We show how to learn causal structure from interventions with unknown effects and/or side effects by adding the intervention variables to the graph and using Bayesian inference to learn the resulting two-layered graph structure. We show that, on a datatset consisting of protein phosphorylation levels measured under various perturbations, learning the targets of intervention results in models th...

Partial differential equations (PDEs) play a prominent role in many disciplines such as applied mathematics, physics, chemistry, material science, computer science, etc. PDEs are commonly derived based on physical laws or empirical observations. However, the governing equations for many complex systems in modern applications are still not fully known. With the rapid development of sensors, comp...

Much attention is currently being focussed on the use of the World Wide Web as a delivery channel for teaching and learning. A significant problem with the Web as a learning environment is that it does not adapt to the needs of the individual learner. VALIENT is an attempt to add a degree of adaptability to the Web. VALIENT combines conventional Web-based delivery with what are termed Intellige...

The Learning Objects Structure Petri Net, LOSPN describes the structure and mutual dependence of a set of learning objects, LOs. It allows to model the context of each learning object in terms of preconditions (prerequisites) and postconditions (learning objectives or learning targets). It is this property which makes re-use of learning objects in different courses and in different departments ...

Most traditional algorithms for compressive sensing image reconstruction suffer from the intensive computation. Recently, deep learning-based reconstruction algorithms have been reported, which dramatically reduce the time complexity than iterative reconstruction algorithms. In this paper, we propose a novel Deep Residual Reconstruction Network (DRNet) to reconstruct the image from its Compress...

The optimal interpolative (OI) classification network is extended to include fault tolerance and make the network more robust to the loss of a neuron. The OI net has the characteristic that the training data are fit with no more neurons than necessary. Fault tolerance further reduces the number of neurons generated during the learning procedure while maintaining the generalization capabilities ...

Net-based collaborative learning discourses often suffer from deficiencies such as lack of coherence and coordination. It is suggested that the provision of two functionalities, referencing and typing, which learners may optionally use to ground their contributions during a chatbased discourse, can improve collaborative learning. In particular, we examined if goal focus, type of task and group ...

The rapid rise in popularity of multimedia applications, such as VoIP, IPTV and Video Conferencing, intensifies the need to consider resource management for user satisfaction. Furthermore, improving Quality of Experience (QoE) in Software Defined Networks (SDNs) services is one of the important issues to be addressed by provisioning optimum resource management. In this paper, resource allocatio...