Maritime decarbonization and strict international regulations have forced liner companies to
find new solutions for reducing fuel consumption and greenhouse gas emissions in recent …

Abstract Machine learning provides a data-driven approach for creating a digital twin of a
system–a digital model used to predict the system behavior. Having an accurate digital twin …

Limiting carbon dioxide emissions is one of the main concerns of green shipping. As an
important carbon intensity indicator, the Energy Efficiency Operational Index (EEOI) …

The asymmetric demands of metro lines in megacities can cause high passenger wait times
and substantial underutilization of vehicle capacity. The problem is difficult to address …

A cyclic redundancy check (CRC) is a widely used technique in data communication for
detecting data transmission errors. However, existing FPGA-based parallel CRC hardware …

Traffic flow prediction in spatio-temporal networks is a crucial aspect of Intelligent
Transportation Systems (ITS). Existing traffic flow forecasting methods, particularly those …

Abstract Advanced Driver Assistance System (ADAS) is the latest buzzword in the
automotive industry aimed at reducing human errors and enhancing safety. In ADAS …

The computational complexity of Nonlinear Model Predictive Control (NMPC) often hinders
their application to cyber-physical systems with fast dynamics, such as mobile robots or …

Machine learning algorithms are widely used in many intelligent applications and cloud
services. Currently, the hottest topic in this field is Deep Learning represented often by …

Autonomous driving has become an important research area in recent years, and the
corresponding system creates an enormous demand for computations. Heterogeneous …