Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases by Jina Lee (3138492)

“…In this study, we developed a Python-based open-source algorithm compatible with the aqueous physical property models provided in the electrolyte templates of AspenTech software. …”

Developed energy optimization model with LSC based on OAWDO algorithm. by Hisham Alghamdi (20114096)

“…<p>Developed energy optimization model with LSC based on OAWDO algorithm.…”

Data Sheet 1_Development of a novel artificial intelligence algorithm for interpreting fetal heart rate and uterine activity data in cardiotocography.docx by Rohit Pardasani (22253656)

“…The algorithm using deep learning and rule-based techniques was developed to identify segments of interest (accelerations, decelerations, and contractions). …”

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

“…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …”

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

“…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …”

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

“…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …”

Triboelectric Sensors Based on Glycerol/PVA Hydrogel and Deep Learning Algorithms for Neck Movement Monitoring by Bingbing Qu (17603577)

“…By leveraging the convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) algorithm, sensor data can be efficiently analyzed in both spatial and temporal dimensions, achieving a promising recognition accuracy of 97.14%. …”

Data Sheet 1_A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.pdf by Tianli Wang (1438498)

Genome-wide identification of candidate regions associated with birth weight in Lori-Bakhtiari sheep using Random Forest algorithm by Mohammad Hossein Moradi (11400671)

“…This study was conducted to identify genetic loci associated with birth weight in a meat-type sheep using a Random Forest (RF) algorithm applied to genomic data. …”

Code and data - WST 895 thesis by Hoosain Ebrahim (14058588)

Subjects:

Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …”

Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …”

ECG lead-based algorithm diagram. by Pauline Guyot (8566470)

Subjects:

Clustering results obtained using Classical GMM on scaled TF-IDF data, representing the distribution of news articles among different clusters based on textual similarities. by Sajida Perveen (8256378)

Solution results of different algorithms. by Meilin Zhu (688698)

“…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …”

Image 2_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Table 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.docx by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Image 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Data for Figs 3–9. by Xiaogang Li (299205)

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process by Ruilin Yang (151028)

“…Here we report an ultrafast (0.4 s) hydrogen detection system based on a wafer-scale fabrication process. It consists of a low power (20.2 mW) hydrogen sensor based on vertical thermal conduction structure and a signal processing circuit introduced with a neural network prediction algorithm based on sensor response process. …”