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: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Reparameterizing the generalized linear model to accelerate gibbs sampler convergence

Abstract: Albert and Chib introduced a complete Bayesian method to analyze data arising from the generalized linear model in which they used the Gibbs sampling algorithm facilitated by latent variables. Recently, Cowles proposed an alternative algorithm to accelerate the convergence of the Albert-Chib algorithm. The novelty in this latter algorithm is achieved by using a Hastings algorithm to generate latent variables and bin boundary parameters jointly instead of individually from their respective full conditionals. In the same spirit, we reparameterize the cumulative-link generalized linear model to accelerate the convergence of Cowles’ algorithm even further. One important advantage of our method is that for the three-bin problem it does not require the Hastings algorithm. In addition, for problems with more than three bins, while the Hastings algorithm is required, we provide a proposal density based on the Dirichlet distribution which is more natural than the truncated normal density used in the competing algo...

Multiobjective Reinforcement Learning for Cognitive Satellite Communications Using Deep Neural Network Ensembles

Abstract: Future spacecraft communication subsystems will potentially benefit from software-defined radios controlled by artificial intelligence algorithms. In this paper, we propose a novel radio resource allocation algorithm leveraging multiobjective reinforcement learning and artificial neural network ensembles able to manage available resources and conflicting mission-based goals. The uncertainty in the performance of thousands of possible radio parameter combinations and the dynamic behavior of the radio channel over time producing a continuous multidimensional state–action space requires a fixed-size memory continuous state–action mapping instead of the traditional discrete mapping. In addition, actions need to be decoupled from states in order to allow for online learning, performance monitoring, and resource allocation prediction. The proposed approach leverages the authors’ previous research on constraining decisions predicted to have poor performance through ”virtual environment exploration.” The simulation results show the performance for different communication mission profiles, and accuracy benchmarks are provided for the future research reference. The proposed approach constitutes part of the core cognitive engine proof-of-concept delivered to the NASA John H. Glenn Research Center’s SCaN Testbed radios on-board the International Space Station.

Modeling the impact of changing patient flow processes in an emergency department: Insights from a computer simulation study

Abstract: We report on the use of discrete-event simulation modeling to support process improvements in a hospital emergency department (ED), namely the implementation of a split-flow process. Our partner hospital was effective in treating patients, but wait time and congestion in the ED created patient dissatisfaction, unsafe conditions and staff morale issues. The split-flow concept is an emerging approach to manage ED processes by splitting patient flow according to patient acuity and enabling parallel processing. We contrast the split-flow operational model to other types of ED triage. While early implementations of the split-flow concept have demonstrated significant improvements in patient wait times, a systematic evaluation of operational configurations is lacking. We created a discrete-event simulation model and established its face validity for Saint Vincent Hospital in Worcester, USA, a community-teaching, Level II Trauma Center. Seventeen scenarios were tested to estimate the likely impact of a split-flow process redesign, including staffing level changes and patient volume changes. The scenarios were compared in terms of Door-to-Doctor time and length-of-stay for different patient acuity levels. Findings from the study supported implementation of the split-flow improvements. Statistical analysis of data taken before and after the implementation indicate that waiting time measures were significantly improved and overall patient length-of-stay was reduced. To gauge the success of the current split-flow process at Saint Vincent we compare performance metrics from three different sources: benchmark metrics, hospital data prior to split-flow implementation, and performance metrics post implementation.