Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
— This paper considers scheduling divisible workloads from multiple sources in linear networks of processors. We propose a two phase scheduling strategy (TPSS) to minimize the ov...
This paper presents a task allocation scheme via selforganizing swarm coalitions for distributed mobile sensor network coverage. Our approach uses the concepts of ant behavior to ...
Kian Hsiang Low, Wee Kheng Leow, Marcelo H. Ang Jr...
We present an application of formal concept analysis aimed at creating and representing a meaningful structure of knowledge communities under the form of a lattice-based taxonomy ...
Camille Roth, Sergei A. Obiedkov, Derrick G. Kouri...
Research indicates that impasse-driven learning can have important benefits for improving student mastery of material. When students recognize gaps in their understanding of a con...