In recent years, the infrastructure of Wireless Internet of Sensor Networks (WIoSNs) has
been more complicated owing to developments in the internet and devices' connectivity. To …

A growing portfolio of research has been reported on the use of machine learning-based
architectures and models in the domain of healthcare. The development of data-driven …

The usage of IoT-based smart meter in electric power consumption shows a significant role
in helping the users to manage and control their electric power consumption. It produces …

Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of
the brain which results in recurrent seizures. Though the epilepsy in general is considered …

In this study, a weighted federated learning approach is proposed for electrocardiogram
(ECG) arrhythmia classification. The proposed approach considers the heterogeneity of data …

The deep learning techniques have been playing an important role in the identification and
classification problems such as diseases in medical science, marketing in the industry …

The abnormality of haemoglobin in the human body is the fundamental cause of
thalassemia disease. Thalassemia is considered a common genetic blood condition that has …

The innovation in technologies related to health facilities today is increasingly helping to
manage patients with different diseases. The most fatal of these is the issue of heart disease …

The method outlined in this paper employs transfer learning and adversarial training to
enhance the precision of pneumonia identification in chest X-rays. The authors use the …

Hydrogen storage using liquid organic hydrogen carriers (LOHCs) is a promising method.
The data sets for hydrogen storage using dibenzyltoluene (DBT) are considered in this …