Johnson

Walden Dissertations and Doctoral Studies

Financial socialization encompasses the process of acquiring financial values, attitudes, norms, knowledge, and behaviors, with parental influence being pivotal in shaping children's financial understanding and well-being. This study addresses the lack of comprehensive research on the financial socialization experiences of African American women and the role played by parents in shaping their financial management skills, self-efficacy, and identity. By bridging this gap, this study provides valuable insights into the financial socialization processes within African American families, which can have long-term impacts on economic outcomes and wealth-building strategies. Recognizing a gap in the literature, this study addresses the lack of comprehensive …

Meta-Analysis Of Set-Based Multiple Phenotype Association Test Based On Gwas Summary Statistics From Different Cohorts, Lirong Zhu, Shuanglin Zhang, Qiuying Sha

Michigan Tech Publications

Genome-wide association studies (GWAS) have emerged as popular tools for identifying genetic variants that are associated with complex diseases. Standard analysis of a GWAS involves assessing the association between each variant and a disease. However, this approach suffers from limited reproducibility and difficulties in detecting multi-variant and pleiotropic effects. Although joint analysis of multiple phenotypes for GWAS can identify and interpret pleiotropic loci which are essential to understand pleiotropy in diseases and complex traits, most of the multiple phenotype association tests are designed for a single variant, resulting in much lower power, especially when their effect sizes are small and …

Analysis Of Deixis And Optimistic Values In Kun Anta Song Lyrics, Asy Syifa Reza Amelya, Arina Dienana, Bening Anjaswara, Mohamad Zaka Al Farisi, Isna Fitria Solihah

Bahasa dan Seni: Jurnal Bahasa, Sastra, Seni, dan Pengajarannya

A popular language expression is music, as it is a symbolic avenue for conveying thoughts and emotions. In this research, Kun Anta songs will be analyzed and classi-fied into several types of deixis using Levinson’s framework, while correlating the con-tained optimism with relevant phenomena. It is shown that deixis is fundamental in expression. This study adopts a qualitative descriptive approach, focusing on the pro-cess and providing descriptive data to better understand the phenomenon under investigation. The data undergoes three phases of analysis: data reduction, display, and conclusion drawing, followed by verification. In our analysis we have found that the song …

Strategies Cybersecurity Professionals Use To Mitigate Cybersecurity Threats In Small Businesses, Michael Bert Branham

Walden Dissertations and Doctoral Studies

Small business owners are concerned about incorporating security best practices, security frameworks, and critical business functions into a cybersecurity strategy, which is necessary to adapt to the increased sophistication and occurrence of cyber-attacks. Grounded in Von Bertalanffy’s general system theory, the purpose of this qualitative pragmatic study was to explore strategies cybersecurity professionals use to mitigate cybersecurity threats in small businesses. A sample of 14 security professionals on LinkedIn shared their perspectives on how cybersecurity strategies successfully mitigated recent cybersecurity threats. Data were collected through semi-structured interviews, and data analysis was performed by coding keywords, phrases, and methods. The following …

Acclaimed Children's Literature As Global Resources, Sunah Chung, Melanie D. Koss, Kathleen A. Paciga

Faculty Publications

Acclaimed children's books in the United States (U.S.) may be utilized as resources to instruct global issues. As children’s literature reflects social context and values, acclaimed books may provide curricular materials for those within the U.S. and to international audiences. Stakeholders, including librarians, teachers, national industry experts, and parents, are among those who review and award prizes to children’s literature. This work has resulted in booklists teachers, families, and librarians use to guide their book purchasing and sharing practices. We investigate the histories, composition, and criteria for 22 award and acclaimed U.S. children’s book lists containing 4,244 titles. Fewer than …

A Panel Data Regression Model For Defense Merger And Acquisition Activity, Corey D. Mack, Clay Koschnick, Michael Brown, Jonathan D. Ritschel, Brandon M. Lucas

Faculty Publications

Excerpt: This paper examines the relationship between a prime contractor's financial health and its mergers and acquisitions (M&A) spending in the defense industry. It aims to provide models that give the United States Department of Defense (DoD) indications of future M&A activity, informing decision-makers and contributing to ensuring competitive markets that benefit the consumer.

The results show a significant relationship between efficiency and M&A spending, indicating that companies with lower efficiency tend to spend more on M&As. However, there was no significant relationship between M&A spending and a company's profitability or solvency. These results were consistent with previous research and …

Angular Momentum Flow Without Anything Carrying It, Yakir Aharonov, Daniel Collins, Sandu Popescu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Transfer of conserved quantities between two remote regions is generally assumed to be a rather trivial process: a flux of particles carrying the conserved quantities propagates from one region to another. However, we demonstrate a flow of angular momentum from one region to another across a region of space in which there is a vanishingly small probability of any particles (or fields) being present. This shows that the usual view of how conservation laws work needs to be revisited.

Methane Fluxes In Tidal Marshes Of The Conterminous United States, Ariane Arias-Ortiz, Jaxine Wolfe, Scott D. Bridgham, Sara Knox, Gavin Mcnicol, Brian A. Needelman, Julie Shahan, Ellen J. Stuart-Haëntjens, Lisamarie Windham-Myers, Patty Y. Oikawa, Dennis D. Baldocchi, Joshua S. Caplan, Margaret Capooci, Kenneth M. Czapla, R. Kyle Derby, Heida L. Diefenderfer, Inke Forbrich, Gina Groseclose, Jason K. Keller, Cheryl Kelley, Amir E. Keshta, Helena S. Kleiner, Ken W. Krauss, Robert R. Lane, Sarah Mack, Serena Moseman-Valtierra, Thomas J. Mozdzer, Peter Mueller, Scott C. Neubauer, Genevieve Noyce, Katrina V. R. Schäfer, Rebecca Sanders-Demott, Charles A. Schutte, Rodrigo Vargas, Nathaniel B. Weston, Benjamin Wilson, J. Patrick Megonigal, James R. Homquist

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Methane (CH4) is a potent greenhouse gas (GHG) with atmospheric concentrations that have nearly tripled since pre-industrial times. Wetlands account for a large share of global CH4 emissions, yet the magnitude and factors controlling CH4 fluxes in tidal wetlands remain uncertain. We synthesized CH4 flux data from 100 chamber and 9 eddy covariance (EC) sites across tidal marshes in the conterminous United States to assess controlling factors and improve predictions of CH4 emissions. This effort included creating an open-source database of chamber-based GHG fluxes (https://doi.org/10.25573/serc.14227085). Annual fluxes across chamber and EC sites averaged 26 ± 53 g CH4 …

Vegetation Masking Of Remote Sensing Data Aids Machine Learning For Soil Fertility Prediction, Hans Edwin Winzeler, Marcelo Mancini, Joshua Michael Blackstock, Zamir Libohova, Phillip R. Owens, Amanda J. Ashworth, David Miller, Sergio Silva

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Soil nutrient content varies spatially across agricultural fields in hard-to-predict ways, particularly in floodplains with complex fluvial depositional history. Satellite reflectance data from the Sentinel-2 (S2) mission provides spatially continuous land reflectance data that can aid model development when used with point observations of nutrients. Reflectance from vegetation is assumed to obstruct land reflectance of bare soil, such that researchers have masked vegetation in models. We developed a routine for masking vegetation within Google Earth Engine (GEE) using Random Forest classification for iterative application to libraries of S2-images. Using gradient boosting, we then developed soil nutrient models for surface soils …

Data Analysis On Predicting The Top 12 Fantasy Football Players By Position, Alan Abadzic, Jacquelyn Cheun, Milan Patel

SMU Data Science Review

Fantasy football enthusiasts rely on rankings populated by their platform of choice to draft winning teams and make strategic roster decisions. This study presents a comprehensive analysis of player performance data to forecast the top 12 fantasy points performers per position for the upcoming season. Leveraging machine learning techniques and historical data, our model identifies key performance indicators and trends to inform player evaluations. Insights gleaned from positional trends, breakout candidates, risk assessment, and matchup analysis offer a competitive edge. By addressing limitations, ethical considerations, and avenues for future research, this study contributes to the advancement of fantasy sports analysis …

Enhancing Imputation Accuracy: A Multi-Faceted Approach For Missing Data In Chicago Arrest Records, Steve Bramhall, Jae Chung, Nicholas Mueller

SMU Data Science Review

This paper introduces a novel approach to enhance the imputation process for missing data, utilizing crime records from Chicago with arrests as the target feature. Robust imputation techniques are crucial in the era of burgeoning datasets for generating reliable insights. Our core objective is to present an innovative method that improves imputation techniques, augmenting model performance and bolstering the reliability of analytical outcomes. Leveraging numeric crime data, we establish a Gradient Boosting (GBM) baseline model, then introduce ensemble methods including Random Forest and Decision Trees for further refinement. By systematically exploring multiple imputation processes, we establish a baseline for comparative …

Geospatial Temporal Crime Prediction Using Convolution And Lstm Neural Networks: Enhancing The Las Vegas Cardiff Model, Corey D. Holmes, Christian Orji, Chris Papesh

SMU Data Science Review

According to the Department of Justice, more than half of violent crimes go unreported to law enforcement in the United States (Kollar et al., 2018). This data gap reduces the opportunity to implement proven solutions in the areas with the greatest need. In 1996, Dr. Shepherd developed the Cardiff Model with the aim of bringing together hospitals, law enforcement, and community leaders through the sharing of data. We partnered with ongoing efforts to implement the Cardiff Model in Las Vegas, Nevada. Our goal was to provide a geospatial temporal model that can predict the next 30 days of crime. By …

Rethinking Retrieval Augmented Fine-Tuning In An Evolving Llm Landscape, Nicholas Sager, Timothy Cabaza, Matthew Cusack, Ryan Bass, Joaquin Dominguez

SMU Data Science Review

This study explores the utilization of Retrieval Augmented Fine-Tuning (RAFT) to enhance the performance of Large Language Models (LLMs) in domain-specific Retrieval Augmented Generation (RAG) tasks. By integrating domain-specific information during the retrieval process, RAG aims to reduce hallucination and improve the accuracy of LLM outputs. We investigate the use of RAFT, an approach that enhances LLMs by incorporating domain-specific knowledge and effectively handling distractor documents. This paper validates previous work, which found that RAFT can considerably improve the performance of Llama2-7B in specific domains. We also expand upon previous work into new state-of-the-art open-source models and other datasets with …

Enhancing Shap With Multi-Core Parallelization And Distributed Computation, Matthew David, William Jones, Hayley Horn

SMU Data Science Review

In recent years, the adoption of complex machine learning algorithms, often perceived as “black box” models, has grown exponentially across various disciplines. However, the lack of understanding regarding how these models come to their predictions often fosters skepticism and mistrust. In response to the demand for transparency and interpretability, Explainable AI techniques, such as SHapley Additive exPlanations (SHAP), have emerged as powerful tools for comprehending and trusting these algorithms. However, SHAP has an exponential computational demand O( x2 ), where x is the number of features. This becomes increasingly problematic with the larger datasets standard in most industries. Many frameworks …