Job-shop scheduling is one of the most difficult production scheduling problems in industry. This paper proposes an adaptive neural network and local search hybrid approach for the job-shop scheduling problem. The adaptive ...

This paper proposes a simulated annealing (SA) algorithm based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce ...

In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the ...

This paper examines Vaudenay’s privacy model, which is one of the first and most complete privacy models that featured the notion of different privacy classes. We enhance this model by introducing two new generic adversary ...

Online virtual communities are becoming increasingly popular both within the able-bodied and disabled user communities. These games assume the use of keyboard and mouse as standard input devices, which in some cases is ...

Producing large numbers of garment variants will only be economically viable if it requires very little human effort. But garment customisation cannot always be fully automated. Applying grading rules maintain the same ...

Learners engaged in informal learning tasks often find sharing their learning experience to be helpful. Informally, a learning experience describes what a learner has done, with what learning resources. We explore technological ...

This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyond the traditional data-centric methods for activity ...