Table 1_Entropy-adaptive differential privacy federated learning for student performance prediction and privacy protection: a case study in Python programming.docx by Shanwei Chen (12031760)

“…This study proposes an Entropy-Adaptive Differential Privacy Federated Learning method (EADP-FedAvg) to enhance the accuracy of student performance prediction while ensuring data privacy. Based on online test records from Python programming courses for Electronic Engineering students (grade 2021–2023) at the School of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, China, the study uses a Multilayer Perceptron (MLP) model and 10 distributed clients for training. …”

Optimal radiomics feature of MRI. by Jiangfa Li (18345033)

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Optimal radiomics feature of CT. by Jiangfa Li (18345033)

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Extracted CT and MRI images and outlined ROI. by Jiangfa Li (18345033)

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Statistically relevant information. by Jiangfa Li (18345033)

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Cross-validation of Lasso regression of enhanced MRI images. by Jiangfa Li (18345033)

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Univariate and multivariate results of MVI-positive and MVI-negative in training group. by Jiangfa Li (18345033)

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The cross-validation diagram of Lasso regression of enhanced CT combined with MRI images. by Jiangfa Li (18345033)

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Cross-validation of Lasso regression of enhanced CT images. by Jiangfa Li (18345033)

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Comparison of general clinical data between training group and verification group. by Jiangfa Li (18345033)

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Optimal radiomics features of CT combined with MRI. by Jiangfa Li (18345033)

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Partial Rank Correlation Coefficient (PRCC) sensitivity analysis results, obtained using LHS with 1000 samples and run in Python version 3.11.0. by Tinashe Victor Mupedza (22022124)

Prediction accuracy on varying attack types. by Mohanad Faeq Ali (21354273)

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Error in percentage for used hybrid prediction method versus actual. by Ahmed G. Ismail (21519374)

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Prediction accuracy analysis over time steps. by Mohanad Faeq Ali (21354273)

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<b>Map 104. </b>Distribution of <i>Python natalensis </i>records in south-eastern Zimbabwe. by Kurt van Wyk (20481341)

Actual versus hybrid prediction method for (Maximum, Average and Minimum) demand. by Ahmed G. Ismail (21519374)

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S1 Code - by Christina M. Homer (3561131)

LSTM algorithm for cyber attack prediction in IoMT. by Mohanad Faeq Ali (21354273)

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Python’s Evolution on Stack Overflow: An Empirical Analysis of Topic Trends by Hu Fengqi (20971700)

“…The original data source is from : <b>h</b><b>ttps://archive.org/details/stackexchange</b></p><h2>Training Data</h2><p dir="ltr">Each set contains two files, Training Set and Rater, Training Set is the content of the training set, i.e., the file in which the model is directly trained, and the Grade column is the result of the machine's prediction.The Rater file contains the data of the manual scoring, and contains the following sections:</p><p dir="ltr">1. the rating data for each rater, with the specific column name Rater- rater number (e.g. …”