Abstract

Abstract

Abstract
The endoscopic capsule is a recent technological breakthrough with high clinical importance. Exam analysis duration is its main setback, requiring an average of two hours from a trained specialist. Automation is required and this paper presents a topographic segmentation tool using low-level features that can reduce annotation times up to 15 minutes per exam. This is accomplished using Bayesian classifiers and MPEG-7 visual descriptors.

Abstract
The paper proposes a dependability model which the evaluation of Profibus-DP networks in scenarios transient faults which affect data communications. The behavior of Profibus-DP communication stack is including: cyclic process data exchange between and slave stations; configuration, parameterization and agnostics of slave stations. The model is based on a level Stochastic Petri Net formalism referred as Activity Networks (SAN), supported by the Mobius High modeling power, state-of-the-art analytical and lation solutions, and a flexible and integrated are their main features. Dependability measures are lished from the fulfillment of the real-time (deadlines) defined on process data messages between master and slave stations. The reward concept used to define the measures, which are obtained by of a simulation approach. A case study is proposed to assess the model performance.

Abstract

Abstract