Combined Confusion matrix: (a) Rear hand punch recognition (b) Lead hand punch recognition. by Saravanan Manoharan (21273304)

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Confusion matrix-punch classification. by Saravanan Manoharan (21273304)

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Combined Confusion matrix: (a) Rear hand punch classification (b) Lead hand punch classification. by Saravanan Manoharan (21273304)

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Accuracy metrics with different percentage of the training dataset. by Saravanan Manoharan (21273304)

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When a Twist Makes a Difference: Exploring PCET and ESIPT on a Nonplanar Hydrogen-Bonded Donor–Acceptor System by Emmanuel Odella (5059871)

“…Strategic incorporation of a methyl group disrupts the coplanarity between the aromatic units, causing a pronounced twist, weakening the intramolecular hydrogen bond, decreasing the phenol redox potential, reducing the chemical reversibility, and quenching the fluorescence emission. …”

How Do Zn²⁺ Ions Promote Methane Activation on Zinc-Modified Zeolites? A Hybrid Quantum-Chemical Study by Zoya N. Lashchinskaya (8102741)

“…It was found that the rate of H/D hydrogen exchange between alkane and zeolite BAS increased dramatically, and the activation barrier decreased for Zn²⁺-modified zeolite compared to H-form zeolite. …”

Emergence of New Nitrogen-Rich Compounds in Lead–Nitrogen Phase Diagram Under Pressure by Sylvain Pitié (12010033)

“…This finding is related to a decrease in the charge transfer from Pb to N₂ dimers. …”

An illustration of how GBT works. by Hoang Thanh Nhon (22311837)

“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”

The average performance of the test set. by Hoang Thanh Nhon (22311837)

“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”

The variables used and equations. by Hoang Thanh Nhon (22311837)

“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”

An illustration of how RF works. by Hoang Thanh Nhon (22311837)

“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”

The proposed method work-flow. by Hoang Thanh Nhon (22311837)

“…For example, the deep neural network model shows a decrease in RMSE from 0.926 to 0.375, MAE from 0.337 to 0.196, and MAPE from 134.63 to 114.71. …”

Histogram of the extracted parameters. by Qiuyu Du (20760848)

“…Firstly, the aorta was segmented automatically by TotalSegmentator and its centerline was extracted. …”

Effect of Molecular Structure on the B3LYP-Computed HOMO–LUMO Gap: A Structure −Property Relationship Using Atomic Signatures by Ahmed Mohamed (628889)

“…The atomic fragments containing π-bonds in various aromatic compounds were found to be the most significant atomic Signatures, explaining nearly 50% of the variance in the data, with regression coefficients that decreased <i>E</i>_gap. …”

Average kidney and heart weight of rats. by Diana Bylan (20421873)

“…To date, there are no treatments to reverse kidney fibrosis. Cannabis is an aromatic herb that is widely known for its anti-diabetic and anti-inflammatory properties. …”

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

“…This research proposes a new RNN architecture that decreases the prediction error up to 50% for cargo vessels when compared to the OU model. …”

Weak magnetic fields disturb cytoskeleton reassembly after nocodazole exposure, and influence actin polymerization. by Abasalt Bahrami (21989867)

HG module schematic. by Wenhao Ren (2561731)

“…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…”

Label data volume and label distribution. by Wenhao Ren (2561731)

“…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…”

The structure of the context guided block. by Wenhao Ren (2561731)

“…Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.…”