Abstract
We consider the weight-constrained minimum spanning tree problem which has important applications in telecommunication networks design. We discuss and compare several formulations. In order to strengthen these formulations, new classes of valid inequalities are introduced. They adapt the well-known cover, extended cover and lifted cover inequalities. They incorporate information from the two subsets: the set of spanning trees and the knapsack set. We report computational experiments where the best performance of a standard optimization package was obtained when using a formulation based on the well-known Miller-Tucker-Zemlin variables combined with separation of cut-set inequalities.

Abstract
In this paper we examine how the virtual recommendation may influence co-shopping behavior specifically associated with "match dyad" within online social networks. Drawing on better match theory in economics and social network literature, we develop and propose a conceptual model describing how different antecedents of customer's recommendation influence their intentions and leads to positive outcomes, such as recommendation behavior and coshopping influence. We also describe which consumer and network characteristics accentuate this influence examining the moderator effect of customers' incentives, network structure and interactivity. The study contributes to propose that "match dyad" in small social network provide high-quality valuable information that will improve the match between the product and the potential customer and, matched online social connections, act as a proxy for information about the potential market that is difficult and expensive to measure or observe directly such as customer needs, and to access. The paper concludes with a consideration of the implications of predictions for marketing practice.

Abstract
Image processing of particulate phases can provide an important assistance for the estimation of particle size and shape distributions in multiphase systems. The knowledge of these distributions is of major importance in the modeling of agitated liquid-liquid systems either for hydrodynamic and mass transfer (with or without chemical reaction) simulation. Often, obtaining these distributions implies visual/manual techniques for identifying, counting and measuring the particles. This implies high costs, intensive labor, weariness build-up and consequent high error rates. A largely automated computational approach presents a great potential for better performance. In this paper we describe our technique in image processing for shape discrimination and size classification for liquid drops in monochromatic digitized frames. We empirically evaluate our approach on examples of images.

Abstract
In this paper we describe a parameter optimization approach to a simulation algorithm of a mixer-settler system in the transient state. The model we are using for the shallow-layer settler, in a mixer-settler system, is able to describe the hydrodynamic phenomena of the transient state of a liquid liquid system. Its mathematical model includes parameters of the drop transport process as well as of the drop drop and drop-interface coalescence with the active interface. The most adequate values of these parameters are unknown. In order to tune the model parameters we have Linked the mixer-settler simulation algorithm to an optimization procedure. We have used the Hooke-Jeeves optimization algorithm to fit these parameters to given experimental results.

Abstract
In this paper we address the accurate estimation of the frequency of sinusoids of natural signals such as singing, voice or music. These signals are intrinsicly harmonic and are normally contaminated by noise. Taking the Cramér-Rao Lower Bound for unbiased frequency estimators as a reference, we compare the performance of several DFT-based frequency estimators that are non-iterative and that use the rectangular window or the Hanning window. Tests conditions simulate harmonic interference and two new ArcTan-based frequency estimators are also included in the tests. Conclusions are presented on the relative performance of the different frequency estimators as a function of the SNR. ©2010 IEEE.

Abstract
The accurate estimation of the frequency of sinusoids is a frequent problem in many signal processing problems including the real-time analysis of the singing voice. In this paper we rely on a single DFT magnitude spectrum in order to perform frequency estimation in a non-iterative way. Two new frequency estimation methods are derived that are matched to the time analysis window and that reduce the maximum absolute estimation error to about 0.1% of the bin width of the DFT. The performance of these methods is evaluated including the parabolic method as a reference, and considering the influence of noise. A combined model is proposed that offers higher noise robustness than that of a single model. ©2010 IEEE.