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Indoor air quality contributes to one’s comfort, wellbeing and work productivity depending on whether it is contaminated or not. Aircraft cabin environment is a type of indoor environment, which is different in terms of its need for pressurization, high occupant density and movement restriction thereby posing danger to both passengers and crew. The present study was aimed at studying the cabin air quality by ascertaining ultrafine particles on aircraft cabin at different phases of flight. Air samples were collected from 100 flights of 5 different aircraft types (B757 cargo, BAe 146, BAe 757, Airbus 319 and Airbus 320) at the 10 different phases of flights from engine start to landing and taxi-in. Mean, median and quartile values of ultrafine particle concentrations were calculated for the 10 phases of flight for individual aircraft types. The result revealed that, phases of flight where the aircraft were on ground had the higher mean values for all aircraft than other flight phases when the aircraft is in air thereby suggesting different particle sources for ground and air. Also Boeing 757 passenger aircraft recorded the highest particle concentration compared to the other 4 aircraft types. This also occurred while aircraft were on the ground, prior to the engines being started. Ultrafine particle concentration in both ground and air phases seem to be comparable with those in other indoor environments, suggesting fewer particle sources within the cabin itself and also effectiveness of the aircraft air conditioning system in removing or minimizing ultrafine particles.

The drive to extend the Web by taking advantage of automated symbolic reasoning (the so-called Semantic Web) has been dominated by a traditional model of knowledge sharing, in which the focus is on task-independent standardisation of knowledge. It appears to be difficult, in practice, to standardise in this way because the way in which we represent knowledge is strongly influenced by the ways in which we expect to use it. We present a form of knowledge sharing that is based not on direct sharing of "true" statements about the world but, instead, is based on sharing descriptions of interactions. By making interaction specifications the currency of knowledge sharing we gain a context to interpreting knowledge that can be transmitted between peers, in a manner analogous to the use of electronic institutions in multi-agent systems. The narrower notion of semantic commitment we thus obtain requires peers only to commit to meanings of terms for the purposes and duration of the interactions in which they appear. This lightweight semantics allows networks of interaction to be formed between peers using comparatively simple means of tackling the perennial issues of query routing, service composition and ontology matching. A basic version of the system described in this paper has been built (via the OpenKnowledge project); all its components use established methods; many of these have been deployed in substantial applications; and we summarise a simple means of integration using the interaction specification language itself.

Games between staff and people with intellectual disabilities serve to promote social engagement and inclusion. However, when the person has limited and idiosyncratic communicative abilities, it may be hard to gauge what his/her own view of the matter is. We examine video-taped records of two episodes in which a staff member of a group home prompted a resident with profound intellectual disabilities to play a verbal and a non-verbal 'game'. We examine how the staff member in these two cases designs her actions to solve the dilemma she faces between, on the one hand, abandoning an activity when the resident does not provide clear indications that she/he wants to continue or, on the other hand, persisting with it until the resident begins to enjoy it or, at least, participate more fully. The solution lies in a pervasive institutional practice: treat resistance or ambiguity as temporary reluctance. We discuss these interactions as examples of how principles of empowerment, inclusion and independence play out in the details of everyday interaction.

We present a manifesto for a new form of knowledge sharing that is based not on direct sharing of "true" statements about the world but, instead, is based on sharing descriptions of interactions. By making interaction specifications the currency of knowledge sharing we gain a context to interpreting knowledge that can be transmitted between peers. The narrower notion of semantic commitment we thus obtain requires peers only to commit to meanings of terms for the purposes and duration of the interactions in which they appear. This lightweight semantics allows networks of interaction to be formed between peers using comparatively simple means of tackling the perennial issues of query routing, service composition and ontology matching. Although the entire system described in this manifesto has not been built, all its components use established methods; many of these have been deployed in substantial applications; and we summarize a simple means of integration.

In this paper we define an abstract machine model for the mλ typed intermediate language. This abstract machine is used to give a formal description of the operation of run-time module replacement from the programming language Dynamic ML. The essential technical device which we employ for module replacement is a modification of two-space copying garbage collection.

Service-oriented architectures are a popular architectural paradigm for building software applications from a number of loosely coupled, distributed services. Through a set of procedural rules, workflow technologies define how groups of services coordinate with one another to achieve a shared task. A problem with workflow specifications is that often the patterns of interaction between the distributed services are too complicated to predict and analyse at design-time. In certain cases, the exact patterns of message exchange and the concrete services to call cannot be predicted in advance, due to factors such as fluctuating network load or the availability of services. It is a more realistic assumption to endow software components with the ability to make decisions about the nature and scope of their interactions at runtime. Multiagent systems offer a complementary paradigm: building software applications from a number of self interested, autonomous agents. This thesis presents an investigation into fusing the agency and service-oriented architecture paradigms, in order to facilitate flexible, workflow composition. Our approach offers an agent-based solution to service choreography and is founded on the concept of shared interaction protocols. By adopting an agent-based approach to service choreography, active autonomous agents can utilise the typically passive service-oriented architectures, found in Internet and Grid systems. In contrast with statically defined, centralised service orchestrations, decentralised agents can perform service choreography at runtime, allowing them to operate in scenarios where it is not possible to define the pattern of interaction in advance. Application to real scenarios is a driving factor behind this research. By working closely with a number of active Grid projects, namely AstroGrid and the Large-Synoptic Survey Telescope (LSST), a concrete set of requirements for scientific workflow have been derived, based on realistic science problems. This research has resulted in the MultiAgent Service Choreography (MASC) language to express scientific workflow, methodology for system building and a software framework which performs agent based Web service choreography, in order to enact distributed e-Science experiments. Evaluation of this thesis is conducted through case study, applying the language, methodology and software framework to solve a motivating set of workflow scenarios.