The main notations used in this paper. by Bin Zhao (276445)

“…In this paper, we present an feedback fluid queueing network model to address CPDSE, integrating random traffic demand, time-varying transition probabilities, and state-dependent stochastic service capabilities. A recursive algorithm is developed to analyze the feedback queueing network model. …”

Abbreviations used in the algorithm. by Richa Jain (6550391)

Decision model based on the NSO. by Hui Zhao (7395)

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Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx by Xinying Yu (16400811)

“…</p>Conclusion<p>This study represents the first application of an ML algorithm techniques to the endoscopic classification of serrated polyps. …”

Schematic diagram of fusion model based on voting mechanism. by Jingru Dong (14076094)

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SHAP values and feature interaction scores in logistic regression (LR)-based prediction. by Xiaoyan Yang (259084)

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Data Sheet 2_A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes.pdf by Shuheng Yang (11680249)

Data Sheet 1_A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes.pdf by Shuheng Yang (11680249)

Average Betti number curves along different filtration parameters using data from a) previously collected existing RNA topologies in 2021, b) predicted RNA-like graphs, c) predicte... by Rui Wang (52434)

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Data Algorithms by Inmaculada Lizasoain (20698447)

Results of the sensor data detection model using the 2-classification CMHS dataset. by Tao Yang (184280)

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Results of the sensor data detection model using the 2-classification WADI dataset. by Tao Yang (184280)

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Table 1_Leveraging data augmentation for machine learning models in predicting depression and anxiety using the Revised Child Anxiety and Depression Scale clinical reports.docx by Saleha Noor (22697930)

“…</p>Conclusion<p>The findings suggest that the Random Forest algorithm using 46 features suits the data well and has the potential to be further developed as a decision support system for the concerned professionals and improve the usual way of screening anxiety and depression in children and adolescents.…”

Table 2_Leveraging data augmentation for machine learning models in predicting depression and anxiety using the Revised Child Anxiety and Depression Scale clinical reports.docx by Saleha Noor (22697930)

“…</p>Conclusion<p>The findings suggest that the Random Forest algorithm using 46 features suits the data well and has the potential to be further developed as a decision support system for the concerned professionals and improve the usual way of screening anxiety and depression in children and adolescents.…”

Global Aridity Index and Potential Evapotranspiration Climate Database v3.1 - Algorithm Code (Python) by Robert Zomer (12796235)

Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow by Son Gyo Jung (17913002)

“…More recently, transformer-based language models have emerged as powerful tools. …”

Demonstration of algorithm convergence. by Quyuan Wang (8724972)

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G R code algorithm. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Statistics of GI data processing using different algorithms at various input CTTDs. by Ki Hyun Nam (5813819)

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Graphical representation of the dial data and its classification into epochs using our algorithm. by Eleftheria Pistolas (20313429)