Fraunhofer-Publica
The Fraunhofer-Publica has been successfully documenting the research results of the Fraunhofer-Gesellschaft for over 30 years. The platform enables the collaborative linking of research-relevant objects and disseminates within the international scientific community.
The Fraunhofer-Publica thus fulfils its responsibility to promote the transfer of knowledge and know-how to industry and society.
Categories
Research outputs
As an application-oriented research organisation, Fraunhofer aims to conduct highly innovative and solution-oriented research - for the benefit of society and to strengthen the German and European economy.
Projects
Fraunhofer is tackling the current challenges facing industry head on. By pooling their expertise and involving industrial partners at an early stage, the Fraunhofer Institutes involved in the projects aim to turn original scientific ideas into marketable products as quickly as possible.
Researchers
Scientific achievement and practical relevance are not opposites - at Fraunhofer they are mutually dependent. Thanks to the close organisational links between Fraunhofer Institutes and universities, science at Fraunhofer is conducted at an internationally first-class level.
Institutes
The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Institutes and research facilities work under its umbrella at various locations throughout Germany.
Recent Additions
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PublicationA Coud-based Data Processing and Visualization Pipeline for the Fibre Roll-out in Germany( 2024)To support the roll-out of fibre broadband Internet in Germany, Deutsche Telekom has set itself the goal of connecting more than 2.5 million households per year to FTTH (Fibre to the Home). However, planning and approval processes have been very complex and time-consuming in the past due to high communication overhead between stakeholders, missing automation, and lack of information about planning areas. Telekom addresses this problem by collecting large amounts of geospatial data (3D point clouds and 360◦ panorama images), which can be used to automatically find suitable routes for fibre optic lines, to determine possible locations for distribution cabinets, as well as to build a 3D visualization helping to create detailed plans and to present them to decision makers. This speeds up planning tremendously, but processing this data and creating the visualization in a short time requires automation. In this systems paper, we present a data processing platform that we have built and operated together with Telekom over the course of the last six and a half years. The platform makes use of the cloud to manage Big Data in a scalable and elastic manner. It builds upon research results from us, specifically a scientific workflow management system to automate processing, as well as Fibre3D, a web-based tool that planners can use to display the processed data and to perform fine-planning. Besides the technological aspects, this paper also describes a practical use case that shows how the platform and Fibre3D help Telekom speed up the planning and approval process. We also summarize lessons learned and give recommendations for the design of systems similar to ours. With the presented technology, Telekom has been able to already connect more than 8 million households to FTTH and expects to even improve on this in the future. We consider our collaboration, therefore, an example of how well knowledge and technology transfer between research and industry can work, and, at the same time, what impact it can have on society.
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PublicationExplaining Face Recognition Through SHAP-Based Pixel-Level Face Image Quality Assessment( 2023)Biometric face recognition models are widely used in many different real-world applications. The output of these models can be used to make decisions that may strongly impact people. However, an explanation of how and why such outputs are derived is usually not given to humans. The lack of explainability of face recognition models leads to distrust in their decisions and does not encourage their use. The performance of face recognition models is influenced by the quality of the input image. In case the quality of a face image is too low, the face recognition system will reject it to avoid compromising its performance. The quality is evaluated by Face Image Quality (FIQ) approaches, which assigned quality scores to the input images. Pixel-level face image quality (PLFIQ) increases the explainability of quality scores by explaining face image quality at the pixel level. This allows the users of face recognition systems to spot low-quality areas and allows them to make guided corrections. Previous works introduced the concept of PLFIQ and proposed evaluation procedures. This work proposes a new way of computing PLFIQ values depending on given FIQ methods using Shapley Values. They score the contribution of each pixel to the overall image quality evaluation. Therefore, Integrating Shapley Values increases the explainability of the FIQ models. Results show that using these methods leads to significantly better and more robust PLFIQ values estimates and thus provide better explainability.
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PublicationErfolgsrezepte( 2024)Dieses Whitepaper wurde durch das Bayerische Staatsministerium für Wirtschaft, Landesentwicklung und Energie im Rahmen des "Fraunhofer Blockchain Center (20-3066-2-6-14)" gefördert. Wir danken an dieser Stelle für die Unterstützung.
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PublicationEvaluating the reliability of environmental concentration data to characterize exposure in environmental risk assessments( 2024-02-02)Environmental risk assessments often rely on measured concentrations in environmental matrices to characterize exposure of the population of interest—typically, humans, aquatic biota, or other wildlife. Yet, there is limited guidance available on how to report and evaluate exposure datasets for reliability and relevance, despite their importance to regulatory decision‐making. This paper is the second of a four‐paper series detailing the outcomes of a Society of Environmental Toxicology and Chemistry Technical Workshop that has developed Criteria for Reporting and Evaluating Exposure Datasets (CREED). It presents specific criteria to systematically evaluate the reliability of environmental exposure datasets. These criteria can help risk assessors understand and characterize uncertainties when existing data are used in various types of assessments and can serve as guidance on best practice for the reporting of data for data generators (to maximize utility of their datasets). Although most reliability criteria are universal, some practices may need to be evaluated considering the purpose of the assessment. Reliability refers to the inherent quality of the dataset and evaluation criteria address the identification of analytes, study sites, environmental matrices, sampling dates, sample collection methods, analytical method performance, data handling or aggregation, treatment of censored data, and generation of summary statistics. Each criterion is evaluated as “fully met,” “partly met,” “not met or inappropriate,” “not reported,” or “not applicable” for the dataset being reviewed. The evaluation concludes with a scheme for scoring the dataset as reliable with or without restrictions, not reliable, or not assignable, and is demonstrated with three case studies representing both organic and inorganic constituents, and different study designs and assessment purposes. Reliability evaluation can be used in conjunction with relevance evaluation (assessed separately) to determine the extent to which environmental monitoring datasets are “fit for purpose,” that is, suitable for use in various types of assessments.
Most viewed
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PublicationDirecting nitrogen-doped carbon support chemistry for improved aqueous phase hydrogenation catalysis( 2020)Selective hydrogenations in the aqueous phase are an important transformation in the context of developing biorefinery concepts. In this report the application and optimisation of nitrogen-doped carbon (NDC) supported Pd nanoparticles as hydrogenation catalysts is discussed in the context of directing support (e.g. N) chemistry for improved catalytic performance in the aqueous phase. As a demonstrative example, the aqueous phase hydrogenation of phenol to cyclohexanone (e.g. a platform for polyamide production) is utilised. Catalyst supports were prepared based on an initial hydrothermal synthesis to yield NDC xerogels (from biomass precursors), the chemistry of which (e.g. functionality) was directed using a secondary thermal carbonisation (Tc) step at different temperatures (i.e. 350, 550, 750, 900 and 1000 °C). After Pd introduction, it was found that size, dispersion and electronic structure of the formed nanoparticles is affected by the surface chemistry of the NDC. This consequently led to higher turn-over frequency (TOF) and stability of the prepared catalysts compared to a ""nitrogen-free"" carbon supported Pd and a commercial, carbon supported Pd (Pd/AC) catalyst. Pd/NDC 900 (featuring predominantly quaternary and pyridinic N) catalysed the complete conversion of phenol at 99% selectivity to cyclohexanone, with excellent stability over 11 recycles and no discernible catalyst sintering or leaching (in contrast to the commercial catalyst). High catalytic stability, activity and selectivity make the Pd/NDC 900 catalyst highly applicable for aqueous phase hydrogenation reactions, whilst the general principle opens scope for support tailoring for application (e.g. biorefinery hydrogenations) and the development of structure/activity relationships.
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PublicationMeasurement of Local Recombination Activity in High Diffusion Length Semiconductors( 2023)We present a conceptual approach for the localisation and characterisation of local sites of recombination in high diffusion length semiconductors under photovoltaic field conditions. While established imaging techniques operate in this very regime of uniform "1 sun" illumination, inevitable lateral diffusion of charge carriers veils the origin and severity of localised recombination sites. To reduce this limitation due to lateral diffusion the natural choice is using focussed charge carrier excitation and detection in combination with scanning the specimen. The resulting photoluminescence intensity maps are of high spatial resolution and may be composed of a superposition of a multitude of recombination active defects influencing each other due to the high bulk diffusion length. We demonstrate the feasibility of a self-consistent calibration of the setup quantum efficiency in such experimental condition which delivers a charge carrier density map in absolute units. A solution is presented to disentangle the superposition of local sites of recombination to isolate the actual recombination activity of every site. We demonstrate the feasibility of the approach experimentally on the high diffusion length semiconductor silicon.