A Framework of Fuzzy Diagnosis

Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent eLearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e. g., the fault diagnosis of student behaviors in the eLearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, Fuzzy Diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the Fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world eLearning case is described to demonstrate the application of our diagnostic framework.

Papillary urothelial neoplasm of low malignant potential: reliability of diagnosis and outcome

OBJECTIVE To determine the ability of pathologists to reproducibly diagnose a newly defined lesion, i.e. the papillary urothelial neoplasm of low malignant potential (PUNLMP) using the published criteria, defined by the 1998 World Health Organisation/International Society of Urological Pathology (WHO/ISUP) classification system; in addition, debate remains about the clinical behaviour of these lesions, thus the rates of recurrence and progression of PUNLMP lesions were assessed and compared with low-grade papillary urothelial carcinomas (LG-PUC) and high-grade (HG-PUC) over a 10-year follow-up. PATIENTS AND METHODS Forty-nine cases of superficial bladder cancer (G1-3 pTa) representing an initial diagnosis of transitional cell carcinoma made in 1990 were identified and re-graded using the 1998 WHO/ISUP classification by two pathologists. Inter-observer agreement was assessed using Cohen weighted kappa statistics. After reclassification the clinical follow-up was reviewed retrospectively, and episodes of recurrence and progression recorded. RESULTS The inter-observer agreement was moderate, regardless of whether one (kappa 0.45) or two (kappa 0.60) pathologists were used to grade these lesions. Re-classification identified 12 PUNLMP, 28 LG-PUC and nine HG-PUC. PUNLMP lesions recurred in 25% (3/12) of cases; no progression was documented. Recurrence rates were 75% (21/28) and 67% (6/9) for LG- and HG-PUC, respectively, and progression rates were 4% (1/28) and 22% (2/9). CONCLUSION The 1998 WHO/ISUP classification of urothelial neoplasms can be reproducibly applied by pathologists, with a moderate level of agreement. There is evidence that PUNLMP lesions have a more indolent clinical behaviour than urothelial carcinomas. However, the risk of recurrence and progression remains, and clinical monitoring of these patients is important.

Multiagent realization of prediction-based diagnosis and loss prevention

A multiagent diagnostic system implemented in a Protege-JADE-JESS environment interfaced with a dynamic simulator and database services is described in this paper. The proposed system architecture enables the use of a combination of diagnostic methods from heterogeneous knowledge sources. The process ontology and the process agents are designed based on the structure of the process system, while the diagnostic agents implement the applied diagnostic methods. A specific completeness coordinator agent is implemented to coordinate the diagnostic agents based on different methods. The system is demonstrated on a case study for diagnosis of faults in a granulation process based on HAZOP and FMEA analysis.