An ad hoc network is an infrastructureless network in which nodes perform terminal as well as routing functions. A routing protocol is the only substitute to complete the communications in the absence of an access point. In spite of that mobile nodes or so called routers uses some mechanism for calculating the best route when it has multiple routes for the same destination. On the basis of one ...

This work presents a novel Content-Based Video Retrieval approach in order to cope with the semantic gap challenge by means of latent topics. Firstly, a supervised topic model is proposed to transform the classical retrieval approach into a class discovery problem. Subsequently, a new probabilistic ranking function is deduced from that model to tackle the semantic gap between low-level features...

We present a new method for proving liveness and termination properties for fair concurrent programs, which does not rely on finding a ranking function or on computing the transitive closure of the transition relation. The set of states from which termination or some liveness property is guaranteed is computed by a backwards reachability analysis. A central technique for handling concurrency is...

Common measures of term importance in information retrieval (IR) rely on counts of term frequency; rare terms receive higher weight in document ranking than common terms receive. However, realistic scenarios yield additional information about terms in a collection. Of interest in this paper is the temporal behavior of terms as a collection changes over time. We propose capturing each term’s col...

Traditionally the use of pseudo relevance feedback (PRF) techniques for query expansion has been demonstrated very effective. Particularly the use of Relevance Models (RM) in the context of the Language Modelling framework has been established as a high-performance approach to beat. In this paper we present an alternative estimation for the RM promoting terms that being present in the relevance...

We propose to model relative attributes that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can capture that animal A is ‘furrier’ than animal B, or image X is ‘brighter’ than image B. Given training data stating how object/scene categories relate according to different attributes, we learn a ranking function per attrib...