Existing approaches often overlook the intricate structural relationships within compounds, limiting both predictive accuracy and generalizability. To address these challenges, we propose TS-AC, a ...

Transfer learning with a graph attention network and weighted loss function provides a high-throughput method for identifying PBMT chemicals with high reliability and broad applicability domains.

Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction ...

Objective: This paper proposes a method for extracting brain functional network features based on directed transfer function (DTF) and graph theory. The method incorporates the extracted brain network ...

This Python tool allows you to draw signal-flow graphs, calculate transfer functions (SymPy code is generated for further use in Jupyter notebooks), do graph manipulations (e.g., node elimination and ...

However, in rotating machinery, the transfer function between the rotating components and the sensor distorts the vibration signal, hence, complicating the ability to apply a digital twin to new ...

Verification of the transfer function: Simplifying the signal flow graph in Figure 13 using the SFG method. In order to find the transfer function, the signal flow graph from Figure 13 is to be ...