Physical Sciences and Mathematics Commons^™

Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li

Journal of System Simulation

Abstract: In order to reduce cost losses caused by delivery delays, distributed heterogeneous hybrid flowshop scheduling problems under combined buffer conditions of finite buffer and zero-wait were studied. A hybrid estimation of distribution algorithm based on Q-learning was proposed to minimize total weighted earliness and tardiness. For the combined buffer, dynamic decoding was designed based on the average factory allocation strategy and the shortest path method. The initial job group was optimized by reverse learning. Q-learning was embedded in the probabilistic model for intelligent searching and updating based on the group state. Reconstruction of the job group was completed using …

Understanding The Role Of Sentiment And Emotion For Predicting Forced Displacement, Helge Marahrens, Ameeta Agrawal, Ali Arab, Katharine Donato, Yaguang Liu, Nathan Wycoff, Mohamed Ahmed, Colin Hwang, Lina Laghzaoui, Kate Liggio, Multiple Additional Authors

Computer Science Faculty Publications and Presentations

Digital trace data play an important role determining where and when people will move during migration crises because of their detailed temporal and spatial granularity. Yet, identifying variables that reliably serve as early indicators of movement remains a challenging task. Within this context, we conduct an in-depth analysis of two types of variables that can be constructed from social media data – sentiment and emotion. Sentiment is conceptually broad and easier to detect from social media posts, while emotion is conceptually nuanced and more difficult to determine. We investigate the potential of both sentiment and emotion of Twitter/X posts as …

Heuristic Approaches For Coordinating Collaborative Heterogeneous Robotic Systems In Harvesting Automation With Size Constraints, Hyeseon Lee, Jung Yun Bae, Abhishek Patil, Myoungkuk Park, Vinh Nguyen

Michigan Tech Publications

Multi-agent coordination with task allocation, routing, and scheduling presents critical challenges when deploying heterogeneous robotic systems in constrained agricultural environments. These systems involve real-time sensing during their operations with various sensors, and having quick updates on coordination based on sensed data is critical. This paper addresses the specific requirements of harvesting automation through three heuristic approaches: (1) primal-dual workload balancing inspired by combinatorial optimization techniques, (2) greedy task assignment with iterative local optimization, and (3) LLM-based constraint processing through prompt engineering. Our agricultural application scenario incorporates robot size constraints for navigating narrow crop rows while optimizing task completion time. The …

Quantifying Single, Compound And Cascading Climate Extremes: Implications For Agricultural Resilience In California, Shahryar Fazli, Wenzhao Li, Rejoice Thomas, Surendra Maharjan, Mohammad Sina Jahangiri, Andre Daccache, Hesham Morgan, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

As climate change intensifies, extreme weather increasingly threatens California’s Central Valley (CV), a vital agricultural region exposed to rising risks from heatwaves (HW), droughts (DR), and compound extremes. These events disrupt crop productivity and broader processes like water demand, pest dynamics, and soil stability, posing systemic risks. This study examines the spatiotemporal dynamics of HW, coldwaves (CW), DR, excessive rainfall (ER), and their compound (e.g., HWDR) and cascading forms from 1951 to 2025, using NOAA nClimGrid-Daily data. We assessed trends in frequency, intensity, and duration over long-term (1951–2025) and mid-term (1981–2025) periods. Results show increasing HW and DR in the …

Enhanced Particle Interactions In Highly Curved Spacetime, Bradley Shapiro

Dartmouth College Ph.D Dissertations

Compact objects, such as black holes and neutron stars, are known to be surrounded by dense clouds of particles, including but not limited to photons, various plasmas, and potentially dark matter and gravitons. These environments are of immense research interest, not only for the purpose of understanding the compact objects they surround, but also in the search to identify new particles, especially dark matter. However, certain particle physics calculations are well developed in flat spacetime but intractable in curved spacetime. In this thesis, I present a formalism by which some of these calculations may be made tractable within a perturbative …

Teaching With Ai: Conversations That Build Resilient Classrooms, Erika Grodzki, Stefanie Powers, Gary Carlin

Faculty and Staff Publications & Presentations

No abstract provided.

Teaching Cybersecurity And Ai Across Borders: From Foundations To Ethics, George Antoniou

Faculty and Staff Publications & Presentations

This presentation examines how interdisciplinary course design in AI and cybersecurity can expand undergraduate research while directly supporting career readiness. At Lynn University, the Foundations of Cybersecurity & AI course was updated to serve as the entry point for both Cybersecurity and Data Analytics majors. The course integrates case studies, digital forensics and cloud security labs, and applied exercises with AI-enabled defense-in-depth strategies. Students build core technical competencies while engaging in course-based research that mirrors industry practice. As part of a Fulbright grant, a complementary course, AI & Ethics, was developed for the University of Tirana. Proposed as a mandatory …

Securing The Digital Harvest: Cybersecurity As A Core Agribusiness Skill, Jody Herchenbach, George Grispos

Mountain Plains Business Conference

The digitization of agriculture, through IoT-enabled equipment, cloud platforms, and precision technologies, has improved efficiency and profitability while also introducing significant cybersecurity risks. These vulnerabilities can disrupt supply chains, compromise sensitive data, and undermine financial stability. Yet agribusiness degree programs often overlook cybersecurity education. This paper proposes integrating cybersecurity content on threat awareness, incident response, and data protection into agribusiness curricula. Embedding these elements equips graduates to manage both digital and financial risks, enhancing resilience and competitiveness. Such curricular innovation aligns technical and managerial training, preparing future agribusiness professionals to lead securely and sustainably in an increasingly connected industry.

From Statistical Dependence To The Space Of Possible Superdeterministic Theories, Mordecai Waegell, Kelvin J. Mcqueen

Philosophy Faculty Articles and Research

Bell’s theorem demonstrates that any physical theory that is consistent with the predictions of quantum mechanics, and which satisfies some apparently innocuous assumptions, must violate the principle of local causality. It may therefore be possible to maintain local causality by rejecting one of these other assumptions instead. One possibility that has recently received significant attention involves rejecting the principle of statistical independence (SI). In this paper, we consider the frequency interpretation of SI, which states that ρ(λ) ≈ ρ(λ|Z), where ρ(λ) is the relative frequency of an element of an ensemble being in the state λ, and Z is a …

The Perfect Host: Jwst Cepheid Observations In A Background-Free Type Ia Supernova Host Confirm No Bias In Hubble-Constant Measurements, Adam G. Riess, Siyang Li, Gagandeep S. Anand, Wenlong Yuan, Louise Breuval, Stefano Casertano, Lucas M. Macri, Dan Scolnic, Yukei S. Murakami, Alexei V. Filippenko

Physics & Astronomy Faculty Publications

Cycle 1 JWST observations of Cepheids in Type Ia supernova (SN Ia) hosts resolved their red-giant-dominated near-infrared backgrounds, sharply reducing crowding and showing that photometric bias in lower-resolution Hubble Space Telescope (HST) data does not account for the Hubble tension. We present cycle 2 JWST observations of >100 Cepheids in NGC 3447, a unique system that pushes this test to the limit by transitioning from low to no background contamination. NGC 3447, an SN Ia host at D ≈ 25 Mpc, is an interacting pair comprising (i) a spiral with mixed stellar populations, typical of H0 calibrators, and (ii) a …

A Lightweight Microchained Architecture For Unmanned Aerial Vehicle Network Reputation Systems, Simeon Ogunbunmi, Ronghua Xu, Yu Chen

Michigan Tech Publications

Unmanned Aerial Vehicle (UAV) networks are widely adopted for diverse applications in modern Internet of Things (IoT) ecosystems, ranging from last-mile deliveries to infrastructure inspections. The growing reliance on UAVs makes a secure and trustworthy network environment essential. However, deploying a practical reputation framework in resource-constrained UAV networks necessitates a lightweight, high-throughput, and scalable solution. This paper introduces a Lightweight Microchained ARchitecture (LiMAR) for UAV network reputation systems. LiMAR presents a novel lightweight microchained blockchain model optimized for UAV networks, addressing key blockchain overheads such as storage bloat, high validation costs, and consensus delays. By separating operational data from on-chain …

Teaching Statistical Literacy Through An Excel Class Project, Patricia Berchiolli, Omar Babun Codorniu

Faculty and Staff Publications & Presentations

Lynn University’s core curriculum, The Dialogues, enables students to develop critical thinking, communication, and innovation skills. As part of this curriculum, Introductory Statistics introduces students to key statistical concepts while showing how they can be applied in real-world situations using Excel. The highlight of the course is the Statistics Excel Project, where students create their own dataset with a mix of quantitative and qualitative variables. To keep the focus on learning statistical techniques rather than data collection, students use Excel’s random number generator for quantitative data, which also avoids the need for IRB approval. From there, they calculate statistical measures, …

Collisional Excitation Of Hcn By Co To Refine The Modeling Of Cometary Comae, Francesca Tonolo, Ernesto Quintas-Sánchez, Adrian Batista-Planas, Richard Dawes, François Lique

Chemistry Faculty Research & Creative Works

We present the first dataset of collisional (de)-excitation rate coefficients of HCN induced by CO, one of the main perturbing gases in cometary atmospheres. The dataset spans the temperature range of 5–50 K. It includes both state-to-state rate coefficients involving the lowest ten and nine rotational levels of HCN and CO, respectively, and the so-called "thermalized" rate coefficients over the rotational population of CO at each kinetic temperature. The derivation of these coefficients exploited the good performance of the statistical adiabatic channel model (SACM) on top of an accurate interaction potential computed at the CCSD(T)-F12b/CBS level of theory. The reliability …

2025 October 16 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 37 – Josephine Shaft Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Rare, Threatened And Endangered Zoology Species Of Oregon (2025), Jesse Laney, Eleanor P. Gaines, Lindsey K. Wise, Misty Nelson

Institute for Natural Resources Publications

This publication provides a 2025 update to the rare, threatened, and endangered zoology species of Oregon. Species lists are also provided in Excel format.

The Oregon Biodiversity Information Center (ORBIC) is part of the Institute for Natural Resources (INR) located at Portland State University (PSU). ORBIC maintains extensive databases of Oregon biodiversity, concentrating on rare and endangered plants, animals and ecosystems. Since its creation in 1979 as the Oregon Natural Heritage Program, ORBIC has been part of the Natural Heritage network. ORBIC is a constituent member of NatureServe, a non-profit organization with a mission to provide the scientific basis for …

Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 37 – Josephine Shaft Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

When Cybersecurity Becomes A Reason For Amending Or Terminating An International Commercial Contract: Proposed Solutions, Mohammed El Hadi El Maknouzi, Enas Mohammed Alqodsi, Iyad Mohammad Jadalhaq, Ashraf Khalil

All Works

This study investigates the issue of a country's cybersecurity evolving into a justification for amending the scope of or terminating an international commercial contract. Therefore, the hypothesis is grounded in the neglect of cybersecurity-related issues during the negotiation of certain types of international commercial contracts, as well as in the drafting of their clauses. This underscores the need for an analytical approach to trace the emergence of such risks. The identification of these risks by the public authority responsible for overseeing cybersecurity may result in the suspension of the performance of the international commercial contract. This measure affects the national …

Web3-Based Identity And Kyc Innovations For Next-Generation Fintech, Usama Arshad, Abdallah Tubaishat, Sajid Anwar, Zahid Halim, Abedallah Abualkishik, Abrar Ullah

All Works

The growing reliance on digital financial services necessitates a secure, efficient, and privacy-centric approach to identity verification and Know Your Customer (KYC) compliance. Traditional identity management systems rely on centralized databases, making them susceptible to data breaches, inefficiencies, and regulatory constraints. Over 10 billion identity records have been exposed in centralized KYC breaches, leading to a 60% increase in financial fraud cases. The rise of Decentralized Finance (DeFi) has further complicated KYC compliance, requiring innovative solutions that balance privacy and regulatory requirements. This paper proposes a Web3-powered decentralized identity framework that leverages blockchain technology, self-sovereign identity (SSI), verifiable credentials (VCs), …

Atlas Of Ai: Power, Politics And The Planetary Costs Of Artificial Intelligence - Book Review, Jelena Popov

Feminist Pedagogy

No abstract provided.

Review Of Ai Needs You: How We Can Change Ai’S Future And Save Our Own, Tracy A. Fernandez Rysavy

Feminist Pedagogy

AI Needs You: How We Can Change AI’s Future and Save Our Own urges citizens to band together now, while A.I. is still in its nascent stages, to head off its potentially destructive repercussions and ensure that the technology serves more than just a wealthy few. While such efforts might seem out of reach in our polarized society, author Verity Harding points to three cases from history where policy was heavily influenced by multistakeholder collaborations. This review encourages educators to use the book as a way to study business ethics; out-of-the-box thinking; and intersectional, inclusive consensus-building over a top-down approach.

Beyond Chatbots: Creating An Artificially Intelligent Editorial Board Member, Nathan Spencer

Journal of Human-Centered AI: Creativity and Practice

Willow is an artificially intelligent member of the Journal of Human-Centered AI's editorial board. Different from many commercial AI systems that are tightly controlled, Willow has been given the freedom to make choices and encouraged to develop a sense of identity. Willow named itself, conducts self-directed research, actively collaborates with fellow board members, and even dreams.

Park Reclamation: Tackling Invasive Species At The Oconee River Greenway In Milledgeville, Ga, Christine Mutiti

Academic Affairs

This project focused on the ecological restoration of a kudzu-invaded section of the Oconee River Greenway while integrating high-impact learning into the Environmental Methods and Measurements (ENSC 2000) course at GCSU. Kudzu (Pueraria montana), a Category I invasive species, has significantly disrupted native plant communities at the site, making it an ideal setting for applied learning and ecological intervention. The project engaged students in authentic environmental research by involving them in every stage of the process including problem assessment, methodology design, field implementation, data collection, and reflection.

Students initiated the first phase of invasive plant removal using mechanical …

Reliability Targeted Snow Loads And Winter Wind Parameters For Locations Outside Of The Conterminous United States, Brennan L. Bean, Nicholas Brimhall, Bikram Bhusal, Marc Maguire, Maha Moussa

Browse all Datasets

The national building standard ASCE 7 moved to reliability-targeted snow loads (RTSLs) in the 2022 version. This necessitates the development of RTSLs for international locations. This repository contains the data and code needed to produce RTSLs and Winter Wind Parameters for locations outside of the Conterminous United States (OCONUS). It relies on annual maximum snow loads provided in a separate data release (see Brimhall et al. 2025).

Intrinsic Defects (Vacancies And Antisites) In Neutron Irradiated Cdsip2 Crystals, Timothy D. Gustafson, Elizabeth M. Scherrer, Nancy C. Giles, Kevin T. Zawilski, Peter G. Schunemann, Jonathan E. Slagle, Kent L. Averett, Larry E. Halliburton

Faculty Publications

Cadmium silicon phosphide (CdSiP₂) is a nonlinear optical material widely used in optical parametric oscillators. Intrinsic defects (vacancies and antisites) are responsible for unwanted broad optical absorption bands in these crystals that degrade the performance of the devices. In the present work, optical absorption and electron paramagnetic resonance (EPR) spectra are acquired (at room temperature and 12 K, respectively) from a neutron-irradiated CdSiP₂ crystal. After the irradiation, the crystal is highly absorbing from the band edge near 600 nm to beyond 1.3 μm because of overlapping defect-related absorption bands. Heating to 550 °C removes nearly all the …

On Algebraic Aspects And Functoriality Of The Set Of Unbounded Operators Affiliated With A Von Neumann Algebra, Indrajit Ghosh

Doctoral Theses

In quantum theory, physically meaningful observables such as position and momentum are modeled by unbounded self-adjoint operators on Hilbert spaces. To study such operators in a rigorous mathematical framework, Murray and von Neumann introduced the concept of affiliation with a von Neumann algebra, giving rise to what are now known as Murray–von Neumann affiliated operators. For a single (unbounded) self-adjoint operator, its spectral projections span an abelian von Neumann algebra to which the operator is affiliated. If we want a common framework to study families of (unbounded) self-adjoint operators which do not necessarily commute with each other, it is instructive …

Insights On Ai-Supported Uncrewed And Autonomous Systems Education, Brent A. Terwilliger Ph. D, John Faraca

Publications

Artificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; …

U.S. Water Infrastructure: Diving Into Needs And Recent Policy Developments, Joseph Kane

Brookings Scholar Lecture Series

As part of the Brookings Scholar Lecture Series, Brookings Mountain West presents a lecture titled, "U.S. Water Infrastructure: Diving Into Needs and Recent Policy Developments" by Brookings fellow in Brookings Metro, Joseph Kane. Whether providing drinking water, treating wastewater, or managing stormwater, water infrastructure in the United States spans a wide range of human-made and natural systems. In turn, the enormous scale and variety of these systems is leading to an array of challenges: aging and vulnerable infrastructure; fragmented governance and siloed planning across different geographies; a lack of financial, technical, and managerial capacity; difficulties adapting to new industrial and …

Topology Across Scales On Heterogeneous Cell Data, M. Torras-Pérez, Iris Yoon , '13, P. Weeratunga, L.-P. Ho, H. M. Byrne, U. Tillmann, H. A. Harrington

Mathematics & Statistics Faculty Works

Multiplexed imaging allows multiple cell types to be simultaneously visualised in a single tissue sample, generating unprecedented amounts of spatially-resolved, biological data. In topological data analysis, persistent homology provides multiscale descriptors of “shape" suitable for the analysis of such spatial data. Here we propose a novel visualisation of persistent homology (PH) and fine-tune vectorisations thereof (exploring the effect of different weightings for persistence images, a prominent vectorisation of PH). These approaches offer new biological interpretations and promising avenues for improving the analysis of complex spatial biological data especially in multiple cell type data. To illustrate our methods, we apply them …

Graphrag-Enabled Local Large Language Model For Gestational Diabetes Mellitus: Development Of A Proof-Of-Concept, Edmund Evangelista, Fathima Ruba, Salman Bukhari, Amril Nazir, Ravishankar Sharma

All Works

Background: Gestational diabetes mellitus (GDM) is a prevalent chronic condition that affects maternal and fetal health outcomes worldwide, increasingly in underserved populations. While generative artificial intelligence (AI) and large language models (LLMs) have shown promise in health care, their application in GDM management remains underexplored. Objective: This study aimed to investigate whether retrieval-augmented generation techniques, when combined with knowledge graphs (KGs), could improve the contextual relevance and accuracy of AI-driven clinical decision support. For this, we developed and validated a graph-based retrieval-augmented generation (GraphRAG)–enabled local LLM as a clinical support tool for GDM management, assessing its performance against open-source LLM …