Bullwhip reduction for ARMA demand: The proportional order-up-to policy versus the full-state-feedback policy

A ‘proportional’ order-up-to policy reacting to ARMA demand is analyzed using stochastic optimal control theory. This policy is compared with a full-state-feedback order-up-to policy. Necessary conditions for an optimum of a weighted sum of the inventory and the ordering variances for both policies are formulated. Based on this a relatively simple expression for the ‘full-state’ policy is derived. The comparison between the two policies demonstrates that the ‘intuitively’ designed proportional policy does not fulfill the objective of controlling both the inventory and ordering variance for all parameter values of the demand model as well as the full-state-feedback policy. The full-state-feedback policy outperforms the proportional policy in several aspects.     

Data decomposition using independent component analysis with prior constraints

In many data analysis problems, it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make of a system are then taken to be related to these sources through some unknown function. Furthermore, the (unknown) number of underlying latent sources may be less than the number of observations. Recent developments in independent component analysis (ICA) have shown that, in the case where the unknown function linking sources to observations is linear, such data decomposition may be achieved in a mathematically elegant manner. In this paper, we extend the general ICA paradigm to include a very flexible source model, prior constraints and conditioning on sets of intermediate variables so that ICA forms one part of a hierarchical system. We show that such an approach allows for efficient discovery of hidden representation in data and for unsupervised data partitioning.     

Reference free part encapsulation: Materials,machines and methods

Reference Free Part Encapsulation (RFPE) is an automatic, universal workholding process developed by researchers at the Massachusetts Institute of Technology and the University of California-Berkeley. The process encapsulates the stock by freezing it in a low melting point material during machining and transfers datums from one setup to another by refilling and restoring the encapsulation to a known shape after each setup. This paper describes the encapsulator materials and machines developed to test and demonstrate RFPE. The encapsulation material must satisfy stringent thermal properties, and a process is described that concludes that the tin–bismuth eutectic is ideal. The similarities of the encapsulation process to manufacturing processes such as die casting and injection molding are considered; however, it is shown that many intrinsic differences exist between the encapsulation process and injection molding or die casting. Two encapsulation machines are presented. The first is a larger encapsulation machine capable of forming encapsulations with a 6 in. by 6 in. footprint. The second, a much smaller portable machine capable of forming encapsulations with a 2 in. by 2 in. footprint, is also presented. Special features of each encapsulation machine are highlighted and various design decisions are discussed.     

Subspace distance analysis with application to adaptive Bayesian algorithm for face recognition

We propose subspace distance measures to analyze the similarity between intrapersonal face subspaces, which characterize the variations between face images of the same individual. We call the conventional intrapersonal subspace average intrapersonal subspace (AIS) because the image differences often come from a large number of persons. An intrapersonal subspace is referred to as specific intrapersonal subspace (SIS) if the image differences are from just one person. We demonstrate that SIS varies significantly from person to person, and most SISs are not similar to AIS. Based on these observations, we introduce the maximum a posteriori (MAP) adaptation to the problem of SIS estimation, and apply it to the Bayesian face recognition algorithm. Experimental results show that the adaptive Bayesian algorithm outperforms the non-adaptive Bayesian algorithm as well as Eigenface and Fisherface methods if a small number of adaptation images are available.     

Averaging of nonsmooth systems using dither

It was shown by Zames and Shneydor and later by Mossaheb that a high-frequency dither signal of a quite arbitrary shape can be used to narrow the effective nonlinear sector of Lipschitz continuous feedback systems. In this paper, it is shown that also discontinuous nonlinearities of feedback systems can be narrowed using dither, as long as the amplitude distribution function of the dither is absolutely continuous and has bounded derivative. The averaged system is proven to approximate the dithered system with an error of the order of dither period.     

An empirical investigation of competency factors affecting e-business success in European SMEs

In the last decade there was growing interest in strategic management literature about factors that influence a company's ability to use IT. There is general consensus that knowledge and competency are necessary in developing an IT capability, but there is very little understanding of what the necessary competencies are, and how they influence IS usage in different contexts. The small and medium-sized enterprise context is particularly interesting for two reasons: it constitutes a major part of the economy and it has been relatively unsuccessful in exploiting e-business.     

Parameter identification for nonlinear systems: Guaranteed confidence regions through LSCR

In this paper we consider the problem of constructing confidence regions for the parameters of nonlinear dynamical systems. The proposed method uses higher order statistics and extends the LSCR (leave-out sign-dominant correlation regions) algorithm for linear systems introduced in Campi and Weyer [2005, Guaranteed non-asymptotic confidence regions in system identification. Automatica 41(10), 1751-1764. Extended version available at 〈http://www.ing.unibs.it/∼campi〉]. The confidence regions contain the true parameter value with a guaranteed probability for any finite number of data points. Moreover, the confidence regions shrink around the true parameter value as the number of data points increases. The usefulness of the proposed approach is illustrated on some simple examples.