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  1. 81

    DataSheet1_Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models.PDF by Miguel Castro Oliveira (11975819)

    Published 2022
    “…These approaches consist on the development of a mixed-integer non-linear programming (MINLP) model and a multi-objective programming (MOP) model using the Python language. …”
  2. 82

    Data_Sheet_1_THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks.pdf by Lukas Muttenthaler (11466658)

    Published 2021
    “…THINGSvision is a new Python module that aims at closing this gap by providing a simple and unified tool for extracting layer activations for a wide range of pretrained and randomly-initialized neural network architectures, even for users with little to no programming experience. …”
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    Resolving Harvesting Errors in Institutional Repository Migration : Using Python Scripts with VS Code and LLM Integration. by satoshi hashimoto(橋本 郷史) (18851272)

    Published 2025
    “…Therefore, we decided to create a dedicated Python program using Large Language Model (LLM)-assisted coding.…”
  8. 88

    Dynamic Thermal Perception: Analyzing Skin Temperature Patterns Under Cyclical Heat Conditions Using Python by Nidhi Veerendra (21663146)

    Published 2025
    “…The study utilized the Python programming language to model the data and fitted its cooling period to Newton's Law of Cooling to assess thermodynamic behavior across multiple body zones. …”
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    Data Bloom 2025: Visualize with Python by Sarah Siddiqui (16670961)

    Published 2025
    “…</p><p dir="ltr">Workshop Description: Want to use Python to visualize your dataset? In this workshop, we will use libraries such as Matplotlib, Seaborn, and more to create meaningful plots. …”
  20. 100

    Tools used in implementing the RNN models. by Fahmi H. Quradaa (17896527)

    Published 2024
    “…In addition, more research is needed to investigate the capabilities of the recurrent neural network techniques for identifying semantic clones across different programming languages and binary codes. The development of standardized benchmarks for languages like Python, Scratch, and C#, along with cross-language comparisons, is essential. …”