Digital Commons Network^™

Challenges In Engineering Machine Learning (Software) Systems, Raffi T. Khatchadourian Ph.D.

Open Educational Resources

Lecture slides on the software engineering challenges unique to machine learning systems, for an undergraduate software engineering course. After contrasting traditional programming with machine learning, the deck examines why the usual tools for managing complexity—abstraction, reuse, and composition—are harder to apply to ML, given the lack of clear specifications and modularity. It covers concept drift, feedback loops (illustrated with crime-prediction and recommendation examples), and the accumulation of technical debt in ML systems, including the role and pitfalls of notebooks in moving from experimentation to production. Based on "Machine Learning in Production/AI Engineering" by Christian Kaestner and Eunsuk Kang (Carnegie Mellon …

Elementary Teachers’ Use Of Sphero Robots To Teach Computational Thinking, Marquita Jackson

Walden Dissertations and Doctoral Studies

The power of play has often been used in K–5 classrooms, but it has not always been implemented as a way to teach computational thinking skills. The use of educational robots such as Sphero have been explored, but not with young learners. The research problem addressed through this study was the lack of understanding of K–5 teachers’ experiences in using Sphero robots to teach computational thinking. The purpose of this basic qualitative study was to explore K-5 teachers’ experiences in implementing Sphero robot activities and specifically to teach computational thinking. The conceptual framework included Magana’s T3 model and Angeli’s computational …

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

Day Family Research Lab Workshop Series

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.

White Nose Syndrome In Bats And Infant Mortality In Georgia, Rhys Medcalfe, Sean Medcalfe, Simon Medcalfe

Journal of the Georgia Public Health Association

Background: White nose syndrome (WNS) is a disease in bats caused by the fungus Pseudogymnoascus destructans that can result in bat mortality rates of over 90%. WNS was discovered in Georgia in 2012 in 3 counties but has continued to spread to 14 counties as of 2023, with P. destructans detected in a further seven. Biodiversity loss has been linked to human health outcomes including infant mortality. Understanding the link between WNS, biodiversity loss, and infant mortality in Georgia is important because Georgia ranks 42^nd out of the 50 states for infant mortality rate.

Methods: Using panel data from …

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.

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.

Understanding The Physiological Mechanisms Of Thermal Tolerance In Three Reef-Bulding Species Of Coral, Rachel Mccarty

Honors Capstone Projects and Theses

No abstract provided.

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.

Designing A Qi Initiative: Preoperative Bathing In The Ed For Adult Hip Fracture Patients, Mihyun Jang, Susan Maynard, Sheri Matter, Andrea Sillner

Biennial Convention (CONV)

Surgical site infections (SSIs) following hip fracture surgeries in adults are severe complications that increase morbidity, mortality, and healthcare costs. Preoperative bathing, particularly with chlorhexidine gluconate (CHG), reduces the risk of surgical site infection after hip fracture surgery by decontaminating skin flora, such as Staphylococcus aureus. Compliance with preoperative bathing protocols remains low, especially among adult patients admitted through emergency departments. To address the gap in preoperative bathing compliance, a quality improvement initiative will implement a preoperative bathing protocol using CHG wipes in the emergency department for adult hip fracture patients. Currently, there is a lack of evidence regarding the …

Hot Ground State Cooling Following Ultrafast Photoisomerization: Time-Resolved Infrared Spectroscopy, James N. Bull, Mark H. Stockett, Pratip Chakraborty, Eleanor K. Ashworth, Anam Fatima, Vincent J. Esposito, Gregory M. Greetham, Partha Malakar, Stephen R. Meech

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The ultrafast photophysics of many isomerizing molecules involves subpicosecond formation of a twisted hot ground state, which transfers energy to the environment through vibrational relaxation (cooling) over several picoseconds. In time-resolved infrared (TR-IR) spectroscopy, hot ground state transients show frequency shifts and band reshapings, which cannot be described through kinetic models that assume static spectral functions. We report a simple anharmonic cascade framework, which uses a single adjustable parameter associated with scaling the probability of vibrational energy transfer to the environment, for describing hot ground state cooling (HGSC) in TR-IR spectroscopy. The model is demonstrated against measurements on the cyan …

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.

Electrochemical Detection Of Aβ42 And Aβ40 At Attomolar Scale Via Optimised Antibody Loading On Pyr-Nhs-Functionalised 3d Graphene Foam Electrodes, Muhsin Dogan, Sophia Nazir, David Jenkins, Yinghui Wei, Genhua Pan

School of Engineering, Computing and Mathematics

Alzheimer’s Disease (AD) is one of the most commonly seen neurodegenerative disorders, where early detection of its biomarkers is crucial for effective management. Conventional diagnostic methods are often expensive, time-consuming, and highly complex, which highlights an urgent need for point-of-care biosensing technology. In this work, we developed assays on three-dimensional (3D) graphene foam electrodes by functionalising them with a 1-Pyrenebutyric acid N-hydroxysuccinimide ester (Pyr-NHS) to enable effective antibody immobilisation for the detection of amyloid beta peptides (Aβ42 and Aβ40), key biomarkers for AD. Pyr-NHS linkers were used for stable functionalisation, followed by binding with Aβ42 and Aβ40 antibodies, and then …

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 …