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This study presents the application of a safe, cost effective, environmental friendly, and efficient technology for the removal of trivalent chromium ions from aqueous solutions, based on the valorisation of a renewable resource, Laminaria digitata seaweed. Insights into trivalent chromium speciation in solution and interaction with the active sites present in the surface of the brown algae were studied. Carboxyl and hydroxyl groups were identified as the major binding sites present in the surface of the biosorbent, in concentrations ( Qmax) of 2.06 ± 0.01 and 1.4 ± 0.7 mmol g −1, and with proton binding parameters ( pK) of 3.28 ± 0.01 and 11 ± 1, respectively. Trivalent chromium uptake at equilibrium conditions was well described at different acidic pH conditions and chromium concentrations, using a model which incorporates trivalent chromium hydrolysis reactions in the aqueous phase and its chemical interactions with the available active sites (carboxyl groups) present in the surface of biosorbent. The distribution profile of trivalent chromium species present in the solution as well as at the binding sites indicated that Cr 3+ and CrOH 2+ exhibit different affinities for the carboxyl groups present in the surface of the biomass according to the pH. A mass transfer kinetics model was applied to describe the kinetics at batch system, being possible to obtain the distribution of CrOH 2+ and Cr 3+ species in solution and at the binding sites. [ABSTRACT FROM AUTHOR]

Infrared focal-plane array (IRFPA) detectors suffer from fixed-pattern noise (FPN) that degrades image quality, which is also known as spatial nonuniformity. FPN is still a serious problem, despite recent advances in IRFPA technology. This paper proposes new scene-based correction algorithms for continuous compensation of bias and gain nonuniformity in FPA sensors. The proposed schemes use recursive least-square and affine projection techniques that jointly compensate for both the bias and gain of each image pixel, presenting rapid convergence and robustness to noise. The synthetic and real IRFPA videos experimentally show that the proposed solutions are competitive with the state-of-the-art in FPN reduction, by presenting recovered images with higher fidelity. [ABSTRACT FROM AUTHOR]

This paper presents the results of a multiscale pattern-matching-based ECG encoder, which employs simple preprocessing techniques for adapting the input signal. Experiments carried out with records from the Massachusetts Institute of Technology-Beth Israel Hospital database show that the proposed scheme is effective, outperforming some state-of-the-art schemes described in the literature. [ABSTRACT FROM AUTHOR]

In this paper, the multidimensional multiscale parser (MMP) is employed for encoding electromyographic signals. The experiments were carried out with real signals acquired in laboratory and show that the proposed scheme is effective, outperforming even wavelet-based state-of- the-art schemes present in the literature in terms of percent root mean square difference × compression ratio. [ABSTRACT FROM AUTHOR]

In this brief, we present new preprocessing techniques for electrocardiogram signals, namely, dc equalization and complexity sorting, which when applied can improve current 2-D compression algorithms. The experimental results with signals from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) database outperform the ones from many state-of-the-art schemes described in the literature. [ABSTRACT FROM AUTHOR]

For the compression of stereo images, several techniques employing the concept of disparity compensation have been developed. In this paper, we present a new method for stereo-image compression which is based on a different paradigm. It relies on approximate matching of multiscale recurrent patterns, which is an extension of ordinary pattern matching, where an image block is represented using dilated, contracted, displaced, and deformed versions of blocks already processed. To achieve this, the input image is segmented into variable-sized blocks. Each segment is represented by an element in a dictionary. The segmentation is performed according to a rate x distortion criterion, and the dictionary is updated with the concatenation, contraction, expansion, displacement, and deformation of previously coded elements. Unlike most other methods, in this approach the disparity map is not transmitted. That is, the generation of the error images, as well as their coding and transmission, is not necessary. In brief, the proposed method presents high-quality results at the decoder end, compared to other coding methods for stereo images that transmit the disparity map. [ABSTRACT FROM AUTHOR]

This paper presents coherent representations of electric power systems signals. These representations are obtained by employing adaptive signal decompositions. They provide a tool to identify structures composing a signal and constitute an approach to represent a signal from its identified components. We use the Matching Pursuits algorithm, which is a greedy adaptive decomposition, that has the potential of decomposing a signal into coherent components. The dictionary employed is composed of damped sinusoids in order to obtain signal components closely related to power systems phenomena. In addition, we present an effective method to suppress the pre-echo post-echo artifacts that often appear when using the Matching Pursuits. However, the use of a dictionary of damped sinusoids alone does not ensure that the decomposition will be meaningful in physical terms. To overcome this constraint, we develop a technique leading to efficient coherent damped-sinusoidal decompositions that are closely related to the physical phenomena being observed. The effectiveness of the proposed method for compression of synthetic and natural signals is tested, obtaining high compression ratios along with high signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

This paper presents a special matrix factorization based on sparse representation that detects anomalies in video sequences generated with moving cameras. Such representation is made by associating the frames of the target video, that is a sequence to be tested for the presence of anomalies, with the frames of an anomaly-free reference video, which is a previously validated sequence. This factorization is done by a sparse coefficient matrix, and any target-video anomaly is encapsulated into a residue term. In order to cope with camera trepidations, domaintransformations are incorporated into the sparse representation process. Approximations of the transformed-domain optimization problem are introduced to turn it into a feasible iterative process. Results obtained from a comprehensive video database acquired with moving cameras on a visually cluttered environment indicate that the proposed algorithm provides a better geometric registration between reference and target videos, greatly improving the overall performance of the anomaly-detection system.