Algorithm performance in different operational phases. by Dongqing Zhang (423941)

Comparative prediction performance analysis of different algorithms. by Dongqing Zhang (423941)

Bioinspired Gradient-Modulus Iontronic Sensors with Drift-Suppressed Stability for Biomechanical Monitoring by Yong Zhang (5893)

“…In biomechanical sensing, achieving flexible sensors with a broad detection range, ultrahigh sensitivity, and long-term stability remains a major challenge. …”

Bioinspired Gradient-Modulus Iontronic Sensors with Drift-Suppressed Stability for Biomechanical Monitoring by Yong Zhang (5893)

“…In biomechanical sensing, achieving flexible sensors with a broad detection range, ultrahigh sensitivity, and long-term stability remains a major challenge. …”

Bioinspired Gradient-Modulus Iontronic Sensors with Drift-Suppressed Stability for Biomechanical Monitoring by Yong Zhang (5893)

“…In biomechanical sensing, achieving flexible sensors with a broad detection range, ultrahigh sensitivity, and long-term stability remains a major challenge. …”

Issues with automatic and team-based QC. by Michael E. Kim (21956727)

gcPCA correctly extracts contrastive facial features in the Chicago Face Dataset. by Eliezyer Fermino de Oliveira (20691761)

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…Our method supports multiple spikes per neuron and introduces a delay learning algorithm that can, in contrast to previous methods, also be applied to recurrent Spiking Neural Networks. …”

Raw dataset. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

FFT feature extraction. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Classification report of XGBoost. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Confusion matrix of RF. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Distribution of faults types. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Classification report of KNN. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Confusion matrix of XGBoost. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Confusion matrix of KNN. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Distribution of fault currents. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Confusion matrix of DT. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

KNN model working [80]. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”

Line plots current over fault type. by Zawar Ahmed Khan (22574556)

“…To address these limitations, this study evaluates different machine learning algorithms for accurate and efficient fault detection using a dataset of triaxial vibrational data converted into current variables. …”