Knowledge acquisition techniques for a military planning system

2002 ◽  
Author(s):  
M. desJardins
Keyword(s):  
Knowledge Acquisition ◽  
Planning System ◽  
Military Planning

Process Modelling and Formulation for the Development of an Intelligent Set-up Planning System

1995 ◽  
Vol 209 (6) ◽  
pp. 455-467 ◽  
Author(s):  
S K Ong ◽  
A Y C Nee
Keyword(s):  
Problem Solving ◽  
Knowledge Acquisition ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Planning System ◽  
Production Rules ◽  
Knowledge Based ◽  
Control Framework ◽  
Thinking Processes ◽  
Set Up

A set-up is a group of features that are machined together in one particular orientation and position of a workpiece. Hence, the task of set-up planning is to group the features that are required on a part into set-ups and sequence these resultant groups to form an optimally ordered plan to produce the part. This ordered plan has forthright effects on the process and fixture plans that are needed to produce this part. This paper presents the knowledge modelling and formulation process for the development of an intelligent set-up planning system. The knowledge-based information needed for set-up planning from experts in the machining domain and the problem-solving procedures of these experts were obtained from a knowledge acquisition process and modelled in this set-up planning system. The acquired knowledge is modelled using production rules and fuzzy sets, and is coupled with a fuzzy-set-based formulation of the problem-solving procedures of these experts. This formulation and a control framework for set-up planning that closely emulates the expert's thinking processes during planning are integrated to formulate set-up plans.

scholarly journals Knowledge Acquisition and Construction of a RDF-Ontology for Computer-Assisted Surgery

2021 ◽  
Author(s):  
Niclas Hagen ◽  
Reinald Kühle ◽  
Frederic Weichel ◽  
Urs Eisenmann ◽  
Petra Knaup-Gregori ◽  
...  
Keyword(s):  
Knowledge Acquisition ◽  
Maxillofacial Surgery ◽  
Computer Assisted Surgery ◽  
Mandibular Reconstruction ◽  
University Hospital ◽  
Planning System ◽  
Oral And Maxillofacial Surgery ◽  
Computer Assisted ◽  
Planning Systems ◽  
Virtual Planning

The integration of surgical knowledge into virtual planning systems plays a key role in computer-assisted surgery. The knowledge is often implicitly contained in the implemented algorithms. However, a strict separation would be desirable for reasons of maintainability, reusability and readability. Along with the Department of Oral and Maxillofacial Surgery at Heidelberg University Hospital, we are working on the development of a virtual planning system for mandibular reconstruction. In this work we describe a process for the structured acquisition and representation of surgical knowledge for mandibular reconstruction. Based on the acquired knowledge, an RDF(S) ontology was created. The ontology is connected to the virtual planning system via a SPARQL interface. The described process of knowledge acquisition can be transferred to other surgical use cases. Furthermore, the developed ontology is characterised by a reusable and easily expandable data model.

The Distinction between Linguistic and Conceptual Semantics in Medical Terminology and its Implication for NLP-Based Knowledge Acquisition

1998 ◽  
Vol 37 (04/05) ◽  
pp. 327-333 ◽  
Author(s):  
F. Buekens ◽  
G. De Moor ◽  
A. Waagmeester ◽  
W. Ceusters
Keyword(s):  
Natural Language ◽  
Knowledge Acquisition ◽  
Natural Language Understanding ◽  
Knowledge Bases ◽  
Linguistic Knowledge ◽  
Medical Terminology ◽  
Language Understanding ◽  
Conceptual Semantics

AbstractNatural language understanding systems have to exploit various kinds of knowledge in order to represent the meaning behind texts. Getting this knowledge in place is often such a huge enterprise that it is tempting to look for systems that can discover such knowledge automatically. We describe how the distinction between conceptual and linguistic semantics may assist in reaching this objective, provided that distinguishing between them is not done too rigorously. We present several examples to support this view and argue that in a multilingual environment, linguistic ontologies should be designed as interfaces between domain conceptualizations and linguistic knowledge bases.

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