Internal changes of the specimen of 0.74 to 0.76. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen 1.55 to 1.60. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 1.70 to 1.75. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

Internal changes of the specimen of 0.89 to 1. حسب Nan Ru (9594384)

"…The ABAQUS finite – element software was used, and a random aggregate placement algorithm for RCA was implemented by writing the built – in scripting language Python to generate digital specimens. …"

A list of all facial muscle movements mentioned in the chimpFACS manual [5] and considered in our present study. حسب Aisha Mahmoud (20623732)

A list of all facial muscle movements mentioned in the catFACS manual [14] and considered in our present study. حسب Aisha Mahmoud (20623732)

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx حسب Piyachat Udomwong (22563212)

"…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"

<b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b> حسب Marly G F Costa (19812192)

"…<p dir="ltr"><b>Use case codes of the DDS3 and DDS4 datasets for bacillus segmentation and tuberculosis diagnosis, respectively</b></p><p dir="ltr">The code was developed in the Google Collaboratory environment, using Python version 3.7.13, with TensorFlow 2.8.2. …"

Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning حسب Joan Alexander (17047170)

"…Focusing first on idealized atmospheric modeling systems, we will tackle challenges associated with coupling interactively an ML-based data-driven scheme and a climate model (e.g., numerical instabilities, linking Python and Fortran). …"

Datasets To EVAL. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

Statistical significance test results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

How RAG work. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

OpenBookQA experimental results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

AI2_ARC experimental results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

TQA experimental results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

E-EVAL experimental results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

TQA Accuracy Comparison Chart on different LLM. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

ScienceQA experimental results. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

Code interpreter with LLM. حسب Jin Lu (428513)

"…<div><p>This paper presents a novel approach to enhancing educational question-answering (Q&A) systems by combining Retrieval-Augmented Generation (RAG) with Large Language Model (LLM) Code Interpreters. …"

Excerpt from a provenance graph depicting the refinement process of a simulation model (SM1) during a simulation study. حسب Andreas Ruscheinski (7880759)