Data‐driven epoch, the development of machine learning (ML) in materials and device
design is an irreversible trend. Its ability and efficiency to handle nonlinear and game …

This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in
developing countries where it is present in significant quantities. It greatly increases the risk …

We consider a high-dimensional nonlinear computational model of a dynamical system,
parameterized by a vector-valued control parameter, in the presence of uncertainties …

On-device ML is increasingly used in different applications. It brings convenience to offline
tasks and avoids sending user-private data through the network. On-device ML models are …

Tower cranes (TCs) are vital equipment highly sought after on construction sites due to their
efficiency in handling and lifting heavy loads. Nevertheless, the use of TCs on construction …

The target detection based on electroencephalogram (EEG) signals is a new target
detection method. This method recognizes the target by decoding the specific neural …

Experimental data of repeated tests on mechanical properties of materials are usually small
due to the high cost and long duration of experiments. In addition, experimental data of …

In this article, we present a collection of fifteen novel contributions on machine learning
methods with low-quality or imperfect datasets, which were accepted for publication in the …

Photodetectors (PDs) based on perovskite materials have become a strong contender for
next-generation optical sensing. Because it has the advantages of high photoelectric …