Consider a Bayesian optimal design with many support points which poses the problem of collecting data with a few number of observations at each design point. Under such a scenario the asymptotic property of using Fisher information matrix for approximating the covariance matrix of posterior ML estimators might be doubtful. We suggest to use Bhattcharyya matrix in deriving the information matri...

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transpo...

This study uses a design of experiments approach to understand the behavior of a neural network to learn the mountain car domain using the TD(λ) algorithm. A large experiment is first performed to characterize the probability of empirical convergence based on three parameters of the TD(λ) algorithm (λ, γ, ), and a logistic regression model is fitted to this data. A detailed analysis of the para...

This paper presents the development of two related machine-learned models which predict (a) whether a student can answer correctly questions in an ILE without requesting help and (b) whether a student’s interaction is beneficial in terms of learning. After presenting the rationale behind the development of these models, the paper discusses how the data collection was facilitated by the integrat...

this paper describes the application of process integration principles to the design of oil refineries hydrogen network. in this regard, a design hierarchy as well as heuristics and required guidelines are proposed. the recommended rules compensate lack of procedure to the design and make the design process easier. the guiding principles of the design are based upon pinch technology and extendi...