Tools used in this study. by Yousef AbuHour (17536686)

“…To tackle this issue, researchers are working on ways to predict and prevent these attacks by studying how malware spreads. …”

Modeling and evacuation simulation of asymmetric attraction-repulsion mechanism of companion group based on Morse potential function by yingshuang he (22678907)

“…<a href="" target="_blank">By introducing the Morse potential function, </a>a <a href="" target="_blank">segmented force field model</a> is constructed, which can differentially characterize the interaction between leaders and followers: strong repulsion within a very short distance to prevent collisions, maintaining weak attraction at a medium distance to maintain group cohesion, and enhancing attraction at a long distance to prevent dispersion. …”

MSc Personalised Medicine at Ulster University by Steven Watterson (100045)

“…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…However, using most of these software tools and choosing the most appropriate algorithm for a given optimization task require substantial technical expertise, which prevents the majority of researchers from using these methods effectively. …”

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 1_Knowledge, attitude, and perception of Pakistani populations toward monkeypox: a cross-section study.pdf by Humayun Yousaf (20667050)

“…Statistical analyses were performed in Jupyter Notebook using Python 3 and the Pandas, Matplotlib, and stats libraries.…”

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Table 1_Knowledge, attitude, and perception of Pakistani populations toward monkeypox: a cross-section study.doc by Humayun Yousaf (20667050)

“…Statistical analyses were performed in Jupyter Notebook using Python 3 and the Pandas, Matplotlib, and stats libraries.…”

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

GameOfLife Prediction Dataset by David Towers (12857447)

“…Excluding 0, the lower numbers also get increasingly unlikely, though more likely than higher numbers, we wanted to prevent gaps and therefore limited to 25 contiguous classes</p><p dir="ltr">NumPy (.npy) files can be opened through the NumPy Python library, using the `numpy.load()` function by inputting the path to the file into the function as a parameter. …”

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

“…Data processing was conducted using Python software. The pandas library was used for data cleaning and preprocessing, involving 68 categorical and 12 continuous variables. …”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”

Core data by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr">For the 5′ UTR library, we developed a Python script to extract sequences and Unique Molecular Identifiers (UMIs) from the FASTQ files. …”