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    Time-Warping Invariants of Multidimensional Time Series
    (Dordrecht [u.a.] : Springer Science + Business Media B.V., 2020) Diehl, Joscha; Ebrahimi-Fard, Kurusch; Tapia, Nikolas
    In data science, one is often confronted with a time series representing measurements of some quantity of interest. Usually, in a first step, features of the time series need to be extracted. These are numerical quantities that aim to succinctly describe the data and to dampen the influence of noise. In some applications, these features are also required to satisfy some invariance properties. In this paper, we concentrate on time-warping invariants. We show that these correspond to a certain family of iterated sums of the increments of the time series, known as quasisymmetric functions in the mathematics literature. We present these invariant features in an algebraic framework, and we develop some of their basic properties. © 2020, The Author(s).
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    Novel fixed-time stabilization of quaternion-valued BAMNNs with disturbances and time-varying coefficients
    (Springfield, MO : AIMS Press, 2020) Wei, Ruoyu; Cao, Jinde; Kurths, Jürgen
    In this paper, with the quaternion number and time-varying coefficients introduced into traditional BAMNNs, the model of quaternion-valued BAMNNs are formulated. For the first time, fixed-time stabilization of time-varying quaternion-valued BAMNNs is investigated. A novel fixed-time control method is adopted, in which the choice of the Lyapunov function is more general than in most previous results. To cope with the noncommutativity of the quaternion multiplication, two different fixed-time control methods are provided, a decomposition method and a non-decomposition method. Furthermore, to reduce the control strength and improve control efficiency, an adaptive fixed-time control strategy is proposed. Lastly, numerical examples are presented to demonstrate the effectiveness of the theoretical results. © 2020 the Author(s), licensee AIMS Press.
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    Existence, iteration procedures and directional differentiability for parabolic QVIs
    (Berlin ; Heidelberg : Springer, 2020) Alphonse, Amal; Hintermüller, Michael; Rautenberg, Carlos N.
    We study parabolic quasi-variational inequalities (QVIs) of obstacle type. Under appropriate assumptions on the obstacle mapping, we prove the existence of solutions of such QVIs by two methods: one by time discretisation through elliptic QVIs and the second by iteration through parabolic variational inequalities. Using these results, we show the directional differentiability (in a certain sense) of the solution map which takes the source term of a parabolic QVI into the set of solutions, and we relate this result to the contingent derivative of the aforementioned map. We finish with an example where the obstacle mapping is given by the inverse of a parabolic differential operator.
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    Corrector estimates in homogenization of a nonlinear transmission problem for diffusion equations in connected domains
    (Chichester, West Sussex : Wiley, 2020) Kovtunenko, Victor A.; Reichelt, Sina; Zubkova, Anna V.
    This paper is devoted to the homogenization of a nonlinear transmission problem stated in a two-phase domain. We consider a system of linear diffusion equations defined in a periodic domain consisting of two disjoint phases that are both connected sets separated by a thin interface. Depending on the field variables, at the interface, nonlinear conditions are imposed to describe interface reactions. In the variational setting of the problem, we prove the homogenization theorem and a bidomain averaged model. The periodic unfolding technique is used to obtain the residual error estimate with a first-order corrector. © 2019 The Authors. Mathematical Methods in the Applied Sciences published by John Wiley & Sons Ltd.
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    Dynamic probabilistic constraints under continuous random distributions
    (Berlin ; Heidelberg : Springer, 2020) González Grandón, T.; Henrion, R.; Pérez-Aros, P.
    The paper investigates analytical properties of dynamic probabilistic constraints (chance constraints). The underlying random distribution is supposed to be continuous. In the first part, a general multistage model with decision rules depending on past observations of the random process is analyzed. Basic properties like (weak sequential) (semi-) continuity of the probability function or existence of solutions are studied. It turns out that the results differ significantly according to whether decision rules are embedded into Lebesgue or Sobolev spaces. In the second part, the simplest meaningful two-stage model with decision rules from L2 is investigated. More specific properties like Lipschitz continuity and differentiability of the probability function are considered. Explicitly verifiable conditions for these properties are provided along with explicit gradient formulae in the Gaussian case. The application of such formulae in the context of necessary optimality conditions is discussed and a concrete identification of solutions presented. © 2020, The Author(s).
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    Time resolution and power consumption of a monolithic silicon pixel prototype in SiGe BiCMOS technology
    (London : Inst. of Physics, 2020) Paolozzi, L.; Cardarelli, R.; Débieux, S.; Favre, Y.; Ferrère, D.; Gonzalez-Sevilla, S.; Iacobucci, G.; Kaynak, M.; Martinelli, F.; Nessi, M.; Rücker, H.; Sanna, I.; Sultan, D.M.S.; Valerio, P.; Zaffaroni, E.
    SiGe BiCMOS technology can be used to produce ultra-fast, low-power silicon pixel sensors that provide state-of-the-art time resolution even without internal gain. The development of such sensors requires the identification and control of the main factors that may degrade the timing performance as well as the characterisation of the dependance of the sensor time resolution on the amplifier power consumption. Measurements with a 90Sr source of a prototype sensor produced in SG13G2 technology from IHP Microelectronics shows a time resolution of 140 ps at an amplifier current of 7 µA and 45 ps at a power consumption of 150 µA. The resolution on the measurement of the signal time-over-threshold, which is used to correct for time walk, is the main factor affecting the timing performance of this prototype. c 2020 CERN. Published by IOP Publishing Ltd on behalf of Sissa Medialab.
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    Patch-Wise Adaptive Weights Smoothing in R
    (Los Angeles, Calif. : UCLA, Dept. of Statistics, 2020) Polzehl, Jörg; Papafitsoros, Kostas; Tabelow, Karsten
    Image reconstruction from noisy data has a long history of methodological development and is based on a variety of ideas. In this paper we introduce a new method called patch-wise adaptive smoothing, that extends the propagation-separation approach by using comparisons of local patches of image intensities to define local adaptive weighting schemes for an improved balance of reduced variability and bias in the reconstruction result. We present the implementation of the new method in an R package aws and demonstrate its properties on a number of examples in comparison with other state-of-the art image reconstruction methods. © 2020, American Statistical Association. All rights reserved.
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    Modelling the Dependency between Inflation and Exchange Rate Using Copula
    (New York, NY : Hindawi, 2020) Kwofie, Charles; Akoto, Isaac; Opoku-Ameyaw, Kwaku
    In this paper, we propose a copula approach in measuring the dependency between inflation and exchange rate. In unveiling this dependency, we first estimated the best GARCH model for the two variables. Then, we derived the marginal distributions of the standardised residuals from the GARCH. The Laplace and generalised t distributions best modelled the residuals of the GARCH(1,1) models, respectively, for inflation and exchange rate. These marginals were then used to transform the standardised residuals into uniform random variables on a unit interval [0, 1] for estimating the copulas. Our results show that the dependency between inflation and exchange rate in Ghana is approximately 7%.
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    Modelling and simulation of flame cutting for steel plates with solid phases and melting
    (Berlin ; Heidelberg : Springer, 2020) Arenas, Manuel J.; Hömberg, Dietmar; Lasarzik, Robert; Mikkonen, Pertti; Petzold, Thomas
    The goal of this work is to describe in detail a quasi-stationary state model which can be used to deeply understand the distribution of the heat in a steel plate and the changes in the solid phases of the steel and into liquid phase during the flame cutting process. We use a 3D-model similar to previous works from Thiébaud (J. Mater. Process. Technol. 214(2):304–310, 2014) and expand it to consider phases changes, in particular, austenite formation and melting of material. Experimental data is used to validate the model and study its capabilities. Parameters defining the shape of the volumetric heat source and the power density are calibrated to achieve good agreement with temperature measurements. Similarities and differences with other models from literature are discussed. © 2020, The Author(s).
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    Beyond just “flattening the curve”: Optimal control of epidemics with purely non-pharmaceutical interventions
    (Berlin ; Heidelberg : Springer, 2020) Kantner, Markus; Koprucki, Thomas
    When effective medical treatment and vaccination are not available, non-pharmaceutical interventions such as social distancing, home quarantine and far-reaching shutdown of public life are the only available strategies to prevent the spread of epidemics. Based on an extended SEIR (susceptible-exposed-infectious-recovered) model and continuous-time optimal control theory, we compute the optimal non-pharmaceutical intervention strategy for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible. In this case, the optimal control must meet competing requirements: First, the minimization of disease-related deaths, and, second, the establishment of a sufficient degree of natural immunity at the end of the measures, in order to exclude a second wave. Moreover, the socio-economic costs of the intervention shall be kept at a minimum. The numerically computed optimal control strategy is a single-intervention scenario that goes beyond heuristically motivated interventions and simple “flattening of the curve”. Careful analysis of the computed control strategy reveals, however, that the obtained solution is in fact a tightrope walk close to the stability boundary of the system, where socio-economic costs and the risk of a new outbreak must be constantly balanced against one another. The model system is calibrated to reproduce the initial exponential growth phase of the COVID-19 pandemic in Germany. © 2020, The Author(s).