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Sökning: WFRF:(Alves Renato) > (2023)

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1.
  • Alves, Dimas irion, et al. (författare)
  • Change Detection Method for Wavelength-Resolution SAR Images Based on Bayes’ Theorem : An Iterative Approach
  • 2023
  • Ingår i: IEEE Access. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 11, s. 84734-84743
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents an iterative change detection (CD) method based on Bayes’ theorem for very high-frequency (VHF) ultra-wideband (UWB) SAR images considering commonly used clutter-plus-noise statistical models. The proposed detection technique uses the information of the detected changes to iteratively update the data and distribution information, obtaining more accurate clutter-plus-noise statistics resulting in false alarm reduction. The Bivariate Rayleigh and Bivariate Gaussian distributions are investigated as candidates to model the clutter-plus-noise, and the Anderson-Darling goodness-of-fit test is used to investigate three scenarios of interest. Different aspects related to the distributions are discussed, the observed mismatches are analyzed, and the impact of the distribution chosen for the proposed iterative change detection method is analyzed. Finally, the proposed iterative method performance is assessed in terms of the probability of detection and false alarm rate and compared with other competitive solutions. The experimental evaluation uses data from real measurements obtained using the CARABAS II SAR system. Results show that the proposed iterative CD algorithm performs better than the other methods. Author
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2.
  • Alves Machado Filho, Manoel, et al. (författare)
  • Self-Induced Core–Shell InAlN Nanorods: Formation and Stability Unraveled by Ab Initio Simulations
  • 2023
  • Ingår i: ACS Nanoscience Au. - : American Chemical Society (ACS). - 2694-2496. ; 3:1, s. 84-93
  • Tidskriftsartikel (refereegranskat)abstract
    • By addressing precursor prevalence and energetics using the DFT-based synthetic growth concept (SGC), the formation mechanism of self-induced InAlN core–shell nanorods (NRs) synthesized by reactive magnetron sputter epitaxy (MSE) is explored. The characteristics of In- and Al-containing precursor species are evaluated considering the thermal conditions at a typical NR growth temperature of around 700 °C. The cohesive and dissociation energies of In-containing precursors are consistently lower than those of their Al-containing counterparts, indicating that In-containing precursors are more weakly bonded and more prone to dissociation. Therefore, In-containing species are expected to exhibit lower abundance in the NR growth environment. At increased growth temperatures, the depletion of In-based precursors is even more pronounced. A distinctive imbalance in the incorporation of Al- and In-containing precursor species (namely, AlN/AlN+, AlN2/AlN2+, Al2N2/Al2N2+, and Al2/Al2+ vs InN/InN+, InN2/InN2+, In2N2/In2N2+, and In2/In2+) is found at the growing edge of the NR side surfaces, which correlates well with the experimentally obtained core–shell structure as well as with the distinctive In-rich core and vice versa for the Al-rich shell. The performed modeling indicates that the formation of the core–shell structure is substantially driven by the precursors’ abundance and their preferential bonding onto the growing edge of the nanoclusters/islands initiated by phase separation from the beginning of the NR growth. The cohesive energies and the band gaps of the NRs show decreasing trends with an increment in the In concentration of the NRs’ core and with an increment in the overall thickness (diameter) of the NRs. These results reveal the energy and electronic reasons behind the limited growth (up to ∼25% of In atoms of all metal atoms, i.e., InxAl1–xN, x ∼ 0.25) in the NR core and may be qualitatively perceived as a limiting factor for the thickness of the grown NRs (typically <50 nm).
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3.
  • Andrikopoulos, Petros, et al. (författare)
  • Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide
  • 2023
  • Ingår i: Nature Communications. - 2041-1723 .- 2041-1723. ; 14:1
  • Tidskriftsartikel (refereegranskat)abstract
    • The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.
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4.
  • Mittmann Voigt, Gustavo Henrique, et al. (författare)
  • A Statistical Analysis for Intensity Wavelength-Resolution SAR Difference Images
  • 2023
  • Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 15:9
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a statistical analysis of intensity wavelength-resolution synthetic aperture radar (SAR) difference images. In this analysis, Anderson Darling goodness-of-fit tests are performed, considering two different statistical distributions as candidates for modeling the clutter-plus-noise, i.e., the background statistics. The results show that the Gamma distribution is a good fit for the background of the tested SAR images, especially when compared with the Exponential distribution. Based on the results of this statistical analysis, a change detection application for the detection of concealed targets is presented. The adequate selection of the background distribution allows for the evaluated change detection method to achieve a better performance in terms of probability of detection and false alarm rate, even when compared with competitive performance change detection methods in the literature. For instance, in an experimental evaluation considering a data set obtained by the Coherent All Radio Band Sensing (CARABAS) II UWB SAR system, the evaluated change detection method reached a detection probability of 0.981 for a false alarm rate of 1/km2. © 2023 by the authors.
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5.
  • Ramos, Lucas P., et al. (författare)
  • Robust Principal Component Analysis Techniques for Ground Scene Estimation in SAR Imagery
  • 2023
  • Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1939-1404 .- 2151-1535. ; 16, s. 9697-9710
  • Tidskriftsartikel (refereegranskat)abstract
    • Robust principal component analysis (RPCA) has been widely used for processing and interpreting high-dimensional data in different applications such as data classification, face recognition, video analytics, and recommendation system design. However, the advancement of multisensor-based technologies and the emergence of large data sets have highlighted the limitations of traditional matrix-based models, which have paved the way for higher-order extensions such as tensor RPCA (TRPCA) techniques. These signal separation techniques can be useful for ground scene estimation (GSE) in synthetic aperture radar (SAR) imagery. GSE estimates the clutter-plus-noise content in the scene, and therefore, change detection (CD) methods can benefit, reducing the number of false alarms (FA). This paper presents two new GSE methods for SAR imagery based on robust PCA techniques. The first proposed method uses the RPCA via Principal Component Pursuit (PCP) to obtain the GSE-RPCA. The second method uses TRPCA via New Tensor Nuclear Norm (TNN) to obtain the GSE-TRPCA. The methodology allows the GSE to be obtained through a generalized regularization parameter. The alternating direction method of multipliers (ADMM) algorithm is utilized to solve both optimization problems. Experimental results are evaluated considering real SAR imagery from two data sets acquired with the CARABAS II and ALOS PALSAR systems, respectively. Additionally, the proposed techniques were evaluated under several input characteristics, e.g., eight-image stacks and image pairs. Both GSE techniques are more robust to outliers and missing data when compared to existing solutions found in the literature. Finally, GSE-TRPCA achieved a minimum-square error performance of 0.0018 for some of the evaluated scenarios. 
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