Computational Tools & Automation

CS Estimation for Fly Ash-Blended Green Concrete

This project developed a graphical user interface (GUI) to estimate the compressive strength (CS) of fly ash-blended green concrete. The GUI allows users to input material parameters such as aggregates, cement composition, fly ash content, curing age, and water percentage. Using integrated Extreme Learning Machine (ELM) models with multiple optimization algorithms, the system predicts compressive strength with improved accuracy. The GUI also supports single and multiple dataset inputs (via Excel upload) and provides model accuracy metrics (R, RMSE).

GUI for Fly Ash-Blended Concrete CS Estimation

GitHub Repository - GUI code, model scripts, and documentation.

Factor of Safety Analysis GUI

This project developed a graphical user interface (GUI) to calculate the Factor of Safety (FoS) for structural components under various loads. Built with Python (Tkinter), the GUI allows users to input material properties and load conditions, computing FoS as FoS = ultimate stress / working stress. The result below shows the GUI displaying computed FoS, stress values, and input parameters. A collaborative effort by Amrit Roy (GUI development, visualization) and Amrit Roy (algorithm design, validation).

GitHub Repository - GUI script, Python code, and README.

Web Scraping for Asian Food Data

This project automated the extraction of Asian food data, such as recipes and ingredients, from public websites using Python (BeautifulSoup, Scrapy). Over 1200 images were processed by first extracting the dataset, then using machine learning (e.g., OpenCV, TensorFlow) to remove backgrounds, followed by removing initial logos and adding a new logo for improved accuracy. The process adhered to ethical practices (e.g., robots.txt compliance, rate limiting). Results showcase the scraped and processed data in structured formats. A collaborative effort by Aayusha Singh (scraper development, data processing) and Amrit Roy (data validation, automation scripting).

GitHub Repository - Scraper scripts, image processing code, sample data, and README.