Processing system accepting exceptional numbers

A processing system comprises: input means arranged to receive at least one input group of bits representing at least one respective input number; output means arranged to output at least one output group of bits representing at least one respective output number; and processing means arranged to perform an operation on the at least one input group of bits to produce the at least one output group of bits such that the at least one output number is related to the at least one input number by a mathematical operation; and wherein each of the numbers can be any of a set of numbers which includes a series of numbers, positive infinity, negative infinity and nullity.

A model of intelligent building energy management for the indoor environment

People's interaction with the indoor environment plays a significant role in energy consumption in buildings. Mismatching and delaying occupants' feedback on the indoor environment to the building energy management system is the major barrier to the efficient energy management of buildings. There is an increasing trend towards the application of digital technology to support control systems in order to achieve energy efficiency in buildings. This article introduces a holistic, integrated, building energy management model called `smart sensor, optimum decision and intelligent control' (SMODIC). The model takes into account occupants' responses to the indoor environments in the control system. The model of optimal decision-making based on multiple criteria of indoor environments has been integrated into the whole system. The SMODIC model combines information technology and people centric concepts to achieve energy savings in buildings.

Housing supply and planning controls: the impact of development control processing times on housing supply in England

The National Housing and Planning Advice Unit commissioned Professor Michael Ball of Reading University to undertake empirical research into how long it was taking to obtain planning consent for major housing sites in England. The focus on sites as opposed to planning applications is important because it is sites that generate housing.

On the nature and cause of Specific Language Impairment: a view from sentence processing and infant research

This paper addresses the nature and cause of Specific Language Impairment (SLI) by reviewing recent research in sentence processing of children with SLI compared to typically developing (TD) children and research in infant speech perception. These studies have revealed that children with SLI are sensitive to syntactic, semantic, and real-world information, but do not show sensitivity to grammatical morphemes with low phonetic saliency, and they show longer reaction times than age-matched controls. TD children from the age of 4 show trace reactivation, but some children with SLI fail to show this effect, which resembles the pattern of adults and TD children with low working memory. Finally, findings from the German Language Development (GLAD) Project have revealed that a group of children at risk for SLI had a history of an auditory delay and impaired processing of prosodic information in the first months of their life, which is not detectable later in life. Although this is a single project that needs to be replicated with a larger group of children, it provides preliminary support for accounts of SLI which make an explicit link between an early deficit in the processing of phonology and later language deficits, and the Computational Complexity Hypothesis that argues that the language deficit in children with SLI lies in difficulties integrating different types of information at the interfaces.

Exploring carrier agents in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? The work reported in this paper is motivated towards bridging this gap by proposing a swarm-array computing approach based on ‘Intelligent Agents’ to achieve autonomy for distributed parallel computing systems. In the proposed approach, a task to be executed on parallel computing cores is carried onto a computing core by carrier agents that can seamlessly transfer between processing cores in the event of a predicted failure. The cognitive capabilities of the carrier agents on a parallel processing core serves in achieving the self-ware objectives of autonomic computing, hence applying autonomic computing concepts for the benefit of parallel computing systems. The feasibility of the proposed approach is validated by simulation studies using a multi-agent simulator on an FPGA (Field-Programmable Gate Array) and experimental studies using MPI (Message Passing Interface) on a computer cluster. Preliminary results confirm that applying autonomic computing principles to parallel computing systems is beneficial.

An MPI-based implementation of intelligent agents on clusters

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Eyes, amygdala, and other models of face processing: Questions for the SIMS model

This commentary raises general questions about the parsimony and generalizability of the SIMS model, before interrogating the specific roles that the amygdala and eye contact play in it. Additionally, this situates the SIMS model alongside another model of facial expression processing, with a view to incorporating individual differences in emotion perception.