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  • 1
    Electronic Resource
    Electronic Resource
    [S.l.] : American Institute of Physics (AIP)
    Journal of Applied Physics 65 (1989), S. 3347-3350 
    ISSN: 1089-7550
    Source: AIP Digital Archive
    Topics: Physics
    Notes: We have observed spatial-frequency selection using downconversion optical parametric amplification in lithium iodate. A mode-locked Nd:YAG laser with a second harmonic generator provided the pump beam at 532 nm and the signal beam at 1064 nm. An image was placed on the signal beam and spatial frequencies from 0 to 60 lines/mm were selectively amplified from the image by rotating the lithium iodate crystal 0°–0.77° from the phase-match angle. The optical parametric amplifier's passband behavior was in excellent agreement with the existing theory.
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 8 (1992), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1572-901X
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract A series of substituted tricarbonyl(trimethylenemethane)-iron complexes were prepared by functionalization of (3-butenyltrimethylenemethane)Fe(CO)3 (3) or (formyltrimethylenemethane)Fe(CO)3 (14). The products are characterized by 1H and 13C-n.m.r., i.r. and high resolution mass spectroscopy. In addition, the X-ray diffraction analysis of one of these derivatives (13a) was accomplished. Reactions of (3), which introduce a new chiral centre, occur in a non-diastereoselective fashion, while reactions of (14) that introduce a new chiral centre proceed with good diastereoselectivity. The remote nature of the reactive functionality and the (TMM)Fe(CO)3 group is responsible for the lack of diastereoselectivity for (3). The present work demonstrates the robust nature of the (TMM)Fe(CO)3 fragment, embodied in its resistance toward oxidation, and to attack by nucleophiles.
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  • 4
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 40 (1994), S. 1639-1649 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Elliptical basis function (EBF) networks are introduced as a new nonparametric method of estimating probability density functions for process data. Unlike Parzen window density estimators that use identical hyperspherical basis functions, the EBF method uses elliptical basis functions adapted to the local character of the data. This technique overcomes the spikiness problem associated with Parzen windows, where in high dimension, they can fail to produce smooth probability density estimates. The EBF estimator produces valid density functions that converage to the underlying distribution of the data in the limit of an infinite number of training examples. A technique based on statistical cross validation is introduced for evaluating different density estimators. The criterion is a measure of how well the density estimator estimates the density of data not used in the training. The EBF density estimation method and the evaluation technique are demonstrated using several examples of fault diagnosis.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 37 (1991), S. 233-243 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Nonlinear principal component analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA, like PCA, is used to identify and remove correlations among problem variables as an aid to dimensionality reduction, visualization, and exploratory data analysis. While PCA identifies only linear correlations between variables, NLPCA uncovers both linear and nonlinear correlations, without restriction on the character of the nonlinearities present in the data. NLPCA operates by training a feedforward neural network to perform the identity mapping, where the network inputs are reproduced at the output layer. The network contains an internal “bottleneck” layer (containing fewer nodes than input or output layers), which forces the network to develop a compact representation of the input data, and two additional hidden layers. The NLPCA method is demonstrated using time-dependent, simulated batch reaction data. Results show that NLPCA successfully reduces dimensionality and produces a feature space map resembling the actual distribution of the underlying system parameters.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 40 (1994), S. 1328-1340 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: We present a method for synthesizing chemical process models that combines prior knowledge and artificial neural networks. The inclusion of prior knowledge is investigated as a means of improving the neural network predictions when trained on sparse and noisy process data. Prior knowledge enters the hybrid model as a simple process model and first principle equations. The simple model controls the extrapolation of the hybrid in the regions of input space that lack training data. The first principle equations, such as mass and component balances, enforce equality constraints. The neural network compensates for inaccuracy in the prior model. In addition, inequality constraints are imposed during parameter estimation. For illustration, the approach is applied in predicting cell biomass and secondary metabolite in a fed-batch penicillin fermentation. Our results show that prior knowledge enhances the generalization capabilities of a pure neural network model. The approach is shown to require less data for parameter estimation, produce more accurate and consistent predictions, and provide more reliable extrapolation.
    Additional Material: 8 Ill.
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  • 7
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 36 (1990), S. 1121-1127 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Additional Material: 1 Ill.
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  • 8
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 34 (1988), S. 1441-1454 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: A method of qualitative simulation for continuous process systems that predicts the steady-state measurement patterns generated as a result of process malfunctions is presented. The method is based on qualitative versions of the steady-state process equations and requires no numerical information beyond the signs and relative values of certain groups of parameters. Previous methods of qualitative simulation (Umeda et al., 1980; de Kleer and Brown, 1984; Forbus, 1984; Kuipers, 1986) have tended to generate multiple solutions that do not coincide with any observable system behaviors. In the current method, spurious solutions are reduced using “latent” constraints associated with analytically redundant model equations, and “nonlatent” constraints based on causality, and derived from the extended signed directed graph (ESDG). The ESDG is similar to the signed directed graph (SDG) (Iri et al., 1979), but includes certain nonphysical branches that account for complex dynamics (inverse and compensatory response due to negative feedback). Necessary conditions based on the topology of the SDG for the occurrence of complex dynamics are developed. Based on these criteria, assumptions concerning disturbance propagation are introduced that minimize spurious interpretations of system behavior while guaranteeing inclusion of the steady-state response. The method is demonstrated by simulating the effects of equipment malfunctions on a model process.
    Additional Material: 10 Ill.
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  • 9
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 41 (1995), S. 2415-2426 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: A maximum likelihood rectification (MLR) technique that poses the data-rectification problem in a probabilistic framework and maximizes the probability of the estimated plant states given the measurements is proposed. This approach does not divide the sensors into “normal” and “gross error” classes, but uses all of the data in the rectification, each sensor being appropriately weighted according to the laws of probability. In this manner, the conventional assumption of no sensor bias is avoided, and both random errors (noise) and systematic errors (gross errors) are removed simultaneously. A novel technique is introduced that utilizes historical plant data to determine a peior probability distribution of the plant states. This type of historical plant information, which contains the physical relationships among the variables (mass balances, energy balances, thermodynamic constraints), as well as statistical correlations among the variables, has been ignored in prior data-rectification schemes. This approach can use the historical plant information to solve a new class of data-rectification problems in which there are no known model constraints. The MLR method is demonstrated on data from a simulated flow network and a simulated heat-exchanger network. The MLR technique provides considerably improved performance over existing data-reconciliation schemes in these examples.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    New York, NY : Wiley-Blackwell
    International Journal of Chemical Kinetics 16 (1984), S. 559-578 
    ISSN: 0538-8066
    Keywords: Chemistry ; Physical Chemistry
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: The advantages and disadvantages of various methods of parametric sensitivity analysis in chemical kinetic modeling are discussed. Particular attention is given to estimates of computational labor for realistic problems, and quantitative comparisons are made utilizing a 52-reaction, 11-species CO oxidation mechanism. The authors′ CHEMSEN/AIM program compares favorably to other techniques in many circumstances, and provides the additional convenience of accepting input information in familiar chemical notation. This paper also reviews recent developments in theory of sensitivity analysis, relevant to chemical kinetic modeling.
    Additional Material: 4 Ill.
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