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Expert Rules (expert + rule)

Distribution by Scientific Domains

Engineering	50%

Selected Abstracts

Rule based processing of the CD4000, CD3200 and CD Sapphire analyser output using the Cerner Discern Expert Module

INTERNATIONAL JOURNAL OF LABORATORY HEMATOLOGY, Issue 6 2009
P. BURGESS
Summary The latest version of our Laboratory Information System haematology laboratory expert system that handles the output of Abbott Cell-Dyn Sapphires, CD4000s and a CD3200 full blood count analyser in three high-volume haematology laboratories is described. The three hospital laboratories use Cerner Millennium Version 2007.02 software and the expert system uses Cerner Millennium Discern Expert rules and some small Cerner Command Language in-house programs. The entire expert system is totally integrated with the area-wide database and has been built and maintained by haematology staff members, as has the haematology database. Using patient demographic data, analyser numeric results, analyser error and morphology flags and previous results for the patient, this expert system decides whether to validate the main full blood count indices and white cell differential, or if the analyser results warrant further operator intervention/investigation before verifying, whether a blood film is required for microscopic review and if abnormal results require phoning to the staff treating the patient. The principles of this expert system can be generalized to different haematology analysers and haematology laboratories that have different workflows and different software. [source]

A multicriteria evolutionary algorithm for mechanical design optimization with expert rules

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 4 2005
R. Filomeno Coelho
Abstract This paper addresses the problem of optimizing mechanical components during the first stage of the design process. While a previous study focused on parameterized designs with fixed configurations,which led to the development of the PAMUC (Preferences Applied to Multiobjectivity and Constraints) method, to tackle constraints and preferences in evolutionary algorithms (EAs),, the models to be considered in this work are enriched by the presence of topological variables. In this context, in order to create optimal but also realistic designs, i.e. fulfilling not only technical requirements but also technological constraints (more naturally expressed in terms of rules), a novel approach is proposed: PAMUC II. It consists in integrating an inference engine within the EA to repair the individuals violating the user-defined rules. PAMUC II is tested on mechanical benchmarks, and provides very satisfactory results in comparison with a weighted sum method with penalization to deal with the constraints. Copyright © 2004 John Wiley & Sons, Ltd. [source]

A new universal approximation result for fuzzy systems, which reflects CNF DNF duality

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 12 2002
Irina Perfilieva
There are two main fuzzy system methodologies for translating expert rules into a logical formula: In Mamdani's methodology, we get a DNF formula (disjunction of conjunctions), and in a methodology which uses logical implications, we get, in effect, a CNF formula (conjunction of disjunctions). For both methodologies, universal approximation results have been proven which produce, for each approximated function f(x), two different approximating relations RDNF(x, y) and RCNF(x, y). Since, in fuzzy logic, there is a known relation FCNF(x) , FDNF(x) between CNF and DNF forms of a propositional formula F, it is reasonable to expect that we would be able to prove the existence of approximations for which a similar relation RCNF(x, y) , RDNF(x, y) holds. Such existence is proved in our paper. © 2002 Wiley Periodicals, Inc. [source]

Knowledge-based Diagnosis Aiding in Regulation Thermography

PROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2003
Hagen Knaf Dr.
Regulation Thermography is a diagnostic tool in the medical science based on the measurement of the body's thermoregulation ability , the so-called thermogram. The expert's rules for the interpretation of a thermogram can be modelled using Fuzzy Logic. In the present article this modelling process is briefly explained; it leads to a Fuzzy Inference System capable of evaluating thermograms with respect to e.g. signals for the presence of Breast Cancer. Some of the main points of a comparison between the expert rules and the result of a stepwise linear discriminant analysis performed on classified thermograms are presented. [source]