Nicholas Kenelm Taylor

Comparing knowledge elicitation techniques: a case study

Three knowledge elicitation techniques were used to extract knowledge bases from experts on lighting for industrial inspection tasks. The techniques were: I a structured interview; II ‘twenty questions’ —imputing rules from information requests; and III a card sort. The first two techniques generate protocols, and in these cases two knowledge engineers independently extracted production rules from the protocols. In the third technique rules were derived from the classification of lighting solutions. The first two techniques led to about the same number of rules, the card sort to less. There was a slightly higher percentage of agreement between the rules extracted separately by the knowledge engineers for the normal interview than for the ‘twenty questions’ technique. Disagreements between the knowledge engineers were resolved by discussion, and an expert system to select special lights for inspection tasks was implemented. Of the rules finally agreed on, the percentage which could be implemented in the expert system was less for the twenty questions technique than for the others. The agreed rules were mailed to the expert, who indicated whether she agreed, disagreed, or wanted to make a modification. This secondary stage of elicitation revealed no evident difference between the three techniques in terms of the proportion of rules validated by the expert.

Three dimensional analysis of the lamina cribrosa in glaucoma

Background/aim: Structural changes in the lamina cribrosa have been implicated in the pathogenesis of glaucomatous optic atrophy. The aim of this study was to determine a measure the surface variability of the cup floor in normal subjects and patients with glaucoma. Methods: A sample of age matched normal subjects (NN), patients with low tension glaucoma (LTG), and primary open angle glaucoma (POAG) were included in the study. The glaucoma groups were matched for the severity of the visual field loss. Mean 10 degree topographic images of normal and glaucomatous eyes from the Heidelberg retina tomograph were imported into ERDAS image processing software where topographic analysis of the cup floor could be assessed. Each image was processed using customised spatial filters that calculated the surface depth variation in localised neighbourhood areas across each image. The local change in depth across the cup floor surface was determined and compared between the three clinical groups. Results: The depth variation in the cup floor was largest in normal subjects followed by LTG and POAG. Highly statistically significant differences in surface depth variability of the cup floor existed between normal and LTG (p = 0.005), between normal and POAG (p<0.0001), and between LTG and POAG groups (p<0.0001). The variability and skewness of depth difference across the optic cup floor were also significantly different between the three clinical groups. Conclusion: A new parameter quantifying depth variations in the cup floor significantly discriminated between groups of normal and glaucoma patients. This new parameter may contribute to a better understanding of the pathogenesis of the glaucomatous optic nerve damage in different types of glaucoma.

Fault diagnosis on autonomous robotic vehicles with RECOVERY: an integrated heterogeneous-knowledge approach

The need for embedding fault diagnosis into goal-orientated autonomous robotic vehicles for increased mission robustness is described. The RECOVERY system, a method for increasing the diagnostic capability by integrating commonly available heterogeneous knowledge is presented. Initial real-water results using the Ocean Systems Laboratorys RAUVER vehicle are given.

Pervasive Computing in Daidalos

Daidalos offers a platform for service and identity management that supports secure context-aware and personalizable delivery of service discovery, composition, and adaptation. It also provides a runtime environment for deployment and execution.

A Pervasive Environment Based on Personal Self-Improving Smart Spaces

Ubiquitous computing (or ambient intelligence) has been the subject of research in the mobile telecommunications field for many years. Developments such as the Internet of Services and Grid computing have complemented and strengthened this work. The ubiquitous computing paradigm integrates information processing into the objects that surround us in our environment. One particular focus has been on the development of smart spaces in homes, offices and public areas, in which automation can be used to support the user. However, these are static spaces that offer ubiquitous characteristics in a limited environment, like islands in an ocean. When the user steps outside of this island, all of this is lost. The Persist project is investigating a novel approach which combines mobile communications with the notions of these static smart spaces to produce more general ubiquitous or pervasive systems in the form of the self-improving Personal Smart Space. The vision is that a Personal Smart Space will stay with the user as he/she moves around and provide an interface between the user and the various services and sensors which are available, either directly or indirectly, as well as with other neighbouring Personal Smart Spaces. Thus Personal Smart Spaces will be able to interface to local devices and services (even when no Internet connectivity is available to the user) and to interact with other Personal Smart Spaces to create a more powerful and flexible environment for the user and one which is more truly ubiquitous.

Survey of Paid Employment undertaken by Full‐time Undergraduates at an Established Scottish University

abstract This article presents the results of a survey of the paid employment undertaken by a sample of undergraduates during the 1995‐96 academic year. The study was based on questionnaire returns from 191 respondents. The results indicate that the amount of work undertaken increases in each year of study with the exception of the final year. During term time over one‐quarter of respondents were working at weekends and 10% were working during week‐days. The primary reason given for working during term time was financial necessity but academic and other benefits were also perceived by some respondents. The article concludes with a discussion of the findings.

Ant Colony Robot Motion Planning

A new approach to robot motion planning is proposed by applying ant colony optimization with the probabilistic roadmap planner (PRM). The PRM is a path planning method that consists of capturing the connectivity of the robots free space in a network called the roadmap. An ant colony robot motion planning (ACRMP) method is proposed that takes the benefit of collective behaviour of ants foraging from a nest to a food source. Two groups of ants are placed at both the nest and food source respectively. A number of ants (agents) are released from the nest (start configuration) and begin to forage (search) towards the food (goal configuration). Each ant has a certain quantity of pheromone to be dropped along the path. The ants track down the pheromone trails previously dropped by the nests ants to accomplish the path between the two points of nest and food respectively. Results from preliminary tests show that the ACRMP is capable of reducing the intermediate configuration between the initial and goal configuration in an acceptable running time

Managing User Preferences for Personalization in a Pervasive Service Environment

The importance of personalization in many application areas is now well accepted and this is true of both telecommunications and web services. One important research area which spans telecommunications and web services is that of pervasive systems. Here the role of personalization is essential in order for a pervasive system to function effectively without the need for unnecessary interaction with the user and for improving the user experience by providing appropriate support for the actions taken by the user. However, in order to provide personalization in such a system the system needs to build up an adequate set of user preferences. This is a non-trivial task. This paper describes briefly the approaches to personalization included in the development of the pervasive system in the Daidalos project. It discusses some of the strategies involved in managing user preferences and the approaches being taken in the Daidalos system. In particular in the second phase a novel approach is proposed to deal with this problem.

A Personal Smart Space approach to realising Ambient Ecologies

One of the main aims of research in the area of ubiquitous or pervasive computing is that of dealing with the rapidly growing number of sensors, devices and artefacts in the users environment, which have an increasing amount of intelligence built in and which can communicate via wireless technologies. To assist in this the concept of Ambient Ecologies has been proposed as a metaphor for modelling ubiquitous or pervasive applications based on fixed smart spaces, such as the Smart Home. This paper describes the notion of a Personal Smart Space (PSS) and how it can be used to realise Ambient Ecologies. It goes on to show how, using a PSS approach, one can handle more general situations in which an Ambient Ecology is formed dynamically when two or more PSSs come together wherever this may be. The idea of a PSS is fundamental to the prototype pervasive system that has been developed within the Persist project where it has been used to demonstrate a range of different pervasive applications. In particular this prototype has been used to demonstrate a futuristic situation in the smart home where the total environment is under user control. It is shown how the requisite Ambient Ecologies can be handled by PSSs. The paper concludes with an evaluation of the Persist prototype in which mobile PSSs are used to affect the behaviour of fixed PSSs in their environment.

An integrated diagnostic architecture for autonomous underwater vehicles

The architecture of an advanced fault detection and diagnosis (FDD) system is described and applied with an Autonomous Underwater Vehicle (AUV). The architecture aims to provide a more capable system that does not require dedicated sensors for each fault, can diagnose previously unforeseen failures and failures with cause-effect patterns across different subsystems. It also lays the foundations for incipient fault detection and condition-based maintenance schemes. A model of relationships is used as an ontology to describe the connected set of electrical, mechanical, hydraulic, and computing components that make up the vehicle, down to the level of least replaceable unit in the field. The architecture uses a variety of domain dependent diagnostic tools (rulebase, model-based methods) and domain independent tools (correlator, topology analyzer, watcher) to first detect and then diagnose the location of faults. Tools nominate components, so that a rank order of most likely candidates can be generated. This modular approach allows existing proven FDD methods (e.g., vibration analysis, FMEA) to be incorporated and to add confidence to the conclusions. Illustrative performance is provided working in real time during deployments with the RAUVER hover capable AUV as an example of the class of automated system to which this approach is applicable.