163,250 research outputs found
After London.
No full textSite specific exhibition 3 March - 2 April 2011, of art works made by John Timberlake arising from a collaborative enquiry with Dr Joy Sleeman (Slade School of Fine Art, UCL). The exhibition took place at Stephen Lawrence Gallery, The Old Royal Naval College, University of Greenwich, London SE10. The exhibition featured five photograph/painting collage works by John Timberlake, a limited edition booklet with text by Joy Sleeman, and a collaborative piece, made by both. The exhibition considered the legacy and cultural ramifications of the work of Richard Jefferies, a C19th author and resident of Greenwich, who wrote an apocalyptic early science fiction novel entitled After London (1885). A panel discussion, involving John Timberlake, Joy Sleeman, Dr Matthew Beaumont (UCL) and the novelist Will Self took place on Sunday 13th March.
The exhibition curator was David Waterworth of University of Greenwich
Sleeman, J A, 44731
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/428337Surname: Sleeman. Given Name(s) or Initials: J A. Military Service Number or Last Known Location: 44731. Prisoner of War Enquiry Card Index Number: KM.686. Division Enquiry: [No Division recorded]. Rank: A/B.. Unit: HMAS Queensborough327093
Item: [2016.0049.60599] "Sleeman, J A, 44731
J. H. Sleeman et Gilbert Pollet, Lexicon Plotinianum
No full textJoly Robert. J. H. Sleeman et Gilbert Pollet, Lexicon Plotinianum. In: L'antiquité classique, Tome 52, 1983. pp. 344-345
J. H. Sleeman et Gilbert Pollet, Lexicon Plotinianum
No full textJoly Robert. J. H. Sleeman et Gilbert Pollet, Lexicon Plotinianum. In: L'antiquité classique, Tome 52, 1983. pp. 344-345
A system to detect inconsistencies between a domain expert’s different perspectives on (classification) tasks
No full textThis paper discusses the range of knowledge acquisition, including machine learning, approaches used to develop knowledge bases for Intelligent Systems. Specifically, this paper focuses on developing techniques which enable an expert to detect inconsistencies in 2 (or more) perspectives that the expert might have on the same (classification) task. Further, the INSIGHT system has been developed to provide a tool which supports domain experts exploring, and removing, the inconsistencies in their conceptualization of a task. We report here a study of Intensive Care physicians reconciling 2 perspectives on their patients. The high level task which the physicians had set themselves was to classify, on a 5 point scale (A-E), the hourly reports produced by the Unit’s patient management system. The 2 perspectives provided to INSIGHT were an annotated set of patient records where the expert had selected the appropriate category to describe that snapshot of the patient, and a set of rules which are able to classify the various time points on the same 5-point scale.
Inconsistencies between these 2 perspectives are displayed as a confusion matrix; moreover INSIGHT then allows the expert to revise both the annotated datasets (correcting data errors, and/or changing the assigned categories) and the actual rule-set. Each expert achieved a very high degree of consensus between his refined knowledge sources (i.e., annotated hourly patient records and the rule-set).
Further, the consensus between the 2 experts was ~95%. The paper concludes by outlining some of the follow-up studies planned with both INSIGHT and this general approach
Constraint capture and maintenance in engineering design
No full textThe Designers' Workbench is a system, developed by the Advanced Knowledge Technologies (AKT) consortium to support designers in large organizations, such as Rolls-Royce, to ensure that the design is consistent with the specification for the particular design as well as with the company's design rule book(s). In the principal application discussed here, the evolving design is described against a jet engine ontology. Design rules are expressed as constraints over the domain ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench's knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a system, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. Further we hypothesize that in order to appropriately apply, maintain and reuse constraints, it is necessary to understand the underlying assumptions and context in which each constraint is applicable. We refer to them as “application conditions” and these form a part of the rationale associated with the constraint. We propose a methodology to capture the application conditions associated with a constraint and demonstrate that an explicit representation (machine interpretable format) of application conditions (rationales) together with the corresponding constraints and the domain ontology can be used by a machine to support maintenance of constraints. Support for the maintenance of constraints includes detecting inconsistencies, subsumption, redundancy, fusion between constraints and suggesting appropriate refinements. The proposed methodology provides immediate benefits to the designers and hence should encourage them to input the application conditions (rationales)
Searching and ranking ontologies on the Semantic Web
No full textThe number of ontologies available online is increasing constantly. Tools that are capable of searching, retrieving, and ranking ontologies are becoming crucial to facilitate ontology search and reuse. In this document, we describe OntoSearch, which is a tool for capturing and searching ontologies on the Semantic web. We also briefly describe AKTiveRank which is used to rank OWL ontologies based on certain ontology-structure analysis.
The role of ontologies in creating and maintaining corporate knowledge: a case study from the aero industry
No full textThe Designers’ Workbench is a system, developed to support designers in large organizations, such as Rolls-Royce, by making sure that the design is consistent with the specification for the particular design as well as with the company’s design rule book(s). The evolving design is described against a jet engine ontology. Currently, to capture the constraint information, a domain expert (design engineer) has to work with a knowledge engineer to identify the constraints, and it is then the task of the knowledge engineer to encode these into the Workbench’s knowledge base (KB). This is an error prone and time consuming task. It is highly desirable to relieve the knowledge engineer of this task, and so we have developed a tool, ConEditor+ that enables domain experts themselves to capture and maintain these constraints. The tool allows the user to combine selected entities from the domain ontology with keywords and operators of a constraint language to form a constraint expression. Further, we hypothesize that to apply constraints appropriately, it is necessary to understand the context in which each constraint is applicable. We refer to this as “application conditions”. We show that an explicit representation of application conditions, in a machine interpretable format, along with the constraints and the domain ontology can be used to support the verification and maintenance of constraints
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
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