Optimization approaches in machine learning (ML) are essential for training models to
obtain high performance across numerous domains. The article provides a comprehensive …

The Sixth Generation network (6G) can support autonomous driving along with various
vehicular applications like Vehicular Edge Computing (VEC), a distributed computing …

Smart cities have attracted a lot of attention from interdisciplinary research, and plenty of
artificial intelligence based solutions have been proposed. However, cyber security has …

Classifying network time series (NTS) is crucial for automating network administration and
ensuring cyberspace security. It enables the detection of anomalies, the identification of …

Abstract The evolution of Autonomous Vehicles (AVs) has blurred the distinction between
drivers and passengers, resulting in increased demand for in-car entertainment …

Traffic forecasting plays a vital role in the management of urban road networks and the
development of intelligent transportation systems. To effectively capture spatial and temporal …

Deep learning-based univariate time series classification can improve the user experience
of Open Radio Access Network (RAN)-based Cellular Vehicle-to-Everything (CV2x) …

The field of autonomous driving research has made significant strides toward achieving full
automation, endowing vehicles with self-awareness and independent decision making …

Obstructive Sleep Apnea (OSA) is the cessation in breathing that must be identified as early
as possible to save the patient's life. Apart from physical diagnosis, a deep learning model …

The effectiveness of implementing intelligent reflecting surface (IRS) for millimeter-wave
(mmWave)-non-orthogonal multiple-access (NOMA) systems has allowed for significant sum …