Digital Commons Network^™

Humans Vs. Llms On Open Domain Scientific Claim Verification: A Baseline Study, Benjamin Curtis, Stefania Dzhaman, Matthew Maisonave, Jian Wu

Computer Science Faculty Publications

Verifying scientific claims is challenging for the general public because most people lack domain knowledge. Manual verification by subject domain experts is accurate, but it is obviously not scalable to meet the rising number of scientific claims on the Web. Whether the emerging large language models and large reasoning models can be used for scientific claim verification, and how their performances compare to humans, are still research questions. To this end, we developed a new benchmark MSVEC2 that consists of 138 claims from credible fact verification websites and science news outlets. Two tasks were given to both human and LLM …

Privshap: A Finer-Granularity Network Linearization Method For Private Inference, Xiangrui Xu, Zhenzhen Wang, Rui Ning, Chunsheng Xiu, Hongyi Wu

Computer Science Faculty Publications

Private inference applies cryptographic techniques like homomorphic encryption, garble circuit and secret sharing to keep both sides privacy in a client-server setting during inference. It is often hindered by the high communication overheads, especially at non-linear activation layers such as ReLU. Hence ReLU pruning has been widely recognized as an efficient way to accelerate private inference. Existing approaches to ReLU pruning typically rely on coarse hypothesis, which assume an inverse correlation between the importance of ReLU and linear layers or shallow activation layers have less importance for universal models, to assign the budgets according to the layer while preserving the …

Border Decriminalization As A State Project: Lessons From Marijuana And Assisted Suicide Legalization Across The United States, Victor C. Romero

Faculty Scholarship

My prior work argued for the decriminalization of border crossings without proof of specific intent to violate another law (like drug trafficking), which is even less likely to happen now than it was when the piece was published, given the current presidential administration’s zealous deportation strategy and Congress’s seeming acquiescence. As such, I advocate for a second-best solution involving federal-state cooperative agreements wherein border states abutting both Mexico and Canada are given the option by the federal government to pass local legislation decriminalizing border crossings into their states as their communities desire. To the extent that the current presidential administration …

Integrated Roadside Vegetation Management Technical Manual [2025], Kristine Nemec, Josh Brandt, Kirk Henderson, Jim Uthe

Faculty Book Gallery

The objective of this publication is to provide basic technical support for new and existing Iowa county roadside programs. This manual is also intended to provide guidance to policymakers and engineers interested in adopting or expanding integrated roadside vegetation management in county rights-of-way.

Position: Benchmarking Is Broken - Don't Let Ai Be Its Own Judge, Zerui Cheng, Stella Wohnig, Ruchika Gupta, Samiul Alam, Tassallah Abdullahi, João Alves Ribeiro, Christian Nielsen-Garcia, Saif Mir, Siran Li, Jason Orender, Seyed Ali Bahrainian, Daniel Kirste, Aaron Gokaslan, Carsten Eickhoff, Pramod Viswanath, Ruben Wolff

Computer Science Faculty Publications

The meteoric rise of Artificial Intelligence (AI), with its rapidly expanding market capitalization, presents both transformative opportunities and critical challenges. Chief among these is the urgent need for a new, unified paradigm for trustworthy evaluation, as current benchmarks increasingly reveal critical vulnerabilities. Issues like data contamination and selective reporting by model developers fuel hype, while inadequate data quality control can lead to biased evaluations that, even if unintentionally, may favor specific approaches. As a flood of participants enters the AI space, this "Wild West" of assessment makes distinguishing genuine progress from exaggerated claims exceptionally difficult. Such ambiguity blurs scientific signals …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Computer Science Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

A Real-Time Approach To Capture Ambient And Focal Attention In Visual Search, Gavindya Jayawardena, Yasith Jayawardana, Yasasi Abeysinghe, Bhanuka Mahanama, Sampath Jayarathna, Jacek Gwizdka

Computer Science Faculty Publications

During visual search, individuals’ attention shifts between ambient and focal states in response to task demands and stimuli. The ambient/focal coefficient K is a statistically validated measure of these states, computed offline from fixation duration and saccade amplitude data. While current methods compute K offline, real-time computation could enable applications such as monitoring user attention, creating attention-adaptive user interfaces, and optimizing graphics rendering. However, real-time computation of K requires stable estimates for the parameters of fixation duration and saccade amplitude distributions. Since these distributions are heavy-tailed, the real-time estimates exhibit high variance and slow convergence. To overcome this, we propose …

Research News, Publications, 2025, Volume 4, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of October 1 - December 31, 2025.

Research News, Publications, 2025, Volume 3, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of July 1 - September 30, 2025.

Research News, Publications, 2025, Volume 2, Soumyajit Majumdar

Publications (2015-)

Publications that appeared during the period of April 1 - June 30, 2025.

Social Support Networks’ Influence On First-Generation Professionals’ Career Success, Melissa-Ann M. Lagunas

Clinical Psychology Dissertations

This dissertation examines how perceived social support influences career success among first-generation professionals (FGPs)—individuals who are first in their families to pursue white- collar careers. Drawing on Seibert et al.'s (2001) Social Capital Theory of Career Success, I investigate direct and indirect pathways through which social support affects three dimensions of career success: sense of belonging, professional flourishing, and career satisfaction, while exploring mediating roles of perceived support network quality and resilience. A sample of 230 FGPs (Mage = 31.9 years, SD = 5.32) completed a 62-item online survey hosted on Qualtrics. Participants represented diverse professional disciplines classified into five …

Douglas K. Newell Oral History, Douglas K. Newell, Katherine O'Neil

50 Years of Douglas K. Newell

The following is the written transcript of the oral history of Edmund O. Belsheim Professor of Law Emeritus Douglas K. Newell. This transcript has been slightly edited by Professor Newell for accuracy.

The interviews capturing the oral history were conducted by Katherine O'Neil '77 during 2023-2024, transcribed and then edited by Professor Newell in 2025.

The history chronicles Professor Newell's life from his early humble beginnings in Glendale, California, attending Pomona College, being accepted into Harvard Law School, his Clerkship with U.S. District Judge for Los Angeles' Central District William M. Byrne, his brief foray into private practice, and his …

Ieee 802.11n And Ieee 802.11ax Networks Under Various Propagation Models, Jun Peng

Electrical and Computer Engineering Faculty Publications

IEEE 802.11n networks are the first generation of Wi-Fi networks to reach data rates of hundreds of megabits per second. They are also the first to use MIMO technologies in Wi-Fi networks. They can operate in both 2.4 GHz and 5 GHz frequency bands and use 20 or 40 MHz channel width. Similarly, IEEE 802.11ax networks can operate in both 2.4 GHz and 5.0 GHz frequency bands and use 20, 40, 80, or 160 MHz channel width. For channel access, IEEE 802.11ax networks use CSMA/CA, multi-user MIMO (MU-MIMO), and OFDMA. They can reach data rates of multiple gigabits per second. …

Shooting For The Stars: The Place Of International Economic Law In The International Legal Order, Valentina Vadi

Indian Journal of International Economic Law

In the universe of international law, the galaxy of international economic law (IEL) consists of various legal instruments, institutions, and experts that – like stars, planets, and vast clouds of dust – are all bound together by gravity. Like cosmonauts, international economic courts ‘must look for reliable reference points in the known legal cosmology.’2 This article aims to contextualise the galaxy of international economic law within the universe of international law, discuss its role within the same, and identify some reference points that can help adjudicators navigate by the stars.

Beyond A Boundary Of Systemic Anti-Black Racism In The Workplace In Canada, Adelle Blackett

Dalhousie Law Journal

In this lecture, I will, however, focus on one of the legacies of slavery, that is, the largely untold story of racial segregation in the world of work in Canada. We have come so effectively, and rightly, to focus on the effects of discrimination, that we may have inadvertently walked past the history. Reclaiming this history will comprise the first part of my talk.

The second part of my talk will reference the emergence of the duty of fair representation. I will seek to illustrate the weight of the erasure of anti-Black racism through this duty. In other words, far …

Bridging Movement Lawyering & International Human Rights Advocacy, Citlalli Ochoa

Scholarly Works

The human rights field is often criticized for its lack of enforcement and implementation, lawyering methodologies, and its roots in imperialism, exceptionalism, and Eurocentric values. In response to some of these critiques, human rights scholars and advocates have embraced more grassroots approaches that in many instances resemble the movement lawyering methodologies employed in social justice advocacy in the United States. In the same way that movement lawyers have centered impacted communities and engaged in long term, coordinated legal and political advocacy to achieve normative change, human rights advocates have used the international human rights framework to exert political pressure, facilitate …

Artificial Intelligence In Science And Society: The Vision Of Usern, Tommaso Dorigo, Gary D. Brown, Carlo Casonato, Artemi Cerda, Joseph Ciarrochi, Mauro Da Lio, Nicole D'Souza, Nicolas R. Gauger, Steven C. Hayes, Stefan G. Hofmann, Robert Johansson, Marcus Liwicki, Fabien Lotte, Juan J. Nieto, Giulia Olivato, Peter Parnes, George Perry, Alice Plebe, Idupulapati M. Rao, Nima Rezaei, Fredrik Sandin, Andrey Ustyuzhanin, Giorgio Vallortigara, Pietro Vischia, Niloufar Yazdanpanah

All Peer-Reviewed Publications

The recent rise in relevance and diffusion of Artificial Intelligence (AI)-based systems and the increasing number and power of applications of AI methods invites a profound reflection on the impact of these innovative systems on scientific research and society at large. The Universal Scientific Education and Research Network (USERN), an organization that promotes initiatives to support interdisciplinary science and education across borders and actively works to improve science policy, collects here the vision of its Advisory Board members, together with a selection of AI experts, to summarize how we see developments in this exciting technology impacting science and society in …

Global Strategies To Manage Huanglongbing (Hlb) And Its Vectors: Insights And Implications For The Mediterranean Region, Meritxell Pérez-Hedo, Mark S. Hoddle, Fernando Alferez, Lochy Batista, George A.C. Beattie, Shourish Chakravarty, Paul Holford, Fathiya Mbarak Khamis, Inusa Jacob Ajene, Aruna Manrakhan, Paul H. Fourie, Maritza Luis, Eduardo Osorio-Hernández, Mamoudou Sétamou, Alejandro Tena, Pedro Takao Yamamoto, Tara Wade, Changyong Zhou, Nian Wang, Lukasz L. Stelinski, Alberto Urbaneja

All Peer-Reviewed Publications

Huanglongbing (HLB), also known as citrus greening disease, poses a severe threat to the global citrus industry. This disease is caused by three species of bacteria, ‘Candidatus Liberibacter asiaticus’, ‘C. L. africanus’, and ‘C. L. ameri-canus’. The primary pathogen vectors are the Asian citrus psyllid (Diaphorina citri Kuwayama, Hemiptera: Psyllidae) and the African citrus psyllid (Trioza erytreae Del Guercio, Hemiptera: Triozidae). The disease is incurable, and its management relies on reducing vector densities and the adverse effects of bacterial infections on host trees. Managing psyllid vec-tors, especially D. citri, has proven exceptionally challenging due to its rapid spread and subsequent …

Academic Procrastination And Health Behaviors Among University Students, Shelley D. Sadler

Doctor of Nursing Practice Projects

Abstract

Sixty-eight percent of college and university students have indicated that procrastination is their greatest challenge to academic accomplishment. Academic procrastination has been associated with suboptimal health behaviors such as lack of sleep and poor diet due to increased stress and anxiety levels from this academic procrastination. The purpose of this Doctor of Nursing Practice Quality Improvement Project was to provide evidence-based online modules to help university students lessen academic procrastination while increasing healthy behaviors. Participants included students in their first through fourth semesters at a regional mid-South university. The Academic Procrastination Scale (APS) and the Wellness Behavior Inventory (WBI) …

Advancing Multivariate Time Series Similarity Assessment: An Integrated Computational Approach, Franck B.N. Tonle, Henri E.Z. Tonnang, Milliam M.Z. Ndadji, Maurice Tchoupe Tchendji, Armand Nzeukou, Kennedy Senagi, Saliou Niassy

All Peer-Reviewed Publications

Data mining, particularly multivariate time series data analysis, is crucial in extracting insights from complex systems and supporting informed decision-making across diverse domains. However, assessing the similarity of multivariate time series data presents several challenges, including dealing with large datasets, addressing temporal misalignments, and necessitating efficient and comprehensive analytical frameworks. A novel integrated computational approach, Multivariate Time series Alignment and Similarity Assessment (MTASA) is proposed to address these challenges. MTASA is built upon a hybrid methodology designed to optimise time series alignment, complemented by a multiprocessing engine that enhances the utilisation of computational resources. This integrated approach comprises four key …

A Review On Knowledge And Information Extraction From Pdf Documents And Storage Approaches, Salvador D. Atagong, Henri Tonnang, Kennedy Senagi, Mark Wamalwa, Komi M. Agboka, John Odindi

All Peer-Reviewed Publications

Introduction: Automating the extraction of information from Portable Document Format (PDF) documents represents a major advancement in information extraction, with applications in various domains such as healthcare, law, or biochemistry. However, existing solutions face challenges related to accuracy, domain adaptability, and implementation complexity. Methods: A systematic review of the literature was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to examine approaches and trends in PDF information extraction and storage approaches. Results: The review revealed three dominant methodological categories: rule-based systems, statistical learning models, and neural network-based approaches. Key limitations include the rigidity of rule-based …

Performance Of The Dssat Manihot-Cassava Model For Cassava Cultivation In The Recôncavo Baiano, Diego M. De Melo, Paola De F. Bongiovani, Fabio L.S. Costa, Patricia Moreno-Cadena, Alexandre B. Heinemann, Julian Ramirez-Villegas, Mauricio A. Coelho Filho

All Peer-Reviewed Publications

The aim of the present study was to calibrate the DSSAT MANIHOT-Cassava model with information from cassava varieties grown in the Recôncavo Baiano region, Bahia state, Brazil. The database used to calibrate the model was obtained in the dry sub-humid tropical climate in Cruz das Almas city, from 2019 to 2020. The model was calibrated with experimental data obtained under irrigated and rainfed conditions for the BRS Novo Horizonte and Eucalipto varieties. The calibration was carried out by adjusting parameters related to the characteristics of each variety. Model performance was evaluated with statistical indices that indicate the precision and accuracy …

Predicting Food Prices In Kenya Using Machine Learning: A Hybrid Model Approach With Xgboost And Gradient Boosting, Benard O. Ogol, Evans Omondi, John Olukuru, Betsy Muriithi, Kennedy Senagi

All Peer-Reviewed Publications

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the application of machine learning methods, employing a hybrid approach that combines XGBoost and gradient boosting, to predict food prices in Kenya. The food prices data from the World Food Programme, covering the period from January 2006 to September 2024, as well as currency exchange rates data from the Central Bank of Kenya in US dollars (USD) and inflation rates data, were collated and preprocessed to be ready for analytics and machine learning. The augmented …

Integrating Machine Learning And Symbolic Regression For Predicting Damage Initiation In Hybrid Frp Bolted Connections, Sherif Sorour

Mechanical Engineering

No abstract provided.

Automated Vulnerability Scanning And Security Audit Framework For Maritime Systems, Avanthika Vineetha Harish

School of Engineering, Computing and Mathematics Theses

The maritime industry is a well-established sector, with the shipping industry dating back hundreds of years. The devices in this sector differ from those in the Information Technology (IT) sector in their usage, operations, hardware, andprotocols. Technological advancements have introduced new challenges in the sector, including the increased risk of cyber attacks. To effectively identify, respond to, and analyse these threats, it is essential to understand the cyber securityvulnerabilities in maritime systems and system-of-systems.Currently, there are no standardised methods or automated tools for conducting cyber security testing of maritime systems. This thesis presents an automated vulnerability scanning and security audit …

A Framework For Tailored Organisational Cyber Security Training, Zinnar Ghasem

School of Engineering, Computing and Mathematics Theses

Zinnar Ahmed Ghasem A framework for tailored organisational cyber security training AbstractSociety is increasingly becoming dependent on cyberspace; in such it is becoming an integral part of every-day life of most people in both work and home context. This dependency spans across individuals, businesses, and organisations including governments who are relying on cyberspace for various services, ranging from email to social networking, and from cloud computing to ecommerce and financial automated process and transactions. These services are vulnerable and face sophisticated cyber threats, risks and attacks, and potentially can result in financial losses and compromise the confidentiality, integrity, and availability …

Synthesis Study: Review Of Durability And Performance Of The Latest Epoxy-Coated Rebar, Julio A. Ramirez, Luis A. Quesada Jimenez

JTRP Technical Reports

The use of de-icing salts on roads during the winter months has caused corrosion damage to bridge reinforcements, which has increased maintenance costs. The corrosion protection system most widely used by various State Departments of Transportation is a combination of quality concrete, adequate cover, and fusion bonded epoxy-coated reinforcing bars. This report contains a summary of the latest developments in the fabrication and use of fusion epoxy-coated and Allium (stainless steel coated) reinforcing steel within concrete bridge decks and one-way solid slab and T-beam bridges. The study findings indicate that although original epoxy materials are still used, significant improvements in …

Assessing The Asset Management Programs Of Locals: Bridges And Pavement Conditions, Richard Ajagu, Dongyoon Song, David Holguin Mejia, Deepak Benny, Mohammadhosein Pourgholamali, Isaiah C. Mwamba, Kumares Sinha, Samuel Labi

JTRP Technical Reports

Indiana’s 2016 House Enrolled Act (HEA) 1001 provided a funding mechanism for transportation infrastructure that required Local Public Agencies (LPAs) to have an Asset Management Plan (AMP) to be eligible for funding. In 2022, the Indiana General Assembly desired to know the extent to which LPAs had adopted AMPs in response to this legislation. This study’s literature review found that LPAs nationwide are increasingly adopting asset management practices. Analysis of aggregate data on local road expenditures and revenues in Indiana showed significant reductions in maintenance expenditures in post-HEA 1001-2016 years, suggesting the efficacy of the 2016 legislation. The data trend …

Stone Matrix Asphalt (Sma) Overlay Performance Evaluation, Jusang Lee, Jongmyung Jeon, Abdullah Al Mamun, Maya Khajehvand, John E. Haddock

JTRP Technical Reports

Stone matrix asphalt (SMA) is a specialized asphalt mixture designed to improve pavement performance by combining a coarse aggregate skeleton with a high-binder content mortar. This innovative design, adopted by the Indiana Department of Transportation (INDOT) in the late 1990s, offers distinct advantages over conventional hot mix asphalt (HMA). Currently, INDOT SMA-surfaced pavements are undergoing a second round of rehabilitation, which presents a valuable opportunity to assess their performance and return on investment (ROI). In Indiana, steel slag is used as the primary SMA coarse aggregate because of its toughness and durability. However, it may be possible to use other, …

Autonomous Mower Pilot Project, John T. Evans, Greg M. Shaver, Michael A. Mardikes, Nathan C. Sprauge, Timothy J. Wiegman, Shreyas Supe, Ethan M. Brown

JTRP Technical Reports

The Indiana Department of Transportation (INDOT) spends approximately $19 million annually on roadside mowing, which is a process that is time-consuming, costly, and poses safety risks. Automated mowing solutions have the potential to reduce costs and increase safety, but they will need to be extremely well tested before being deployed. In this work, data from current mowing practices was collected using machine mounted cameras, which was used to inform the creation of a digital twin environment that allows for rigorous initial testing of potential autonomous solution with no risk. The digital twin was created using digital elevation models of Indiana …