Effectiveness of organic certification: a study on an italian organic certificator's data.

The aim of this paper is to implemnt risk-based models for the inspection procedures in the organic certification. particularly, the aim is to analyse the the relationship between the type of sanction a farm receives, and the farm's structure and productions, aiming at the definition of potential risk factors

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case

Ensemble Joint Sparse Low Rank Matrix Decomposition for Thermography Diagnosis System

Composite is widely used in the aircraft industry and it is essential for manufacturers to monitor its health and quality. The most commonly found defects of composite are debonds and delamination. Different inner defects with complex irregular shape is difficult to be diagnosed by using conventional thermal imaging methods. In this paper, an ensemble joint sparse low rank matrix decomposition (EJSLRMD) algorithm is proposed by applying the optical pulse thermography (OPT) diagnosis system. The proposed algorithm jointly models the low rank and sparse pattern by using concatenated feature space. In particular, the weak defects information can be separated from strong noise and the resolution contrast of the defects has significantly been improved. Ensemble iterative sparse modelling are conducted to further enhance the weak information as well as reducing the computational cost. In order to show the robustness and efficacy of the model, experiments are conducted to detect the inner debond on multiple carbon fiber reinforced polymer (CFRP) composites. A comparative analysis is presented with general OPT algorithms. Not withstand above, the proposed model has been evaluated on synthetic data and compared with other low rank and sparse matrix decomposition algorithms