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- Akiyama, Kazunori, et al.
(author)
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First Sagittarius A* Event Horizon Telescope Results. II. EHT and Multiwavelength Observations, Data Processing, and Calibration
- 2022
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In: Astrophysical Journal Letters. - : American Astronomical Society. - 2041-8213 .- 2041-8205. ; 930:2
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Journal article (peer-reviewed)abstract
- We present Event Horizon Telescope (EHT) 1.3 mm measurements of the radio source located at the position of the supermassive black hole Sagittarius A* (Sgr A*), collected during the 2017 April 5-11 campaign. The observations were carried out with eight facilities at six locations across the globe. Novel calibration methods are employed to account for Sgr A*'s flux variability. The majority of the 1.3 mm emission arises from horizon scales, where intrinsic structural source variability is detected on timescales of minutes to hours. The effects of interstellar scattering on the image and its variability are found to be subdominant to intrinsic source structure. The calibrated visibility amplitudes, particularly the locations of the visibility minima, are broadly consistent with a blurred ring with a diameter of similar to 50 mu as, as determined in later works in this series. Contemporaneous multiwavelength monitoring of Sgr A* was performed at 22, 43, and 86 GHz and at near-infrared and X-ray wavelengths. Several X-ray flares from Sgr A* are detected by Chandra, one at low significance jointly with Swift on 2017 April 7 and the other at higher significance jointly with NuSTAR on 2017 April 11. The brighter April 11 flare is not observed simultaneously by the EHT but is followed by a significant increase in millimeter flux variability immediately after the X-ray outburst, indicating a likely connection in the emission physics near the event horizon. We compare Sgr A*'s broadband flux during the EHT campaign to its historical spectral energy distribution and find that both the quiescent emission and flare emission are consistent with its long-term behavior.
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- Alves, Dimas, I, et al.
(author)
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Incoherent Change Detection Methods for Wavelength-Resolution SAR Image Stacks Based on Masking Techniques
- 2020
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In: 2020 IEEE National Radar Conference - Proceedings. - : IEEE. - 9781728189420
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Conference paper (peer-reviewed)abstract
- This paper presents two incoherent change detection methods for wavelength-resolution synthetic aperture radars (SAR) image stacks based on masking techniques. The first technique proposed is the Simple Masking Detection (SMD). This method uses the statistical behavior of pixels-sets in the image stack to create a binary mask, which is used to remove pixels that are not related to changes in a surveillance image from the same interest region. The second technique is the Multiple Concatenated Masking Detection (MCMD), which produces a more selective mask than the SMD by concatenating multiple masks from different image stacks. The MCMD can be used in specific applications where multiple stacks share common patterns of target deployments. Both proposed techniques were evaluated using 24 incoherent SAR images obtained by the CARABAS II system. The experimental results revealed that the proposed detection methods have better performance in terms of probability of detection and false alarm rate when compared with other change detection techniques, especially for high detection probabilities scenarios.
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- Alves, Dimas I., et al.
(author)
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Neyman-Pearson Criterion-Based Change Detection Methods for Wavelength-Resolution SAR Image Stacks
- 2022
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In: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
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Journal article (peer-reviewed)abstract
- This letter presents two new change detection (CD) methods for synthetic aperture radar (SAR) image stacks based on the Neyman-Pearson criterion. The first proposed method uses the data from wavelength-resolution images stack to obtain background statistics, which are used in a hypothesis test to detect changes in a surveillance image. The second method considers a priori information about the targets to obtain the target statistics, which are used together with the previously obtained background statistics, to perform a hypothesis test to detect changes in a surveillance image. A straightforward processing scheme is presented to test the proposed CD methods. To assess the performance of both proposed methods, we considered the coherent all radio band sensing (CARABAS)-II SAR images. In particular, to obtain the temporal background statistics required by the derived methods, we used stacks with six images. The experimental results show that the proposed techniques provide a competitive performance in terms of probability of detection and false alarm rate compared with other CD methods. CCBY
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- Freisling, Heinz, et al.
(author)
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Lifestyle factors and risk of multimorbidity of cancer and cardiometabolic diseases : a multinational cohort study
- 2020
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In: BMC Medicine. - : Springer Science and Business Media LLC. - 1741-7015. ; 18:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. METHODS: In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. RESULTS: During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. CONCLUSION: Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.
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- Mittmann Voigt, Gustavo Henrique, et al.
(author)
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A Statistical Analysis for Intensity Wavelength-Resolution SAR Difference Images
- 2023
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In: Remote Sensing. - : MDPI. - 2072-4292. ; 15:9
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Journal article (peer-reviewed)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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- Müller, Matias I., et al.
(author)
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Data-Driven Input-Passivity Estimation Using Power Iterations
- 2021
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In: IFAC PAPERSONLINE. - : ELSEVIER. - 2405-8963. ; , s. 619-624
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Conference paper (peer-reviewed)abstract
- In this work we develop a non-parametric method to estimate the input-passivity index of an unknown linear and time-invariant (LTI) system from iterative experiments based on the power method from numerical linear algebra. Inspired by the power method for estimating the H-infinity-norm (or l(2)-gain) from data, we propose an algorithm that time-reverses input-output data in order to emulate measurements of a virtual system whose l(2)-gain matches the passivity index of the original system under study. While the proposed method requires exciting the original system twice, we also introduce an improved sampling scheme where only one experiment per iteration is needed.
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| 9. |
- Müller, Matias I., et al.
(author)
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Iterative H-infinity-norm Estimation Using Cyclic-Prefixed Signals
- 2020
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In: 2020 59Th IEEE Conference On Decision And Control (Cdc). - : IEEE. ; , s. 2869-2874
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Conference paper (peer-reviewed)abstract
- The problem of estimating the largest gain of an unknown linear and time-invariant filter is studied, known as the H-infinity -norm estimation problem. The approach presented in this paper is iterative and corresponds to the combination of two state-of-the-art methods: Power Iterations and Weighted Thompson Sampling. The combination is done by means of a well-known technique in communications known as a cyclic prefix, in which the last points of a signal are prepended to it. This allows to take considerably more exact measurements of the frequency response of the system at a set of equispaced frequencies. The discussion is complemented with a simulation study, showing that the proposed algorithm has an increased speed of convergence to the quantity of interest.
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| 10. |
- Müller, Matias I.
(author)
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Learning Sequential Decision Rules in Control Design: Regret-Optimal and Risk-Coherent Methods
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Engineering sciences deal with the problem of optimal design in the face of uncertainty. In particular, control engineering is concerned about designing policies/laws/algorithms that sequentially take decisions given unreliable data. This thesis addresses two particular instances of optimal sequential decision making for two different problems.The first problem is known as the H∞-norm (or, in general, ℓ2-gain for nonlinear systems) estimation problem, which is a fundamental quantity in control design through, e.g., the small gain theorem. Given an unknown system, the goal is to find the maximum ℓ2-gain which, in a model-free approach, involves solving a sequential input design problem. The H∞-norm estimation problem (or simply "gain estimation problem") is cast as the composition of multi-armed bandit problem generating data, and an optimal estimation problem given that data. The problem of generating data is a sequential input-design problem in which, at every round, the decision-maker chooses one (or many) frequencies to sample from the unknown frequency response of the system under study. We show that Thompson Sampling (TS), a classical bandit algorithm, is optimal within the class of algorithms that chooses only one frequency per round. Additionally, we introduce Weighted Thompson Sampling (WTS), which is a TS-based algorithm that can sample many frequencies at every round. In this thesis, we prove that WTS is an optimal bandit policy within the class of algorithms that can sample many frequencies simultaneously. On the other hand, the problem of estimating the H∞-norm of the system using the data provided by the bandit algorithm is also discussed. In particular, we show that the expected estimation error of the gain of the system asymptotically matches the Cramér-Rao lower bound for a proposed estimator, and for every bandit policy in a wide class of algorithms.In the second part, we address the problem of risk-coherent optimal control design for disturbance rejection under uncertainty, where optimality is studied from an H2 and an H∞ sense. We consider a parametric model for the plant and the noise spectrum, where the modeling error between the model and the real system is uncertain. This uncertainty is condensed in a probability density function over the different realizations of the parameters defining the model. We use this information to design a controller that minimizes the risk of falling into poor closed-loop performance within a financial theory of risk framework. When the parameters in the plant are not known with sufficient accuracy for control purposes, we introduce a framework that allows us to tackle the joint-stabilization problem by means of sequential convex relaxations, each of them leading to a semi-definite program. On the other hand, when the noise spectrum is uncertain, we propose a systematic scenario approach for designing H2- and H∞-optimal controllers in terms of quadratically-constrained linear programs and sequential semi-definite programming, respectively. Simulations show that, from a risk-theoretical perspective, exploiting the information encoded in the probability density function of the parameters defining the models better balances the risk of falling into poor closed-loop performances.
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