Flowchart for teaching and learning implementation of the 2D aesthetic program cluster in rural schools. by Zhankun Han (20529082)

Word cloud with key elements of an Active Learning Classroom. by Mairena Sánchez-López (684092)

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AI KRegression by CHIN-CHENG CHU (20718575)

Long-term divergence of nitrogen and phosphorus dynamics in small lakes across China by Shaojuan Du (22465949)

Predicting Dinitrogen Activation and Coupling with Carbon Dioxide and Other Small Molecules by Methyleneborane: A Combined DFT and Machine Learning Study by Feiying You (22119041)

“…Here, we predict through density functional theory calculations that the coupling of dinitrogen with carbon dioxide by methyleneborane becomes favorable both thermodynamically and kinetically. Machine learning analysis suggests that increasing the HOMO–LUMO gap or the charge on the boron atom or decreasing the charge of the nitrogen atom will reduce the reaction energies. …”

Aims, outcomes and main results of the included studies. by Mairena Sánchez-López (684092)

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Characteristics of the studies. by Mairena Sánchez-López (684092)

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PRISMA flow chart of the study selection process. by Mairena Sánchez-López (684092)

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Relationship between ordinal regression and binary classification performance. by Thierry Jean (20691795)

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Passive sensing data. by Thierry Jean (20691795)

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Binary classification task performance. by Thierry Jean (20691795)

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Time-based splitting strategy and forecast horizons. by Thierry Jean (20691795)

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Label distributions across mental states and dataset splits. by Thierry Jean (20691795)

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Effect of class imbalance on predictive performance. by Thierry Jean (20691795)

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Ordinal regression predictions. by Thierry Jean (20691795)

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Binary classification predictions. by Thierry Jean (20691795)

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Ordinal regression task performance. by Thierry Jean (20691795)

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Surveys. by Thierry Jean (20691795)

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A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira (18704596)

“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”

Figure 2 from Individualized Prediction of Drug Response and Rational Combination Therapy in NSCLC Using Artificial Intelligence–Enabled Studies of Acute Phosphoproteomic Changes by Elizabeth A. Coker (15024165)