Abstract Mobile Robots (MRs) and their applications are undergoing massive development,
requiring a diversity of autonomous or self-directed robots to fulfill numerous objectives and …

The impact of air pollution on public health is substantial, and accurate long-term predictions
of air quality are crucial for early warning systems to address this issue. Air quality prediction …

With recent advances in sensing technologies, a myriad of spatio-temporal data has been
generated and recorded in smart cities. Forecasting the evolution patterns of spatio-temporal …

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …

Optimization algorithms are used to improve model accuracy. The optimization process
undergoes multiple cycles until convergence. A variety of optimization strategies have been …

Unsupervised graph-level representation learning has recently shown great potential in a
variety of domains, ranging from bioinformatics to social networks. Plenty of graph …

Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …

Big data has a substantial role nowadays, and its importance has significantly increased
over the last decade. Big data's biggest advantages are providing knowledge, supporting …

Human activity recognition (HAR) is a challenging issue in several fields, such as medical
diagnosis. Recent advances in the accuracy of deep learning have contributed to solving the …

Traffic flow prediction plays an instrumental role in modern intelligent transportation systems.
Numerous existing studies utilize inter-embedded fusion routes to extract the intrinsic …