Get Artificial Intelligence and Symbolic Mathematical Computing: PDF

By J. Calmet, J. A. Campbell (auth.), Jacques Calmet, John A. Campbell (eds.)

ISBN-10: 0387573224

ISBN-13: 9780387573229

ISBN-10: 3540573224

ISBN-13: 9783540573227

This quantity includes the papers, up-to-date at times, awarded on the first AISMC (Artificial Intelligence and Symbolic Mathematical Computations)conference, held in Karlsruhe, August 3-6, 1992. This was once the 1st convention to be dedicated to this kind of subject after an extended interval while SMC made no visual appeal in AI meetings, although it was once welcome within the early days of AI. a few meetings have been held lately on arithmetic and AI, yet none used to be at once similar in scope to this convention. a result of novelty of the area, authors got longer allocations of time than traditional within which to offer their paintings. consequently, prolonged and fruitful discussions every one paper. The introductory bankruptcy during this booklet, which used to be no longer provided through the convention, displays in lots of methods the flavour of those discussions and goals to set out the framework for destiny actions during this area of analysis. as well as the advent, the amount comprises 20 papers.

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The information summarized in the process characterization report provides a basis for defining the full-scale process. 4. Verification Verification is required before a process is scaled up and transferred to production. The timing of this verification may be critical from a regulatory point of view, as the there is little or no room for modifying the parameter values and Copyright © 2003 Marcel Dekker, Inc. specifications, particularly shifting or expanding after the regulatory submission is made.

Box, G. E. and Hunter, J. Y. (1978). 19. Hendrix, C. , What every technologist should know about experimental design, CHEMTECH (March 1979). 20. Chapman, K. , The PAR approach to process validation, Pharm. , Dec. 1984. 21. , Marcel Dekker, New York (1997). 22. Schwartz, J. , Optimization techniques in product formulation. J. Soc. Cosmet. Chem. 32:287–301 (1981). 23. Butler, J. , Statistical quality control, Chem. Eng. (Aug. 1983). 24. Deming, S. , Quality by Design, CHEMTECH, (Sept. 1988). 25. , Improved plant performance with statistical process control, Chem.

Individual assay results from content uniformity testing Individual tablet hardness values Individual tablet thickness values Tablet or capsule weight variation Individual tablet or capsule dissolution time (usually at t50%) or disintegration time 6. Individual tablet or capsule moisture content 2. Semisolid and Liquid Dosage Forms 1. 2. 3. 4. 5. 6. pH value (aqueous system) Viscosity Density Color or clarity values Average particle size or distribution Unit weight variation and/or potency values The statistical methods that may be employed to analyze numerical output data from the manufacturing process are listed as follows: 1 2.

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Artificial Intelligence and Symbolic Mathematical Computing: International Conference AISMC-1 Karlsruhe, Germany, August 3–6, 1992 Proceedings by J. Calmet, J. A. Campbell (auth.), Jacques Calmet, John A. Campbell (eds.)


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