Research framework. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Parameter configuration for TextCNN model. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Model performance on the validation set. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Performance comparison of different models. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Performance evaluation of models on test dataset. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Topic classification based on KeyBERT-TextCNN. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Summary of perceived risk dimensions. by Lin Qi (128224)

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”

Example of a typical workflow to construct a network using NeKo. by Marco Ruscone (11747264)

Incremental Inverse Design of Desired Soybean Phenotypes by Joseph Zavorskas (19761296)

Subjects:

Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase algorithm for multi-material topology optimization [34].... by Zhao Li (300229)

“…(b) An alternating active-phase algorithm for multi-material topology optimization [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0321100#pone.0321100.ref034" target="_blank">34</a>]. …”

Causal Relationship between Potential Shift and Molecular Structure in Concentrated Electrolytes by Yumika Yokoyama (18422218)

Subjects:

LBQANA python code + Merged Gene Expression Dataset from GSE10810, GSE17907, GSE20711, GSE42568, GSE45827, and GSE61304 for Breast Cancer Biomarker Discovery by M RN (9866504)

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…”

Software: Order-flow and long-memory in a simulated financial market by Shane Silverman (22497770)

“…Key scripts apply custom metaorder generation algorithms to the empirical data to estimate and compare the $\alpha$ and $\gamma$ exponents.…”

Active Control of Laminar and Turbulent Flows Using Adjoint-Based Machine Learning by Xuemin Liu (20372739)

“…This dissertation extends and applies an adjoint-based machine learning method, the deep learning PDE augmentation method (DPM), for closed-loop active control on both laminar and turbulent flows. The end-to-end sensitivities for optimization are computed using adjoints of the governing equations without restriction on the terms that may appear in the objective function, which we construct using algorithmic differentiation applied to the flow solver. …”

Validation tests of feature decoding during the associative memory paradigm. by Sam Hall-McMaster (10343795)

Associative memory paradigm used to train the feature decoders. by Sam Hall-McMaster (10343795)

Data Sheet 1_Hybrid machine learning algorithms accurately predict marine ecological communities.pdf by Luciana Erika Yaginuma (10477013)

“…In the supervised stage, these associations were modeled as a function of the environmental features by five supervised algorithms (Support Vector Machine, Random Forest, k-Nearest Neighbors, Naive Bayes, and Stochastic Gradient Boosting), using 80% of the samples for training, leaving the remaining for testing. …”

Decoding results. by Sam Hall-McMaster (10343795)