Electrical and chemical diagnostics of transformers insulation .A. Aged transformer samples

This paper describes the application of two relatively new diagnostic techniques for the determination of insulation condition in aged transformers. The techniques are (a) measurements of interfacial polarization spectra by a DC method and (b) measurements of molecular weight and its distribution by gel permeation chromatography. Several other electrical properties of the cellulose polymer were also investigated. Samples were obtained from a retired power transformer and they were analysed by the developed techniques. Six distribution transformers were also tested with the interfacial polarization spectra measurement technique, and the molecular weight of paper/pressboard samples from these transformers were also measured by the gel permeation chromatography. The variation of the results through different locations in a power transformer is discussed in this paper. The possible correlation between different measured properties was investigated and discussed in this paper.

Electrical and chemical diagnostics of transformers insulation .B. Accelerated aged insulation samples

This paper describes the analysis of accelerated aged insulation samples to investigate the degradation processes observed in the insulation from aged transformers. Short term accelerated ageing experiments were performed on paper wrapped insulated conductors and on pressboard samples. The condition of aged insulation samples was investigated by two relatively new diagnostic techniques: (a) measurements of interfacial polarization spectra by a DC method (b) measurements of molecular weight and its distribution by gel permeation chromatography. Several other electrical properties of the paper/pressboard samples were also studied. Possible correlations have been investigated among the different measured properties. The GPC results have been used to predict how molecular weights change with temperature and time.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

The new craft skills of engineering: The impact of innovation technology on engineering practices

This chapter explores the impact of innovation technologies such as simulation, modelling, and rapid prototyping on engineering practice. Innovation technologies help redefine the role of engineers in the innovation process, creating a new division of innovative labour both with and across organizations. This chapter also explores the boundaries of experimentation and inertia within particular domains of problem-solving to create new opportunities and value.

Tooth Tissue Engineering: Optimal Dental Stem Cell Harvest Based on Tooth Development

Our long-term objective is to devise reliable methods to generate biological replacement teeth exhibiting the physical properties and functions of naturally formed human teeth. Previously, we demonstrated the successful use of tissue engineering approaches to generate small, bioengineered tooth crowns from harvested pig and rat postnatal dental stem cells (DSCs). To facilitate characterizations of human DSCs, we have developed a novel radiographic staging system to accurately correlate human third molar tooth developmental stage with anticipated harvested DSC yield. Our results demonstrated that DSC yields were higher in less developed teeth (Stages 1 and 2), and lower in more developed teeth (Stages 3, 4, and 5). The greatest cell yields and colony-forming units (CFUs) capability was obtained from Stages 1 and 2 tooth dental pulp. We conclude that radiographic developmental staging can be used to accurately assess the utility of harvested human teeth for future dental tissue engineering applications.

An investigation of the microstructure/electrical conductivity relationship in In2O3-substituted LSGM

The effect of controlled In3+ substitution on to the B-site in the perovskite oxygen ion conductor La0.9Sr0.1Ga0.8Mg0.2O2.85 (LSGM) has been examined with a view to exploring the influence on oxygen ion conductivity. In combination with the electrical conductivity study, detailed microstructural analysis was used to verify the location of the substituting cation and to determine the nature of secondary phase formation. The indium species clearly substituted for Ga3+ on the B-site of the lattice and the electrical conductivity showed a gradual decrease as the In+3 content increased. The interpretation of this data was complicated by the formation of the secondary phases LaInO3 and LaSrGaO4. (C) 2001 Elsevier Science Ltd. All rights reserved.

Application of Petrov-Galerkin methods to transient boundary value problems in chemical engineering: adsorption with steep gradients in bidisperse solids

Petrov-Galerkin methods are known to be versatile techniques for the solution of a wide variety of convection-dispersion transport problems, including those involving steep gradients. but have hitherto received little attention by chemical engineers. We illustrate the technique by means of the well-known problem of simultaneous diffusion and adsorption in a spherical sorbent pellet comprised of spherical, non-overlapping microparticles of uniform size and investigate the uptake dynamics. Solutions to adsorption problems exhibit steep gradients when macropore diffusion controls or micropore diffusion controls, and the application of classical numerical methods to such problems can present difficulties. In this paper, a semi-discrete Petrov-Galerkin finite element method for numerically solving adsorption problems with steep gradients in bidisperse solids is presented. The numerical solution was found to match the analytical solution when the adsorption isotherm is linear and the diffusivities are constant. Computed results for the Langmuir isotherm and non-constant diffusivity in microparticle are numerically evaluated for comparison with results of a fitted-mesh collocation method, which was proposed by Liu and Bhatia (Comput. Chem. Engng. 23 (1999) 933-943). The new method is simple, highly efficient, and well-suited to a variety of adsorption and desorption problems involving steep gradients. (C) 2001 Elsevier Science Ltd. All rights reserved.