The impact of fast moving items, modeled by auto-regressive moving average (ARMA) type processes, on the bullwhip effect is well known. However, slow moving items that can be modeled using integer ARMA processes have received little attention. Herein, we measure the impact of bullwhip effect under a first order integer auto-regressive, INAR(1), demand process. We consider a simple two-stage sup...

This paper proposes a stochastic multipath model useful for generating MIMO channel matrices in timevariant environments. The multipath model is developed by first extracting the relevant characteristics from measured indoor channel data and subsequently capturing these characteristics in an auto-regressive stochastic model. This model is then used to generate channel matrices whose space-time ...

Since Clark and Scarf’s pioneering work, most advances in multi-echelon inventory systems have been based on demand processes that are time-independent. This paper revisits the serial multi-echelon inventory system of Clark and Scarf, and develops three key results. First, we provide a simple lower bound approximation to the optimal echelon inventory levels and an upper bound to the total syste...

In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and...

The Mel-Frequency Cepstrum Coefficients (MFCC) is a widely used set of feature used in automatic speech recognition systems introduced in 1980 by Davis and Mermelstein [2]. In this traditional implementation, the 0 coefficient is excluded for the reason it is somewhat unreliable. In this paper, we analyze this term and find that it can be regarded as the generalized frequency band energy (FBE) ...

The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. To automate the process of motion modeling we consider a class of learned dynamic models cast in the framework of dynamic Bayesian networks (DBNs) applied to analysis and tracking of the human figure. While direct learning of DBN parameters is possible, Bayesian learning formalism suggests that ...

Spam has been one of the most difficult problems to be addressed since the invention of Internet. Outbound spam can reflect the information security level of an organization as most spam emails are generated by compromised computers. Understanding the trend of outbound spam can help organizations adopt proactive policies and measures toward a more informed decision on resource allocation in ter...