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Direct sampling method via Landweber iteration for an absorbing scatterer with a conductive boundary
(2024)
In this paper, we consider the inverse shape problem of recovering isotropic scatterers with a conductive boundary condition. Here, we assume that the measured far-field data is known at a fixed wave number. Motivated by recent work, we study a new direct sampling indicator based on the Landweber iteration and the factorization method. Therefore, we prove the connection between these reconstruction methods. The method studied here falls under the category of qualitative reconstruction methods where an imaging function is used to recover the absorbing scatterer. We prove stability of our new imaging function as well as derive a discrepancy principle for recovering the regularization parameter. The theoretical results are verified with numerical examples to show how the reconstruction performs by the new Landweber direct sampling method.
We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.
Analysis and computation of the transmission eigenvalues with a conductive boundary condition
(2022)
We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber–Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.
An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.
The hot spots conjecture is only known to be true for special geometries. This paper shows numerically that the hot spots conjecture can fail to be true for easy to construct bounded domains with one hole. The underlying eigenvalue problem for the Laplace equation with Neumann boundary condition is solved with boundary integral equations yielding a non-linear eigenvalue problem. Its discretization via the boundary element collocation method in combination with the algorithm by Beyn yields highly accurate results both for the first non-zero eigenvalue and its corresponding eigenfunction which is due to superconvergence. Additionally, it can be shown numerically that the ratio between the maximal/minimal value inside the domain and its maximal/minimal value on the boundary can be larger than 1 + 10− 3. Finally, numerical examples for easy to construct domains with up to five holes are provided which fail the hot spots conjecture as well.
There is a very large number of very important situations which can be modeled with nonlinear parabolic partial differential equations (PDEs) in several dimensions. In general, these PDEs can be solved by discretizing in the spatial variables and transforming them into huge systems of ordinary differential equations (ODEs), which are very stiff. Therefore, standard explicit methods require a large number of iterations to solve stiff problems. But implicit schemes are computationally very expensive when solving huge systems of nonlinear ODEs. Several families of Extrapolated Stabilized Explicit Runge-Kutta schemes (ESERK) with different order of accuracy (3 to 6) are derived and analyzed in this work. They are explicit methods, with stability regions extended, along the negative real semi-axis, quadratically with respect to the number of stages s, hence they can be considered to solve stiff problems much faster than traditional explicit schemes. Additionally, they allow the adaptation of the step length easily with a very small cost.
Two new families of ESERK schemes (ESERK3 and ESERK6) are derived, and analyzed, in this work. Each family has more than 50 new schemes, with up to 84.000 stages in the case of ESERK6. For the first time, we also parallelized all these new variable step length and variable number of stages algorithms (ESERK3, ESERK4, ESERK5, and ESERK6). These parallelized strategies allow to decrease times significantly, as it is discussed and also shown numerically in two problems. Thus, the new codes provide very good results compared to other well-known ODE solvers. Finally, a new strategy is proposed to increase the efficiency of these schemes, and it is discussed the idea of combining ESERK families in one code, because typically, stiff problems have different zones and according to them and the requested tolerance the optimum order of convergence is different.
A second-order L-stable exponential time-differencing (ETD) method is developed by combining an ETD scheme with approximating the matrix exponentials by rational functions having real distinct poles (RDP), together with a dimensional splitting integrating factor technique. A variety of non-linear reaction-diffusion equations in two and three dimensions with either Dirichlet, Neumann, or periodic boundary conditions are solved with this scheme and shown to outperform a variety of other second-order implicit-explicit schemes. An additional performance boost is gained through further use of basic parallelization techniques.
In this article, a concept of implicit methods for scalar conservation laws in one or more spatial dimensions allowing also for source terms of various types is presented. This material is a significant extension of previous work of the first author (Breuß SIAM J. Numer. Anal. 43(3), 970–986 2005). Implicit notions are developed that are centered around a monotonicity criterion. We demonstrate a connection between a numerical scheme and a discrete entropy inequality, which is based on a classical approach by Crandall and Majda. Additionally, three implicit methods are investigated using the developed notions. Next, we conduct a convergence proof which is not based on a classical compactness argument. Finally, the theoretical results are confirmed by various numerical tests.
The inverse scattering problem for a conductive boundary condition and transmission eigenvalues
(2018)
In this paper, we consider the inverse scattering problem associated with an inhomogeneous media with a conductive boundary. In particular, we are interested in two problems that arise from this inverse problem: the inverse conductivity problem and the corresponding interior transmission eigenvalue problem. The inverse conductivity problem is to recover the conductive boundary parameter from the measured scattering data. We prove that the measured scatted data uniquely determine the conductivity parameter as well as describe a direct algorithm to recover the conductivity. The interior transmission eigenvalue problem is an eigenvalue problem associated with the inverse scattering of such materials. We investigate the convergence of the eigenvalues as the conductivity parameter tends to zero as well as prove existence and discreteness for the case of an absorbing media. Lastly, several numerical and analytical results support the theory and we show that the inside–outside duality method can be used to reconstruct the interior conductive eigenvalues.
The aim of the current study was to investigate the performance of integrated RF
transmit arrays with high channel count consisting of meander microstrip antennas
for body imaging at 7 T and to optimize the position and number of transmit ele-
ments. RF simulations using multiring antenna arrays placed behind the bore liner
were performed for realistic exposure conditions for body imaging. Simulations were
performed for arrays with as few as eight elements and for arrays with high channel
counts of up to 48 elements. The B1+ field was evaluated regarding the degrees of
freedom for RF shimming in the abdomen. Worst-case specific absorption rate
(SARwc ), SAR overestimation in the matrix compression, the number of virtual obser-
vation points (VOPs) and SAR efficiency were evaluated. Constrained RF shimming
was performed in differently oriented regions of interest in the body, and the devia-
tion from a target B1+ field was evaluated. Results show that integrated multiring
arrays are able to generate homogeneous B1+ field distributions for large FOVs, espe-
cially for coronal/sagittal slices, and thus enable body imaging at 7 T with a clinical
workflow; however, a low duty cycle or a high SAR is required to achieve homoge-
neous B1+ distributions and to exploit the full potential. In conclusion, integrated
arrays allow for high element counts that have high degrees of freedom for the pulse
optimization but also produce high SARwc , which reduces the SAR accuracy in the
VOP compression for low-SAR protocols, leading to a potential reduction in array
performance. Smaller SAR overestimations can increase SAR accuracy, but lead to a
high number of VOPs, which increases the computational cost for VOP evaluation
and makes online SAR monitoring or pulse optimization challenging. Arrays with
interleaved rings showed the best results in the study.
Im Verfahren gegen die Österreichische Post AG (Rs. C-300/21) befasste sich der EuGH erstmals mit dem in Art. 82 DS-GVO geregelten datenschutzrechtlichen Schadensersatzanspruch. Mit den Klarstellungen des EuGH verschieben sich die Probleme nun stärker zu den „klassischen“ Fragen des Schadensersatzrechts im Zivilprozess. Relevant sind dabei vor allem Aspekte der Darlegungs- und Beweislast und deren Besonderheiten mit Blick auf den Ersatz immaterieller Schäden. Der Beitrag fokussiert sich auf die Voraussetzungen und den dabei zu führenden Tatsachenbeweis bei der Klage des Betroffenen gegen den Verantwortlichen auf Ersatz immaterieller Schäden.
Kartellrecht vs. Datenschutzrecht: Rechtsgrundlagen für die Datenverarbeitung in sozialen Netzwerken
(2023)
Bald eine Dekade ist es her, dass diese annähernd mantraartig wiederholte Phrase Unternehmen zur Umsetzung datenschutzrechtlicher Vorgaben incentivierte. Was ist davon geblieben? Nur wenige in Deutschland verhängte Bußgelder erreichten Millionenhöhe. Hintergrund ist (auch) das deutsche Ordnungswidrigkeitenrecht, welches in einem Spannungsverhältnis zu den Vorgaben der DS-GVO steht. Ein Bußgeldbescheid der Berliner Datenschutzaufsicht gegen die Deutsche Wohnen sollte Auslöser eines langen, fortdauernden Rechtsstreits werden. Auf Vorlage des KG hatte der EuGH in der Rechtssache C-807/21 („Deutsche Wohnen“) erstmals Gelegenheit, sich zur Frage der Bußgeldhaftung zu positionieren.
Seit Ende 2022 prägt das Schlagwort „Künstliche Intelligenz“ (KI) nicht nur den rechtswissenschaftlichen Diskurs. Die allgemeine Verfügbarkeit von generativen KI-Modellen, allen voran die großen Sprachmodelle (Large Language Models, kurz: LLM) wie ChatGPT von OpenAI oder Bing AI von Microsoft, erfreuen sich größter Beliebtheit: LLM sind in der Lage, auf Grundlage statistischer Methoden – eine entsprechende Schnittstelle (Interface) vorausgesetzt – auch technisch wenig versierten Nutzern verständliche Antworten auf ihre Fragen zu liefern. Dabei werden nicht nur umfassend Nutzerdaten verarbeitet, sondern auch auf weitere personenbezogene Daten zugegriffen sowie neue Daten erzeugt. Der Beitrag geht der Frage nach, welche spezifischen datenschutzrechtlichen Herausforderungen sich für Unternehmen beim Einsatz solcher LLM stellen.
Das Thema Datenschutz wurde bei der öffentlichen Auftragsvergabe bislang vor allem in Bezug auf Drittlandtransfers personenbezogener Daten in die USA diskutiert. Jedoch spielt der Datenschutz für das Vergabeverfahren und für die Ausführung datenschutzrelevanter Leistungen generell eine wesentliche Rolle. Gleichwohl herrschen bislang unter öffentlichen Auftraggebern Schwierigkeiten, datenschutzrechtlich relevante Fallkonstellationen zu erkennen, die möglichen Risiken daraus abzuleiten und, sofern dies gelingt, diesen Risiken angemessen zu begegnen. Der vorliegende Beitrag befasst sich mit der datenschutzrechtlichen Verantwortlichkeit, ihren Folgen und den daraus resultierenden Konsequenzen für die Gestaltung von Vergabeverfahren und Vergabeunterlagen.
In this work, we present a compact, bifunctional chip-based sensor setup that measures the temperature and electrical conductivity of water samples, including specimens from rivers and channels, aquaculture, and the Atlantic Ocean. For conductivity measurements, we utilize the impedance amplitude recorded via interdigitated electrode structures at a single triggering frequency. The results are well in line with data obtained using a calibrated reference instrument. The new setup holds for conductivity values spanning almost two orders of magnitude (river versus ocean water) without the need for equivalent circuit modelling. Temperature measurements were performed in four-point geometry with an on-chip platinum RTD (resistance temperature detector) in the temperature range between 2 °C and 40 °C, showing no hysteresis effects between warming and cooling cycles. Although the meander was not shielded against the liquid, the temperature calibration provided equivalent results to low conductive Milli-Q and highly conductive ocean water. The sensor is therefore suitable for inline and online monitoring purposes in recirculating aquaculture systems.
Magnetic Resonance Imaging (MRI) of moving organs requires synchronization with physiological motion or flow, which dictate the viable window for data acquisition. To meet this challenge, this study proposes an acoustic gating device (ACG) that employs acquisition and processing of acoustic signals for synchronization while providing MRI compatibility, immunity to interferences with electro-magnetic and acoustic fields and suitability for MRI at high magnetic field strengths. The applicability and robustness of the acoustic gating approach is examined in a pilot study, where it substitutes conventional ECG-gating for cardiovascular MR. The merits and limitations of the ACG approach are discussed. Implications for MR imaging in the presence of physiological motion are considered including synchronization with other structure- or motion borne sounds.