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B Debska

Publications and source records attributed to B Debska.

3 recordsLinked to original sources

Prediction of physical and chemical qualities of crude-oil using statistical time series analysis.

An application of a statistical time series analysis method is given for the interpretation of physical and chemical qualities of crude-oil samples taken from two oil-fields in Poland. The analytical data was gathered in the years 1995-1999, the information being collected once a month. Randomly selected crude-oil samples were examined in several analytical laboratories. For each sample examined, the following chemical-physical parameters were defined: date, source of the sample, specific gravity, density, colour, relative viscosity, viscosity, kinematic viscosity, drip point, setting point, etc. The data obtained played a decisive role in classifying the samples of crude-oil and in forecasting the properties of crude-oil that will be obtained from the mines in the future. To process the data obtained, the STATISTICA programme was used. It contains a module for time series analysis and for graphical presentation of the results.

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Fuzzy definition of molecular fragments in chemical structures

This paper presents a methodology for seeking the relationships between chemical substructures (molecular fragments) and spectral parameters using a computer collection data of molecular spectra. To establish the spectrum-structure correlations, the program has to search the chemical structure base in order to find compounds containing a given molecular fragment in the molecule. There exists no sole definition of a substructure, as it always depends on the type of problem dealt with. In the problem of structural identification, fuzzy definitions of substructures are applied, and their forms are imposed by the spectral methods used.

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Automatic generation of knowledge base from infrared spectral database for substructure recognition

This paper presents a new methodology of chemical substructure recognition by interpretation of an infrared spectrum. The approach in spectrum interpretation is based on the determination of functional groups, which may be present or absent in compounds whose structure is unknown. The process of searching for spectrum-substructure correlation is realized by application of a statistical algorithm. In this method, correlations are generalized and condensed into a set of interpretation rules which are applied to the interpretation of an unknown compound's spectrum in order to predict whether the respective substructures are present or absent in the unknown molecule.

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