Computational Engineering Commons^™

Sinergia Para Un Futuro Sostenible. Tecnologías Y Agrosistemas, Jaime Eduardo Andrade Ramírez, Angélica Bravo Bojórquez

Ingeniería

Este libro reúne los resultados más relevantes del proyecto de investigación “Laboratorio Experimental de Sistemas Tecnológicos Orientados a Modelos Acuapónicos (Lestoma)” desarrollado en la Universidad de Cundinamarca, Extensión Facatativá, liderado por el Grupo de Investigación de Sistemas y Tecnología Facatativá (GISTFA). Lestoma también contó con la colaboración de los grupos de investigación Axioma, Agrociencia y Cundinamarca Agroambiental, adscritos respectivamente al programa de Ingeniería de Sistemas y Computación, Ingeniería Agronómica e Ingeniería Ambiental de las Facultades de Ingeniería y Ciencias Agropecuarias. El proyecto también contó con la colaboración estratégica del grupo de investigación Centro de Investigaciones Ambientales de la Universidad del …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

Mapping Leo Satellite Internet Performance Using Mobile Starlink Deployment, Annika Govil, Jacob Gray

UROP Posters

High-speed, low-latency internet connectivity on the move is a critical challenge for applications in connected vehicles, disaster response, and remote education. While terrestrial networks such as 4G or 5G are widespread, they lack coverage in remote or rural geographic areas.

Low Earth Orbit (LEO) satellite constellations, such as SpaceX's Starlink, promise global high-bandwidth, low-latency internet. However, their performance is well-documented in stationary scenarios, while data for *mobile* applications is scarce. This project explores the feasibility and real-world performance of LEO satellite internet while in motion.

Current research documents the performance of LEO satellite constellations in stationary settings. However, data concerning …

Unveiling The Transformative Power Of Unsupervised Machine Learning Through Clustering, Vishnu S. Pendyala

Open Educational Resources

Clustering methods demonstrated their transformative potential across various industries through image segmentation, anomaly detection, bioinformatics, and customer segmentation. The presentation explores these techniques in unsupervised machine learning, focusing on foundational clustering algorithms such as K-means, Hierarchical Clustering, and DBSCAN. Through an in-depth analysis of their underlying principles and computational intricacies, the presentation highlights how these methods have evolved to address complex, high-dimensional data problems. The presentation provides insights into how K-means remains a versatile tool for partitioning data in linear spaces. It delves into Hierarchical Clustering's unique approach to building dendrograms and capturing multi-scale data relationships, and how DBSCAN's density-based …

Modelled Flooding Impacts On Lower Fish River Watershed, Sebastian Loschner

Shelby Hall Graduate Research Forum Posters

This study investigates the impacts of compound flooding in the Lower Fish River watershed, Baldwin County, Alabama, with a focus on the potential effects of sea level rise due to climate change. Coastal flooding, particularly in smaller watersheds, is a growing concern as it results from the interaction of multiple factors, including rainfall, tidal changes, and extreme weather events. Compound flooding, which involves multiple flood drivers, is expected to worsen with climate change, as increased precipitation and rising sea levels create heightened flood risks. However, existing research on compound flooding predominantly focuses on large-scale watersheds, leaving a knowledge gap in …

Quantitative Analysis Of Machine Learning Model Performance And The Need To Consider Explainability, Vishnu S. Pendyala

Open Educational Resources

This presentation, titled "Quantitative analysis of Machine Learning model performance and the need to consider explainability," delves into various metrics used for evaluating machine learning models. It thoroughly examines fundamental classification metrics like accuracy, precision, recall, and F-score, while also discussing more advanced measures such as the Kappa Statistic and Matthews Correlation Coefficient (MCC), particularly highlighting their relevance in scenarios with imbalanced datasets. The presentation underscores the importance of model accuracy in real-world applications and briefly introduces regression metrics like R-squared and F-statistic. Additionally, it addresses challenges related to data imbalance and fairness in ML models, stressing the critical need …

Machine Learning Applications And Sustainable Development, Vishnu Pendyala

Open Educational Resources

This presentation, "Machine Learning Applications and Sustainable Development," explores the intersection of machine learning and its impact on privacy, equity, and societal well-being. It delves into the potential for re-identification of "anonymized" data through various techniques like k-anonymity, L-diversity, and the vulnerabilities of large language models, illustrating these concepts with real-world examples such as the AOL search data, Netflix Prize dataset, and Strava's fitness tracking. The presentation also discusses solutions to enhance data privacy, including differential privacy and the emerging field of machine unlearning, highlighting their applications and limitations. Finally, it addresses the broader implications for civil rights and ethical …

Slowly Changing Dimensions And Fast Changing Facts - The Story Of The Traditional Data Warehouse, Vishnu Pendyala

Open Educational Resources

This presentation, "Slowly Changing Dimensions and Fast Changing Facts - The Story of the Traditional Data Warehouse," explores how to generate actionable insights from organizational performance data. It begins by discussing the challenges of generating insights directly from existing databases and introduces the concept of data cubes for efficient aggregate storage. The core of the presentation focuses on dimensional modeling, particularly the Star Schema, as a solution for analytical processing needs that cannot be met by transactional systems. It details the characteristics of fast-changing fact tables (long, lean, numeric) and slowly changing dimension tables (descriptive, wide, containing strings and numbers). …

Exploring The Math In Support Vector Machines, Vishnu Pendyala

Open Educational Resources

“SVMs are a rare example of a methodology where geometric intuition, elegant mathematics, theoretical guarantees, and practical algorithms meet” – Bennet and Campbell

Support Vector Machines (SVMs) are used for supervised machine learning and have been successful in many applications, including those like image classification that favor deep learning. SVM owes its power to the intriguing math involved in its fabrication. This talk will introduce SVM and cover some of that math. Topics covered will include constrained and unconstrained optimization, convexity, the general notion of a function space, minmax equilibrium, duality, the Cover theorem, Kernels, and the Mercer theorem.

More …

Machine Learning, The Mortar Of Modernization, Vishnu Pendyala

Open Educational Resources

Machine Learning is advancing civilization and is one of the key drivers of the economy today. Machine Learning literacy may one day become essential, the way computer literacy is today. This talk intends to explain Machine Learning concepts to wider audiences by using easy-to-relate real-world analogies and serves as a refresher to those already initiated. A fundamental concept in machine learning is similarity. The dot product that is ubiquitously present in machine learning is a measure of similarity. Similarity is key to human learning as well. We learn in delta increments by comparing and contrasting with what we already know. …

Meta-Algorithms In Machine Learning, Vishnu Pendyala

Open Educational Resources

This presentation explores how to make the best of models impacted by bias and variance. Meta-learning minimizes loss. Ensemble methods, including Bagging, Adaboost, Random Forest, Gradient Boosting, and Stacking, are discussed. These methods perturb data (X or Y) using techniques like bootstrap sampling, k-fold sampling, weighted sampling, and random subspaces. Models are generated in parallel or sequentially, with aggregation strategies such as mean, mode, weighted response, and metamodel. The presentation also touches upon deep learning and one-shot learning, and explains how distances become less meaningful in high dimensions.

More details: https://events.vtools.ieee.org/m/315184

Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning

Numerical Analysis Of Taylor Impact With Various Nose Shapes, Jean C. Santiago Padilla, Erik M. Chappell

ME 4233/6233 Fundamentals of FEA

The Taylor impact test is an experimental technique used to determine dynamic material response and to validate constitutive models used in numerical simulations. It generally consists of shooting a cylinder rod of a select material against a rigid target at different velocities. After impact, the plastic deformation of the cylinder is recorded and is directly compared to numerical predictions. Another application for Taylor impact was proposed by Li et al. (2021) where the nose shape of the cylinder is modified to create different loading environments that can test electronic equipment in penetration weapons. FEA models where designed in ABAQUS/Explicit to …

Blown To Bits Project, David Schmidt

Informatics Open Educational Resources

The book, Blown to Bits, uncovers the many ways that the new digital world has changed and is changing our whole environment. Some changes are incremental but others are more revolutionary. Some of the changes that we welcome are slowly eroding our privacy and are changing the rules of ownership. This book illuminates the complexities of these changes. I have attempted to capture the central points in selected chapters, and in some cases I have added new material or new examples to replace dated material. I picked chapters to summarize that address the following topics (and more). There are many …

Evaluation Of Tcp Header Fields For Data Overhead Efficiency, Justin K. Yirka

UROP Posters

Bandwidth across the internet is constricted by monetary factors and hardware development, so researchers are left to improve the efficiency of data transmitted in order to improve internet speeds. The transmission control protocol (TCP) is the primary transport protocol on the modern internet, ensuring reliable delivery of the majority of data transmitted. I evaluated the TCP header fields for efficient use of data overhead so as to determine current waste and to suggest possible areas for revision. I examined original specifications for TCP mechanisms, comparing them to modern implementations as determined by updated standards and modern practices in the networking …