Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Film thickness measurement techniques applied to micro-scale two-phase flow systems

Recently semi-empirical models to estimate flow boiling heat transfer coefficient, saturated CHF and pressure drop in micro-scale channels have been proposed. Most of the models were developed based on elongated bubbles and annular flows in the view of the fact that these flow patterns are predominant in smaller channels. In these models, the liquid film thickness plays an important role and such a fact emphasizes that the accurate measurement of the liquid film thickness is a key point to validate them. On the other hand, several techniques have been successfully applied to measure liquid film thicknesses during condensation and evaporation under macro-scale conditions. However, although this subject has been targeted by several leading laboratories around the world, it seems that there is no conclusive result describing a successful technique capable of measuring dynamic liquid film thickness during evaporation inside micro-scale round channels. This work presents a comprehensive literature review of the methods used to measure liquid film thickness in macro- and micro-scale systems. The methods are described and the main difficulties related to their use in micro-scale systems are identified. Based on this discussion, the most promising methods to measure dynamic liquid film thickness in micro-scale channels are identified. (C) 2009 Elsevier Inc. All rights reserved.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Application of molecular techniques to evaluate the methanogenic archaea and anaerobic bacteria in the presence of oxygen with different COD : sulfate ratios in a UASB reactor

In this paper, the microbial characteristics of the granular sludge in the presence of oxygen (3.0 +/- 0.7 mg O-2 1(-1)) were analyzed using molecular biology techniques. The granules were provided by an upflow anaerobic sludge blanket (UASB) operated over 469 days and fed with synthetic substrate. Ethanol and sulfate were added to obtain different COD/SO42- ratios (3.0, 2.0, and 1.6). The results of fluorescent in situ hybridization (FISH) analyses showed that archaeal cells, detected by the ARC915 probe, accounted for 77%, 84%, and 75% in the COD/SO42- ratios (3.0, 2.0, and 1.6, respectively). Methanosaeta sp. was the predominant acetoclastic archaea observed by optical microscopy and FISH analyses, and confirmed by sequencing of the excised bands of the DGGE gel with a similarity of 96%. The sulfate-reducing bacterium Desulfovibrio vulgaris subsp. vulgaris (similarity of 99%) was verified by sequencing of the DGGE band. Others identified microorganism were similar to Shewanella sp. and Desulfitobacterium hafniense, with similarities of 95% and 99%, respectively. These results confirmed that the presence of oxygen did not severely affect the metabolism of microorganisms that are commonly considered strictly anaerobic. We obtained mean efficiencies of organic matter conversion and sulfate reducing higher than 74%. (C) 2008 Elsevier Ltd. All rights reserved.

Post-processing and visualization techniques in 2D boundary element analysis

Most post-processors for boundary element (BE) analysis use an auxiliary domain mesh to display domain results, working against the profitable modelling process of a pure boundary discretization. This paper introduces a novel visualization technique which preserves the basic properties of the boundary element methods. The proposed algorithm does not require any domain discretization and is based on the direct and automatic identification of isolines. Another critical aspect of the visualization of domain results in BE analysis is the effort required to evaluate results in interior points. In order to tackle this issue, the present article also provides a comparison between the performance of two different BE formulations (conventional and hybrid). In addition, this paper presents an overview of the most common post-processing and visualization techniques in BE analysis, such as the classical algorithms of scan line and the interpolation over a domain discretization. The results presented herein show that the proposed algorithm offers a very high performance compared with other visualization procedures.

Proposal for underwater structural analysis using the techniques of ESPI and digital holography

The purpose of this article is to study the application of the holographic interferometry techniques in the structural analysis of submarine environment. These techniques are widely used today, with applications in many areas. Nevertheless, its application in submarine environments presents some challenges. The application of two techniques, electronic speckle pattern interferometry (ESPI) and digital holography, comparison of advantages and disadvantages of each of them is presented. A brief study is done on the influence of water properties and the optical effects due to suspended particles as well as possible solutions to minimize these problems. (C) 2009 Elsevier Ltd. All rights reserved.

Modeling and Filtering Double-Frequency Jitter in One-Way Master-Slave Chain Networks

One-way master-slave (OWMS) chain networks are widely used in clock distribution systems due to their reliability and low cost. As the network nodes are phase-locked loops (PLLs), double-frequency jitter (DFJ) caused by their phase detectors appears as an impairment to the performance of the clock recovering process found in communication systems and instrumentation applications. A nonlinear model for OWMS chain networks with P + 1 order PLLs as slave nodes is presented, considering the DFJ. Since higher order filters are more effective in filtering DFJ, the synchronous state stability conditions for an OWMS chain network with third-order nodes are derived, relating the loop gain and the filter coefficients. By using these conditions, design examples are discussed.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

Metal separation from mixed types of batteries using selective precipitation and liquid-liquid extraction techniques

The purpose of this paper is to study metal separation from a sample composed of a mixture of the main types of spent household batteries, using a hydrometallurgical route, comparing selective precipitation and liquid-liquid extraction separation techniques. The preparation of the solution consisted of: grinding the waste of mixed batteries, reduction and volatile metals elimination using electric furnace and acid leaching. From this solution two different routes were studied: selective precipitation with sodium hydroxide and liquid-liquid extraction using Cyanex 272 [bis(2,4,4-trimethylpentyl) phosphoric acid] as extracting agent. The best results were obtained from liquid-liquid extraction in which Zn had a 99% extraction rate at pH 2.5. More than 95% Fe was extracted at pH 7.0, the same pH at which more than 90% Ce was extracted. About 88% Mn, Cr and Co was extracted at this pH. At pH 3.0, more than 85% Ni was extracted, and at pH 3.5 more than 80% of Cd and La was extracted. (C) 2010 Elsevier Ltd. All rights reserved.

Localization of Pantoea ananatis inside lesions of maize White Spot Disease using transmission electron microscopy and molecular techniques

The etiological agent of maize white spot (MWS) disease has been a subject of controversy and discussion. Initially the disease was described as Phaeosphaeria leaf spot caused by Phaeosphaeria maydis. Other authors have Suggested the existence of different fungal species causing similar symptoms. Recently, a bacterium, Pantoea ananatis, was described as the causal agent of this disease. The purpose of this Study was to offer additional information on the correct etiology of this disease by providing visual evidence of the presence of the bacterium in the interior of the MWS lesions by using transmission electron microscopy (TEM) and molecular techniques. The TEM allowed Visualization of a large amount of bacteria in the intercellular spaces of lesions collected from both artificially and naturally infected plants. Fungal structures were not visualized in young lesions. Bacterial primers for the 16S rRNA and rpoB genes were used in PCR reactions to amplify DNA extracted from water-soaked (young) and necrotic lesions. The universal fungal oligonucleotide ITS4 was also included to identity the possible presence of fungal structures inside lesions. Positive PCR products from water-soaked lesions, both from naturally and artificially inoculated plants, were produced with bacterial primers, whereas no amplification was observed when ITS4 oligonucleotide was used. On the other hand, DNA amplification with ITS4 primer was observed when DNA was isolated from necrotic (old) lesions. These results reinforced previous report of P. ananatis as the primary pathogen and the hypothesis that fungal species may colonize lesions pre-established by P. ananatis.

Soil CO(2) emission estimated by different interpolation techniques

Soil CO(2) emissions are highly variable, both spatially and across time, with significant changes even during a one-day period. The objective of this study was to compare predictions of the diurnal soil CO(2) emissions in an agricultural field when estimated by ordinary kriging and sequential Gaussian simulation. The dataset consisted of 64 measurements taken in the morning and in the afternoon on bare soil in southern Brazil. The mean soil CO(2) emissions were significantly different between the morning (4.54 mu mol m(-2) s(-1)) and afternoon (6.24 mu mol m(-2) s(-1)) measurements. However, the spatial variability structures were similar, as the models were spherical and had close range values of 40.1 and 40.0 m for the morning and afternoon semivariograms. In both periods, the sequential Gaussian simulation maps were more efficient for the estimations of emission than ordinary kriging. We believe that sequential Gaussian simulation can improve estimations of soil CO(2) emissions in the field, as this property is usually highly non-Gaussian distributed.

Biophysical techniques used to evaluate the stratum corneum

Assortments of biophysical methods are used to the study the stratum corneum morphology and dynamic with the objective to elucidate the correlation between its structure and functions. Among these methods, there are: X-ray diffraction, electron paramagnetic resonance, differential scanning calorimetry, Raman spectroscopy with Fourrier transform, infrared spectroscopy and photoacustic spectroscopy. In this manuscript, methods are presented and discussed in relation to the use indication, interpretation of results and advantages and limitations to the stratum corneum analysis.

Computationally efficient solution techniques for adsorption problems involving steep gradients in bidisperse particles

A piecewise uniform fitted mesh method turns out to be sufficient for the solution of a surprisingly wide variety of singularly perturbed problems involving steep gradients. The technique is applied to a model of adsorption in bidisperse solids for which two fitted mesh techniques, a fitted-mesh finite difference method (FMFDM) and fitted mesh collocation method (FMCM) are presented. A combination (FMCMD) of FMCM and the DASSL integration package is found to be most effective in solving the problems. Numerical solutions (FMFDM and FMCMD) were found to match the analytical solution when the adsorption isotherm is linear, even under conditions involving steep gradients for which global collocation fails. In particular, FMCMD is highly efficient for macropore diffusion control or micropore diffusion control. These techniques are simple and there is no limit on the range of the parameters. The techniques can be applied to a variety of adsorption and desorption problems in bidisperse solids with non-linear isotherm and for arbitrary particle geometry.