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At least 757 records · Page 42Linked to original sources
PubMed2002

Expert system for the on-line diagnosis of anaerobic wastewater treatment plants.

A diagnosis system for anaerobic wastewater treatment processes is presented. The system is able to recognise the state and trend of the operation and suggest the appropriate control action. The on-line variables measured were gas flow rate and composition (methane and carbon monoxide), feed and recycling flow rates, temperature and pH, while the manipulable inputs are feed, recycling and buffer-addition flow rates. The diagnosis system comprises a structured rule base, incorporating expert knowledge using fuzzy logic features. The structure of the system is based on the classification of information related to the process in three categories: i) the state of the process, ii) its trend and iii) the recommended set-point values for the inputs manipulated: feeding, buffer and recycling pumps. The system was applied to diagnose the operation of a 1.1 m3 hybrid UASB-UAF treating wastewater from a fibreboard production factory under different conditions (overload and underload), corresponding to some of the typical causes of destabilisation in anaerobic wastewater treatment plants. These situations require control action in order to maintain the stability and the treatment capacity of the reactor. The application of the system developed for the purpose of managing the situation proved to be reliable for supplying the actual state and trend of the process, as well as the adequate set point values to recover stable operation and/or to avoid further destabilisation.

Bacteria, Anaerobic↗
PubMed1996

Comparison of an expert system with other clinical scores for the evaluation of severity of asthma.

"Asthmaexpert" was produced at the special request of several clinicians in order to obtain a better understanding of the medical decisions taken by clinical experts in the management of asthmatic patients. In order to assess the severity of asthma, a new score called Artificial Intelligence score (AI score), produced by Asthmaexpert, was compared with three other scores (Aas, Hargreave and Brooks). One hundred patients were enrolled prospectively in the study during their first consultation in the out-patient clinic. Distribution of severity level according to the different scores was studied, and the reliability between AI and other scores was evaluated by Kappa and MacNemar tests. Correlations with functional parameters were performed. The AI score assessed higher levels of severity than the other scores (Kappa = 18, 28 and 10% for Aas, Hargreave and Brooks, respectively) with significant MacNemar test in all cases. There was a significant correlation between AI score and forced expiratory volume in one second (FEV1) (r = 0.73). These data indicate that the AI score is a severity score which defines higher levels of severity than the chosen scores. Correlations for functional parameters are good. This score appears easy to use for the first consultation of an asthmatic patient.

Adult↗
PubMed2005

A Grid-based HIV expert system.

OBJECTIVES: This paper addresses Grid-based integration and access of distributed data from infectious disease patient databases, literature on in-vitro and in-vivo pharmaceutical data, mutation databases, clinical trials, simulations and medical expert knowledge. METHODS: Multivariate analyses combined with rule-based fuzzy logic are applied to the integrated data to provide ranking of patient-specific drugs. In addition, cellular automata-based simulations are used to predict the drug behaviour over time. Access to and integration of data is done through existing Internet servers and emerging Grid-based frameworks like Globus. Data presentation is done by standalone PC based software, Web-access and PDA roaming WAP access. The experiments were carried out on the DAS2, a Dutch Grid testbed. RESULTS: The output of the problem-solving environment (PSE) consists of a prediction of the drug sensitivity of the virus, generated by comparing the viral genotype to a relational database which contains a large number of phenotype-genotype pairs. CONCLUSIONS: Artificial Intelligence and Grid technology are effectively used to abstract knowledge from the data and provide the physicians with adaptive interactive advice on treatment applied to drug resistant HIV. An important aspect of our research is to use a variety of statistical and numerical methods to identify relationships between HIV genetic sequences and antiviral resistance to investigate consistency of results.

Biometry↗