BACKGROUND Tobacco use is responsible for the death of about 1 in 10 individuals worldwide. Mindfulness training has shown preliminary efficacy as a behavioral treatment for smoking cessation. Recent advances in mobile health suggest advantages to smartphone-based smoking cessation treatment including smartphone-based mindfulness training. This study evaluates the efficacy of a smartphone app-b...

With our busy schedules today and the rising cost of education there is a need to find a convenient and cost effective means of maximizing our educational/training experiences. New trends in the delivery/access of information are becoming more technology based in all areas of society with education being no exception. The ubiquitous use of mobile devices has led to a boom in m-commerce. Mobile ...

Phishing is an online fraudulent technique, which aims to steal sensitive information such as usernames, passwords and online banking details from its victims. To prevent this, anti-phishing education needs to be considered. This research focuses on examining the effectiveness of mobile game based learning compared to traditional online learning to thwart phishing threats. Therefore, a mobile g...

Background Mobile phone has played an increasingly important role in people’s lives; however, there is a global concern that it may cause adverse effects on health. This study aimed to assess the effect of educational intervention based on Health Belief Model (HBM) to d...

Resuscitation training has to be performed under conditions as realistic as possible. This includes both the usual measures in cardio-pulmonary resuscitation (CPR) and advanced measures, e.g. the use of Automatic External Defibrillators (AED). Currently available ECG and patient simulators either do not meet the requirements of modern training for medical professionals and laymen, or are much t...

We propose an algorithm that allows online training of a context dependent DNN model. It designs a state inventory based on DNN features and jointly optimizes the DNN parameters and alignment of the training data. The process allows flat starting a model from scratch and avoids any dependency on a GMM acoustic model to bootstrap the training process. A 15k state model trained with the proposed ...

While traditional approaches in object recognition require the specification of training examples from each class and the application of class specific classifiers, in real world situations, the immensity of the number of image classes makes this task daunting. A novel approach in object recognition is attribute based classification, where instead of training classifiers for the recognition of ...