Background Pancreatic enzyme replacement therapy (PERT) is widely applied to patients with exocrine pancreatic insufficiency (EPI), but its effect and safety has not been quantified. Therefore we performed a meta-analysis to determine the efficacy and tolerance of PERT on patients with EPI. Materials and Methods PubMed, Medline, Cochrane library database, Evidence-based medicine/clinical tria...

We consider a large-scale cyber network with N components. Each component is either in a healthy state (0) or an abnormal state (1). Due to intrusions, the state of each component transits from 0 to 1 over time according to an arbitrary stochastic process. At each time, a subset of K (K < N) components are probed and those observed in abnormal states are fixed. The objective is to design a dyna...

in this study, a bi-objective model for integrated planning of production-distribution in a multi-level supply chain network with multiple product types and multi time periods is presented. the supply chain network including manufacturers, distribution centers, retailers and final customers is proposed. the proposed model minimizes the total supply chain costs and transforming time of products ...

In AI and machine learning techniques such as decision trees and Bayesian networks, there is a growing need for converting continuous data into discrete form. Several approaches are available for discretization, however finding an appropriate and efficient discretization method is a challenging task. In this paper, we present an impurity based dynamic multi-interval discretization approach for ...

During the last decade, reverse logistics networks received a considerable attention due to economic importance and environmental regulations and customer awareness. Integration of leading and reverse logistics networks during logistical network design is one of the most important factors in supply chain. In this research, an Integer Linear Programming model is presented to design a multi-layer...

The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN) that we adopt for the semantic modelling of sentences. The network uses Dynamic k-Max Pooling, a global pooling operation over linear sequences. The network handles input sentences of varying length and induces a feat...