Eisenhower Aldemita II
Projects
MedLink lets patients quickly search for the medical service they need and see which nearby facilities offer it, complete with real-time availability. (Disclaimer: Site operates on test data for now)
Shogimon is a board game with an 8x8 board, chess-like piece movements, with shogi like rules, and pokemon sprites.
Sugarcare was our output for our Artificial Intelligence Capstone project where we were tasked to create ML models to identify Sugarcane Leaf Diseases with Computer Vision using only the provided dataset.
DynaMic is a dynamite explosion detection system designed to address blast fishing by providing automated real-time detection and alerts using long range communication and machine learning.
Project to answer the interest in the economic structure of a separate Mindanao in terms of its production and use of resources in the form of Input-Output Tables.
This website
Papers
This study investigates the optimization of natural fiber-reinforced polymer composite (NFRPCs) creation for bulletproof applications by integrating computational simulation and machine learning (ML). We incorporate abaca (Musa textilis) or pineapple leaf fibers (Piñatex), along with aramid and carbon fibers, into layered composite plates. Ballistic performance was modeled and predicted using simulated data from ANSYS Explicit Dynamics and validated through live bullet testing. ML models, such as Support Vector Machine (SVM) and Random Forest (RF) with optimized hyperparameters, achieved up to 80% prediction accuracy and an F1-score of 82% for abaca-reinforced composites, closely aligning with experimental results. However, lower prediction accuracy was observed for Piñatex-based composites, due to fiber variability and other factors identified in the study. This hybrid methodology highlights the potential of combining simulation and ML to reduce reliance on extensive live bullet testing, providing a data-driven pathway for the efficient development of high-performance bulletproof composite materials.