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The purpose of this paper is to reduce the artifacts in fast Bayesian reconstruction images in electrical tomography. This is in particular important with respect to object detection in electrical tomography applications.

The authors suggest to apply the Box-Cox transformation in Bayesian linear minimum mean square error (BMMSE) reconstruction to better accommodate the non-linear relation between the capacitance matrix and the permittivity distribution. The authors compare the results of the original algorithm with the modified algorithm and with the ground truth in both, simulation and experiments.

The results show a reduction of 50 percent of the mean square error caused by artifacts in low permittivity regions. Furthermore, the algorithm does not increase the computational complexity significantly such that the hard real time constraints can still be met. The authors demonstrate that the algorithm also works with limited observations angles. This allows for object detection in real time, e.g., in robot collision avoidance.

This paper shows that the extension of BMMSE by applying the Box-Cox transformation leads to a significant improvement of the quality of the reconstruction image while hard real time constraints are still met.

Extensible Markup Language (XML)‐based data integration systems (DIS) aim to support global updates. Data consistency among data sources is not yet enforced at the integration level or enforced in an ad hoc manner which leads to redundant checking of consistency or unrepairable mistakes. This paper aims to provide XQuery trigger service to enforce data integrity and data consistency in the DIS at the integration level.

Data consistency is enforced among data sources through providing XQuery trigger service for the XML‐DIS. An XQuery trigger model is defined and shown how to use this model to define different integrity constraints and triggers at the integration level. The paper proposes the architecture of the XQuery trigger service and shows how to enforce data consistency in the DIS. Important components including event detection, condition evaluation and action firing are discussed. Necessary algorithms including how to produce ChangeRecord, how to find activated triggers, how to process LET and FOR clauses and how to create data objects from XML fragment are proposed. Trigger termination and failure handling are also discussed.

XQuery trigger can express miscellaneous data integrity constraints and triggers in the DIS and is highly abstract, refined and easy to understand. XQuery trigger service provides an easy‐to‐maintain method of the data consistency rules and a uniform, nonredundant and centralized enforcement of data consistency.

An XQuery trigger model with namespace annotations, which can define constraints and triggers among different data sources. An XQuery trigger service architecture for the XML‐DIS, which can enforce data consistency at the integration level. For DIS administrators, who want to enforce data consistency when permitting updates at the integration level.