Digital Commons Network^™

Patent Searching With Uspto, Derwent Innovation And Lens.Org, Ibis Anette Moreno-Lozano

Day Family Research Lab Workshop Series

No abstract provided.

High-Resolution Lidar Observations Of Sedimentation-Induced Size Sorting Of Droplets Near A Laboratory Cloud Top, Fan Yang, Yong Meng Sua, Zipei Zheng, Jesse Anderson, Hamed F. Sadi, Jae Min Yeom, Suryadev Pratap Singh, Pei Hou, Will Cantrell, Ernie Lewis, Alex Kostinski, Raymond Shaw

Michigan Tech Publications

No abstract provided.

Nonlinear Excitation Control Of Multimachine Systems Via The Invariant-Set Design, Ehab Bayoumi

Mechanical Engineering

Power grids are inherently vulnerable to many uncertainties. All power networks are prone to instability because of the uncertainties inherent in the operation of power systems. Rotor-angle instability is a challenging issue, and if not properly managed, could give rise to cascading failures and even blackouts. This paper addresses the generator excitation system’s state feedback sliding mode control (SMC). The global system is divided into multiple subsystems to achieve decentralized control. A disturbance is defined as the influence of the system as a whole on a specific subsystem. The state-feedback controller is to be designed taking into account the disturbance …

Sorting It Out, Liza Bondurant, Jane M. Wilburne, Dana Pomykal Franz, Jamaal Young

Publications

We describe a card sorting activity called a Q-sort that teachers can use to foster reflection and discussion.

Orbital Stability Of Solitary Wave Solutions Of The Generalized Benjamin Equation, Leijin Cao, Binhua Feng, Zhaosheng Feng, Yichun Mo

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we study the existence and stability of solitary wave solutions for the generalized Benjamin equation in both the L2-critical and L2-supercritical cases by applying the variational methods and the non-homogeneous Gagliardo–Nirenberg inequality. Our main results generalize and complement the existing results in the literature.

Oregon State Rank Assessment For Plumed Clover (Trifolium Plumosum Var. Plumosum), Nora Dunkirk

Institute for Natural Resources Publications

Oregon state conservation status assessment for Plumed Clover (Trifolium plumosum var. plumosum) using NatureServe methodology, 2025.

An Exploratory Study Of Machine Learning-Based Open-Angle Glaucoma Detection Using Specific Autoantibodies, Naoko Takada, Yukitoshi Izumi, Charles F Zorumski, Et Al.

2020-Current year OA Pubs

No abstract provided.

German Memories Of Icaria: Carl Zwicker's "Four Years' Experience Of A Communistic Life" (1878), Philip Lockley

Communal Societies

No abstract provided.

Supporting Best Practices In Family Engagement: Our Week Of The Young Child Experience, Michelle Fazio Brunson, Faith S. Birdwell, April Giddens

Spark! Innovations in Early Childhood Education: A Research-to-Practice Journal for Educators

Family engagement is a collaborative process where early childhood professionals, families, and children build positive, goal-oriented relationships. Incorporating family engagement into preschool programs is not merely beneficial but essential for promoting holistic child development in programs where children feel safe, cared for, and secure. In this article, we share the benefits of effective family engagement activities for families with young children and describe how we celebrated the National Association for the Education of Young Children's 2025 Week of the Young Child.

Using Food As A Fun And Effective Teaching Tool In Preschool, Kelly Furr, Melani Duffrin, Eugene A. Geist

Spark! Innovations in Early Childhood Education: A Research-to-Practice Journal for Educators

Food is one of the most engaging, hands-on materials for preschool classrooms. This article highlights research from the Food FAN Academy (Furr, 2023), which demonstrates how food can be used as a teaching tool across early childhood learning environments. Practical strategies are provided for preschool teachers, including detailed lesson plans that connect to early math, science, literacy, and social development. The article emphasizes the importance of using everyday materials, cultural inclusivity, and active learning methods to promote curiosity, health awareness, and foundational skills in young learners.

Full Issue - Excelsior 18.1, Excelsior

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Creating A Decision-Making Curriculum For Students With And Without Disabilities In Grades P-12, Gina Riley, Elizabeth Klein, Alfonso Perez, Imani Irving Perez, Adriana D. Nathan

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Empowering Future Teacher Leaders Through Peer Mentoring, Stephanie M. Banks

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Preservice Teachers And Creativity: Beliefs, Experiences, And Intentions For Future Practice, Joanna M. Weld

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Learning To Love Science: Preservice Elementary Teachers Conceptualizations Of Science Teaching And Self-Efficacy To Teach Science, Christine Mcgrail, Stephanie B. Purington, Alicia Gonzales

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Teacher Candidates’ Perceptions Of Online Tutoring As Early Field Experience, Kathryn Alton, Alison Puliatte, Megan Lawless, Yong Yu

Excelsior: Leadership in Teaching and Learning

No abstract provided.

Improving Road Safety Through Multimodal Deep Learning For Driver Drowsiness Detection, Hadel A. Hussain, Mohammed A. Subhi, Ahmed S. Al Tmeme, Ahmed D. Radhi, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

One of the most common causes of road accidents globally is driver drowsiness and it needs solutions that are reliable and can be applicable in numerous real-life situations. We present this paper with the aim of developing a deep-learning system that is capable of reliably detecting drowsiness in diverse and varied conditions across different drivers, environments, and sensor types. Our system is known as Multimodal Attention Network (MMAN), which combines information of eye and head movement, heart-rate and breathing pattern, and vehicle-dynamics signal. MMAN has a gradient-reversal layer that enables the layer to be domain-adaptive such that it does not …

Deep Learning-Based Fog-Cloud Approach Intrusion Detection System In Iomt, Yahya Rbah, Mohammed Mahfoudi, Mohammed Fattah, Younes Balboul, Said Mazer, Moulhime Elbekkali

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) creates an interconnected environment linking humans, devices, sensors, and systems, enhancing healthcare services through advanced technologies. Nonetheless, these IoMT devices are susceptible to cyberattacks, which can endanger patient safety and healthcare services. To identify and mitigate cyberattacks in IoMT, techniques such as threat intelligence, log monitoring, and intrusion detection systems are employed. As attackers evolve their strategies, there is a growing trend towards leveraging artificial intelligence to achieve more predictive and accurate attack detection. Since IoMT devices are inherently low-power, they require minimal computing resources. Existing intrusion detection systems are generally trained in the …

Multitaskvenationnet: A Multi-Task Deep Neural Network With Strip Pooling And Hybrid Upsampling For Leaf Vein Segmentation, Ishak Ariawan, Ahmad Ashari, Moh. Edi Wibowo

Iraqi Journal for Computer Science and Mathematics

Leaf vein segmentation is a critical task in plant phenotyping and species classification, yet it remains challenging due to the hierarchical, curvilinear nature of veins and interference from complex backgrounds. Existing methods face three key limitations. First, they lack directional context modeling, leading to blurred vein boundaries and the omission of fine venation. Second, they fail to effectively capture global dependencies, limiting semantic coherence across spatial regions. Third, they do not incorporate explicit mechanisms for detecting vein discontinuities, which is essential for complete topological understanding. To address these challenges, we propose MultiTaskVenationNet (MTV-Net), a multi-task deep segmentation framework that integrates …

Model-Based Vision System For Evaluation And Improvement Of Gaits In Legged Locomotion, Kenneth P. Clark, Christopher R. Meng, Laurence J. Ryan

Defensive Publications Series

This disclosure relates to the evaluation and improvement of gaits in legged locomotion of humans, animals, and robots by superimposing a biomechanical figure selected from a spectrum of models onto the recorded motion of a test subject. For gait evaluation, a model is selected from a database to closely match the observed gait and existing performance parameters are obtained. For gait improvement, an incrementally superior model is selected from the database to provide enhanced performance goals. This Model Vision Evaluation (MoVE) system thus includes spectrums of biomechanical models over a range of inferior to superior levels of skill and performance …

Book Of Abstracts, Seton Hall University

2025 Augustine Undergraduate Research Symposium

No abstract provided.

My First Conversation With Chatgpt (February 22, 2023): Origins Of A Generative Dialogue, David Smith

Publications and Research

This working paper presents the first recorded interaction between the author and the generative AI system ChatGPT, written on February 22, 2023 during the initial weeks of a faculty sabbatical in Boston. The document preserves a complete and unedited transcript of an exploratory conversation conducted without predetermined research aims, marking the author’s first encounter with a large-language-model conversational interface. Although the exchange includes creative experimentation—including musical and poetic prompts—the discussion remains informal and wide-ranging, and no theoretical framework is articulated at this stage. Rather, this transcript is published as primary-source material documenting the moment of discovery and experimentation that precedes …

Bayesian Alignment Prior To Connectionist Temporal Classification Loss, Lawry Sorenson

Theses and Dissertations

We propose revisions of Connectionist Temporal Classification (CTC) loss and forced alignment to support longer input sequences. CTC loss is normally used for training in speech and handwriting recognition tasks when the labels are not fully aligned with the data, while forced alignment is a downstream task that finds the optimal path for segmentation purposes. The current implementations consider all possible alignments between the input and label, which grows exponentially with the size of the input. We show that in cases when silence is removed and speaking rate is consistent, the true alignment is a mostly straight line across time …

Commutative Schur Rings Over Characteristic 2 Special Orthogonal Groups, Andrew Haviland

Theses and Dissertations

We study commutative Schur rings over the special orthogonal groups $\mathrm{SO}^{\pm}(n,2)$ that contain the class $\mathcal{C}$ of transvections. We show that the partition of $\mathcal{C}$ determined by a commutative Schur ring has either one or two parts. We classify all remaining partitions of $\mathcal{C}$ that could be determined by a commutative Schur ring.

Empowering Digital Fluency: A Course-Based Strategy For Practical Ai Tool Integration In Higher Education, Melissa J. Brooks

Teaching Repository of AI-Infused Learning

This course was designed to introduce students to a range of AI tools while enabling hands-on experience in their practical application. Students were required to explore multiple AI tools across domains such as content generation, data visualization, video production, note-taking, and accessibility. The course culminated in a final project where students selected and applied an AI tool (or set of tools) to create a resume, a cover letter, and a presentation about themselves and how they anticipate the use of AI in their chosen Industry. Tools recommended were Jenni.AI, ChatGPT, Slide bean, Canva, Grammarly, Gamma, Synthesia.AI, and Perplexity, Otter.AI. One …

Practicing Disciplinary Role-Play With Ai: Bioinspired Innovation Meets Business Strategy, Christine R. Rodriguez

Teaching Repository of AI-Infused Learning

Students use Blackboard’s AI Conversation tool to rehearse their team’s innovation pitch with a simulated investor. This role-play activity prepares students to confidently communicate scientific ideas in business contexts and strengthens final group presentations.

Beat Chatgpt: Cultivating Critical Ai Literacy Through Student-Created Problems, Sybil Prince Nelson

Teaching Repository of AI-Infused Learning

Beat ChatGPT is a gamified assignment that positions AI as both a rival and a resource to foster critical AI literacy. Students either design statistics problems that ChatGPT is likely to answer incorrectly or critique flawed AI-generated solutions, then provide accurate responses and reflections. This strategy not only deepens disciplinary understanding but also equips students to engage with AI tools thoughtfully, ethically, and creatively.

Elementary Teachers’ Perceptions Of A District Tutoring Program Focused On Improving Minoritized Students’ Proficiency, Asia M. Michael

Walden Dissertations and Doctoral Studies

The problem that was addressed through this study is that 75% of minoritized students in Grades 3–5 are not meeting proficiency goals in math at a suburban New Jersey school district (NJSD, a pseudonym), which prompted the implementation of a high-impact tutoring program for all students. Grounded in Dewey’s theory of action, the purpose of this mixed-methods study was to explore upper elementary teachers’ perceptions of the high-impact tutoring program and its influence on minoritized students’ math proficiency at NJSD. Data were collected from 22 upper elementary teachers through an anonymous survey, including both quantitative and qualitative prompts. The quantitative …

Implementing Dataops: A Scalable Framework For Modern Data Warehousing, Dmytro Valiaiev

Theses and Dissertations

DataOps has been coined as a novel term that emerged as a synthesis of data management practices with software engineering concepts, such as DevOps and Agile, with the goal of improving data quality and governance in enterprises. The proliferation of scratch table use and transformation tools, such as dbt, has led to an exponential increase in the number of data models, which complicates standardization efforts and increases maintenance overhead. Although the market is saturated with various flavors of text-to-SQL engines that promote increased productivity and self-service use in organizations, there are limited tools available to optimize individual queries, enforce consistency, …

Inferring Disease Progression Networks To Predict Comorbidities, Nolan Stuessy

Honors Capstone Projects and Theses

No abstract provided.