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Optimization comparison

Fig. 14. Economic optimization comparison. Total cost of A, plate and frame, and B, stack cells. Fig. 14. Economic optimization comparison. Total cost of A, plate and frame, and B, stack cells.
Samineni S, Parvataneni S, Kelly C, Gangur V, Karmaus W, Brooks K. Optimization, comparison, and application of colorimetric vs. chemiluminescence based indirect sandwich ELISA for measurement of human IL-23. J Immunoassay Immunochem 2006 27 183-193. [Pg.139]

GourtsoyiannisN, PapanikolaouN, Grammatikakis J, Maris T, Prassopoulos P (2001) MR enteroclysis protocol optimization comparison between 3D FLASH with fat saturation after intravenous gadolinium injection and true FISP sequences. Eur Radiol 11 908-913... [Pg.24]

Thus the complexity of chemical process synthesis is twofold. First, can we identify all possible structures Second, can we optimize each structure for a valid comparison When optimizing the structure, there may be many ways in which each individual task can be performed and many ways in which the individual tasks can be interconnected. This means that we must simulate and optimize... [Pg.4]

In many cases, the methods used to solve identification problems are based on an iterative minimization of some performance criterion measuring the dissimilarity between the experimental and the synthetic data (generated by the current estimate of the direct model). In our case, direct quantitative comparison of two Bscan images at the pixels level is a very difficult task and involves the solution of a very difficult optimization problem, which can be also ill-behaved. Moreover, it would lead to a tremendous amount of computational burden. Segmented Bscan images may be used as concentrated representations of the useful... [Pg.172]

This paper is structured as follows in section 2, we recall the statement of the forward problem. We remind the numerical model which relates the contrast function with the observed data. Then, we compare the measurements performed with the experimental probe with predictive data which come from the model. This comparison is used, firstly, to validate the forward problem. In section 4, the solution of the associated inverse problem is described through a Bayesian approach. We derive, in particular, an appropriate criteria which must be optimized in order to reconstruct simulated flaws. Some results of flaw reconstructions from simulated data are presented. These results confirm the capability of the inversion method. The section 5 ends with giving some tasks we have already thought of. [Pg.327]

Kofke D A and Cummings P T 1997 Quantitative comparison and optimization of methods for evaluating the chemical potential by molecular simulation Mol. Phys. 92 973-96... [Pg.2283]

Baker J 1993 Techniques for geometry optimization a comparison of Cartesian and natural Internal coordinates J. Comput. Chem. 14 1085... [Pg.2357]

Figure 2.28 Comparison of the analytical solution with the finite element result obtained using optimal upwinding... Figure 2.28 Comparison of the analytical solution with the finite element result obtained using optimal upwinding...
For geometry optimizations and comparison of total energies (which should be carried out with ZINDO/1, not ZINDO/S), both overlap weighting factors (Sigma-Sigma and Pi-Pi) should be set to 1 in the Semi-empirical Options dialog box. [Pg.295]

By comparison, high performance composite laminates ate not only ctossphed like plywood, but actually have laminae stacked at very specific angles to one another to achieve optimal uniform properties in the x—y plane (2). [Pg.531]

Optimization. Optimi2ation of the design variables is an important yet often neglected step in the design of extractive distillation sequences. The cost of the solvent recovery (qv) step affects the optimi2ation and thus must also be included. Optimi2ation not only yields the most efficient extractive distillation design, it is also a prerequisite for vaUd comparisons with other separation sequences and methods. [Pg.187]

Economic Aspects. Several pubUcations probe the various areas of electroorganic process cost. CeUs (90), overaU process costs (41,91—93), economic optimization (94,95), and a comparison between the chemical and electrochemical methods (91,96) are aU discussed. [Pg.95]

The recent development and comparative application of modern separation techniques with regard to determination of alkylphosphonic acids and lewisite derivatives have been demonstrated. This report highlights advantages and shortcomings of GC equipped with mass spectrometry detector and HPLC as well as CE with UV-Vis detector. The comparison was made from the sampling point of view and separation/detection ability. The derivatization procedure for GC of main degradation products of nerve agents to determine in water samples was applied. Direct determination of lewisite derivatives by HPLC-UV was shown. Also optimization of indirect determination of alkylphosphonic acids in CE-UV was developed. Finally, the new instrumental development and future trends will be discussed. [Pg.278]

The optimization of the biorecognition layer by the modification of a transducer used. Nanostmctured poly aniline composite comprising Prussian Blue or poly-ionic polymers has been synthesized and successfully used in the assembly of cholinesterase sensors. In comparison with non-modified sensors, this improved signal selectivity toward electrochemically active species and decreased the detection limits of Chloropyrifos-Methyl and Methyl-Pai athion down to 10 and 3 ppb, respectively. [Pg.295]


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Comparison with the Multidimensional Optimization

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