MATLAB code to generate the figure in S2 Appendix. by Francesco Colussi (22421582)

AI KRegression by CHIN-CHENG CHU (20718575)

Highly Flexible, Breathable, and User-Comfortable All-Porous Polymeric Triboelectric Sensors for Wearable Sign Language Interpretation by Min-Kyu Seo (21756507)

“…The fabrication of porous Ecoflex utilizes an innovative methodology that employs a sacrificial brown sugar template, resulting in a highly porous structure that enhances breathability and user comfort for prolonged wearable applications. …”

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. …”

Effect of the replacement parameter . by Fynn Bachmann (21409831)

Dataset2. by Francesco Colussi (22421582)

Dataset1. by Francesco Colussi (22421582)

Proxy FC provides limited explanatory power in understanding empirical FC patterns. by Michael Forrester (6165878)

Exemplar proxy FC computed from eigenvectors of the structural connectivity matrix <i>w</i>_<i>ij</i>, computed by taking the outer product of an eigenvector with itself. by Michael Forrester (6165878)

Digital generation: the association between daily smartphone app use and well-being by Konstantin Schenkel (5555525)

Presents the bibliometric search results. by Yan She (8639796)

S1 Data. Bibliometric analysis. S2 Data. Estrogen level analysis. S3 Data. MicroCT quantification. S4 Data. Markers of bone metabolism. by Yan She (8639796)

Modeling results of 8-week-old female C57BL/6J mice. by Yan She (8639796)

Sexual maturity status of female C57BL/6J Mice at different ages. by Yan She (8639796)

Flow chart of data screening and analysis. by Yan She (8639796)

Summary of the literature. by Narisetti Ashok Kumar (22821918)

“…The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. …”

Three-phase Inverter model configuration. by Narisetti Ashok Kumar (22821918)

“…The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. …”

Comparison analysis of THD. by Narisetti Ashok Kumar (22821918)

“…The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. …”

Schematic model of proposed PQ mitigation model. by Narisetti Ashok Kumar (22821918)

“…The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. …”

Comparison of with and without controller. by Narisetti Ashok Kumar (22821918)

“…The input of the proposed optimal controller was considered as dc voltage, coupling voltage and load current, based on these values, the controller generated a pulse signal of a three-phase inverter to decrease the power supply from PV and wind to maintain a constant frequency and power factor. …”