Melt filtration of recycled PVC

The separation of PVC from contaminants is one of the most important steps in recycling PVC. Earlier works have shown that one can separate PVC from other polymers by using the X-ray fluorescence technique. However, in many cases, even after careful separation, there is a remaining impurity level of about 0.1% due to the limitations of the separation processes. In many applications, impurities, particularly nonmeltables, cause defects in the PVC matrix and must be removed for best performance and appearance. Melt filtration appears to be the best technique to remove the nonmeltable impurities.     

Efficient solution of population balance equations with discontinuities by finite elements

Two refinements of Galerkin's method on finite elements were evaluated for the solution of population balance equations for precipitation systems. The traditional drawbacks of this approach have been the time required for computation of the two-dimensional integrals arising from the aggregation integrals and the difficulty in handling discontinuities that often arise in simulations of seeded reactors. The careful arrangement of invariant integrals for separable aggregation models allows for a thousandfold reduction in the computational costs. Discontinuities that may be present due to the hyperbolic nature of the system may be specifically tracked by the method of characteristics. These discontinuities will arise only from the initial distribution or nucleation and are readily identified. A combination of these techniques can be used that is intermediate in computational cost while still allowing discontinuous number densities. In a case study of calcium carbonate precipitation, it is found that the accuracy improvement gained by tracking the slope discontinuity may not be significant and that the computation speed may be sufficient for dynamic online optimization.     

Alternative Granulation Technique: Melt Granulation

A melt granulation process has been investigated (1, 2) which efficiently agglomerates pharmaceutical powders for use in both immediate- and sustained-release solid dosage forms. The process utilizes materials that are effective as granulating fluids when they are in the molten state. Cooling of the agglomerated powders and the resultant solidification of the molten materials completes the granulation process. Both the molten agglomeration and cooling solidification were accomplished in a high shear Collette Gral mixer equipped with a jacketed bowl. Hence, the melt granulation process replaces the conventional granulation and drying operations which use water or alcohol solutions. The melt granulation process has been investigated using immediate- and sustained-release TAVIST® (clemastine fumarate USP) tablet formulations. The TAVIST granulations have been characterized by power consumption monitoring, measurement of the granulation particle size distribution, bulk and tapped density determinations, and loss-on-drying measurements. Scale-up of the melt granulation process for the sustained release TAVIST tablet formulation was judged successful based on a comparison of the hardness, friability, weight uniformity during compression, disintegration time, and dissolution rate data obtained at different manufacturing scales.     

The Best Deal in Town [Supercomputers]

At one time, supercomputing, a term that was synonymous with the Cray-1, was considered to be the best deal in town. However, by the 1990s, manufacturers began to question the need to continue the development of high-speed computers, turning their attention instead to the potential for developing a "high-capacity and high-speed national research and education computer network."     

On the cramer-rao bound for carrier frequency estimation in the presence of phase noise

We consider the carrier frequency offset estimation in a digital burst-mode satellite transmission affected by phase noise. The corresponding Cramer-Rao lower bound is analyzed for linear modulations under a Wiener phase noise model and in the hypothesis of knowledge of the transmitted data. Even if we resort to a Monte Carlo average, from a computational point of view the evaluation of the Cramer-Rao bound is very hard. We introduce a simple but very accurate approximation that allows to carry out this task in a very easy way. As it will be shown, the presence of the phase noise produces a remarkable performance degradation of. the frequency estimation accuracy. In addition, we provide asymptotic expressions of the Cramer-Rao bound, from which the effect of the phase noise and the dependence on the system parameters of the frequency offset estimation accuracy clearly result. Finally, as a by-product of our derivations and approximations, we derive a couple of estimators specifically tailored for the phase noise channel that will be compared with the classical Rife and Boorstyn algorithm, gaining in this way some important hints on the estimators to be used in this scenario     

Parallel Computation of High-Dimensional Robust Correlation and Covariance Matrices

The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices are very sensitive to outliers. Robust methods, such as Quadrant Correlation (QC) and the Maronna method, have been proposed. However, existing algorithms for QC only give acceptable performance when the dimensionality of the matrix is in the hundreds; and the Maronna method is rarely used in practice because of its high computational cost. In this paper we develop parallel algorithms for both QC and the Maronna method. We evaluate these parallel algorithms using a real data set of the gene expression of over 6000 genes, giving rise to a matrix of over 18 million entries. In our experimental evaluation, we explore scalability in dimensionality and in the number of processors, and the trade-offs between accuracy and computational efficiency. We also compare the parallel behaviours of the two methods. From a statistical standpoint, the Maronna method is more robust than QC. From a computational standpoint, while QC requires less computation, interestingly the Maronna method is much more parallelizable than QC. After a thorough experimentation, we conclude that for many data mining applications, both QC and Maronna are viable options. Less robust, but faster, QC is the recommended choice for small parallel platforms. On the other hand, the Maronna method is the recommended choice when a high degree of robustness is required, or when the parallel platform features a large number of processors (e.g., 32).     

Solving applied general equilibrium models represented as a mixture of linearized and levels equations

General equilibrium moels are usually represented as a system of levels equations (e.g., in North America) or a system of linearized equations (e.g., in Australia). Either representation can be used to obtain accurate solutions. General-purpose software is available in both cases-GAMS or MPS/GE is typically used by levels modellers and GEMPACK by linearizers. Some equations (notably accounting identities) are naturally expressed in the levels while others (especially behavioural equations) are naturally expressed in a linearized form. This paper describes the new GEMPACK facility for solving models represented as a mixture of levels and linearized equations and discusses the advantages to modellers of using such a representation.     

A survey of research in deliberative real-time artificial intelligence

This paper surveys recent research in deliberative real-time artificial intelligence (AI). Major areas of study have beenanytime algorithms, approximate processing, and large system architectures. We describe several systems in each of these areas, focusing both on progress within the field, and the costs, benefits and interactions among different problem and algorithm complexity limitations used in the surveyed work.