A New Method of Testing and Evaluating the Quality of Refined Montan Wax: Digital Color and GC Fingerprint

To establish a new method of testing and evaluating the quality of refined montan wax (RMW), digital color and GC fingerprint technology were introduced and applied. CIE Lab color mode was used to digitize the exterior colors of RMW, and the score obtained through a fitting function was also used to reflect its quality. It is shown that they were in complete accord with the human visual perception trend. The GC fingerprint was used to characterize the internal chemical information of RMW, and the composition of its internal features was reflected through the relative retention time (RRT) and relative peak area (RPA) values. It is shown that there was a high degree of similarity between the fingerprints, while certain differences also existed. This can be used to implement effective application of RMW to aspects such as quality control, adulteration identification, and origin attributions.

     

<Emphasis Type="Italic">FCC/BCC</Emphasis> competition and enhancement of saturation magnetization in nanocrystalline Co-Ni-Fe films

The structure, chemical composition, and magnetic properties of electrochemically deposited nanocrystalline Co-Ni-Fe films were investigated using a number of techniques. A high saturation magnetic induction up to B _s = 21 kG was attained. An enhancement of the saturation magnetization compared to the ideal anticipated one was revealed, which correlated with the nonlinear behavior of the structural phase composition and lattice parameters with the change of the composition. The text was submitted by the authors in English.     

Forecasting call frequency at a financial services call centre

A forecasting model is developed for the number of daily applications for loans at a financial services telephone call centre. The purpose of the forecasts and the associated prediction intervals is to provide effective staffing policies within the call centre. The model building process is constrained by the availability of only 2 years and 7 months of data. The distinctive feature of the data is that demand is driven in the main by advertising. The analysis given focuses on applications stimulated by press advertising. Unlike previous analyses of broadly similar data, where ARIMA models were used, a model with a dynamic level, multiplicative calendar effects and a multiplicative advertising response is developed and shown to be effective.     

Quadratic data envelopment analysis

Data Envelopment Analysis (DEA) offers a piece-wise linear approximation of the production frontier. The approximation tends to be poor if the true frontier is not concave, eg in case of economies of scale or of specialisation. To improve the flexibility of the DEA frontier and to gain in empirical fit, we propose to extend DEA towards a more general piece-wise quadratic approximation, called Quadratic Data Envelopment Analysis (QDEA). We show that QDEA gives statistically consistent estimates for all production frontiers with bounded Hessian eigenvalues. Our Monte-Carlo simulations suggest that QDEA can substantially improve efficiency estimation in finite samples relative to standard DEA models.     

Applications of coupled LC-GC: A review

Although coupled liquid chromatographygas chromatography (LC-GC) was first demonstrated ten years ago, only in the last few years has there been a sudden surge of interest in the technique. Approximately 70% of the total number of LC-GC applications have been published in the last two years (1987–88) alone. This review categorizes LC-GC publications into four main application areas: fossil fuels, foods, environmental samples, biologiical/pharmaceutical samples, and miscellaneous samples. Multidimensional separations carried out using other coupled-column chromatographic techniques (such as supercritical fluid chromatography (SFC) with GC, and on-line trace enrichment-GC) have also been included in this review.     

A Language for Teaching Discrete-event Simulation

Courses which teach discrete-event simulation are based on many different simulation languages. The requirements for a language to support teaching simulation are discussed. In particular, it is recommended that such languages separate into distinct modules those aspects of simulation which are taught as separate topics. Implementation of the separation is discussed. The SEESIM language, developed as a teaching aid, is described, and examples of its use are given. Straightforward use of SEESIM can be learned quickly, yet the language provides facilities for a staged introduction to advanced concepts of simulation.     

Hybrid reordering strategies for ILU preconditioning of indefinite sparse matrices

Incomplete LU factorization preconditioning techniques often have difficulty on indefinite sparse matrices. We present hybrid reordering strategies to deal with such matrices, which include new diagonal reorderings that are in conjunction with a symmetric nondecreasing degree algorithm. We first use the diagonal reorderings to efficiently search for entries of single element rows and columns and/or the maximum absolute value to be placed on the diagonal for computing a nonsymmetric permutation. To augment the effectiveness of the diagonal reorderings, a nondecreasing degree algorithm is applied to reduce the amount of fill-in during the ILU factorization. With the reordered matrices, we achieve a noticeable improvement in enhancing the stability of incomplete LU factorizations. Consequently, we reduce the convergence cost of the preconditioned Krylov subspace methods on solving the reordered indefinite matrices.