This study proposes integrated image processing and deep learning approaches for wheat rust disease detection and grading. Wheat stripe rust is one of the diseases affecting the crop in nearly all wheat-growing countries, where humidity and high temperatures characterize the growing season. The...

Some unusual combinations of predictor values in multivariate regression often influence tampering with the output, and filtering those observations becomes the trickiest and most challenging task. This concern is prevalent and predominant in ecological domains, especially in soil samples, as...

Motion artifacts reduce the quality of information in the electroencephalogram (EEG) signals. In this study, we have developed an effective approach to mitigate the motion artifacts in EEG signals by using empirical wavelet transform (EWT) technique. Firstly, we decompose EEG signals into...

The Internet of Things (IoT), cloud computing, and machine learning opened an opportunity for new smart systems. These technologies have triggered huge traffic and delay by continuously transmitting telemetry data to the cloud. IoT edge choice made decision-making closer to the environment,...

Over the years, women cricketers have garnered little media or societal attention. There has been much research on men’s cricket but relatively little on women’s cricket. This study aims to quantify women’s batting performances in one-day international (ODI) matches. The average batting...

The importance of the components of a system has been widely studied in the literature. The main objective of such component importance measures (CIMs) is to evaluate the effect that the components can cause in the system under study by not being present or to quantify the participation of their...