Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Population & Data envelopment analysis. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

How many suppliers are best? A decision-analysis approach

Abstract: As more supply chains are becoming dependent upon suppliers, an interruption of supply networks can obstruct the functionality of the entire supply chain. The purpose of this paper is to present what we believe is a useful way to think about the number of suppliers needed in the presence of risks. We model the decision-making process using a decision tree approach. We consider catastrophic, “super-events,” which affect many/all suppliers, as well as “unique events” that affect only a single supplier. The probabilities of these events, the financial loss caused by disasters, and the operating cost of working with multiple suppliers are captured by decision trees, from which the expected cost function is obtained and the optimal number of suppliers is determined. Our methodology will help purchasing managers, materials management, as well as academics that are considering such issues.

Missing covariates in generalized linear models when the missing data mechanism is non-ignorable

Abstract: We propose a method for estimating parameters in generalized linear models with missing covariates and a non-ignorable missing data mechanism. We use a multinomial model for the missing data indicators and propose a joint distribution for them which can be written as a sequence of one-dimensional conditional distributions, with each one-dimensional conditional distribution consisting of a logistic regression. We allow the covariates to be either categorical or continuous. The joint covariate distribution is also modelled via a sequence of one-dimensional conditional distributions, and the response variable is assumed to be completely observed. We derive the E- and M-steps of the EM algorithm with non-ignorable missing covariate data. For categorical covariates, we derive a closed form expression for the E- and M-steps of the EM algorithm for obtaining the maximum likelihood estimates (MLEs). For continuous covariates, we use a Monte Carlo version of the EM algorithm to obtain the MLEs via the Gibbs sampler. Computational techniques for Gibbs sampling are proposed and implemented. The parametric form of the assumed missing data mechanism itself is not `testable' from the data, and thus the non-ignorable modelling considered here can be viewed as a sensitivity analysis concerning a more complicated model. Therefore, although a model may have `passed' the tests for a certain missing data mechanism, this does not mean that we have captured, even approximately, the correct missing data mechanism. Hence, model checking for the missing data mechanism and sensitivity analyses play an important role in this problem and are discussed in detail. Several simulations are given to demonstrate the methodology. In addition, a real data set from a melanoma cancer clinical trial is presented to illustrate the methods proposed.

An FPGA-based performance evaluation of the AES block cipher candidate algorithm finalists

Abstract: The technical analysis used in determining which of the potential Advanced Encryption Standard candidates was selected as the Advanced Encryption Algorithm includes efficiency testing of both hardware and software implementations of candidate algorithms. Reprogrammable devices such as field-programmable gate arrays (FPGAs) are highly attractive options for hardware implementations of encryption algorithms, as they provide cryptographic algorithm agility, physical security, and potentially much higher performance than software solutions. This contribution investigates the significance of FPGA implementations of the Advanced Encryption Standard candidate algorithms. Multiple architectural implementation options are explored for each algorithm. A strong focus is placed on high-throughput implementations, which are required to support security for current and future high bandwidth applications. Finally, the implementations of each algorithm will be compared in an effort to determine the most suitable candidate for hardware implementation within commercially available FPGAs.