Efficient Acoustic Echo Suppression with Condition-Aware Training

The topic of deep acoustic echo control (DAEC) has seen many approaches with various model topologies in recent years. Convolutional recurrent networks (CRNs), consisting of a convolutional encoder and decoder encompassing a recurrent bottleneck, are repeatedly employed due to their ability to preserve nearend speech even in double-talk (DT) condition. However, past architectures are either computationally complex or trade off smaller model sizes with a decrease in performance. We propose an improved CRN topology which, compared to other realizations of this class of architectures, not only saves parameters and computational complexity, but also shows improved performance in DT, outperforming both baseline architectures FCRN and CRUSE. Striving for a condition-aware training, we also demonstrate the importance of a high proportion of double-talk and the missing value of nearend-only speech in DAEC training data. Finally, we show how to control the trade-off between aggressive echo suppression and near-end speech preservation by fine-tuning with condition-aware component loss functions.Comment: 5 pages, accepted to WASPAA 202

Immersed boundary parametrizations for full waveform inversion

Full Waveform Inversion (FWI) is a successful and well-established inverse method for reconstructing material models from measured wave signals. In the field of seismic exploration, FWI has proven particularly successful in the reconstruction of smoothly varying material deviations. In contrast, non-destructive testing (NDT) often requires the detection and specification of sharp defects in a specimen. If the contrast between materials is low, FWI can be successfully applied to these problems as well. However, so far the method is not fully suitable to image defects such as voids, which are characterized by a high contrast in the material parameters. In this paper, we introduce a dimensionless scaling function $\gamma$ to model voids in the forward and inverse scalar wave equation problem. Depending on which material parameters this function $\gamma$ scales, different modeling approaches are presented, leading to three formulations of mono-parameter FWI and one formulation of two-parameter FWI. The resulting problems are solved by first-order optimization, where the gradient is computed by an ajdoint state method. The corresponding Fr\'echet kernels are derived for each approach and the associated minimization is performed using an L-BFGS algorithm. A comparison between the different approaches shows that scaling the density with $\gamma$ is most promising for parameterizing voids in the forward and inverse problem. Finally, in order to consider arbitrary complex geometries known a priori, this approach is combined with an immersed boundary method, the finite cell method (FCM).Comment: 23 pages, 21 figure

Isogeometric Multi-Resolution Full Waveform Inversion based on the Finite Cell Method

Full waveform inversion (FWI) is an iterative identification process that serves to minimize the misfit of model-based simulated and experimentally measured wave field data, with the goal of identifying a field of parameters for a given physical object. The inverse optimization process of FWI is based on forward and backward solutions of the (elastic or acoustic) eave equation. In a previous paper [1], we explored opportunities of using the finite cell method (FCM) as the wave field solver to incorporate highly complex geometric models. Furthermore, we demonstrated that the identification of the model's density outperforms that of the velocity -- particularly in cases where unknown voids characterized by homogeneous Neumann boundary conditions need to be detected. The paper at hand extends this previous study: The isogeometric finite cell analysis (IGA-FCM) -- a combination of isogeometric analysis (IGA) and FCM -- is applied for the wave field solver, with the advantage that the polynomial degree and subsequently also the sampling frequency of the wave field can be increased quite easily. Since the inversion efficiency strongly depends on the accuracy of the forward and backward wave field solution and of the gradient of the functional, consistent and lumped mass matrix discretization are compared. The resolution of the grid describing the unknown material density is the decouple from the knot span grid. Finally, we propose an adaptive multi-resolution algorithm that refines the material grid only locally using an image processing-based refinement indicator. The developed inversion framework allows fast and memory-efficient wave simulation and object identification. While we study the general behavior of the proposed approach on 2D benchmark problems, a final 3D problem shows that it can also be used to identify voids in geometrically complex spatial structures.Comment: 19 pages, 14 figure

Decreasing initial telomere length in humans intergenerationally understates age-associated telomere shortening

Telomere length shortens with aging, and short telomeres have been linked to a wide variety of pathologies. Previous studies suggested a discrepancy in age-associated telomere shortening rate estimated by cross-sectional studies versus the rate measured in longitudinal studies, indicating a potential bias in cross-sectional estimates. Intergenerational changes in initial telomere length, such as that predicted by the previously described effect of a father's age at birth of his offspring (FAB), could explain the discrepancy in shortening rate measurements. We evaluated whether changes occur in initial telomere length over multiple generations in three large datasets and identified paternal birth year (PBY) as a variable that reconciles the difference between longitudinal and cross-sectional measurements. We also clarify the association between FAB and offspring telomere length, demonstrating that this effect is substantially larger than reported in the past. These results indicate the presence of a downward secular trend in telomere length at birth over generational time with potential public health implications

Cybersecurity in Power Grids: Challenges and Opportunities

Increasing volatilities within power transmission and distribution force power grid operators to amplify their use of communication infrastructure to monitor and control their grid. The resulting increase in communication creates a larger attack surface for malicious actors. Indeed, cyber attacks on power grids have already succeeded in causing temporary, large-scale blackouts in the recent past. In this paper, we analyze the communication infrastructure of power grids to derive resulting fundamental challenges of power grids with respect to cybersecurity. Based on these challenges, we identify a broad set of resulting attack vectors and attack scenarios that threaten the security of power grids. To address these challenges, we propose to rely on a defense-in-depth strategy, which encompasses measures for (i) device and application security, (ii) network security, and (iii) physical security, as well as (iv) policies, procedures, and awareness. For each of these categories, we distill and discuss a comprehensive set of state-of-the art approaches, as well as identify further opportunities to strengthen cybersecurity in interconnected power grids

Implicit-Explicit Time Integration for the Immersed Wave Equation

Immersed boundary methods simplify mesh generation by embedding the domain of interest into an extended domain that is easy to mesh, introducing the challenge of dealing with cells that intersect the domain boundary. Combined with explicit time integration schemes, the finite cell method introduces a lower bound for the critical time step size. Explicit transient analyses commonly use the spectral element method due to its natural way of obtaining diagonal mass matrices through nodal lumping. Its combination with the finite cell method is called the spectral cell method. Unfortunately, a direct application of nodal lumping in the spectral cell method is impossible due to the special quadrature necessary to treat the discontinuous integrand inside the cut cells. We analyze an implicit-explicit (IMEX) time integration method to exploit the advantages of the nodal lumping scheme for uncut cells on one side and the unconditional stability of implicit time integration schemes for cut cells on the other. In this hybrid, immersed Newmark IMEX approach, we use explicit second-order central differences to integrate the uncut degrees of freedom that lead to a diagonal block in the mass matrix and an implicit trapezoidal Newmark method to integrate the remaining degrees of freedom (those supported by at least one cut cell). The immersed Newmark IMEX approach preserves the high-order convergence rates and the geometric flexibility of the finite cell method. We analyze a simple system of spring-coupled masses to highlight some of the essential characteristics of Newmark IMEX time integration. We then solve the scalar wave equation on two- and three-dimensional examples with significant geometric complexity to show that our approach is more efficient than state-of-the-art time integration schemes when comparing accuracy and runtime

Crowdsourcing the State of the Art(ifacts)

In any field, finding the "leading edge" of research is an on-going challenge. Researchers cannot appease reviewers and educators cannot teach to the leading edge of their field if no one agrees on what is the state-of-the-art. Using a novel crowdsourced "reuse graph" approach, we propose here a new method to learn this state-of-the-art. Our reuse graphs are less effort to build and verify than other community monitoring methods (e.g. artifact tracks or citation-based searches). Based on a study of 170 papers from software engineering (SE) conferences in 2020, we have found over 1,600 instances of reuse; i.e., reuse is rampant in SE research. Prior pessimism about a lack of reuse in SE research may have been a result of using the wrong methods to measure the wrong things.Comment: Submitted to Communications AC

Balancing heat saving and supply in local energy planning: Insights from 1970-1989 buildings in three European countries

This study investigates the cost balance between heat energy savings through building envelope retrofits and supply from low-carbon decentralised and centralised technologies in a generic urban district, composed of residential and non-residential buildings from the 1970–1989 construction period. For generalisability, the district is analysed in three European countries (Bulgaria, Germany, Finland), each with distinct weather conditions and price levels. Using bottom-up energy modelling and adopting a societal perspective that includes external costs, the study finds the cost-effectiveness of retrofits to be context-specific. In Bulgaria, retrofits prove largely cost-effective, whereas in Germany and Finland, high labour and material costs pose challenges. Heat pumps, whether decentralised in buildings or centralised in district heating systems, emerge as key options for heat supply, even in cold climates. The study underscores the importance of integrated energy planning in line with the ‘energy efficiency first’ principle and corresponding incentive structures to promote sustainable urban energy systems

Implementation of a mixed-reality flight simulator: blending real and virtual with a video-see-through head-mounted display

Conventional flight simulators usually include a complex and expensive outside vision projection system. Especially scenarios where the helicopter pilots look far to the side or through the windows near the pedals require a large projection dome to provide an image of the outside world. Additionally, simulators used for research need to be highly customizable: For rapid prototyping of new flight deck designs, the cockpit mockup must be adaptable enough to change the appearance and arrangement of its elements. The recent technological advancements of head-mounted displays (HMDs) offer many new ways to create a simulator that fulfills the stated requirements at moderate cost. A non-see-through HMD can immerse the pilots into a computer-generated cockpit with "unrestricted" virtual out-the-window view. The downwards view is even better than with dome projections. Such a fully virtual approach, however, requires complex finger-tracking and haptic feedback solutions to enable the user to interact with the cockpit. By contrast, a video-see-through HMD allows us to selectively combine a highly customizable virtual world with a video-stream of the real surroundings. One can, for instance, show the pilot's hands and relevant parts of the physical flight deck mockup, enriched with virtual elements and virtual out-the-window view. In such a mixed setup, the pilots can naturally and directly interact with conventional input devices in an otherwise virtual environment. The paper presents our implementation of a mixed reality simulator with the Varjo XR-3 video-see-through HMD. We assess different variants, discuss implementation details like real-to-virtual-world-alignment, and explain the major challenges of such setups