Effects of silicon addition on the electrical and magnetic properties of copper-doped (La,Ca)MnO3 compounds

In this paper we report about the electrical properties of La 0.7Ca0.3MnO3 compounds substituted by copper on the manganese site and/or deliberately contaminated by SiO2 in the reactant mixture. Several phenomena have been observed and discussed. SiO2 addition leads to the formation of an apatite-like secondary phase that affects the electrical conduction through the percolation of the charge carriers. On the other hand, depending on the relative amounts of copper and silicon, the temperature dependence of the electrical resistivity can be noticeably modified: our results enable us to compare the effects of crystallographic vacancies on the A and B sites of the perovskite with the influence of the copper ions substituted on the manganese site. The most original result occurs for the compounds with a small ratio Si/Cu, which display double-peaked resistivity vs. temperature curves. © 2003 Elsevier B.V. All rights reserved.

Comparison of manual and user guided methodologies for the classification and retrieval of construction site images

The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.