Recurrent neural networks (RNNs) are an excellent fit for regression problems where sequential data the norm since their recurrent internal structure can analyse and process long. However, RNNs prone to phenomenal vanishing gradient problem (VGP) that causes network stop learning generate poor prediction accuracy, especially in long-term dependencies. Originally, gated units such as long short-...

A hybrid algorithm based on machine learning and quantum ensemble is proposed to find an approximate solution a partial differential equation with good precision favorable scaling in the required number of qubits. The classical component consists training several regressors (weak-learners), capable solving approximately using learning. adapting QBoost solve regression problems build learners. W...

Possible links of cyberbullying with suicide and psychological problems have recently received considerable attention. Suicide-related behaviors have also been linked with viewing of associated web content. Studies on traditional bullying indicate that the roles of bullying involvement (bullies, victims, and bully-victims) matter in terms of associations with specific suicide-related behaviors ...

Purpose: The first aim of this study was to test the acculturative stress hypothesis within the Australian context predicting that immigrant adolescents are more prone to psychological and socio-cultural adaptation problems than their national Australian peers. The second aim of the study was to profile the socio-demographic factors underlying adaptation problems. Methods: The study utilised st...