On model order priors for Bayesian identification of SISO linear systems

A method for the identification of single input single output linear systems is presented. The method employs a Bayesian approach to compute the posterior distribution of the model parameters given the data-set. Since this distribution is often unavailable in closed form, a Metropolis Hastings algorithm is implemented to draw samples from it. To implement the sampler, the inclusion of prior information regarding the model order of the identified system is discussed. As one of the main contributions of this work, a prior over the Hankel singular values of the model is imposed. Numerical examples illustrate the method.     

Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.     

Bridging challenges of clinical decision support systems with a semantic approach. A case study on breast cancer

The integration of Clinical Decision Support Systems (CDSS) in nowadays clinical environments has not been fully achieved yet. Although numerous approaches and technologies have been proposed since 1960, there are still open gaps that need to be bridged. In this work we present advances from the established state of the art, overcoming some of the most notorious reported difficulties in: (i) automating CDSS, (ii) clinical workflow integration, (iii) maintainability and extensibility of the system, (iv) timely advice, (v) evaluation of the costs and effects of clinical decision support, and (vi) the need of architectures that allow the sharing and reusing of CDSS modules and services. In order to do so, we introduce a new clinical task model oriented to clinical workflow integration, which follows a federated approach. Our work makes use of the reported benefits of semantics in order to fully take advantage of the knowledge present in every stage of clinical tasks and the experience acquired by physicians. In order to introduce a feasible extension of classical CDSS, we present a generic architecture that permits a semantic enhancement, namely Semantic CDSS (S-CDSS). A case study of the proposed architecture in the domain of breast cancer is also presented, pointing some highlights of our methodology.     

Drying Schedules for Canelo Wood

Canelo wood is a highly valued native species in Chile that shows delicate marbling patterns with a pinkish soft silver luster. Due to its decorative qualities, canelo wood is dried for the manufacture of furniture and musical instruments. However, canelo wood lacks vessels cells that typically transport the water in hardwoods. Per its drying behavior, canelo wood is considered a transition species between hardwoods and softwoods. Therefore, this article reports drying schedules that were developed for drying 25-mm and 50-mm canelo lumber. In addition, this article reports experimental overall mass transfer coefficients, so that drying times for each of the drying stages can be easily estimated.     

A novel numerical method of high‐order accuracy for flow in unsaturated porous media

We construct finite volume schemes of very high order of accuracy in space and time for solving the nonlinear Richards equation (RE). The general scheme is based on a three‐stage predictor–corrector procedure. First, a high‐order weighted essentially non‐oscillatory (WENO) reconstruction procedure is applied to the cell averages at the current time level to guarantee monotonicity in the presence of steep gradients. Second, the temporal evolution of the WENO reconstruction polynomials is computed in a predictor stage by using a global weak form of the governing equations. A global space–time DG FEM is used to obtain a scheme without the parabolic time‐step restriction caused by the presence of the diffusion term in the RE. The resulting nonlinear algebraic system is solved by a Newton–Krylov method, where the generalized minimal residual method algorithm of Saad and Schulz is used to solve the linear subsystems. Finally, as a third step, the cell averages of the finite volume method are updated using a one‐step scheme, on the basis of the solution calculated previously in the space–time predictor stage. Our scheme is validated against analytical, experimental, and other numerical reference solutions in four test cases. A numerical convergence study performed allows us to show that the proposed novel scheme is high order accurate in space and time. Copyright © 2011 John Wiley & Sons, Ltd.     

Preparation and characterisation of chemical manganese dioxide: Effect of the operating conditions

In this study MnO₂ preparation by chemical methods is investigated for possible applications in dry cell batteries of chemical manganese dioxide (CMD) instead of electrolytic manganese dioxide (EMD). Three preparation procedures were tested: precipitation–oxidation by air plus acid activation (two-step-air), precipitation–oxidation by H₂O₂ plus acid activation (two-step-H₂O₂), precipitation–oxidation by KClO₃ (single-step-ClO₃). Replicated factorial designs and related statistical analysis of experimental data by analysis of variance were performed in order both to obtain a preliminary optimization of the operating conditions and to take into account the intrinsic sample heterogeneity associated to each specific procedure. Comparisons among three different preparations denoted that in the investigated conditions two-step preparations give larger yields of activated solid in comparison with single-step preparation. Preliminary optimized conditions denoted final solid yields (80–86%) for both two-step procedures. The effect of operating conditions on the chemical, structural and electrochemical properties of CMDs produced in preliminary optimised conditions was investigated and compared with those of a commercial EMD sample by acid and acid-reducing leaching for Mn speciation in solid phase, potentiometric titrations, X-ray and IR spectra and cyclic voltammetry. These characterisation tests denoted the significant effect of acid activation in both preparation procedures to obtain CMD samples with high % of Mn(IV)oxides. Potentiometric titrations of solid samples obtained by first and second steps denoted that both procedures gives two CMD samples with the same acid–base properties, which in comparison with commercial EMD present a residual dissociation in the basic pH range (similar structure and proton insertion properties for CMDs and EMD, but different structural defects). X-ray and IR spectra of solid samples by first and second steps denoted highly disordered systems and the presence of Mn₂O₃ in first step products and of γ-MnO₂ in second step product. Voltammetric cycles denoted that CMD samples obtained after acid digestion present similar peaks than commercial EMD but with higher current intensity.     

Determination of simple sugars,malic acid and total phenolic compounds in apple pomace by infrared spectroscopy and PLSR

The aim of this work was to develop a fast, versatile, inexpensive and environmentally safe analytical method to quantify simple sugars, malic acid and total phenolic compounds in apple pomace, considering its potential use as a raw material with value instead of as an industrial waste. Diffuse reflectance infrared spectroscopy (DRIFTS) measurements of twenty‐six samples of apple pomace were analysed by partial least squares regression (PLSR), using several signal pre‐processing methods. Multivariate models developed with four to five latent variables (LVs) and based in the MIR (mid‐infrared) region had good prediction for the determination of sucrose, fructose, malic acid and total phenolic compounds, with average errors between 3.9% and 6.6%. By contrast, glucose was better determined by models developed in the NIR (near‐infrared) region and using six LVs, yielding an average error lower than 7.4%. These results confirmed the feasibility of the multivariate spectroscopic approach as an alternative for expensive and time‐consuming conventional chemical methods.