Automatically detecting important moments from everyday life using a mobile device

This paper proposes a new method to detect important moments in our lives. Our work is motivated by the increase in the quantity of multimedia data, such as videos and photos, which are capturing life experiences into personal archives. Even though such media-rich data suggests visual processing to identify important moments, the oft-mentioned problem of the semantic gap means that users cannot automatically identify or retrieve important moments using visual processing techniques alone. Our approach utilises on-board sensors from mobile devices to automatically identify important moments, as they are happening

AN ARCHITECTURE-BASED TECHNIQUE TO MOBILE CONTACT RECOMMENDATION FOR EMERGENCY SITUATION IN NIGERIA

Smart technologies such as smart phones, iPad and Tablets are ubiquitous in today’s society. They possess increasing computing and storage potentials. Thus, emerging as a dominant computing platform for different kinds of end-users. However, these technological possibilities have not been fully explored for emergency situations where close relatives must be contacted. This paper therefore presents an Emergency Contact Recommendation Model (ECRM) that was implemented into an emergency contact recommendation system. An architectural based approach was employed to highlight the contribution this paper made to extant knowledge. The leveraged of the Dust miner algorithmic technique, the direct discriminative pattern mining, and the Bayesian Inference Network technique were used to formulate the ECRM. The ECRM was implemented using the Java development and android tool kit. The model demonstrated commendable capabilities - considering the foregoing techniques when compared with what obtains in literature- to make useful recommendation in emergency situation(s) after implementation.   http://dx.doi.org/10.4314/njt.v36i12