Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management by Pavel Izosimov (20096259)

“…</li><li><a href="https://obfuscator.xn--mxac.net/" target="_blank"><b>Python Obfuscator Online</b></a>: An online tool for cloud-based Python code obfuscation, enabling further <b>code obfuscation in Python</b>.…”

Local Python Code Protector Script: A Tool for Source Code Protection and Secure Code Sharing by Pavel Izosimov (20096259)

“…</li></ul><h2>Additional Features</h2><ul><li><a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank"><b>Protect Python Code</b></a>: The tool effectively protects your Python code, preventing unauthorized access or modification.…”

System Hardware ID Generator Script: A Cross-Platform Hardware Identification Tool by Pavel Izosimov (20096259)

“…</li></ul><h2>Applications and Use Cases</h2><ul><li><b>Software Licensing</b>: By integrating the HWID into licensing systems, developers can bind software licenses to specific devices, control installations, and prevent unauthorized software usage. This enhances <a href="https://xn--mxac.net/local-python-code-protector.html" target="_blank">source code protection</a> and ensures compliance with licensing terms.…”

Animal bite risk map for Mymensingh district in 2022 and 2023. by Chandra Shaker Chouhan (17262842)

S2 Fig - by Philippos Michaelides (18463232)

“…<div><p>Hospitals are highly dynamic environments where Covid-19 is highly transmissible if effective measures are not taken. General preventive policies are not necessarily effective; however, agent-based modelling can offer a way to tailor policies in such specific settings. …”

Experimental set-up. by Philippos Michaelides (18463232)

“…<div><p>Hospitals are highly dynamic environments where Covid-19 is highly transmissible if effective measures are not taken. General preventive policies are not necessarily effective; however, agent-based modelling can offer a way to tailor policies in such specific settings. …”

Metrics and statistics for Scenarios 1-7. by Philippos Michaelides (18463232)

“…<div><p>Hospitals are highly dynamic environments where Covid-19 is highly transmissible if effective measures are not taken. General preventive policies are not necessarily effective; however, agent-based modelling can offer a way to tailor policies in such specific settings. …”

Design and Implementation of a Browser-Based Toolfor Protecting Gaming Assets from UnauthorizedAccess by Alim Imashev (22606007)

“…<p dir="ltr">The project <b>“Design and Implementation of a Browser-Based Tool for Protecting Gaming Assets from Unauthorized Access”</b> focuses on developing a security-oriented software solution that safeguards digital game assets within browser environments.…”

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. …”

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 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 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. …”

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. …”

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. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)