Machine learning models are used to create and enhance various disease prediction
frameworks. Ensemble learning is a machine learning technique that combines multiple …

Mental health is a basic need for a sustainable and develo** society. The prevalence and
financial burden of mental illness have increased globally, and especially in response to …

Soft sensors are widely constructed in process industry to realize process monitoring, quality
prediction, and many other important applications. With the development of hardware and …

Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …

Artificial intelligence (AI) and machine learning, a subset of AI, are increasingly used in
medicine. AI excels at performing well-defined tasks, such as image recognition; for …

In the face of a growing global population, plant breeding is being used as a sustainable tool
for increasing food security. A wide range of high-throughput omics technologies have been …

With the influx of technological advancements and the increased simplicity in
communication, especially through emails, the upsurge in the volume of unsolicited bulk …

Recent advancements and major breakthroughs in machine learning (ML) technologies in
the past decade have made it possible to collect, analyze, and interpret an unprecedented …

Since the inception of Industry 4.0 in 2012, emerging technologies have enabled the
acquisition of vast amounts of data from diverse sources such as machine tools, robust and …

Safety and reliability are absolutely vital for sophisticated Railway Point Machines (RPMs).
Hence, various kinds of sensors and transducers are deployed on RPMs as much as …