Experimental setup under ablation experiments. by Long Di (9977453)

Static obstacle avoidance scene setup. by Long Di (9977453)

fNIRS source-detector array setup. Red Indicates Source; Yellow Indicates Detector. by Swati M. Surkar (8399427)

Experimental Setup and live ECG recording during an on-air primetime TV interview: On the left side, the science communicator was interviewed by Marco Dedola, director of the “Scie... by David Vagni (8060432)

AI KRegression by CHIN-CHENG CHU (20718575)

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. …”

Model and learning rule. by Janis Keck (21587252)

“…<b>(C), (D)</b> Invariance of learning rules with respect to temporal order. We plot synaptic weight change of a single synapse in a setup with a single pre- and postsynaptic neuron, respectively. …”

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)

LSTM model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

CNN model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Ceramic bearings. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Geometric contact arc length model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Indentation fracture mechanics model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Grinding particle cutting machining model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Three stages of abrasive cutting process. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

CNN-LSTM action recognition process. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”