Anderes
Permanent URI for this collection
Browse
Browsing Anderes by Title
-
Publication21Staatskunst. Folge 17 - Ralf Lindner( 2023)
-
Publication25 Jahre duale Ausbildung in der GMD. Video(GMD Forschungszentrum Informationstechnik, 2000)
-
Publication2nd Common Symposium of FP6 Ecobuildings Projects, 7-8 April 2008, Stuttgart, Germany( 2008)The programme and the highlights of the presentations, posters and round table discussions at the 2nd Common Ecobuildings Symposium held in Stuttgart at the beginning of April 2008, are summarised in this information paper.
-
Publication360° gestreamt - Ein Rundum-Fernseherlebnis( 2019)Im Zeitalter der digitalen Medien kommen Videos und Livestreams eine immer größere Bedeutung zu. Immer gefragter sind auch 360°-Videos, die dank verschiedener Blickwinkel ein immersives Videoerlebnis ermöglichen. Doch ausgerechnet auf dem Heim-TV bereitete das Streaming solcher Videos bisher Probleme, da hierfür eine hohe Bandbreite sowie eine enorme Verarbeitungs- und Grafikleistung benötigt wird. Das Fraunhofer Institut für Offene Kommunikationssysteme FOKUS hat eine Technologie entwickelt, die das Abspielen von 360°-Videos auf allen internetfähigen Video-Wiedergabe-Geräten möglich macht.
-
Publication3d imaging and analysis of cracks in loaded concrete samples( 2023)Concrete plays a central role as the standard building material in civil engineering. Experimental characterization of the concrete microstructure and a description of failure mechanisms are important to understand the concrete’s mechanical properties. Computed tomography is a powerful source of information as it yields 3d images of concrete specimens. However, complete visual inspection is often infeasible due to very large image sizes. Hence, automatic methods for crack detection and segmentation are needed. A region-growing algorithm and a 3d U-Net showed promising results in a previous study. Cracks in normal concrete and high-performance concrete that were initiated via tensile tests were investigated. Here, the methods are validated on a more diverse set of concrete types and crack characteristics. Adequate adaptions of the methods are necessary to deal with the complex crack structures. The segmentation results are assessed qualitatively and compared to those of a template matching algorithm which is well-established in industry.
-
Publication500 GHz plasmonic Mach-Zehnder modulator enabling sub-THz microwave photonics( 2018)Broadband electro-optic intensity modulators are essential to convert electrical signals to the optical domain. The growing interest in THz wireless applications demands modulators with frequency responses to the sub-THz range, high power handling and very low nonlinear distortions, simultaneously. However, a modulator with all those characteristics has not been demonstrated to date. Here we experimentally demonstrate that plasmonic modulators do not trade off any performance parameter, featuring - at the same time - a short length of 10s of micrometers, record-high flatfrequency response beyond 500 GHz, high power handling and high linearity, and we use them to create a sub-THz radio-over-fiber analog optical link. These devices have the potential to become a new tool in the general field of microwave photonics, making the sub-THz range accessible to e.g. 5G wireless communications, antenna remoting, IoT, sensing, and more.
-
Publication5G-Industry Campus Europe - Forschungsnetz für 5G in der Produktion( 2022)
-
PublicationA causal model of safety assurance for machine learning( 2022)This paper proposes a framework based on a causal model of safety upon which e ective safety assurance cases for ML-based applications can be developed. In doing so, we build upon established principles of safety engineering as well as previous work on structuring assurance arguments for ML. The paper de nes four categories of safety case evidence and a structured analysis approach within which these evidences can be e ectively combined. Where appropriate, abstract formalisations of these contributions are used to illustrate the causalities they evaluate, their contributions to the safety argument and desirable properties of the evidences. Based on the proposed framework, progress in this area is re-evaluated and a set of future research directions proposed in order for tangible progress in this eld to be made.
-
PublicationA Comparison of Methods for Player Clustering via Behavioral Telemetry( 2014)The analysis of user behavior in digital games has been aided by the introduction of user telemetry in game development, which provides unprecedented access to quantitative data on user behavior from the installed game clients of the entire population of players. Player behavior telemetry datasets can be exceptionally complex, with features recorded for a varying population of users over a temporal segment that can reach years in duration. Categorization of behaviors, whether through descriptive methods (e.g. segmention) or unsupervised/supervised learning techniques, is valuable for finding patterns in the behavioral data, and developing profiles that are actionable to game developers. There are numerous methods for unsupervised clustering of user behavior, e.g. k-means/c-means, Non-negative Matrix Factorization, or Principal Component Analysis. Although all yield behavior categorizations, interpretation of the resulting categories in terms of actual play behavior can be difficult if not impossible. In this paper, a range of unsupervised techniques are applied together with Archetypal Analysis to develop behavioral clusters from playtime data of 70,014 World of Warcraft players, covering a five year interval. The techniques are evaluated with respect to their ability to develop actionable behavioral profiles from the dataset.
-
PublicationA Digitization Pipeline for Mixed-Typed Documents Using Machine Learning and Optical Character Recognition( 2022)
-
PublicationA Dimension-adaptive Combination Technique for Uncertainty Quantification( 2022-04-12)We present an adaptive algorithm for the computation of quantities of interest involving the solution of a stochastic elliptic PDE where the diffusion coefficient is parametrized by means of a Karhunen-Loève expansion. The approximation of the equivalent parametric problem requires a restriction of the countably infinite-dimensional parameter space to a finite-dimensional parameter set, a spatial discretization and an approximation in the parametric variables. We consider a sparse grid approach between these approximation directions in order to reduce the computational effort and propose a dimension-adaptive combination technique. In addition, a sparse grid quadrature for the high-dimensional parametric approximation is employed and simultaneously balanced with the spatial and stochastic approximation. Our adaptive algorithm constructs a sparse grid approximation based on the benefit-cost ratio such that the regularity and thus the decay of the Karhunen-Loève coefficients is not required beforehand. The decay is detected and exploited as the algorithm adjusts to the anisotropy in the parametric variables. We include numerical examples for the Darcy problem with a lognormal permeability field, which illustrate a good performance of the algorithm: For sufficiently smooth random fields, we essentially recover the rate of the spatial discretization as asymptotic convergence rate with respect to the computational cost.
-
PublicationA fluorescent nanosensor paint reveals the heterogeneity of dopamine release from neurons at individual release sites( 2021)The neurotransmitter dopamine is released from discrete axonal structures called varicosities. Its release is essential in behaviour and is critically implicated in prevalent neuropsychiatric diseases. Existing dopamine detection methods are not able to detect and distinguish discrete dopamine release events from multiple varicosities. This prevents an understanding of how dopamine release is regulated across populations of discrete varicosities. Using a near infrared fluorescent (980 nm) dopamine nanosensor 'paint' (AndromeDA), we show that action potential-evoked dopamine release is highly heterogeneous across release sites and also requires molecular priming. Using AndromeDA, we visualize dopamine release at up to 100 dopaminergic varicosities simultaneously within a single imaging field with high temporal resolution (15 images/s). We find that 'hotspots' of dopamine release are highly heterogeneous and are detected at only ~17% of all varicosities. In neurons lacking Munc13 proteins, which prime synaptic vesicles, dopamine release is abolished during electrical stimulation, demonstrating that dopamine release requires vesicle priming. In summary, AndromeDA reveals the spatiotemporal organization of dopamine release.
-
PublicationA local input-to-state stability result w.r.t. attractors of nonlinear reaction-diffusion equations( 2019)We establish the local input-to-state stability of a large class of disturbed nonlinear reaction-diffusion equations w.r.t. the global attractor of the respective undisturbed system.
-
PublicationA neural code for egocentric spatial maps in the human medial temporal lobe( 2020)Spatial navigation relies on neural systems that encode spatial information relative to the external world or relative to the navigating organism. Ever since the proposal of cognitive maps, the neuroscience of spatial navigation has focused on allocentric (world-referenced) representations such as place cells. Here, using single-neuron recordings during virtual navigation, we reveal a neural code for egocentric (self-centered) spatial information in humans: ""anchor cells"" represent egocentric directions towards proximal ""anchor points"" located in the environmental center or periphery. Anchor cells were abundant in parahippocampal cortex, supported full vectorial representations of egocentric space, and were integrated into a neural memory network. Anchor cells may thus facilitate egocentric navigation strategies, assist in transforming percepts into allocentric spatial representations, and may underlie the first-person perspective in episodic memories.
-
PublicationA novel method for functional testing of ankle braces based on a modified prosthetic foot testing machine( 2022)The aim of this study is to investigate the feasibility of a new dynamic testing method for ankle braces, to quantify the mechanical stability of different orthotic designs. A mechanical, artificial foot model has been designed, considering the anatomy and biomechanics of the human foot. Sensors were built into the ankle joint, based on medical and technical principles. Together with an actuator, they were used as a test bench for validating ankle braces. For a first feasibility study, the influence of five different types of ankle orthoses for selected movement sequences was investigated.
-
PublicationA Ray Tracing Technique for the Navigation on a Non-convex Pareto Front( 2020)A new interactive approach to navigate on approximations of in general non-convex but connected Pareto fronts is introduced. Given a finite number of precalculated representative Pareto-efficient solutions, an adapted Delaunay triangulation is generated. Based on interpolation and ray tracing techniques, real time navigation in the vicinity of Pareto-optimal solutions is made possible.
-
PublicationA Systematic and Automated Design Flow Approach for Robust Analog/Mixed-Signal Chips( 2021)
-
PublicationA vehicle for energy-efficient lighting: EN15193: Energy performance of buildings - energy lighting requirements( 2008)This information paper presents the general approach that should be used to determine lighting energy consumption within prEN 15193-1 Energy performance of buildings - Energy requirements for lighting - Part 1:Lighting energy estimation.
-
-
PublicationAccelerating Deep Tech Innovations( 2023-01-09)Systemic innovation success in Europe lags behind its expectations as Europe spends most funding in basic research and development (R&D) while commercialization takes place in other regions such as the US or China. Therefore, this whitepaper aims to enhance the technology transfer for Deep Tech innovations in Europe through developing a framework for actors in Deep Tech ecosystems based on a case study analysis. For this, 25 actors from science and industry in three Deep Tech areas are analyzed – lithium-ion battery cells, semiconductors and electrolyzers. Based on a cross-industrial synthesis, recommendations for actions are derived building on the individual actors’ strengths and weaknesses. As Deep Tech is considered a disruptive technology with a high degree of uncertainty regarding its actual feasibility, investments in such technologies are associated with high risks but great economic and societal opportunities. To benefit from such high-risk investments, it is mandatory that sufficient support is provided from research all the way to commercialization. This technology transfer includes both public funding of fundamental research and private funding for scaling and commercializing innovations. In addition to insufficient risk capital in basic research, however, a lack of consistent funding on the path from research to commercialization can be observed in Europe. This gap phenomenon between public and private funding is often referred to as the Valley of Death. To foster the technology transfer for Deep Tech innovations, three needs for action are derived from the analyzed case studies: First, collaboration between actors should be strengthened to deliver Deep Tech innovations more effectively. Furthermore, a sufficient environment needs to be created in which the individual actors’ strengths complement each other optimally. Finally, protection spaces for intellectual property must be created to avoid legal disputes from the outset. By following these recommendations and taking the individual profiles of actors into account, the Valley of Death can be minimized.
