BACKGROUND Functional magnetic resonance imaging (fMRI) is commonly applied to study the neural substrates of language in clinical research and for neurosurgical planning. fMRI language mapping is used to assess language lateralisation, or determine hemispheric dominance, and to localise regions of the brain involved in language. Routine fMRI has been introduced in the Epilepsy Unit at Mediclin...

In crisis response, hierarchical organizations are being replaced by dynamic assemblies of autonomous agents that promise more agility. However, these autonomous agents might cause a decrease in effectiveness when individually constructed plans for moderately-coupled tasks are not jointly feasible. Existing coordination techniques can be applied in the pre-planning phase to guarantee feasible j...

In this paper, we propose a general-purpose framework to develop spoken dialogue systems that dynamically adapt their behavior to user requirements and preferences, as well as to the interaction context. A data-driven technique is proposed to build task structures and dialogue models within the framework. Our proposal reduces the effort required for both the implementation of a new system and t...

Cross-lingual pre-training has achieved great successes using monolingual and bilingual plain text corpora. However, most pre-trained models neglect multilingual knowledge, which is language agnostic but comprises abundant cross-lingual structure alignment. In this paper, we propose XLM-K, a model incorporating knowledge in pre-training. XLM-K augments existing with two tasks, namely Masked Ent...

The research found that there are no easy answers. But some factors emerged as particularly important in achieving and sustaining reductions in waiting times at a local level: n a sustained focus on the task, organisationally and through management and clinical effort n an understanding of the nature of waiting lists and how they form part of a whole system of care n the importance of detailed ...

We present an architecture that provides a robust, scalable and flexible software framework for planning and scheduling systems through the use of standardized industrial-strength middleware and multi-agent technology. It utilizes knowledgebased components that dynamically perform and verify the system’s configuration. The system is based on a proper formal account of hybrid planning, the integ...

Accomplishments of planning and scheduling tasks (of variable success) are performed routinely in all sorts of domains of human activity. Detailed models and analyses of this task can further the efforts of AI developers working in this domain. There are a few general issues involved in schedule management that need to be considered in an interface with a scheduling system, for example: dynamic...

Many real-world application domains that demand planning and scheduling support do not allow for a clear separation of these capabilities. Typically, an adequate mixture of both methodologies is required, since some aspects of the underlying planning problem imply consequences on the scheduling part and vice versa. Several integration efforts have been undertaken to couple planning and scheduli...

As a sustainability property, energy efficiency is of an extreme importance, especially in environments that are heavy energy consumers, such as homes and buildings. Nowadays, homes and buildings are equipped with many devices that could be exploited in order to make them smart and energy-efficient. Our vision is to bring convergence of smart environments, energy efficiency and automated planni...