IWES Fraunhofer-Institut für Windenergiesysteme
6. Energieforschungsprogramm „Forschung für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung“
Beschleunigte Dauerprüfung von Blattlagern für Multi-Megawatt-Turbinen
Bundesministerium fur Wirtschaft und Energie BMWi (Deutschland)
This dataset contains the bearing load distributions of different load cases of a third rotor star FE-model of the IWES Wind Turbine 7.5, which is a 7.5 MW nearshore turbine model. Using combinations of the resulting blade moment, the angle of said moment, and the pitch angle of the blade, a total of 260 simulations were FE simulated. These simulations were performed for the publication "Fatigue lifetime calculation of wind turbine blade bearings considering blade-dependent load distribution" in the Wind Energy Science Journal.
FE-simulated bearing load distributions for different load cases of the IWT7.5 turbine
IFF Fraunhofer-Institut für Fabrikbetrieb und -automatisierung
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Staatskanzlei und Ministerium für Kultur des Landes Sachsen-Anhalt
The dataset contains albedo and normal image and a 3D triangle mesh with additional features (multi scale integral invariants) for the obverse of medieval coins. There are three different types of coins. Within each typ there are many samples of various state of conservation. Numismatists can recognize similarities between samples of one type and differences between samples of different type. We are interested in the development of computer methods, which can measure such similarities and differences based on these digital representations of the coins.
Images and 3D triangle meshes generated with a single-camera, multi-light setup (photometric stereo)
Medieval coins of three different types and of various states of preservation
IIS Fraunhofer-Institut für Integrierte Schaltungen
Bundesministerium für Wirtschaft und Klimaschutz BMWK (Deutschland)
The Semantic textual similarity (STS) task is commonly used to evaluate the semantic representations that language models (LMs) learn from texts, under the assumption that good-quality representations will yield accurate similarity estimates. When it comes to estimating the similarity of two utterances in a dialogue, however, the conversational context plays a particularly important role. We argue for the need of benchmarks specifically created using conversational data in order to evaluate conversational LMs in the STS task. We introduce GiCCS, a first conversational STS evaluation benchmark for German. We collected the similarity annotations for GiCCS using best-worst scaling and presenting the target items in context, in order to obtain highly-reliable context-dependent similarity scores. We present benchmarking experiments for evaluating LMs on capturing the similarity of utterances. Results suggest that pretraining LMs on conversational data and providing conversational context can be useful for capturing similarity of utterances in dialogues. GiCCS will be publicly available to encourage benchmarking of conversational LMs.
GiCCS: A German in-Context Conversational Similarity Benchmark
IGP Fraunhofer-Einrichtung für Großstrukturen in der Produktionstechnik
Ein aminvernetztes Epoxidharz (EP) wird Wasser bei 100, 150, 200 und 250 °C ausgesetzt, wobei alle Temperaturen über der Glasübergangstemperatur (Tg) des Polymers liegen. Aufgrund der verringerten Dichte und Viskosität der flüssigen Phase bei diesen Temperaturen und des gummiartigen Zustands des EP ist es möglich, in weniger als drei Stunden eine Wasseraufnahme von mehr als 10 % zu erreichen. Die Ergebnisse von dynamisch-mechanischen Analysen und Zugversuchen bestätigen die erwartete Tg-Abnahme und die Verringerung der Zugfestigkeit und des Moduls mit steigender Alterungstemperatur bzw. Wasseraufnahme.
Influence of accelerated hydrothermal aging on physical and mechanical properties of an amine-cured epoxy resin
ISI Fraunhofer-Institut für System- und Innovationsforschung
Joining Efforts for Responsible Research and Innovation
The data has been generated by Fraunhofer ISI and TNO by carrying out and recording expert interviews about existing RRI practices and ways to further institutionalize RRI at both organisations.
IWM Fraunhofer-Institut für Werkstoffmechanik
Bruchflächenaufnahmen von Metallen gelabelt nach "interkristallin" und "Sprödbruch". Die Bilddaten stammen von unterschiedlichen Proben.
Mit dem Rasterelektronenmikroskop (REM) erzeugte Aufnahmen von Bruchflächen von Metallen für eine spätere statistische Auswertung
Fracture surfaces of metals acquired with the SEM
Gewichtsreduzierung in Leichtbaustrukturen dynamisch belasteter Systeme durch neue energie-dissipative Elemente
The information on how the data was obtained is explained in the Paper "Potential of friction to damp vibrations in the use case of a car tailgate" by Marion Kugler, Frank Koschnick, David Marx, Dennis Weber, Martin Dienwiebel.
Daten zur Dämpfung im Stahl-Aluminium-Kontakt unter vibrierender Belastung für die Nutzung in einer Heckklappe
Data about the damping in a steel-aluminium-contact under vibrating load for the use in a cars tailgate
UMSICHT Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik
Es handelt sich um Hintergrunddaten zu einer Studie. Der Datensatz enthält eine Beschreibung sowie ein umfassendes Tabellenblatt zu verwendeten Ökobilanzdaten und -ergebnissen.
Zwei Varianten der Instandsetzung im ökologischen Wettbewerb
Reparatur vs. Austausch bei Unfallschäden an Pkw
IPK Institut für Produktionsanlagen und Konstruktionstechnik
Sensorische Erfassung, automatisierte Identifikation und Bewertung von Altteilen
We present MVIP, a novel dataset for multi-modal and multi-view application oriented industrial part recognition. Here we combine a calibrated RGBD multi-view dataset with additional object context such as physical properties, natural language, and super-classes. Our main goal with MVIP is to study and push transferability of various state-of-the-art methods within related downstream tasks towards an efficient deployment of industrial classifiers. Additionally, we intent to push with MVIP research regarding several modality fusion topics, (automated) synthetic data generation, and complex data sampling methods -- combined in a single application oriented benchmark.
MVIP: A Dataset for Industrial Part Recognition
IPA Fraunhofer-Institut für Produktionstechnik und Automatisierung
The interview guide and online questionnaire were used in an exploratory sequential mixed-methods design. The aim of the study was to investigate the cost estimation of products in the early phases of product development in mechanical engineering, as well as practitioners’ expectations of cost estimation assisted by artificial intelligence (AI).
Supplementary Material: Interview Online Questionnaire - Why cost estimation matters for design decisions in the early phases of product development and what practitioners expect from artificial intelligence
Innovationswettbewerb "Künstliche Intelligenz als Treiber für volkswirtschaftlich relevante Ökosysteme"
SPEAKER - Aufbau einer führenden Sprachassistenzplattform ”Made in Germany”
The inCLINC dataset (incremental intent annotations of the CLINC dataset) contains 121 distinct utterances (queries directed to a voice assistant) in their complete form and in partial form for a total of 538 utterances, which were labeled with intent categories in a crowdsourcing study by 126 coders. The tagset consisted of 37 intent categories plus one out-of-scope category. Each utterance was annotated by 6 to 9 coders. To refer to inCLINC in any publication, please cite the following paper: Hrycyk, L., Zarcone, A., & Hahn, L. (2021). Not So Fast, Classifier – Accuracy and Entropy Reduction in Incremental Intent Classification. In Proceedings of the 3rd Workshop on NLP for Conversational AI (NLP4ConvAI 2021).
inCLINC: incremental intent annotations of the CLINC dataset
IEG Fraunhofer-Einrichtung für Energieinfrastrukturen und Geothermie
Transformation process for the municipal energy transition
The two datasets are supplement to the publication Oberle, Stella; Gnann, Till; Wayas, Louis; Wietschel, Martin "Analyzing the regulatory framework gaps for gas distribution networks with decreasing natural gas demand in Germany" (to be published): German energy system studies, investigating the energy transition pathways to the set climate targets, depict a significant decrease in gas demand. This leads to a discussion about the long-term need of gas distribution networks. The discussion intensified with the war in Ukraine and the subsequent energy price crisis. The German regulatory agency responded to these developments with adjusting the regulatory framework to the current challenges. Up to now, the depreciation period of network components varies between 45 to 65 years, and consequently the monetary capital is tied up for a long time, lowering the flexibility of network operators to react to current challenges. Therefore, the German regulatory agency allows the shortening of depreciation periods of new gas network assets. Nonetheless, it is still unclear how to deal with existing assets at risk of becoming stranded assets and how to regulate the decommissioning of gas networks. Therefore, this paper addresses the research question: “What effect do different regulations for decommissioning of gas distribution networks have on operators and users?”. To answer the question the model MERLIN is applied, which integrates the current and future regulation options into long-term investment decision analysis. The results show a need of shortening the depreciation period of existing assets to avoid stranded assets. Further, partial decommissioning with including the decommission costs in the regulatory framework and hence finance it through the network users, is the most economical attractive option for network operator and users.
Analyzing the regulatory framework gaps for gas distribution networks with decreasing natural gas demand in Germany
IPT Fraunhofer-Institut für Produktionstechnologie
Europäischer Fonds für regionale Entwicklung (EFRE)
Standardisierte und integrierte Verfahren zur personalisierten stammzellbasierten Wirkstoffprädiktion mittels reprogrammierter Blutzellen
Images of iPSCs taken in the StemCellFactory (more information about the project: Elanzew A, Nießing B, Langendoerfer D et al. (2020) The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells. Front. Bioeng. Biotechnol. 8:580352. doi: 10.3389/fbioe.2020.580352). The images show induced pluripotent stem cells at different times during their development. A Nikon Ti-Eclipse phase contrast microscope equipped with faster stage (Märzhäuser Wetzlar Scan IM 130 x 85), camera (PCO Edge 4.2) and lighting was used for all images.
Bilder von iPS, die in der StemCellFactory aufgenommen wurden (weitere Informationen über das Projekt: Elanzew A, Nießing B, Langendoerfer D et al. (2020) The StemCellFactory: A Modular System Integration for Automated Generation and Expansion of Human Induced Pluripotent Stem Cells. Front. Bioeng. Biotechnol. 8:580352. doi: 10.3389/fbioe.2020.580352). Die Bilder zeigen induzierte pluripotente Stammzellen zu verschiedenen Zeitpunkten ihrer Entwicklung. Für alle Untersuchungen wurde ein Nikon Ti-Eclipse Phasenkontrastmikroskop mit schnellerem Tisch (Märzhäuser Wetzlar Scan IM 130 x 85), Kamera (PCO Edge 4.2) und Beleuchtung verwendet.
iPSC colony, acquired with high-speed microscope
iPSC-Kolonie, aufgenommen mit High-Speed-Mikroskop
IZFP Fraunhofer-Institut für Zerstörungsfreie Prüfverfahren
This dataset provides the numerical results and optimization routines used to harmonize different Jiles–Atherton (JA) hysteresis model variants. The goal of the study was to determine whether parameter sets of one JA formulation can be transformed such that another formulation reproduces the same B(H) behaviour.
Parameter Harmonization of Jiles-Atherton model Variants
Robocasting keramischer 3D-Strukturen: Experimentelle Untersuchungen und numerische Simulation des Gefüges und der Makrostruktur
This simulation has been performed using the Herschel Bulkley rheology model, $\tau = \tau_0 + K \dot{\gamma} ^n$, with $\tau$ the resulting stress, a consistency $K$ = 2000 Pa s, a flow behavior index $n$ = 0.2, a yield stress $\tau_0$ = 500 Pa and and a stress growth exponent of 100 s that is used for the regularized scheme.
Vergleich der gedruckten Stränge im Experiment und in der Simulation
Comparison of experiment and simulation with respect to the shape of the printed filament
Demonstration der Eignung des Herschel Bulkley Models als Rheologiemodell zum Beschreiben des Robocasting Prozesses
Demonstration of the Herschel Bulkley model as useable rheology model to describe the robocasting process
Image is Part of the paper
EIPPBM_IFIPSummerSchool: Image "End-User Information Privacy Protection Behavior"
IESE Fraunhofer-Institut für Experimentelles Software Engineering
Digitale Medien in der beruflichen Bildung
Enhanced ParamedIC vocational training with Serious games And Virtual Environments
In multimedia research, the presence experience is attributed a central role in experiential learning in highly immersive virtual educational environments. In this paper, the hypothetical cause-effect relationships between a spatial presence experience and different learning and training effects are theoretically analyzed and empirically tested. The field study was carried out in the EPICSAVE project. In this project, a virtual reality simulation environment for the training in paramedical education was developed and tested in educational practice. The main results indicate that presence experience does not per se have a direct impact on all learning and training effects.
Dem Präsenzerleben wird eine das Lernen verstärkende Rolle in hoch-immersiven virtuellen Lern- oder Trainingswelten zugeschrieben. In diesen Beitrag werden hypothetische Wirkungszusammenhänge zwischen einem räumlichen Präsenzerleben und Lern- bzw. Trainingseffekten rekonstruiert und empirisch geprüft. Die Feldstudie wurde im Rahmen des Projekts EPICSAVE durchgeführt. In diesem Projekt wurde eine auf Virtual-Reality-Technologie basierende Simulationsumgebung für angehende Notfallsanitäter entwickelt und in der Bildungspraxis erprobt. Die Ergebnisse zeigen, dass das Präsenzerleben nicht per se einen direkten Einfluss auf alle Lern- und Trainingseffekte gleichermaßen hat.
Der Einfluss des Präsenzerlebens auf die Lern- und Trainingseffekte in einer Virtual-Reality Simulationsumgebung
IFAM Fraunhofer-Institut für Fertigungstechnik und Angewandte Materialforschung
Prozessintegrierte Immobilisierung von optischen Markern an Formteiloberflächen zur individuellen und robusten Bauteilkennzeichnung
Lichtmikroskopische Aufnahmen von PUF Markierungen auf PC und PBT
This data set contains two files. The first file "process-parameters-to-reach-target-shear-distribution.csv" provides a detailed set of curves in accordance with Figure 3.4 in the linked paper. Here, the first row "PhiGammaSuf" is the ordinate and all following rows are the respective abscissae for a certain pair of sufficient shear (gammaSuf) and flow exponent n. Please refer to the main text of the paper for a detailed explanation. The second file "relation-consistency-to-mean-velocity.csv" consists of the data set in accordance with Figure 3.7. Here, the first column "R-DeltaP-By-L-tau0" is the ordinate and all subsequent columns belong to a certain flow index. The headers have a format of "y-for-n={value}", where "y" is a substitution for $\frac{K}{\tau_0} \left(\frac{v_\text{mean}}{R}\right)^n$ as shown on the abscissa in Figure 3.7 and {value} is the corresponding flow index of interest. Again, please refer to the main text for a detailed explanation.
Auxiliary data tables relating process parameters and parameters of the Herschel-Bulkley rheology model to a deformation profile
Entwicklung einer Methodik zur Bestimmung der Energieeffizienz von Gebäuden auf Basis von optimierten in situ Messungen
This document and dataset sets out the specification for the empirical validation experiment conducted on the Twin Houses at the Fraunhofer IBP test site in Holzkirchen, Germany in the winter of 2018/19, as part of IEA EBC Annex 71. This document, together with the additional information provided (images, thermal bridge calculations, layout drawings, experimental details and experimental data) constitutes a full specification of the experiment, makeing it available for further validation and training purposes.
Twin House Experiment IEA EBC Annex 71 Validation of Building Energy Simulation Tools - Specifications and dataset
This document represents the original questions for the survey conducted in the paper “Influencing Factors for Users' Privacy and Security Protection Behavior in Smart Speakers: Insights from a Swiss User Study” by Frank Ebbers and Murat Karaboga. Original screenshots and the questions in text are present in German, French and Italian.
For Paper: Ebbers, Karaboga (2022): Influencing Factors for Users' Privacy and Security Protection Behavior in Smart Speakers: Insights from a Swiss User Study. The 4th Workshop on Security, Privacy, Organizations, and Systems Engineering, held at ESORICS 2022
Questionnaire layout, order and screenshots
ITWM Fraunhofer-Institut für Techno- und Wirtschaftsmathematik
Synthetic, Optically Realistic Image Data of Surface Structures for AI-Based Inspection Systems
Visual surface inspection images of aluminum test objects with different manufacturing surface textures and defects. The textures were produced by sandblasting, paralel milling and spiral milling. The dataset was used to support study of influence of surface texture on defect recognition. It contains real images, synthetic images and segmentation masks for both. Objects were inspected using a ring light and grayscale matrix camera monted on a robotic manipulator.
SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection
Application of digital ecosystem criteria on digital ecosystem service candidates, to classify these candidates as digital ecosystem services or non digital ecosystem services.
Note: In case one criterium for a digital ecosystem service candidate is not fulfilled, the remaining ones have not been checked, indicated through "n/a".
Digital Ecosystem Service Classification
AISEC Fraunhofer-Institut für Angewandte und Integrierte Sicherheit
Automatisierter Transport zwischen Logistikzentren auf Schnellstraßen im Level 4. Teilvorhaben: Security-Umfänge
Die Zusammenarbeit zwischen verschiedenen Bereichen der Automobilindustrie, darunter Fahrzeugentwicklung, Produktion und Backend-Services, erhöht die Komplexität des Cybersicherheitsrisikomanagements. Standards wie ISO/SAE 21434, die ISO/IEC 27000-Familie und die IEC 62443-Reihe bieten zwar jeweils branchenspezifische Leitlinien, doch eine gezielte Analyse zeigt, dass sie kein vollständig integriertes, bereichsübergreifendes Rahmenwerk bieten. Vielmehr enthalten sie verstreute Leitlinien zu Themen wie Kommunikationskanälen, externen Abhängigkeiten und abgestimmten Risikokriterien, sodass es den Unternehmen überlassen bleibt, diese Elemente zu vereinheitlichen. Um zu untersuchen, wie sich diese Lücke in der Praxis äußert, wurden semi-strukturierte Interviews mit sechs Automobilherstellern durchgeführt, in denen reale Herausforderungen und Strategien für das bereichsübergreifende Cybersicherheitsrisikomanagement erfasst wurden. Die Ergebnisse zeigen unterschiedliche Methoden der Risikobewertung, uneinheitliche Terminologie und fragmentierte Kommunikationskanäle zwischen diesen Bereichen, die eine ganzheitliche Sicherheitsstrategie erschweren. Umgekehrt unterstreichen die Ergebnisse die Vorteile koordinierter Strategien, wie z. B. eine verbesserte Risikotransparenz, eine effizientere Ressourcenzuweisung und eine stärkere Einhaltung gesetzlicher Vorschriften.
Collaboration across multiple divisions in the automotive industry, including vehicle engineering, production, and backend services, complicates cybersecurity risk management. While standards such as ISO/SAE 21434, the ISO/IEC 27000 family, and the IEC 62443 series each offer domain-specific guidance, a focused review shows they do not offer a fully integrated, cross-divisional framework. Rather, they present scattered guidance on topics like communication channels, external dependencies, and aligned risk criteria, leaving it to organizations to unify these elements. To explore how this gap manifests in practice, semi-structured interviews were conducted with six automotive manufacturers, capturing real-world challenges and strategies for cross-divisional cybersecurity risk management. The findings reveal disparate risk assessment methods, inconsistent terminology, and fragmented communication channels among these divisions, which hinder a holistic security posture. Conversely, the results highlight the benefits of coordinated strategies, such as enhanced risk transparency, more efficient resource allocation, and stronger regulatory compliance.
Transcripts of expert interviews concerning requirements and current practices of cross-divisional cybersecurity risk management in automotive
Transkripte von Experteninterviews zu Anforderungen und aktuellen Praktiken von bereichsübergreifendem Cybersecurity Risikomanagement in der Automobilindustrie
IOSB Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung
KI-Leuchttürme für Umwelt, Klima, Natur und Ressourcen
Energetisch Smarte Fabrik für die ressourcenschonende Produktion
Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz BMUV (Deutschland)
The system is an injection molding production facility that is operated in the SmartFactoryOWL living lab. Plastic cups are produced in a two-cavity mold. The injection molding production consists of an injection molding machine, granulate drying, temperature regulation, cooling, laser marking and robotics. The data set contains energy consumption of the complete system over four days of production (07.11.2023 to 10.11.2023). Two energy strings are included in the data set, as well as the total energy consumption
Energy Consumption of Production System in SmartFactoryOWL over four days (07.11.2023 to 10.11.2023).
Semantische Plattform zur intelligenten Entscheidungs- und Einsatzunterstützung in Leitstellen und Lagezentren
Um Transparenz und Reproduzierbarkeit zu ermöglichen, wird der Forschungsplan zur Feldforschung im Projekt veröffentlicht. Die Feldforschung adressiert Aspekte der Aufmerksamkeitsverteilung und des Mental Workloads während der Prozesse "Notrufannahme" und "Einsatzdisposition".
Forschungsplan zur Feldstudie im Forschungsprojekt SPELL
Exposé zur Feldstudie im Forschungsprojekt SPELL
Exposé of the field study in the research project SPELL
IPMS Fraunhofer-Institut für Photonische Mikrosysteme
A measurement setup based on an accelerometer, MEMS gyroscope and magnetometer was used to gather data on a conveyor belt to determine the tension of the belt. 100,000 data points are split into 10 measurement series with 10,000 data points each. Each data point consists of 9 time series of the 3 sensors with 3 axis each.
Data set for AI a ssisted detection of the belt tension on a conveyer belt for condition monitoring
This data set comprises questionnaire data that was captured to investigate the relevance of requirements artifacts for conducting role specific tasks from the viewpoint of software architects, designers and software testers. Moreover, the data set includes questionnaire data of a case study that was conducted to investigate benefits and limitations of role-specific views on software requirements specifications. The data served as empirical baseline for several data analysis activities conducted within the scope of a PhD Thesis entitled "Role-Specific Views on Software Requirements Specifications - An Empirical Approach".
Empirical Baseline that underlies PhD Thesis "Role-Specific Views on Software Requirements Specifications" - An Empirical Approach
Rohdaten Empirischer Studien zur PhD Thesis "Role-Specific Views on Software Requirements Specifications" - An Empirical Approach
Empirical Baseline for the Investigation of Role-Specific Information Needs
Digitalisierung: Chance für Nachhaltigkeit und Energiewende
The MaterialDigital or BWMD dataset is an RDF data repository generated by the Use Case Metals within the framework of the MaterialDigital project. It showcases the digitalization of the aluminum permanent mold casting process, followed by a two-stage heat treatment, involving solution annealing and artificial aging by means of ontology based semantic data structures. For the purposes of the study, the casting alloy AlSi10Mg was used. In two casting campaigns, project-specific databases were established using test bars, which were subjected to mechanical and analytical material characterization. A demonstrator casting was also cast, and subjected to static bending stress on a laboratory test rig. For both casting campaigns, variations in chemical composition of the AlSi10Mg alloy were introduced with respect to the silicon and magnesium content. Accompanying the casting campaigns were casting simulations to refine model parameters through temperature measurements in the test bar mold. There were two primary objectives of the project. The first aim was to leverage the digital workflow to structure the data from the test bar characterization campaign. Individual data sets from each process step were linked together to create a comprehensive and coherent knowledge graph of the process chain, which was then transferred to a graph database. The development of a domain ontology for the process chain allowed the extraction of expert knowledge on the impact of chemical composition and heat treatment parameters on various mechanical properties from the material data space. Beyond querying metadata, the heterogeneous raw data sets could also be accessed by machines, as evidenced by tensile tests. This technology is thus transformative in its ability to capture material- and process-specific expert knowledge, serving as the basis for further data-based analyses. In practical terms, this can guide decision-making regarding the ideal heat treatment parameters given the chemical composition that will ensure the attainment of specific material strength.
ISST Fraunhofer-Institut für Software- und Systemtechnik
This online supplementary appendix to the paper "Decision Criteria for Selecting Data Infrastructure Design Options in the Private Sector" presents additional material from our Design Science Research project that was omitted from the original publication. Appendix A provides a complete list of publications included in the literature review process. Appendix B presents a practical methodology for applying the catalog of criteria to identify and evaluate design options for private-sector data infrastructures for data sharing. Finally, Appendix C offers a multi-criteria decision-making tool for selecting the most suitable design option for private-sector data infrastructures for data sharing.
Online Supplementary Appendix - Decision Criteria for Selecting Data Infrastructure Design Options in the Private Sector
Quality-Aware Rapid Software Development
It contains materials used during the second formative evaluation of the Q-Rapids project.
iCampus Arbeitspaket 6: Multi-Sensor Condition Monitoring
A METROM CNC mill was equipped with a microphone and an accelerometer to determine whether the used milling tool was in a good state or blunt. The measurement data was collected over several measurement series. The used tool was replaced at the beginning of each series with a new, similar tool. The working material was always steel. Machine parameters such as feed rate and rotational speed of the tool has been varied between different series. The machine was operated over a defined time frame while data was collected. After that, the machine was stopped, and the operator classified the quality of cut. The quality is directly related to the condition of the tool. The higher the wear, the worse the quality. Using this approach, we build a dataset consisting of different measurement series to show the degradation of a CNC cutter using vibration and acoustic measurements.
Dataset for AI-assisted detection of the wear level of a cutting tool on a CNC mill
This dataset includes Large Language Models (LLM) prompts and the cover text, used for the three experiments conducted in the conference paper "Security and Detectability Analysis of Unicode Text Watermarking Methods Against Large Language Models". It also includes the results of all three experiments.
Supplementary Data of the Conducted Experiments in the Conference Paper
Supplementary Data for "Security and Detectability Analysis of Unicode Text Watermarking Methods Against Large Language Models"
This data set contains the documentation of the first round of workshops (goal setting workshops) that were carried out by Fraunhofer ISI within the EU project JERRI (Joining Efforts for Responsible Research and Innoavtion). The first round of workshops were dedicated to develop long-term RRI goals. As part of work package 2 "development of RRI goals at Fraunhofer", the development of these goals evolved around five workshop-based processes related to the five key dimension of Responsible Research and Innovation (RRI) - Ethics, Societal Engagement, Open Access, Gender Equality and Science Education. Beyond the documentation of the developed visions, long-term orientations and goals, this data set contains also a description of the developed concrete actions (pilot activities) that are considered as a start for a long-term transformation of Fraunhofer towards RRI and to fulfill these goals.
JERRI Goal setting workshop documentation FhG
This data set contains the interview results with Fraunhofer staff concerning the topic of RRI (Responsible Research and Innovation) and the possibilites but also the challenges of how to create organizational transformation towards RRI. These interviews were carried within the EU project JERRI (Joining Efforts for Responsible Research and Innovation).
Supplementary datasets to the journal paper in excel format for results and GIS-datasets in vector format for datasets
journal paper publication: Manz, P.; Billerbeck, A.; Kök, A.; Fallahnejad, M.; Fleiter, T.; Kranzl, L.; Braungardt, S.; Eichhammer, W.: Spatial analysis of renewable and excess heat potentials for climate-neutral district heating in Europe, Renewable Energy, 2023 [under review]
Spatial analysis of renewable and excess heat potentials for climate-neutral district heating in Europe
IIS Fraunhofer-Institut für Integrierte Schaltungen - Institutsteil Entwicklung Adaptiver Systeme EAS
This dataset contains vibration data recorded on a rotating drive train. This drive train consists of an electronically commutated DC motor and a shaft driven by it, which passes through a roller bearing. With the help of a 3D-printed holder, unbalances with different weights and different radii were attached to the shaft. Besides the strength of the unbalances, the rotation speed of the motor was also varied. This dataset can be used to develop and test algorithms for the automatic detection of unbalances on drive trains. Datasets for 4 differently sized unbalances and for the unbalance-free case were recorded. The vibration data was recorded at a sampling rate of 4096 values per second. Datasets for development (ID "D[0-4]") as well as for evaluation (ID "E[0-4]") are available for each unbalance strength. The rotation speed was varied between approx. 630 and 2330 RPM in the development datasets and between approx. 1060 and 1900 RPM in the evaluation datasets. For each measurement of the development dataset there are approx. 107min of continuous measurement data available, for each measurement of the evaluation dataset 28min. Details of the recorded measurements and the used unbalance strengths are documented in the README.md file.
Dieser Datensatz enthält Vibrationsdaten, die an einem rotierenden Antriebsstrang aufgezeichnet wurden. Der Antriebsstrang besteht dabei aus einem elektronisch kommutierten Gleichstrommotor und einer von diesem angetriebenen Welle, die durch ein Wälzlager läuft. An der Welle wurden mithilfe eines 3D-gedruckten Halters Unwuchten mit verschiedenen Gewichten und an unterschiedlichen Radien befestigt. Neben der Stärke der Unwuchten wurde auch die Drehzahl des Motors variiert. Mit diesem Datensatz können Algorithmen für die automatische Erkennung von Unwuchten an Antriebssträngen entwickelt und getestet werden. Es wurden Datensätze für 4 unterschiedlich große Unwuchten und für den unwuchtfreien Fall aufgenommen. Die Vibrationsdaten wurden mit einer Abtastrate von 4096 Werten pro Sekunde aufgezeichnet. Für jede Unwuchtstärke stehen Datensätze sowohl für die Entwicklung (ID "D[0-4]") als auch für die Evaluation (ID "E[0-4]") von Klassifikationsmodellen zur Verfügung. Die Drehzahl wurde in den Entwicklungsdatensätzen zwischen ca. 630 und 2330 U/min und in den Auswertungsdatensätzen zwischen ca. 1060 und 1900 U/min variiert. Für jede Messung des Entwicklungsdatensatzes stehen ca. 107min an kontinuierlichen Messdaten zur Verfügung, für jede Messung des Evaluationsdatensatzes 28min. Details zu den aufgezeichneten Messungen und den verwendeten Unwuchtstärken sind in der Datei README.md dokumentiert.
Vibrationsmessungen an einer rotierenden Welle bei verschiedenen Unwuchtstärken
Vibration Measurements on a Rotating Shaft at Different Unbalance Strengths
Im Rahmen einer Masterarbeit zum Thema »Positionsbestimmung wissenschaftlicher Bibliotheken in der externen Wissenschaftskommunikation am Beispiel des Fraunhofer-Fachinformationsmanagements« wurde eine Online-Befragung durchgeführt. Sie richtete sich an Fraunhofer-Fachinformationsmanager:innen und Mitarbeitende der Kommunikationsabteilungen, um ihre Aktivitäten in und Einstellungen zur externen Wissenschaftskommunikation zu erheben. Nähere Informationen zur Durchführung und Auswertung können der im Datenbankeintrag verlinken Masterarbeit entnommen werden.
An online survey was conducted as part of a master's thesis on "Positioning of scientific libraries in external science communication using the example of Fraunhofer's scientific information management". It was directed at Fraunhofer library and information services and employees of the communication departments in order to ascertain their activities in and attitudes toward science communication. Further information on the survey can be found in the master's thesis linked in the database entry.
Fraunhofer-Fachinformationsmanagement in der externen Wissenschaftskommunikation
This compilation presents in-situ stress orientations derived from hydrofracturing tests and borehole logs carried out in six, now abandoned, coal mines within the greater Ruhr region in western Germany. All stress information was analysed and compiled in a standardized format and quality-ranked, using the established quality ranking schemes of the World Stress Map (WSM) project, for reliability and comparability. The compilation displays A-C quality of in-situ stress orientation data records. The database presents unique and high-quality stress input data for future reservoir and geomechanical numerical models and should aid the subsurface operations in the region. More detailed information on the WSM quality ranking scheme, guidelines for the various stress indicators, and software for stress map generation and the stress pattern analysis is available at http://www.world-stress-map.org.
In-Situ Stress Orientation Data from the Greater Ruhr Region (Germany) Derived from Hydrofracturing Tests and Borehole Logs
SPP 2122 - Materials for Additive Manufacturing
Numerical and experimental investigations of dimensionless material parameters in laser additive manufacturing of polymers for accelerated material development and process optimization
Smoothed particle hydrodynamics simulations in two dimensions are used to calculate the transient melt pool temperature distribution in the laser powder bed fusion process of polymers. The effects of laser power, scan speed, hatch distance, absorptance, emissivity, density, heat capacity, heat transfer, latent heat, thermal conductivity, melting and re-solidification, viscosity and surface tension are considered in the model. A wide range of these laser parameters and material properties is investigated. Complementary to the simulation results, infrared camera measurements of the transient surface temperature are provided.
Numerical simulations and infrared camera measurements of temperature distributions in laser powder bed fusion of polymers
The CROWDSS dataset (Crowdsourced Wizard of Oz Dialogue dataset based on Situated Scenarios) contains 113 German dialogues collected in a Wizard-of-Oz fashion (i.e., simulating human-machine interaction). To refer to CROWDSS in any publication, please cite the following paper: Frommherz, Y. and Zarcone, A. (2021). Crowdsourcing ecologically-valid dialogue data for German. In Frontiers in Computer Science, Vol 3, doi: 10.3389/fcomp.2021.686050
CROWDSS: A crowdsourced, ecologically-valid dialogue dataset for German
IPM Fraunhofer-Institut für Physikalische Messtechnik
The data includes SO2 measurements, which were carried out under laboratory conditions. Furthermore, the data includes the measured values on a container ship field test. In addition, the python script, which was used to analyse the gathered data, can be found.
On-board monitoring of SO2 ship emissions using resonant photoacoustic gas detection in the UV range
ISE Fraunhofer-Institut für Solare Energiesysteme
This working paper describes the quantitative and model-based methodology used in HYPAT to assess hydrogen and Power-to-X (PtX) export potentials in the countries Morocco, Ukraine, Namibia, Turkey, United Arab Emirates, Kenya, Chile, Canada, Brazil, and New Zealand. The results of the techno-economic assessment are further used as a basis for a global hydrogen and PtX atlas, and as an indication of the price development of hydrogen and PtX.
Export Potentials of Green Hydrogen - Methodology for a Techno-Economic Assessment. Annex A.1 - Modeling parameters
The data set contains the power generated by a PV system over one week. The PV system has a total output of 55kWp and is located on the roof of the SmartFactoryOWL in Lemgo. The data was recorded with an interval of 5 minutes.
PV data of SmartFactoryOWL over one week (25.11.2024 to 01.12.2024)
Bundesministerium für Verkehr und digitale Infrastruktur BMVI (Deutschland)
Predictions of energy consumption are crucial for energy retailers to minimize deviations from energy acquired in the day-ahead market and the actual consumption of their customers. The increasing spread of smartmeters means that retailers have access to hourly consumption values of all their contracted customers in realtime. Using machine learning algorithms, these hourly values can be used to calculate predictions for the future energy consumption of the customers. The present data set allows the training and validation of AI-based prediction models.
Energieverbrauchskurven von 499 Kunden aus Spanien
Energy Consumption Curves of 499 Customers from Spain
Tabular Data for a Conference Paper.
Effects of the GDPR in South East Asia vs. Europe - A Large-scale Analysis of IoT Devices
This dataset contains 3-axial vibration data of an aluminium milling process recorded at a large industrial tooling machine (MAHO MH 800C). The data has been recorded by an enDAQ S5-E25D40 vibration sensor module. Each datapoint consists of 8000 samples (duration: 1 second) for 3-axial vibration data along x, y & z axis of the tooling machine. Each datapoint represents a segment of a 1-axial milling movement (+/-x, +/-y). The data is to be used for the investigation of process quality monitoring, therefore each signal segment has been assigned a label "1" (good) or "0" (bad). The label was given to all movements of a (partial) pattern by a domain expert, depending on the surface quality of the workpiece after milling.
Milling of Aluminium at a MAHO MH 800C Tooling Machine
MillingVibes: 3-Axial Vibration Data of a Milling Process Performed by a Tooling Machine
These datasets accompany the WES preprint: Watson, Wolken-Möhlmann & Gottschall (2025), Evaluating the Impact of Motion Compensation on Turbulence Intensity Measurements from Continuous-Wave and Pulsed Floating Lidars (DOI: 10.5194/wes-2025-45). They cover the FINO3 campaign (German North Sea; 10-min aggregation; wind sector 220°–300°) and compare raw vs motion-compensated TI from a floating ZX300M (cw) and a floating Windcube V2.1 (pulsed) together with a fixed ZX300M reference at 101 m, against Met Mast Cup TI from 101 m.
File 2 - 10-minute time series data Title: TI time series at 101 m (raw vs motion-compensated) with fixed lidar reference What’s inside: Underlying 10-min TI used for File 1. Instruments: Floating ZX300M (cw), floating Windcube V2.1 (pulsed), fixed ZX300M. Columns: WLBZ6_Raw_TI_101_m, WLBZ6_Compensated_TI_101_m, WLBW4_Raw_TI_101_m, WLBW4_Compensated_TI_101_m, FINO3_Fixed_Lidar_TI_101_m. Processing: Deterministic motion compensation for LoS tilt/rotation and platform surge/sway/heave/tilt. Access: Repository record and metadata are public and citable. Files are temporarily restricted due to ongoing commercial use in a third-party Stage-3 maturity certification. Non-commercial research access may be granted on request under a mutual Data Use Agreement (DUA). Terms will be reviewed after certification completion and, if certification is not granted, annually thereafter. How to request: Email the corresponding author (warren.watson@iwes.fraunhofer.de) with institution, non-commercial purpose, intended analyses/outputs, and requested period.
File 1 — Binned statistics (public) Title: Binned TI statistics at 101 m (raw vs motion-compensated) with fixed lidar reference What’s inside: Wind-speed–binned (0.5 m s⁻¹) TI metrics from the analysis period 2024-04-06 to 2024-07-09: mean, min, max, std, Q90, count, MBE/RMBE, RMSE/RRMSE, representative TI error. Instruments: Floating ZX300M (cw), floating Windcube V2.1 (pulsed), fixed ZX300M. Columns: WLBZ6_Raw, WLBZ6_Compensated_TI, WLBW4_Raw, WLBW4_Compensated_TI, FINO3_Fixed_Lidar. Processing: Deterministic motion compensation for LoS tilt/rotation and platform surge/sway/heave/tilt.
Evaluating the Impact of Motion Compensation on Turbulence Intensity Measurements from Continuous-Wave and Pulsed Floating Lidars
This data set contains information about microstructure-sensitive damage in ferritic steel (EN 1.4003) specimens. We provide both graph and tabular data sets. In the graph data set, each node is a grain in the material, and each edge connects adjacent grains. Annotation is provided to each of the grains mentioning if it developed damage (protrusion in this case) during a fatigue test. The annotation is provided based on fatigue tests performed on the specimen.
Microstructural damage dataset (pytorch geometric dataset)
Digitale Vernetzungsplattform für Energie- und Ressourceneffizienz zum optimierten Anlagenbetrieb
The data set contains the coordinates of start and end points of a point-to-point trajectory of a collaborative robot.
Start and end poses for energy modeling of a collaborative robot
This data set contains the reports from the goal setting process of TNO within the EU project JERRI. The reports outline for every key dimension of RRI (Responsible Research and Innovation) which goals TNO want to achieve in the long run and which concrete measures are being taken to achieve these goals.
AI Innovation Center "Learning Systems and Cognitive Robotics"
This dataset provides real and synthetic images with instance annotations for each objects. The images per scene are created in an iterative context, for the real images and a part of the synthetic images the individual iteration images are provided.
ILIS - Iteratively Labeled Instance Segmentation
EMFT Fraunhofer-Einrichtung für Mikrosysteme und Festkörper-Technologien
Subcutaneous injection of medication is crucial for the treatment of many diseases. Especially if regular or continuous injections are beneficial, automated dosing units are advantageous. How-ever, existing devices are still large and therefore uncomfortable, visible under clothing, or inter-fere with physical activity. Thus, the development of small, energy efficient and reliable patch pumps or implantable systems is necessary and research on microelectromechanical system (MEMS) based drug delivery devices gained increasing interest. However, the requirements of medical application are not yet fully met and especially dosing precision and reliability pose a challenge for MEMS pumps. To enable further miniaturization, we propose a precise 5x5 mm² sil-icon micropump. Detailed experimental evaluation of ten pumps proves a backpressure capability with air of 12.5 ± 0.8 kPa, which indicates the ability to transport bubbles at moderate backpres-sures. The maximal water flow rate is 74 ± 6 µl/min and the pumps’ average blocking pressure is 51 kPa. The evaluation of the dosing precision for bolus deliveries with water and insulin shows a high repeatability of dosed package volumes. The pumps show a mean standard deviation of only 0.02 mg for 0.5 mg packages and therefore stay below the generally accepted 5% deviation, even for this extremely small amount. This high precision enables the combination with higher concen-trated medication and is the foundation for the development of an extremely miniaturized patch pump.
Experimental characterisation of piezoelectric silicon micropump for drug delivery applications
Experimentelle Charakterisierung piezoelektrischer Mikromembranpumpen für Medikamentendosierung
Experimental data of particle transport
Particle transport with piezoelectric micro diaphragm pumps
journal paper publication: Manz, P.; Billerbeck, A.; Kök, A.; Fallahnejad, M.; Fleiter, T.; Kranzl, L.; Braungardt, S.; Eichhammer, W.: Spatial analysis of renewable and excess heat potentials for climate-neutral district heating in Europe, Renewable Energy, 10.1016/j.renene.2024.120111
IIS Fraunhofer-Institut für Integrierte Schaltungen : Institutsteil Entwicklung Adaptiver Systeme EAS
This dataset contains vibration data recorded on a rotating drive train. This drive train consists of an electronically commutated DC motor and a shaft driven by it, which passes through a roller bearing. With the help of a 3D-printed holder, unbalances with different weights and different radii were attached to the shaft. Besides the strength of the unbalances, the rotation speed of the motor was also varied. This dataset can be used to develop and test algorithms for the automatic detection of unbalances on drive trains. Datasets for 4 differently sized unbalances and for the unbalance-free case were recorded. The vibration data was recorded at a sampling rate of 4096 values per second. Datasets for development (ID "D[0-4]") as well as for evaluation (ID "E[0-4]") are available for each unbalance strength. The rotation speed was varied between approx. 630 and 2330 RPM in the development datasets and between approx. 1060 and 1900 RPM in the evaluation datasets. For each measurement of the development dataset there are approx. 107min of continuous measurement data available, for each measurement of the evaluation dataset 28min. Overview of the dataset components: ID Radius [mm] Mass [g] 0D/ 0E - - 1D/ 1E 14 3.281 2D/ 2E 18.5 3.281 3D/ 3E 23 3.281 4D/ 4E 23 6.614
This compilation presents in-situ stress magnitudes derived from hydrofracturing tests and borehole logs carried out in six, now abandoned, coal mines and two coal bed methane boreholes at depths between 600 and 1950 m within the greater Ruhr region in western Germany. All stress information was analysed and compiled in a standardized format and quality-ranked, using the established quality ranking schemes of the World Stress Map (WSM) project, for reliability and comparability. The compilation displays A-C quality of in-situ stress orientation data records. The database presented here is the world's largest public database of stress magnitudes from a single region and presents unique and high-quality stress input data for future reservoir and geomechanical numerical models and should aid the subsurface operations in the region. This dataset supplements the Stress Magnitude Database of Germany (https://doi.org/10.5880/wsm.2020.004) with additional 429 data records, doubling the amount of available stress data records for Germany from 568 to 997. More detailed information on the WSM quality ranking scheme, guidelines for the various stress indicators, and software for stress map generation and the stress pattern analysis is available at http://www.world-stress-map.org.
In-Situ Stress Magnitude Data from the Greater Ruhr Region (Germany) Derived from Hydrofracturing Tests and Borehole Logs
Der Datensatz umfasst sämtliche zugrundeliegende Daten für die Berechnungen.
Evaluation of a local heating network supplied by a pyrolysis plant
TeaM Cables - European Tools and Methodologies for an efficient ageing management of nuclear power plant Cables
Teraherz measurements performed on xlpe specimens.
IME-BR Fraunhofer-Institut für Molekularbiologie und Angewandte Oekologie - Institutsteil Bioressourcen des Fraunhofer IME
LOEWE Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz
MS, MS/MS and NMR data for publication "Genomic and chemical decryption of the Bacteroidetes phylum for its potential to biosynthesize natural products".
Genomic and chemical decryption of the Bacteroidetes phylum for its potential to biosynthesize natural products
Europäischer Fonds für regionale Entwicklung (EFRE) 2014‐2020 „Investitionen in Wachstum und Beschäftigung“
Geothermale Papiertrocknung. Teilvorhaben: Geothermische Erkundung und Erschließungskonzept
The investigation of karst aquifers is inherently challenging due to their heterogeneous nature. A new borehole, measuring 224 metres in depth, was drilled into the 'Massenkalk' formation in the Steltenberg quarry at Hagen, North Rhine-Westphalia, Germany, with the objective of investigating its potential as a geothermal reservoir analogue (Coordinates of well R1: 401398 / 5690212 UTM 32N). Geophysical logging and camera runs revealed the presence of highly permeable karst structures, which visually displayed vuggy porosity. The permeability of the aquifer seems largely dominated by karst structures, specifically fractures that have been widened by dissolution. Instead of intense fracturing, the rock mass generally appears to be characterised by karstification and secondary porosity. The logging and mapping data were finalised in PDF, TXT and AVI formats as supplementary material of: DOI: 10.1127/zdgg/2025/0450
Finalised data of: Optical Borehole Imager, Acoustic Borehole Imager, Calliper, Downhole Video
Wireline-Logging- und Videodaten einer 224 m tiefen Erkundungsbohrung in einem Karbonatkarst in Hagen, Nordrhein-Westfalen, Deutschland
Wireline logging and video data of a 224 m deep exploration well in a carbonate karst in Hagen, North Rhine-Westphalia, Germany
Open source Energiesystemmodellierung – Einfluss von soziokulturellen Faktoren auf Transformationspfade des deutschen Energiesystems
Der Datensatz umfasst Daten einer repräsentativen empirischen Erhebung, bei der das Investitionsverhalten von Privatpersonen in alternative Antriebe bei der Wahl eines Neuwagens untersucht wurde. Es wurde eine Kombination aus Fragebogen und Discrete Choice Experiment (DCE) gewählt. Das DCE wurde mittels Hierarchical Bayes ausgewertet. Die Werte in den DCE Excelblättern sind Nutzenwerte. Neben investitionsrelevanter Faktoren wurden Daten zum Mobilitätsverhalten und zur Unterstützung politischer Maßnahmen erhoben.
Fragebogen und Discrete Choice Experiment
Representative study of investment decisions in alternative vehicles - Survey and choice experiment
Repräsentative empirische Erhebung zur Investitionsbereitschaft in alternative Antriebe
FOKUS Fraunhofer-Institut für offene Kommunikationssysteme
Kompetenzzentrum Öffentliche IT – anwendungsorientierte Begleitforschung
Bundesministerium des Innern, für Bau und Heimat BMI (Deutschland)
In der Umfrage zu Vertrauen in die Verwaltung geht es um das Vertrauen der Bürger:innen in den Umgang mit Daten innerhalb der Verwaltung und Begründungen für mögliches Misstrauen. Ferner werden Einstellungen der Bürger:innen zu Potentialen der Verwaltungsdigitalisierung und die Nutzung der digitalen Steuererklärung Elster erhoben. Für jede Umfrage werden neben den Datensätze (sowohl mit Werten als auch mit Label) die Fragebögen mit dem Codeschema bereitgestellt. Zusätzlich werden die von GMS verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
Virtuell-augmentiertes Training für die Aus- und Weiterbildung in der interprofessionellen Notfallversorgung
The raw data includes socio-demographic information about the participants as well as results of the measurement of situational motivation, usability, virtual reality sickness, and presence.
Psychometric and sociodemographic raw data of training evaluation of paramedic trainees with extended reality in classroom setting within project ViTAWiN.
Psychometrische und soziodemografische Rohdaten der Trainingsevaluation von Notfallsanitäter:innen in Ausbildung mit Extended Reality im Classroom-Setting innerhalb des Projekts ViTAWiN
6. Energieforschungsprogramm Erneuerbare Energie
This set of time series comprises simulation time series of the IWT7.5 reference wind turbine (Revision 2.5) with an IPC controller. The turbine model is available online (first reference), a detailed description of the controller is part of the second reference. The signals of the files are WindSpeed, ElectricalPower, and pitch angles and loads of three blades.
Aero-Elastic Simulation Time Series of IWT7.5 Reference Turbine
European Regional Development Fund (ERDF)
Raw data of the six decision-makers of the analytical hierarchy process (AHP) expert survey. The expert survey was conducted for prioritising sub-criteria of the Simulation Decision Matrix (SDM). The SDM is primarily used for prioritising quality-critical product parameters of hydrogen technologies for simulation applications in their production process.
Simulation Decision Matrix_Analytical Hierarchy Process_raw data_expert survey
Maßgeschneiderte Werkstoffeigenschaften durch Mikrostrukturoptimierung: Maschinelle Lernverfahren zur Modellierung und Inversion von Struktur-Eigenschafts-Beziehungen und deren Anwendung auf Blechwerkstoffe
This is a collection of sets of artificially generated crystallographic textures of steel sheets, histogram-based representations of them and their corresponding properties. The properties are calculated using a Taylor-type crystal plasticity model.
Artificially generated crystallographic textures of steel sheets and their corresponding properties calculated by a Taylor-type crystal plasticity model
Scripts for calculating basic adsorption heat exchanger theory equations including examples. Scripts may be used with R 4.3.0 https://cran.r-project.org/bin/windows/base/ in combination with RStudio https://posit.co/products/open-source/rstudio/
Basic Adsorption Heat Exchanger Theory Calculation Scripts
Innovationen im Einsatz – Praxisleuchttürme der zivilen Sicherheit
AutonomieKIT für die Umrüstung von Arbeitsmaschinen in kooperierende Nutzfahrzeuge zur Unterstützung von Rettungskräften
During accidents involving hazardous chemicals, people in the area may be put at risk of harm. (Semi-)autonomous robots can mitigate this threat by removing leaking containers. However, teleoperation requires extensive training and is difficult in practice. To overcome these limitations, we implemented a perception system on an autonomous excavator that locates individual barrels in chaotic scenes for extraction. Following the human-in-the-loop principle, operators can remotely select which barrel to remove. An efficient U-Net-style, DCAN-flavored neural network is trained using synthetic and collected real-world RGB data (5,000 synthetic and 593 real images) and compared to an inference-heavy Mask R-CNN model. In experiments on a leave-out test set, created from the excavator, our model yielded an ODS mIoU of 85.14% and mAP of 72.19%, while Mask R-CNN achieved an ODS mIoU of 86.6% and mAP of 84.31%. With roughly 0.00584s inference time on 800×576 32-bit tensors, our model is faster than Mask R-CNN with an inference time of roughly 0.0491s. Using the robot calibration data, the point clouds of multiple LiDAR sensors are fused with the RGB segmentation to find local cylinder models for each barrel, delivering the exact poses for extraction using the motion planner to find a collision-free motion plan. Force measurements were included in the gripper to avoid deforming the barrel. Field trials showed that the barrels can be reliably extracted without any damage.
IWU Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik
Novel Concepts for Safer, Lighter, Circular and Smarter Vehicle Structure Design for Enhanced Crashworthiness and Higher Compatibility
This dataset contains time-resolved measurements from crash tests performed on three crash box systems (specifically numbered 5, 6, and 7). The data includes various physical quantities recorded during the impact events. Each quantity is available for two measurement points and includes both raw and filtered signals. The impactor was instrumented using two KYOWA damped accelerometers. The acceleration data were used to calculate force, displacement, and the energy absorbed during impact. A CFC180 filter was applied to the acceleration signals for data smoothing and noise reduction. The columns in the dataset are as follows: Impactor Acceleration 1 – Raw acceleration data from the first impact sensor. Filtered Impactor Acceleration 1 – Filtered acceleration data (CFC180) from the first sensor. Impactor Acceleration 2 – Raw acceleration data from the second impact sensor. Filtered Impactor Acceleration 2 – Filtered acceleration data (CFC180) from the second sensor. Average Impactor Acceleration – Mean of the filtered acceleration data from both sensors. Velocity – Integrated velocity profile of the impactor. Displacement – Integrated displacement profile of the impactor. Force from Impactor Acceleration 1 – Force calculated using the first acceleration signal and impactor mass. Force from Impactor Acceleration 2 – Force calculated using the second acceleration signal and impactor mass. Average Force – Mean of the forces derived from both sensors. Energy – Energy absorbed by the structure, obtained by integrating the force over displacement. Three types of crashbox samples were tested (see also Fig. 8): Crash box 6: Fully riveted crash box system Crash box 7: Crash box system without rivets Crash box 5: Fully riveted crash box system with an aluminium plate (176 × 78 × 3 mm) welded on the top ring
Instrumented Impact Test Data for CFPA6 Crash Box Systems
ISC Fraunhofer-Institut für Silicatforschung
Zentrales Innovationsprogramm Mittelstand (ZIM)
Collected research data (measurements) for in vitro full-thickness skin models from three biological donors A, B, C, which were injured with pressure-induced wounds employing a magnet. The data tables list the results of metabolic analyses (glucose, lactate), viability markers (lactate dehydrogenase), as well as reactive oxygen species (ROS) and analysis of protein levels over the various durations of the pressure treatment and subsequent reperfusion phase, which support the figures in the publication.
Unter Druck: Nachahmung von Druckgeschwüren mit in vitro Vollhautmodellen
Under pressure: Mimicking bedsores with full-thickness skin equivalents in vitro
LCE-08-2016-2017 "Development of next generation biofuel technologies"
Reliable Bio-based Refinery Intermediates — BioMates
Ablative Fast Pyrolysis (AFP) is the first step in the BioMates-concept to convert herbaceous biomass into co-feed with reliable properties for conventional refineries (www.biomates.eu). The document defines samples and sample blends produced by Fraunhofer UMSICHT via AFP within the H2020-project BioMates.
BioMates - WP1: Novel pyrolysis oil from non-food/feed biomass - Data sheet: Identifiers for samples and blends
IGCV Fraunhofer-Institut für Gießerei-, Composite- und Verarbeitungstechnik
Pantomimes Roboter-Teaching für den Großguss; Teilprojekt: Entwicklung eines Teaching-Systems mit Bewegungserfassung einschließlich eines Dummy-Werkzeuges für die automatisierte Reinigung von Großgussteilen mittels Roboter
Bundesministerium für Forschung, Technologie und Raumfahrt -BMFTR-
In der Gießereitechnik bleibt die Nachbearbeitung von Reststrukturen und Graten, insbesondere bei Klein- und Mittelserienproduktion, ein arbeitsintensiver und wissensbasierter Prozess. Hier kommt DemoTeach zum Einsatz, eine neuartige halbautomatische (Human-in-the-Loop) Roboter-Teach-Methode, die mithilfe von Motion-Capture-Demonstrationen (MoCap) die Nachbearbeitung komplexer Gussteile automatisiert. Fachkräfte können ein Dummy-Werkzeug intuitiv entlang der Gussgrate führen, um robotergeeignete Pfade zu erzeugen – ohne Programmierkenntnisse oder aufwendige 3D-Datenverarbeitung. Die Videos zeigen verschiedene Roboter-Teach-Demonstrationen, welche eine intuitive automatisierte Entfernung der Speiser, Grate und Anschnitte in der Klein- und Mittelserie ermöglichen.
DemoTeach - robot programming with MoCap system for foundry applications
DemoTeach – Programmierung von Robotern mit Motion Capture System für Gießerei-Anwendungen
Skalierbare Sensornetzwerke für Condition Monitoring
Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing systems and industrial facilities. The data analysis can be improved by applying machine learning algorithms and fusion of data from heterogeneous sensors. The paper (see <REFERENCE>) presents an approach for a step-wise integration of classifications gained from vibration and acoustic emission sensors, in order to combine the information from signals acquired in the low and high frequency range. A test rig comprising a drive train and bearings with small artificial damages is used for acquisition of experimental data. The results indicate that an improvement of damage classification can be obtained using the proposed algorithm of combining classifiers for vibrations and acoustic emission. This dataset contains vibration data as well as acoustic emission data recorded on a rotating drive train. For vibration measurements, the setup is instrumented with ICP accelerometers (PCB 607A11, 100 mV/g) at the bearing holder frame of the motor and the bearing holder frame of the shaft. Both vibrational sensors are digitized by a DT 9837A USB-DAQ from (Measurement Computing GmbH). This 4-channel signal analyzer is equipped with a 24-bit ADC, that supports sample rates of up to 100 kSPS and is well suited for the vibration measurements. Acoustic emission signals (AE) are acquired by a piezo transducer (Vallen VS30V, 20 kHz – 80 kHz) connected to an AEP5 pre-amplifier for signal conditioning. These signals are digitized with an USB oscilloscope (PicoScope 2204A). This entry-level 2-channel oscilloscope features an 8-bit ADC with sample rates of up to 100 MSPS with an analog bandwidth of 10 MHz.
Measurements of Vibrations and Acoustic Emissions on a Rotating Shaft
Condition Monitoring of Drive Trains by Data Fusion of Acoustic Emission and Vibration Sensors
Fassadenintegrierte Heizung+Kühlung, Lüftung und Sanitär
Die Energieeffizienz von Lüftungsanlagen wird in der Regel als wichtigstes Kriterium bei den technischen Anforderungen an Lüftungsanlagen beschrieben. Bisherige Studien haben jedoch gezeigt, dass eine Lücke zwischen dem Lüftungsverhalten, das erforderlich ist, um das technische Potenzial mechanischer Lüftungssysteme auszuschöpfen, und dem tatsächlichen Verhalten besteht. In dieser Studie wurden verschiedene Arten des Lüftungsverhaltens, das natürliche Lüftungsverhalten im Allgemeinen und die Anforderungen und Prioritäten von Bewohner:innen an mechanische Lüftungssysteme, mittels einer quantitativen Online-Fragebogenerhebung in der deutschen Bevölkerung (N = 952) untersucht. Darüber hinaus wurden Präferenzen für Interfaces der Bedienelemente und Fernsteuerung erfasst.
Natürliches Lüftungsverhalten und Anforderungen an mechanische Lüftungssysteme - eine Studie in der deutschen Bevölkerung
Natural ventilation behavior and requirements for mechanical ventilation systems - a study among the German population
Für die Entwicklung des “Betriebssystems” der Sensormodule wurde das quelloffene Arduino-Framework eingesetzt, das speziell für die einfache und agile Programmierung von Microcontrollern auf Basis der Programmiersprache C++ entwickelt wurde. Das Framework verfügt aufgrund seiner sehr großen Nutzerbasis vor allem über eine Vielzahl externer Bibliotheken, die zur Ansteuerung verschiedenster Peripheriekomponenten wie beispielweise LoRaWAN-Funkmodulen durch einen Microcontroller benötigt werden.
Realisierung der Sensormodule für die mobile Datenerfassung
Forschung und Entwicklung für das Vorhaben „CrowdSensing für Bodensee Online“
Responses of the European IoT ecosystem to the GDPR / Appendix_DiD_Results
Responses of the European IoT ecosystem to the GDPR
Measurement results of particle size analysis of investigated cobalt oxide catalyst. Differential thermal analysis investigation results of thermal response of catalyst towards methane and respective mass spectroscopy investigation.
Impact of particle size and morphology of cobalt oxide on thermal response to methane examined by thermal analysis
The remUCPS library provides an object-oriented implementation of a rate equation model, describing the upconversion dynamics in the upconverter Erbium in the host crystal NaYF4. Additonally, the model features the effects of a photonic structure, currently implemented as a Bragg structure, on the upconversion dynamics. The local energy density is calculated via an implementation of the [transfer materix method](https://zenodo.org/record/1344878#.X3GOr3UzZhE). The local density of optical states is calculated using [MIT Photonic Bands](https://doi.org/10.1364/OE.8.000173). The change in upconversion dynamics due to these two photonic effects can be investigated using remUCPS. The remUCPS code has been developed at Fraunhofer Institute for Solar Energy Systems ISE (Germany). All publications that led up to the current version are listed below. The current version of the model is extensively described in [Hofmann, Eriksen et al. 2018] (https://doi.org/10.1364/OE.26.007537), as are the contributions of all prior publications. The code can be used and adapted by anyone wanting to simulate photonic effects on upconversion or also just an upconversion process on its own. Among the most important parameters that can be scanned in the rate equation model are the design wavelength of the Bragg structure, the excitation wavelength, the angle of incidence and the incident irradiance. Have fun playing around! Contact: clarissa.hofmann@ise.fraunhofer.de
remUCPS - rate equation model of upconversion dynamics including photonic structure effects
Effective disaster response during floods requires quick identification of flooded areas. The typical data source for idenntification is aerial Remote Sensing (RS) imagery, often inexpensive RGB drone images. Reliable flood water detection in RGB images is thus essential. However, detecting water in RGB flood imagery remains challenging, because water, mud, and soil appear similar. Moreover, the sheer volume of data makes manual analysis impractical. To automate water detection, Computer Vision (CV) and Deep Learning (DL) techniques are employed, but state-of-the-art DL methods require large amounts of labeled data; a resource that is time-consuming to produce. We introduce an improved human-in-the-loop strategy which creates labeled data consisting of pairs (RGB image, water mask) from aerial RGB and Near-Infrared (NIR) imagery of the 2021 Bad Neuenahr flood. For our labelling strategy, we integrate the NIR data via a false-color representation. We then apply the Segment Anything Model 2 (SAM 2) on these false-color NIR representations. Because flooded regions have complex shapes, the initial results require manual refinement. However, by leveraging sparse prompts to identify water, these adjustments are less time-consuming compared to traditional methods. The final labeled RGB dataset serves to train DL models to detect flood water regions in RGB images without additional NIR information. As a result of the proposed labeling strategy, to foster further flood detection research, we provide NeuenahrFlood21, an RGB labeled dataset for the task of water segmentation in RGB images. NeuenahrFlood21 matches typical acquisition parameters during a river flooding event and adds to existing data resources with varied flood and vegetation patterns. We evaluate the benefit of the proposed labeling strategy by training state-of-the-art models on NeuenahrFlood21, confirming the enhanced automated flood detection capabilities.
NeuenahrFlood Dataset and an Improved Human-in-the-Loop Strategy for Efficient Flood Water Segmentation
Experimental Data
Microfluidic Cell Transport with Piezoelectric Micro Diaphragm Pumps
Earth Resources and Environmental Remote Sensing/GIS Applications XIV (SPIE Remote Sensing, 2023, Amsterdam, Netherlands)
Natural disasters have devastating effects on communities, necessitating swift and accurate damage assessment. Manual assessment methods are time-consuming and costly, emphasizing the significance of semiautomatic ap- proaches employing remote sensing and drone data. However, current datasets primarily focus on Western countries’ infrastructure, lacking information on damaged buildings in other regions specifically Africa. To bridge this gap, we present the EDDA dataset, comprising of VHR orthorectified mosaic images from drone imagery with building footprint labels classified by damage extent of rural and urban areas of Mozambique affected by Cyclone Ida.
EDDA - Mozambique post disaster building damage dataset
Multiskalen-Batteriemodellierung zur regionen- und nutzungsabhängigen Fahrzeugsimulation
Rheinland-Pfalz, Ministerium für Wissenschaft und Gesundheit
This dataset contains the main simulation results utilized for the manuscript "Multiscale Coupling for the Usage-Specific Simulation of Battery-Electric Vehicles". It features a set of battery simulation files of a Thevenin equivalent circuit model and pseudo-two-dimensional electrochemical model. The simulations cover different usage scenarios such as rate tests, hybrid pulse power characterization (HPPC), electrochemical impedance spectroscopy (EIS) and drive cycles. Additionally, the data set includes results of a multiscale simulation model coupling vehicle and battery dynamics while considering dependencies on region and usage characteristics.
Dataset for "Multiscale Coupling for the Usage-Specific Simulation of Battery-Electric Vehicles"
KI-Anwendungshub Kunststoffverpackungen – nachhaltige Kreislaufwirtschaft durch Künstliche Intelligenz
KI-gestützte Optimierung der Kreislaufführung von Kunststoffverpackungen
The dataset comprises 586 RGB images of post-consumer lightweight packaging waste captured on a conveyor belt. Annotations follow the COCO format. The samples were kindly provided by a recycling plant of Lobbe RSW GmbH in Iserlohn, Germany. Samples were recorded as received, with adherent contaminants and without pretreatment. This dataset is part of the multi-sensor-dataset of the project K3I-Cycling and funded by the Federal Ministry of Research, Technology and Space (BMFTR), Germany under the funding reference 033KI201.
RGB Images of Post Consumer LWP Waste in a realistic Sorting Plant Setting
PackWISE: Datensatz zur Instanzsegmentierung von Verpackungsabfällen für Training und Evaluation von Modellen
PackWISE: Packaging Waste Instance Segmentation Dataset for Model Training and Evaluation
Intelligent Blade Bearing Amplitude Control
Development of a methodology for the creation of digital twins of rotor blade bearings for condition monitoring
Measurement data and python scripts for machine learning models of the friction torque in a test rig for scaled blade bearings ("BEAT1.1"). Measurement data is given as .parquet-files for several different bearing combinations. A Jupyter Notebook for the models is included.
Data for the prediction of the friction torque of scaled blade bearings in a test rig using machine learning
IGD Fraunhofer-Institut für Graphische Datenverarbeitung
Object motion estimation is crucial for tasks like traffic monitoring and animal behavior analysis. However, existing methods typically rely on complex workflows involving spatial projections, coordinate transformations, camera calibration, and model stacking. This increases system complexity, reduces generalization capabilities, and leads to speed estimation susceptible to cumulative front-end errors. To address this, we propose the Physics-based Uniform Particle Space speed Estimation Network (PUPSENet), which predicts objects real-world speed frame-by-frame without requiring calibration or explicit geometric reconstruction. Furthermore, as existing datasets focus solely on planar vehicle motion, we introduce the AquaMotion synthetic dataset to expand the diversity of available resources for speed estimation research. Experiments on AquaMotion and real fish datasets demonstrate that PUPSENet significantly reduces error and enhances robustness, while it achieves competitive performance on the real vehicle scenario. Its lightweight, scene-agnostic end-to-end architecture operates stably across diverse environments, providing a practical and scalable solution for real-time motion analysis.
Introducing a Physics-Based Uniform Particle Space for 3D Motion Estimation from Consecutive Frames
Ganzheitliche Energieeffizienzregelung für versorgungstechnische Anlagen der industriellen Produktion
The data set contains a simulation of a cooling plant, data from this simulation and some detailed optimization results.
Chiller System Simulation and Optimization
Accompanying datasets to the article "A novel non-invasive, non-conductive method for measuring Respiration" published in the Journal of Sensors and Sensor Systems by the same authors as this data sets.
A novel non-invasive, non-conductive method for measuring respiration
The two datasets are supplement to the publication Manz, Pia; Fleiter, Tobias; Eichhammer, Wolfang: "The effect of low-carbon processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis" (https://doi.org/10.1016/j.segy.2023.100103). Excess heat from industrial processes can be utilized in district heating networks, thereby reducing the primary energy demand and possibly CO2 emissions for district heating generation. Many studies found a substantial potential of industrial excess heat; however, they did not systematically consider the potential future changes in the energy system that will affect the potential excess heat utilization. Industrial production will transform to low-carbon processes and district heating needs to be generated without fossil fuels. Here, we quantify industrial excess heat by spatial matching for the EU-27, considering the impact of the transformation to a climate-neutral energy system. In a first step, excess heat potentials from energy-intensive industries are identified as point sources, taking into account process changes. In a subsequent step, the excess heat potentials are spatially matched to district heating areas with a GIS-based approach. The results show, that available excess heat will reduce significantly due to industry transformation. At the same time, the utilization potential could be increased by lower district heating system temperatures and by an expansion of district heating areas, resulting in 3 - 36 TWh/a. Locally, there is a significant contribution of industrial excess heat in the future, even though the major share will need to be supplied by renewables.
Journal paper publication: Manz, P; Fleiter, T.; Eichhammer, W.: The effect of climate-neutral processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis, Smart Energy, 2023 https://doi.org/10.1016/j.segy.2023.100103
The effect of low-carbon processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis
IGCV Fraunhofer-Einrichtung für Gießerei-, Composite- und Verarbeitungstechnik
Mittelstand 4.0-Kompetenzzentrum Augsburg
Ergänzende Informationen (u. a. Vorlagen, Checklisten) und Hilfsdokumente für den "Leitfaden für den ortsflexiblen Einsatz von kollaborativen Robotern".
Zusatzdokumente für "Leitfaden für den ortsflexiblen Einsatz von kollaborativen Robotern"
This compilation presents final and preliminary written reports from hydrofracturing tests carried out between 1986 and 1995 in six, now abandoned, coal mines and two coal bed methane boreholes at depths between 600 and 1950 m within the greater Ruhr region in western Germany.
Reports from Hydrofracturing Tests Performed in the Greater Ruhr Region (Germany) between 1986 and 1995
Multidisciplinary Digital Publishing Institute
To cite this dataset, please reference: Beck, M.; Maier, G.; Flitter, M.; Gruna, R.; Längle, T.; Heizmann, M.; Beyerer, J. An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection. Sensors 2021, 21, 6143. https://doi.org/10.3390/s21186143
Datasets used in the research article "An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection". The datasets provided contain the pre-processed data for the wooden balls and beans dataset referred to in the article. If you are interested in the unprocessed raw data, please contact the corresponding author.
Datasets for research article "An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection". Sensors 2021, 21, 6143
Dynamic Vision Sensor Data for Visual Inspection Tasks
IEE Fraunhofer-Institut für Energiewirtschaft und Energiesystemtechnik
Förderbereich 3.7 „Energetische Nutzung biogener Rest- und Abfallstoffe“
Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase
Daten, die in eine technische und wirtschaftliche Simulation eingeflossen sind. Kontext ist das Forschungsprojekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase. Der Abschlussbericht wird bei der TIB veröffentlicht.
Daten zum Projekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase
Die Daten entsprechen den zugrundeliegenden Messdaten der Veröffentlichung Thieltges, S., Youssef, S. & Hartmann, U. Reconstruction of the Ferromagnetic Hysteresis in the Rayleigh Regime by Means of Impedance Analysis of the Excitation Coil. J Nondestruct Eval 43, 37 (2024) nach dem darin beschriebenen experimentellen Aufbau.
Messdaten zur Bestimmung der ferromagnetischen Hysterese an 20MnMoNi5-5 und 22NiMoCr3-7 im Rayleigh-Regime
Technoökonomische und regulatorische Potenzialanalyse der deutschen Vor-Ort-Versorgung im europäischen Vergleich
This open Data set provides a reference energy community profile set for further scenario analysis. The aim is to reuse the same power flow data set in various follow up studies to facilitate the comparison of different energy community setups.
Synthetic Reference Energy Community load profiles for artificial case studies
IWS Fraunhofer-Institut für Werkstoff- und Strahltechnik
Das Archiv enthält eine tabellarische Übersicht von Messdaten zur Doktorarbeit "Dotierungen von tetraedrisch amorphem Kohlenstoff zur Steigerung der Schadenstoleranz und der Temperaturstabilität" von Martin Zawischa
Archiv der Primärdaten zur Doktorarbeit "Dotierungen von tetraedrisch amorphem Kohlenstoff zur Steigerung der Schadenstoleranz und der Temperaturstabilität"
Archive of primary data for the doctoral thesis "Doping of tetrahedral amorphous carbon to increase damage tolerance and temperature stability"
IVI Fraunhofer-Institut für Verkehrs- und Infrastruktursysteme
The INFRA-3DRC Dataset is a public dataset comprised of 3D automotive Radar and RGB camera data generated using an intelligent roadside infrastructure (also known as smart infrastructure) setup. This work is supported by the Bavarian Ministry of Economic Affairs, Regional Development and Energy (StMWi), Germany within the Project “InFra — Intelligent Infrastructure.”
6. Energieforschungsprogramm der Bundesregierung "Forschung für eine umweltschonende, zuverlässige und bezahlbare Energieversorgung"
Inline imaging methods for next generation solar cells
The data contains the electro- and photoluminescence, and transflection images of 120 multicrystalline silicon passivated emitter and rear solar cells (mc-Si PERC cells) and their current-voltage parameters. The images are neither scaled, nor aligned, rotated, or cropped. The data belongs to a scientific publication on crack detection, further information can be found in the publication by Greulich et al., IEEE Journal of Photovoltaics (2020) (to be published).
Comparison of inline crack detection systems for multicrystalline silicon solar cells: Images and current-voltage data
Flooding is an increasingly common global threat, causing emergencies and severe damage to infrastructure. During crises, organisations like the World Food Programme use remotely sensed images, typically obtained through drones, for rapid situational analysis to plan life-saving actions. Computer Vision tools are needed to support task force experts on-site in the evaluation of the imagery to improve their efficiency and to allocate resources strategically. We introduce the BlessemFlood21 dataset to stimulate research on efficient flood detection tools. The imagery was acquired during the 2021 Erftstadt-Blessem flooding event and consists of high-resolution and georeferenced RGB-NIR images. In the resulting RGB dataset the images are supplemented with detailed water masks, obtained via a semi-supervised human-in-the-loop technique, where in particular the NIR information is leveraged to classify pixels as either water or non-water. We evaluate our dataset by training and testing established Deep Learning models for semantic segmentation. We provide with BlessemFlood21 labelled high-resolution RGB data and a baseline for further development of algorithmic solutions tailored to floodwater detection in RGB imagery.
BlessemFlood21: Advancing Flood Analysis with a high-resolution georeferenced dataset for humanitarian aid support
IME-AE Fraunhofer-Institut für Molekularbiologie und Angewandte Oekologie
Förderung von Nachwuchsgruppen in der Infektionsforschung
Screening of bioresources to identify novel antiviral substances to treat Influenza
Raw UHPLC‐MS/MS data for tolypin used in publication "Structural characterization and bioactivity profiling of the fungal peptaibiotic tolypin reveal protective effects against influenza viruses" Files are provided in Bruker format and in mzML format.
Structural characterization and bioactivity profiling of the fungal peptaibiotic tolypin reveal protective effects against influenza viruses
In der Umfrage zu Künstlicher Intelligenz geht es um die Nutzung von KI-Systemen und Einstellung der Bevölkerung zu künstlicher Intelligenz. Im Allgemeinen bezeichnet künstliche Intelligenz oder KI den Versuch, eine menschenähnliche Intelligenz nachzubilden, d. h., einen Computer zu bauen oder so zu programmieren, dass er eigenständig Probleme bearbeiten kann. Die Fragen richten sich auf Akzeptanz von KI-Systemen in verschiedenen Lebensbereichen und die Einschätzung von Chancen und Risiken der Nutzung von KI. Das Kompetenzzentrum Öffentliche Informationstechnologie (ÖFIT) versteht sich als Ansprechpartner und Denkfabrik für Fragen der öffentlichen IT und untersucht staatliche Gestaltungs- und Regulierungsanforderungen zur Digitalisierung im öffentlichen Raum. Es handelt sich bei dieser Veröffentlichung um Daten einer Bevölkerungsumfrage zu Digitalpolitik und digitalem Engagement, die von der GMS Dr. Jung GmbH Gesellschaft für Markt- und Sozialforschung im Auftrag des Kompetenzzentrums Öffentliche IT (ÖFIT) von November bis Dezember 2017 durchgeführt wurden. Mit der Veröffentlichung der Umfragedaten wollen wir diese der Forschungsgemeinschaft zur Nachnutzung für weitere Forschungszwecke bereitstellen.
Smart-Glass-based Assistance Systems for Machine Tools
The present data sets were created and published within the project "Glassist - Smart-Glass-based Assistance System for Machine Tools". The project is being carried out in collaboration with the project partners Nuromedia GmbH, Oculavis GmbH, Innolite GmbH and Starrag Technology GmbH. The data sets can be assigned to series of experiments. The individual experiments were carried out with a process-integrated measuring system on a machine tool under process parameter variations. In an attached documentation, the data sets are described in detail and notes on interpretation are presented.
Reference data sets for the detection of anomalies in the manufacturing process of cutting machine tools
Referenzdatensätze zur Erkennung von Anomalien im Fertigungsprozess von spanenden Werkzeugmaschinen
The data serve as a supplement to the publication Data Catalogs in the Enterprise: Applications and Integration. It includes a table listing the data catalog offerings surveyed, their application class and commercial characteristics, and a table detailing the questions, approach, and results of the data catalog integration survey.
Supplementary material for publication in Datenbank-Spektrum
Data Catalogs in the Enterprise: Applications and Integration
ITEM Fraunhofer-Institut für Toxikologie und Experimentelle Medizin
Supplementary Material
Threshold of Toxicological Concern—An Update for Non-Genotoxic Carcinogens
Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen, einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase
Quellcode einer technischen und wirtschaftlichen Simulation. Kontext ist das Forschungsprojekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase. Der Abschlussbericht wird bei der TIB veröffentlicht.
Quellcode zur Simulation im Projekt (BGA-PtG)2: Ganzheitliche Bewertung der Integration von Power-to-Gas-Konzepten in Biogas- und Biomethananlagen einschließlich der Entwicklung von Geschäftsmodellen für regenerative Gase
IMTE Fraunhofer-Einrichtung für Individualisierte und Zellbasierte Medizintechnik
The simulation framework in this dataset is intended for use in research related to search and rescue operations. It contains terrain-based movement simulation of a lost person in the Wadden Sea, probability map generation methods, search patterns and search metrics for a UAV.
Probability maps and search strategies for automated UAV search in the Wadden Sea: simulation data.
Datenmanagment mit Wissengraphen und Ontologien zur Optimierung der Additiven Fertigung
It uses Basic Formal Ontology as a Top- and Common Core Ontologies as Mid-Level-Ontologies. Fraunhofer IGCV Manufacturing Application Ontology is used as direct import."^^xsd:string , "This ontology, created for use at Fraunhofer IGCV, includes essential classes specifically relevant to Project ODE_AM within the domain of Additive Manufacturing. It is designed with the capability for successive expansions to accommodate future developments and additional requirements in this field."^^xsd:string , "This ontology, designed for use in data management within the Fraunhofer IGCV's project-specific web-app, includes only those classes that are directly relevant to the project's needs. It primarily integrates existing classes from the Basic Formal Ontology (BFO) and the Common Core Ontologies (CCO), selectively chosen to fit the considered use cases in our project. This focused approach ensures efficient and relevant data categorization and retrieval tailored to our specific project requirements.
Ontologies for FAIR Data in Additive Manufacturing
Supplementary data to the design and integration of the digital holographic 3-D sensor HoloPort: Interferometric vibration measurements inside a machine tool, evaluations of the sensor's data processing and transfer speed, temperature stability and exemplary application measurements inside a machine tool.
HoloPort – design and integration of a digital holographic 3-D sensor in machine tools
FIT Fraunhofer-Institut für Angewandte Informationstechnik
This data set contains the measurement data for the dissertation "The analysis of fluorescence fluctuations by means of the mean single-molecule rate (mSMR)." The measurement data are stored as Python pickle objects (.pkl). The Python scripts for reading the data, for the analysis as well as for the generation of the plots are attached to the data set.
The analysis of fluorescence fluctuations by means of the mean single-molecule rate (mSMR) [source data]
Dataset for Development of Algorithms for Object Detection and Tracking Using Sensor Data Fusion of Infrared Image and Radar Point Cloud in Traffic Analysis.
FlexSense Infrastructure Sensor Dataset: Road Side Infrared Image and 4D Radar Point Cloud for Traffic Analysis
The dataset includes a COMSOL model that replicates the experimental setup used for characterizing ferromagnetic hysteresis. Based on this model, synthetic training data were generated and used to create a surrogate model within COMSOL. This surrogate model was integrated into a MATLAB script that also processes experimental measurement data. The script performs an inverse identification of the Jiles–Atherton parameters using a Differential Evolution algorithm. This approach enables a model-based reconstruction of the ferromagnetic hysteresis curve for the investigated material.
Inverse Bestimmung der Jiles-Atherton-Parameter durch Optimierung (Differential-Evolution) und Surrogatmodellierung
IAIS Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme
The growing interest in free and open-source software which occurred over the last decades has accelerated the usage of versioning systems to help developers collaborating together in the same projects. As a consequence, specific tools such as git and specialized open-source on-line platforms gained importance. In this study, we introduce and share SemanGit which provides a resource at the crossroads of both Semantic Web and git web-based version control systems. SemanGit is actually the first collection of linked data extracted from GitHub based on a git ontology we designed and extended to include specific GitHub features. In this article, we present the dataset, describe the extraction process according to the ontology, show some promising analyses of the data and outline how SemanGit could be linked with external datasets or enriched with new sources to allow for more complex analyses.
This data sets contains the documentation (in German) of the second round of workshops (action plan workshops) that were carried out by Fraunhofer ISI within the EU project JERRI (Joining Efforts for Responsible Research and Innovation). The second round of workshops were dedicated to develop action plans (roadmaps) for several Responsible Research and Innovation (RRI) key dimensions (ethics, gender, open access, societal engagement). The documentation outlines about how the former developed RRI long-term goals can be achieved at Fraunhofer and which measures are needed to fulfill these goals. The results of these workshops were also used for the Deliverable D4.2 'Transformative RRI action plan for Fraunhofer'.
JERRI Action plan workshop documentation FhG
Flexible aktive Sensormatrix für medizinische Anwendungen
Recorded video data of abdominal movement of preterm neonates (clinical study, approval ID: 8584_BO_S_2019) using a time-of-flight camera. In the clinical study, five frame sequences at a duration of 90 s each were acquired with each of five preterm neonates (a total of 25 sequences) at a frame rate of 45 fps
Detection of Breathing Movements of Preterm Neonates by Recording Their Abdominal Movements with a Time-of-Flight Camera
Fördernummer (Förderperiode 2018/19): ITI1 - 17000/11#2
In dieser Umfrage geht es um die Haltung der Befragten zu neuen Technologien, insbesondere um die Nutzung und Erfahrung mit intelligent vernetzten Geräten im Haushalt, also Smart Home bzw. Ambient Assisted Living Anwendungen in verschiedenen privaten Einsatzbereichen. Nutzer:inner von Smart Home Anwendungen wurden nach der Wichtigkeit verschiedener Kaufkritierien befragt. Nicht-Nutzer:innen von Smart Home Anwendungen wurden nach Gründen für die Nicht-Nutzung befragt. Für die Umfrage wird neben dem Datensatz (in zwei Versionen: sowohl mit Werten als auch mit Label) der Fragebogen mit dem Codeschema bereitgestellt. Zusätzlich werden die vom Dienstleister verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
ICT Fraunhofer-Institut für Chemische Technologie
hydrogen for Bremen´s industrial transformation
Das Projekt "hyBit - hydrogen for Bremen`s industrial Information" untersucht die Wasserstofftransformation der Bremer Industrie. Ein Aspekt des Projektes ist die zukünftige Anwendung thermischer Kältemaschinen im Bremer Fernwärmenetz. Im AP 4.1.3 „Kältebereitstellung“ wurde das Ziel formuliert, eine potenzielle Kälteerzeugung aus zusätzlicher industrieller Abwärme oder Fernwärme unter technischen und wirtschaftlichen Aspekten zu untersuchen. Hierzu wurde ein Python-Modell zur Abbildung der Kältemaschinen mit Zero-Order Modellen erstellt. Die Verwendung von Zero-Order Modellen reduziert die Anzahl der erforderlichen Parameter deutlich, während die Genauigkeit bei der einzelnen Maschine ausreichend für das Gesamtergebnis ist, das durch die Summe vieler Einzelfälle entsteht. Das Modell ist einfach zu bedienen und kann der Öffentlichkeit zur Verfügung gestellt werden. Außerdem besteht die Möglichkeit der Verwendung von Daten aus anderen Modellen wie beispielsweise WEnDI, um die Vorhersage an ein spezielles (Typ-) Gebäude anzupassen. Die direkte Kopplung mit den Energiedaten aus WEnDI würde eine gleichzeitige Aussage der Eignung für eine große Anzahl an Typgebäuden liefern.
The project "hyBit - hydrogen for Bremen's industrial information" is investigating the hydrogen transformation of Bremen's industry. One aspect of the project is the future application of thermal refrigeration machines in Bremen's district heating network. In AP 4.1.3 "Kaeltebereitstellung" the goal was formulated to investigate the potential for refrigeration generation from additional industrial waste heat or district heating from a technical and economic perspective. For this purpose, a Python model was created to map the refrigeration machines using zero-order models. The use of zero-order models significantly reduces the number of parameters required, while the accuracy for the individual machine is sufficient for the overall result, which is obtained by summing many individual cases. The model is easy to use and can be made available to the public. It is also possible to use data from other models, such as WEnDI, to adapt the prediction to a specific (type of) building. Direct coupling with the energy data from WEnDI would provide a simultaneous statement of suitability for a large number of building types.
Model for assessing the suitability of thermal refrigeration machines
Modell zur Abschätzung der Eignung von thermischen Kältemaschinen
Adaptive, lernende Systeme - Für eine verständlicheInteraktion zwischen Mensch und komplexer Technik
Intelligente soft-robotische Arm/Hand/Finger-Orthese mit kontinuierlicher Kinematik
This dataset consists of 360 minutes of synchronized video and motion data gathered using a wearable sensor vest equipped with 4 IMUs (one on each upper arm, two on the chest). The data represents about 282 repetitions of a cyclical industrial assembly task performed by 5 different participants. The data has been annotated using six mid-level actions and a null class. The class representation is highly imbalanced, as is the total amount of cycles each participant has recorded.
This source code is meant to support the understanding of our paper Hybrid quantum transfer learning for crack image classification on NISQ hardware. Quantum computers possess the potential to process data using a remarkably reduced number of qubits compared to conventional bits, as per theoretical foundations. However, recent experiments have indicated that the practical feasibility of retrieving an image from its quantum encoded version is currently limited to very small image sizes. Despite this constraint, variational quantum machine learning algorithms can still be employed in the current noisy intermediate scale quantum (NISQ) era. An example is a hybrid quantum machine learning approach for edge detection. In our study, we present an application of quantum transfer learning for detecting cracks in gray value images. We compare the performance and training time of PennyLane’s standard qubits with IBM’s qasm_simulator and real backends, offering insights into their execution efficiency.
Hybrid quantum transfer learning for crack image classification on NISQ hardware
Prototyping the most energy and cost efficient data center in the world: The Boden Type Data Center — BodenTypeDC’
The BodenType Data Center One has been operational since January 2019. The data center has 3 PODS which are configured with slight variations in the fresh air-based cooling systems. The datasets that have been collected since operation commenced in PODs 1 and 3 with the operational period from the perspective of data collection using the database system and DCIM system installed and described in D5.1 being from 5th March 2019 to 2nd March 2020 inclusive, so 52 weeks, 364 days and 8,736 hours. The datasets for POD 1 comprehensively include energy, temperature, relative humidity, fan speeds, average server chip temperatures, average server fan speeds, percentage server utilization and dew point. The POD 3 datasets include average server power consumption and percentage fan speeds, but the period of operation is shorter than POD 1, being only from 26th April 2019 to 24th February 2020 inclusive. The data set also includes weather data over the full 364-day period. Two sets of data are to be made available. The first is an excel spreadsheet with the finest time resolution being for hourly averaged data, but the data is for all 364 days, so 8,736 hours. The second data set is the full data collected during the 9 sets of 5-day test campaigns and a further 9 sets of 6-day test campaigns with a resolution of measured data values being between 15 and 30 seconds resulting in a large data set.
BodenType Data Center One - Performance Measurements
Verbesserte Blechumformsimulation durch 3D-Werkstoffmodelle und erweiterte Schalenformulierungen - Teil 2
Verbesserte Blechumformsimulation durch 3D-Werkstoffmodelle und erweiterte Schalenformulierungen
Data for "Machine learning-based sampling of virtual experiments within the full stress state to identify parameters of anisotropic yield models" by A. Wessel, L. Morand, A. Butz, D. Helm and W. Volk.
Data for "Machine learning-based sampling of virtual experiments within the full stress state to identify parameters of anisotropic yield models"
In der Umfrage geht es um emotionale Assoziationen zu automatisierten Entscheidungen durch Maschinen im Vergleich zu Entscheidungen durch Menschen ebenso wie um die Bewertung des Einsatzes von Künstlicher Intelligenz im Gemeinwesen hinsichtlich positiver oder negativer Effekte auf die Gesellschaft. Für die Umfrage werden neben den Datensätze (sowohl mit Werten als auch mit Label) die Fragebögen mit dem Codeschema bereitgestellt. Zusätzlich werden die von GMS verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
Künstliche Intelligenz, Emotionen und Gemeinwesen
The dataset accompanies the publication "Microstructure quality control of steels using deep learning" and contains images used for a round-robin test where multiple metallographers rated images with respect to the present microstructure and grain size.
Korngrößenklassifizierung Ringversuch Datensatz
Grain size classification round-robin dataset
This publication contains two datasets of particle flow within representative unit cells, generated using the simulation software SimPARTIX (https://www.simpartix.com/). The datasets are used for evaluating a graph-based interaction-aware particle trajectory prediction model, as detailed in the paper available at https://arxiv.org/pdf/2503.00215. The first dataset, "raw_data_simple_periodic_BC.tgz", includes a unit cell calculation with simple periodic boundary conditions and a sinusoidal velocity profile. The second dataset, "raw_data_Lees-Edwards_BC.tgz", includes a unit cell calculation utilizing Lees-Edwards boundary conditions.
Discrete element simulation datasets of particle flow in representative unit cells
This data set contains the results from interviews with researchers from several European Research and Technology Organisations (RTOs). The interviews were conducted within the EU JERRI project and are analyzing existing good RRI practices at several RTOs.
Data collected during the evaluation of the paper "Smarter Evolution: Enhancing Evolutionary Black Box Fuzzing with Adaptive Models". In our publication, we presented an approach to bridge the gap between existing gray box fuzzing strategies and the real-world black box setting of fuzzing industrial control systems. This repository contains the data that was generated during our evaluation and was used to generate the corresponding figures in our paper. The Jupyter Notebook that we used to generate the figures based on this dataset can be found on GitHub: https://github.com/anneborcherding/Smarter-Evolution
Smarter Evolution: Enhancing Evolutionary Black Box Fuzzing with Adaptive Models
This repository provides the full source code and datasets used to compare multiple Jiles–Atherton (JA) hysteresis model variants, including Jiles86, Jiles92, Jiles94, Bergqvist96, Annakkage00, Cheng18, and Xue22. The material contains the numerical framework for computing complete B(H) cycles using a Runge–Kutta integration scheme, the stability assessment across 300 consecutive cycles, and the RMSE-based evaluation of convergence behavior under soft- and hard-magnetic parameter sets. The code enables full reproducibility of the model comparison, including parameter handling, cycle generation, and visualization tools.
Comparative Analysis and Numerical Stability Assessment of Jiles-Atherton Model Variants (Source Code Release)
IST Fraunhofer-Institut für Schicht- und Oberflächentechnik
Materialien für Nachhaltige Tandemsolarzellen mit höchster Umwandlungseffizienz
Combining spectrophotometry, variable angle spectroscopic ellipsometry, and X-ray reflectometry with an algorithm that simultaneously fits all available spectra we determine the complex refractive index of evaporated Spiro-TTB and C60 layers
Complex refractive indices of Spiro-TTB and C60
IKTS Fraunhofer-Institut für Keramische Technologien und Systeme
This item contains data from experiments.
Unraveling processes in an AWE with reference electrodes and EIS
The CovidRestrict project collected data on mobility-related restrictions that were adopted by the governments of six German Federal States in the first wave of the COVID-19 pandemic (01 January - 31 July 2020). The data also discerns between stringency levels of these regulations.
CovidRestrict: mobility restrictions in German Federal States in 2020
Das Team‐Arbeit‐Kontext‐Analyse Inventar nach Hagemann et al. dient zur Erhebung des Arbeitskontextes von High-Responsibility-Teams.
The Team Work Context Analysis Inventory (Hagemann et al.) is designed to assess the work context of high responsibility teams.
TAKAI Team‐Arbeit‐Kontext‐Analyse Inventar
In dieser Umfrage geht es um die Haltung der Befragen zur (digitalen) öffentlichen Verwaltung und dabei insbesondere um das „Once Only“-Prinzip, also die Idee, dass Bürger:innen ihre Daten nur einmalig an die Verwaltung übermitteln und diese dann zwischen unterschiedlichen Akteuren ausgetauscht werden. Die Fragen drehen sich um die Akzeptanz von Once Only, die Freigabe von Informationen an Unternehmen sowie die Wünsche bezüglich Transparenz und Kontrolle über den Datenfluss. Es werden Unterschiede in der Akzeptanz hinsichtlich verschiedener Arten persönlicher Daten, bspw. Finanzdaten oder Gesundheitsdaten, sowie hinsichtlich verschiedener Szenarien, bspw. Umzüge oder Geburten, abgefragt. Für die Umfrage wird neben dem Datensatz (in zwei Versionen: sowohl mit Werten als auch mit Label) auch der Fragebogen mit dem Codeschema bereitgestellt. Zusätzlich werden die vom Dienstleister verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
IRB Fraunhofer-Informationszentrum Raum und Bau
This data set contains data from a survey on research data management which was conducted within the Fraunhofer-Gesellschaft. The survey was carried out c between 3rd March 2017 and 21th March 2017. The Survey was one result of the project FORDATIS – Forschungsdateninfrastruktur. The aim of this project was to establish an infrastructure for research data management at the Fraunhofer-Gesellschaft. Researchers, information managers, and IT managers of all institutes of the Fraunhofer-Gesellschaft were invited to take part in the survey. The aim was to find out how research data is handled at the institutes, and which services already exist in the field of research data management, and to identify further requirements. A total of 235 questionnaires were evaluated, 182 by scientists, 34 by technical information managers and 19 by IT managers. The dataset consists of four parts: 1) the questionnaire underlying the survey 2) the answers to closed questions (raw data) 3) the answers to free questions (raw data, anonymized) 4) a compilation of all results. Answers and comments on the free text fields are included here.
Der vorliegende Datensatz enthält Daten aus einer Umfrage, die innerhalb der Fraunhofer-Gesellschaft zum Thema Forschungsdatenmanagement durchgeführt wurde. Die Umfrage wurde zwischen dem 07.03.2017 und dem 22.03.2017 durchgeführt. Sie ist ein Ergebnis des Projekts FORDATIS – Forschungsdateninfrastruktur, das sich mit dem Aufbau einer Forschungsdateninfrastruktur in der Fraunhofer-Gesellschaft befasste. Befragt wurden Wissenschaftlerinnen und Wissenschaftler, Fachinformationsmanager und IT-Manager aller Institute der Fraunhofer-Gesellschaft. Ziel war es herauszufinden, wie mit Forschungsdaten an den Instituten umgegangen wird, welche Services es im Bereich Forschungsdatenmanagement bereits gibt, und welche weiteren Bedarfe bestehen. Insgesamt wurden 235 Fragebögen ausgewertet, 182 davon von Wissenschaftlern, 34 von Fachinformationsmanagern und 19 von IT-Managern. Der Forschungsdatensatz besteht aus vier Teilen: 1) dem Fragebogen, der der Umfrage zu Grunde liegt 2) die Antworten auf geschlossene Fragen (Rohdaten) 3) die Antworten auf freie Fragen (Rohdaten, anonymisiert) 4) eine Zusammenstellung aller Ergebnisse. Antworten und Kommentare zu den Freitext-Feldern sind hier in Auswahl enthalten.
Forschungsdatenmanagement in der Fraunhofer-Gesellschaft
Research data management within Fraunhofer-Gesellschaft
A dataset composed of experimental and computational data for microstructure-sensitive fatigue modeling. Micromechanical fatigue testing in the very high cycle fatigue regime, complementary analytical techniques (SEM, EBSD), multimodal data registration, deep learning damage segmentation, and crystal plasticity finite element method techniques were applied to create this dataset.
Experimental and Computational Micromechanical Fatigue Damage Initiation Data
Ein KI-basiertes Framework für die Visualisierung und Auswertung der massiven Datenmengen der 4D-Tomographie für Endanwender von Beamlines
Gaining understanding of process-structure-property relationships in materials at a mechanistic level relies on correlative microscopy workflows. These workflows, in turn, fundamentally depend on image matching, i.e., a computer vision task with the objective of finding point correspondences in pairs of images. Matching models are difficult to evaluate quantitatively in the materials field due to a shortage of representative benchmark datasets. Nonetheless, a few small-scale studies indicate that traditional rule-based image matching techniques such as surface-invariant feature transform currently fall short on such matching tasks. We present a dataset for cross-modal image matching and data fusion in the materials microscopy domain, which we coin AmalgaMatch, to support model benchmarking and fine-tuning efforts. All images are micrographs captured using the most widely applied imaging techniques in materials science including light-optical, scanning electron, and transmission electron microscopy, as well as electron backscatter diffraction. Therein, various detectors and imaging modes are employed to capture micrographs of diverse materials. While the majority of images are raw images, some underwent typical processing routes using digital image correlation or EBSD indexing. Common regions in image pairs are populated with hand-annotated keypoint correspondences. While mutual information is limited in cross-modal, multi-scale image pairs, we relied on characteristic defects such as dislocations, grain boundaries, triple junctions, inclusions, pores or surface features for annotation. Furthermore, the dataset is divided into groups and subsets with distinct registration tasks, materials, and/or, imaging configurations representing splitting criteria. The dataset covers many typical use cases for image matching in materials science. In total, it comprises 19 subsets with 35 scenes and 187 annotated image pairs to support autonomous multi-modal materials data fusion. For each image, we provide metadata to facilitate training of hybrid matching models which process textual alongside image-based inputs to improve the matching quality and robustness.
AmalgaMatch: A Correlative Microscopy Dataset for Multimodal Data Fusion and Image Matching in Materials Science
Reliable Bio-based Refinery Intermediates
In the H2020-project BioMates (www.biomates.eu, Grant Agreement No. 727463), Fraunhofer UMSICHT produced samples from ablative fast pyrolysis of herbaceous biomass in a TRL 4-plant. A dedicated document provides identifiers for relevant liquid samples and their blends (DOI: 10.24406/fordatis/156). The document at hand maps it to the substances reported to be used in the deliverables connected to Work Package 1 “Novel pyrolysis oil from non-food/feed biomass” of the BioMates-project.
BioMates-Deliverable D1.2 "Advanced-AFP products from straw & miscanthus", Version 02 - https://s.fhg.de/BioMates-Cordis-D01-02
BioMates-Deliverable D1.1 "Straight-run AFP products from straw & miscanthus", Version 01 - https://s.fhg.de/BioMates-Cordis-D01-01
BioMates - Mapping of samples – Deliverables in WP1: Novel pyrolysis oil from non-food/feed biomass
BioMates - Probenzuordnung - Deliverables in Arbeitspaket 1: Neuartiges Pyrolyseöl aus Biomasse ohne Futter- und Nahrungskonkurrenz
IISB Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie
ICT-25/2015: Generic micro- and nano-electronic technologies
Ion-irradiation-induced Si Nanodot Self-Assembly for Hybrid SET-CMOS Technology
Within the European Project IONS4SET a compact model for a single electron transistor (SET) was developed. The SET is formed by a silicon nanodot embedded in a silicon dioxide layer between two highly doped silicon electrodes. Here, the implementation of the compact model in HSPICE is provided for circuit simulation. In addition, a VBA implementation into Excel is provided which can be used to calculate circuit characterisitcs and stability diagrams.
Kompaktmodell für einen Einzelelektronentransistor in einer geschichteten Nanosäule - Implementierungen in HSPICE und EXCEL/VBA
Compact Model for a Silicon Single Electron Transistor in a Stacked Nanopillar - Implementations in HSPICE and EXCEL/VBA
IKS Fraunhofer-Institut für Kognitive Systeme
Sichere KI am Beispiel fahrerloser Regionalzug
Supplementary material for the evaluation section of a publication at EDCC 2024. The data consists of four images: "1-taxonomy.png" shows a taxonomy of variability in the railway domain. "2-contextual-SCT.png" shows a contextual safety concept tree to argue the fulfillment of the safety goal "No train derailments". The sub-tree that is used in the earlier parts of the paper is marked in grey. "3-context-assumption-formulas.png" shows the refinements of the contextual assumptions used in the contextual safety concept tree, based on elements from the taxonomy of variability. "4-odd_definition.png" shows the mathematical definition of three Operational Design Domains for an Automated Train Operation System, again referencing the taxonomy of variability.
Automatic Deduction of the Impact of Context Variability on System Safety Goals - Supplementary Material for EDCC 2024 Paper
IAO Fraunhofer-Institut für Arbeitswirtschaft und Organisation
Experimenteller Wohnungs- und Städtebau (ExWoSt)
Digitale Stadt gemeinwohlorientiert gestalten durch kommunale Datenkompetenzen
Bundesinstitut für Bau-, Stadt- und Raumforschung BBSR (Deutschland)
Abbildungen zu und Arbeithilfen für die Entwicklung kommunaler Datenkompetenz
Vorgehensmodell und Referenzrahmen für strategisches Handeln - ein Handlungsleitfaden für die kommunale Praxis
Datenkompetenz in kommunalen Verwaltungen
The data set contains the results from interviews that were carried as part of the International Case Studies for the JERRI project. The interviews aimed to analyse RRI-related practices at the Arizona State University (ASU), to learn from their experiences as inputs for shaping the transformation process of FhG and TNO towards RRI.
Accelerating Innovation in Microfabricated Medical Devices
Raw data of the experiments for a capacitive sensor for microfluidic applications, (capacitance sensor and scale data), videos showing a mixing process inside the channel.
Supplementary Materials for Capacitive Dosing using an Alternating Drive Mechanism and Micro Pumps
IAF Fraunhofer-Institut für Angewandte Festkörperphysik
Data presented in the figures of the research article and Supplementary Materials of: Magnetic-field-dependent stimulated emission from nitrogen-vacancy centres in diamond
Data sets for paper and SM: Magnetic-field-dependent stimulated emission from nitrogen-vacancy centres in diamond
Rettungsleitstellen sehen sich mit steigenden Herausforderungen durch kontinuierlich steigende Notrufzahlen konfrontiert. Zur besseren Strukturierung und Priorisierung der Notrufgespräche werden vielerorts standardisierte Abfragesysteme implementiert. Aktuelle Entwicklungen im Bereich der künstlichen Intelligenz eröffnen neue Möglichkeiten der Entscheidungsunterstützung von Disponierenden. Voraussetzung hierfür ist ein prozesshaftes Modell des Notrufdialogs. Anbei finden sich das Zusatzmaterial zur Forschung.
The reasons for calls in medical emergencies: Development of a structured semantic model based on a randomised sample of medical assistance calls from an integrated rescue coordination centre
Anrufgründe bei medizinischen Notfällen: Entwicklung eines strukturierten semantischen Modells auf Basis einer randomisierten Stichprobe medizinischer Hilfeersuche einer integrierten Rettungsleitstelle
In der Umfrage zu digitalen Kompetenzen geht es allgemein um die Nutzung von Internet Anwendungen im Internet, wie häufig das Internet für verschiedene Zwecke genutzt wird, Emotionen bei der Nutzung des Internets, um die Selbsteinschätzung zu digitalen Kompetenzen und um Informationsquellen über die Nutzung von Internetanwendungen. Das Kompetenzzentrum Öffentliche Informationstechnologie (ÖFIT) versteht sich als Ansprechpartner und Denkfabrik für Fragen der öffentlichen IT und untersucht staatliche Gestaltungs- und Regulierungsanforderungen zur Digitalisierung im öffentlichen Raum. Es handelt sich bei dieser Veröffentlichung um Daten einer Bevölkerungsumfrage zu Digitalpolitik und digitalem Engagement, die von der GMS Dr. Jung GmbH Gesellschaft für Markt- und Sozialforschung im Auftrag des Kompetenzzentrums Öffentliche IT (ÖFIT) von November bis Dezember 2017 durchgeführt wurden. Mit der Veröffentlichung der Umfragedaten wollen wir diese der Forschungsgemeinschaft zur Nachnutzung für weitere Forschungszwecke bereitstellen.
SCAI Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen
This is the synthetic dataset from the paper: Jochen Garcke, Sara Hahner, and Rodrigo Iza-Teran. "Alignment of Highly Resolved Time-Dependent Experimental and Simulated Crash Test Data". In: International Journal of Crashworthiness. The work compares highly resolved experimental data with corresponding simulation data. The dataset contains one component from several completed frontal crash simulations of a Chevrolet C2500 pick-up truck model (from National Crash Analysis Center (NCAC)). Additionally, we provide our LiDAR measurements of the component. The data, which is provided here, is described in detail in section 5.3 of the paper.
Truck Component Simulation Meshes and Synthetic LiDAR Measurements
Forschung und Entwicklung von Fähigkeiten im Hinblick auf existenzbedrohende Risiken aus dem Cyber- und Informationsraum für Hochsicherheit in sicherheitskritischen und verteidigungsrelevanten Szenarien (HSK)
Graphen-basierte Informationsaggregation zur Verbesserung des Cybersicherheitsmanagements in kritischen Infrastrukturen
Personas erstellt im Rahmen des MANTRA Projektes (Graphen-basierte Informationsaggregation zur Verbesserung des Cybersicherheitsmanagements in kritischen Infrastrukturen). Die Personas wurden erstellt auf der Basis von Interviews mit Expert:innen und potenziellen Anwender:innen der MANTRA Lösung.
Personas created as part of the MANTRA project (graph-based information aggregation to improve cybersecurity management in critical infrastructures). The personas were created on the basis of interviews with experts and potential users of the MANTRA solution.
MANTRA: Graphen-basierte Informationsaggregation zur Verbesserung des Cybersicherheitsmanagements in kritischen Infrastrukturen
MANTRA: Graph-based information aggregation to improve cybersecurity management in critical infrastructures
Personas aus dem Forschungsprojekt MANTRA
Personas from the MANTRA research project
This publication contains a set of 76980 samples of crystallographic textures (as lists of orientations) and corresponding properties (Youngs modulus E and an anisotropy measure R*, similar to the Lankford coefficients, in three room directions). The data originates from a simulated multi-step metal forming process. The simulation was constrained to perform seven successive process steps of 10% strain at the material point in different directions. In each step, the orientation of the tension operation is chosen randomly from a set of 25 uniformly distributed orientations in the orientation space SO(3).
Crystallographic texture-property data set originating from a simulated multi-step metal forming process
FKIE Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie
This dataset supplements the paper "Approaching Domain Generalisation with Embeddings for Robust Discrimination and Recognition of RF Communication Signals" and is composed as follows: (1) The file "synthetic.zip" contains a total of 4,000 synthetically generated signals, created from 1,000 distinct synthetic wireless protocols. For each protocol, 4 signal examples were generated, each consisting of 16,384 samples. These signals represent the training data used for the RF signal embedding models. (2) The file "vuorenmaa.zip" contains signal bursts of various types extracted from the dataset "Radio-Frequency Control and Video Signal Recordings of Drones" (https://doi.org/10.5281/zenodo.4264467; Authors: Miika Vuorenmaa, Jaakko Marin, Mikko Heino, Matias Turunen, & Taneli Riihonen; License: CC BY 4.0 - https://creativecommons.org/licenses/by/4.0/) and is part 1/3 of the evaluation data. (3) The file "basak.zip" contains signal bursts of various types extracted from the dataset "Drone RF Dataset" (https://doi.org/10.48804/HZRVNZ; Authors: Sanjoy Basak, Sofie Pollin & Bart Scheers; License: CC BY-NC 4.0 - https://creativecommons.org/licenses/by-nc/4.0/) and is part 2/3 of the evaluation data. (4) The files "files_train.json" and "files_eval.json" contain the splitting of the evaluation dataset used in section "4.2. Downstream classification task" of the paper. (5) The file "plot_spectrograms.py" shows how to access the signal data using Python and visualizes the training and evaluation data. For the script to work, the contents of all *.zip files must be unzipped and located in the same folder as the Python script and the *.json files. NOTE: Part 3/3 of the evaluation data has been moved to a separate dataset (https://fordatis.fraunhofer.de/handle/fordatis/461) due to incompatible licences.
Dieser Datensatz ergänzt das Paper „Approaching Domain Generalisation with Embeddings for Robust Discrimination and Recognition of RF Communication Signals“ und setzt sich wie folgt zusammen: (1) Die Datei „synthetic.zip“ enthält insgesamt 4.000 synthetisch erzeugte Signale, die aus 1.000 verschiedenen synthetischen Funkprotokollen erstellt wurden. Für jedes Protokoll wurden 4 Signalbeispiele erzeugt, die jeweils aus 16.384 Samples bestehen. Diese Signale repräsentieren die Trainingsdaten, die für die RF-Signaleinbettungsmodelle verwendet werden. (2) Die Datei „vuorenmaa.zip“ enthält Signalbursts verschiedener Typen, die aus dem Datensatz „Radio-Frequency Control and Video Signal Recordings of Drones“ (https://doi.org/10.5281/zenodo.4264467; Autoren: Miika Vuorenmaa, Jaakko Marin, Mikko Heino, Matias Turunen, & Taneli Riihonen; Lizenz: CC BY 4.0 - https://creativecommons.org/licenses/by/4.0/) und ist Teil 1/3 der Evaluierungsdaten. (3) Die Datei „basak.zip“ enthält Signalbursts verschiedener Typen, die aus dem Datensatz „Drone RF Dataset“ (https://doi.org/10.48804/HZRVNZ; Autoren: Sanjoy Basak, Sofie Pollin & Bart Scheers; Lizenz: CC BY-NC 4.0 - https://creativecommons.org/licenses/by-nc/4.0/) und ist Teil 2/3 der Evaluierungsdaten. (4) Die Dateien „files_train.json“ und „files_eval.json“ enthalten die Aufteilung des Evaluierungsdatensatzes, der in Abschnitt "4.2. Downstream classification task" des Papers verwendet wird. (5) Die Datei „plot_spectrograms.py“ zeigt, wie man mit Python auf die Signaldaten zugreift und visualisiert die Trainings- und Evaluierungsdaten. Damit das Skript funktioniert, muss der Inhalt aller *.zip Dateien extrahiert und in demselben Ordner platziert werden, in dem sich das Python-Skript sowie die *.json Dateien befinden. ANMERKUNG: Teil 3/3 der Evaluierungsdaten wurde in einen separaten Datensatz (https://fordatis.fraunhofer.de/handle/fordatis/461) wegen Lizenz-Inkompabilitäten ausgelagert.
RF Communication Signal Dataset for Wireless Protocol Recognition based on Deep Embeddings (Part I)
Verbundprojekt: VIADUCT - Aufwandsverkleinerung von KI Anwendungen in der Industrie durch Reduzierung von Trainingsdaten
VIADUCT data set provides 49 categories of industrial objects with corresponding 135 defect categories.
VIADUCT: Multisector data set for Visual Industrial Anomaly Detection
Verbundvorhaben EnArgus 3.0 - KI-gestütztes Informationssystem Energieforschungsförderung - KI und Ontologie
This dataset contains 15 German question-answer sets from the domain of energy research. Each question has four possible answers: three generated by LLMs, and one written by a human domain expert.
Evaluating vector-based search and question answering approaches for an information system (QA Dataset)
In the H2020-project BioMates (www.biomates.eu, Grant Agreement No. 727463), Fraunhofer UMSICHT produced samples from ablative fast pyrolysis (AFP) of herbaceous biomass in a TRL 4-plant. A dedicated document provides identifiers for relevant liquid samples and their blends (DOI: 10.24406/fordatis/156). The document at hand maps it to the AFP-derived substances reported to be used in the article "T. Schulzke, S. Conrad, B. Shumeiko, M. Auersvald, D. Kubička, L. F. J. M. Raymakers; Fuels from Reliable Bio-based Refinery Intermediates: BioMates; Waste and Biomass Valorization (2020) 11:579–598; DOI:10.1007/s12649-019-00625-w", and provides further identifiers for samples not indexed earlier.
Mapping of samples – Fuels from Reliable Bio-based Refinery Intermediates: BioMates, Schulzke et al., 2020, DOI:10.1007/s12649-019-00625-w
This data set contains the results from interviews with TNO members concerning barriers and enablers of organisational change towards Responsible Research and Innovation.
WKI Fraunhofer-Institut für Holzforschung Wilhelm-Klauditz-Institut
Altholzgewinnung aus Sperrmüll durch Künstliche Intelligenz und Bildverarbeitung im VIS-, IR- und Terahertz-Bereich
Bundesministerium für Ernährung und Landwirtschaft BMEL (Deutschland)
The dataset contains 44 hyperspectral near-infrared images of bulky waste samples. For each hyperspectral image, there is also an RGB and a label image assigning one of 9 classes to each pixel. The majority of samples are crushed furniture from IKEA and the other objects are from a real waste plant or self-collected bulky waste. Details of the file structure are given in "readme.txt" of the provided dataset. The measurements are part of the work described in https://publica.fraunhofer.de/entities/publication/dde5f89c-f87b-4644-b084-f4edf66c4b19/details
Including class labels and registered RGB images
Inklusive Klassenlabels und registrierte RGB-Bilder
Hyperspektraler nahinfrarot Datensatz von Sperrmüll
Hyperspectral Near-infrared Dataset of Bulky Waste
In der Umfrage zu Plattformen und Privatheit geht es um die Nutzungsgewohnheiten und Einstellungen zu digitalen Plattformen, um Einstellungen und Erfahrungen zum Schutz der Privatsphäre und Vorkehrung zum Datenschutz sowie das Vertrauen in verschiedene Institutionen. Das Kompetenzzentrum Öffentliche Informationstechnologie (ÖFIT) versteht sich als Ansprechpartner und Denkfabrik für Fragen der öffentlichen IT und untersucht staatliche Gestaltungs- und Regulierungsanforderungen zur Digitalisierung im öffentlichen Raum. Es handelt sich bei dieser Veröffentlichung um Daten einer Bevölkerungsumfrage zu Digitalpolitik und digitalem Engagement, die von der GMS Dr. Jung GmbH Gesellschaft für Markt- und Sozialforschung im Auftrag des Kompetenzzentrums Öffentliche IT (ÖFIT) von November bis Dezember 2017 durchgeführt wurden. Mit der Veröffentlichung der Umfragedaten wollen wir diese der Forschungsgemeinschaft zur Nachnutzung für weitere Forschungszwecke bereitstellen.
Richtlinie über die Förderung der Einrichtung von Experimentierfeldern als Zukunftsbetriebe und Zukunftsregionen der Digitalisierung in der Landwirtschaft
Smarte Automatisierungssysteme und -services für den Obstanbau an der Niederelbe
This dataset captures the bloom stage of Elstar Moje-Feindt apple trees in a commercial orchard located in the Altes Land region of northern Germany during the 2024 growing season. The apple trees, planted in 2017, are arranged in a narrow spindle system with a spacing of approximately 1 meter. Data collection was carried out on April 15, 2024, at 10:59 AM under light drizzle conditions and lasted for 8 minutes and 32 seconds, with both sides of the row of 238 apple trees being traversed at an average speed of 3.5 km/h. The dataset was recorded using a ground-based multisensor platform and includes raw data from high-resolution 20MP Basler cameras at a frame rate of 5 fps, 128-layer LiDAR data at a frequency of 10 Hz, IMU data at 500 Hz, and RTK GNSS data at 10 Hz.
Dieser Datensatz erfasst die Blütephase von Elstar Moje-Feindt Apfelbäumen in einer kommerziellen Obstplantage in der Region Altes Land in Norddeutschland während der Wachstumsperiode 2024. Die Apfelbäume, die 2017 gepflanzt wurden, sind in einem schmalen Spindelsystem mit einem Abstand von etwa 1 Meter angeordnet. Die Datenerfassung fand am 15. April 2024 um 10:59 Uhr bei leichtem Nieselregen statt und dauerte 8 Minuten und 32 Sekunden. Die Reihe mit 238 Apfelbäumen wurde dabei von beiden Seiten mit einer Durchschnittsgeschwindigkeit von 3,5 km/h durchfahren. Der Datensatz wurde mit einer bodengestützten Multisensor-Plattform aufgezeichnet und umfasst Rohdaten von hochauflösenden 20MP Basler-Kameras mit einer Bildrate von 5 fps, einem 128-Schicht LiDAR mit einer Frequenz von 10 Hz, IMU-Daten mit 500 Hz und RTK GNSS-Daten mit 10 Hz.
Captured in the Altes Land Region, Northern Germany in Spring 2024
Multisensor Dataset of Elstar Moje-Feindt Apple Trees During Bloom Stage
Multisensor-Datensatz von Elstar Moje-Feindt Apfelbäumen während der Blütephase
Zukunft der Wertschöpfung - Forschung zu Produktion, Dienstleistung und Arbeit
Vernetzung der Akteure zur disziplinübergreifenden Entwicklung komplexer vernetzter soziotechnischer Systeme für die Wertschöpfung von morgen
Die Tabelle enthält eine Validierung & Verifizierung des ASE Kompetenzmodells aus dem Forschungsprojekt AdWiSE anhand eines use cases in der Medizintechnik. Die Daten wurden vom Unternehmen OSYPKA AG in mehreren Expert:inneninterviews iterativ erarbeitet und analysieren die Umsetzung sowie geplante Maßnahmen zur zukünftigen Umsetzung der 6 ASE Kompetenzen im Unternehmen.
Forschungsdaten zur Veröffentlichung "Definition eines Kompetenzmodells für nachhaltiges Engineering im Advanced Systems Engineering"
Definition eines Kompetenzmodells für nachhaltiges Engineering im Advanced Systems Engineering, TDSE 2024 (to be published)
Forschungsdaten zum use case "Implementierung von ASE in einem Medizintechnik-Unternehmen"
Defining a competence model for sustainable engineering in Advanced Systems Engineering
This repository contains a dataset of images featuring concrete panels, designed to support research and development in image-based analysis and defect detection. The dataset is divided into two main categories: crack images with corresponding masks, and crack images without masks, which include both crack and no-crack images.
This data set contains the documentation of the first International Mutual Learning Workshop that was carried out within the JERRI project.
First International Mutual Learning Workshop Documentation
Entwicklung neuer Biosorbenzien zur Spurenstoffelimination aus kommunalem Abwasser
Environmental pollution by man-made toxic and persistent organic compounds, found throughout the world in surface and groundwater, has various negative effects on aquatic life systems and even humans. Therefore, it is important to develop and improve water treatment technologies capable of removing such substances from wastewater or purifying drinking water. The two substances investigated are the widely used painkiller diclofenac and a member of the class of "forever chemicals", perfluorobutane sulfonate, both of which are known to have serious negative effects on living organisms, especially under long-term exposure. In this study, a human hair keratin dimer is investigated for its ability to absorb diclofenac and perfluorobutane sulfonate. Initial predictions for binding sites are obtained via molecular docking and subjected to molecular dynamics simulations for more than 1µs. The binding affinities obtained by the linear interaction energy method are high enough to motivate further research on human hair keratins as a sustainable, low-cost, and easily allocatable filtration material.
K35/K85 structure, and Diclofenac and PFBS force field parameters
This dataset supplements the dataset "RF Communication Signal Dataset for Wireless Protocol Recognition based on Deep Embeddings (Part I)" (https://fordatis.fraunhofer.de/handle/fordatis/460) and is part 3/3 of the evaluation data. The file "iqengine.zip" contains (1) signal bursts extracted from "bluetooth.sigmf-data" (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/bluetooth; Author: Jacob Gilbert; License: CC BY-SA 4.0 - https://creativecommons.org/licenses/by-sa/4.0/), (2) signal bursts extracted from "dect6.sigmf-data" (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/dect6; Author: Jacob Gilbert; License: CC BY-SA 4.0 - https://creativecommons.org/licenses/by-sa/4.0/), and (3) signal bursts extracted from "rfd900p.sigmf-data" (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/rfd900p; Author: Unknown; License: Unknown).
Dieser Datensatz ergänzt den Datensatz „RF Communication Signal Dataset for Wireless Protocol Recognition based on Deep Embeddings (Part I)“ (https://fordatis.fraunhofer.de/handle/fordatis/460) und ist Teil 3/3 der Evaluierungsdaten. Die Datei „iqengine.zip“ enthält (1) Signalbursts, extrahiert aus „bluetooth.sigmf-data“ (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/bluetooth; Autor: Jacob Gilbert; Lizenz: CC BY-SA 4.0 - https://creativecommons.org/licenses/by-sa/4.0/), (2) Signalbursts, die aus „dect6.sigmf-data“ extrahiert wurden (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/dect6; Autor: Jacob Gilbert; Lizenz: CC BY-SA 4.0 - https://creativecommons.org/licenses/by-sa/4.0/), und (3) Signalbursts extrahiert aus „rfd900p.sigmf-data“ (https://iqengine.org/view/api/us-east-1/iqengine-gnuradio/rfd900p; Autor: Unbekannt; Lizenz: Unbekannt).
RF Communication Signal Dataset for Wireless Protocol Recognition based on Deep Embeddings (Part II)
Die Befragung umfasst verschiedene Aspekte der digitalen Lebensgewohnheiten. Es werden Fragen zur Internet- und Smartphone-Nutzung gestellt, die Einstellung gegenüber digitalen Technologien abgefragt und das Nutzungsverhalten im Privatleben beleuchtet. Themen wie Online-Shopping, digitale Kulturveranstaltungen, politische Inhalte (Bundestagswahl) in der digitalen Kommunikation und die Bedeutung von Medien für die Meinungsbildung während der Pandemie werden untersucht. Die Umfrage adressiert auch die Nutzung digitaler Verwaltungsangebote, das mobile Arbeiten, ehrenamtliches Engagement sowie die Freigabe persönlicher Daten im Internet. Digitale Kompetenzen, insbesondere das Verständnis von App-Einstellungen auf Smartphones, werden ebenfalls abgefragt. Insgesamt bietet die Befragung einen umfassenden Einblick in die digitale Lebenswelt der Teilnehmenden und ihre Haltung gegenüber digitalen Technologien. Für die Umfrage wird neben dem Datensatz (in zwei Versionen: sowohl mit Werten als auch mit Label) auch der Fragebogen mit dem Codeschema bereitgestellt. Zusätzlich werden die vom Dienstleister verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
Seismische Überwachung und Charakterisierung von drei geothermischen Fallstudienstandorten
This is an archived version of version 0.1 with small updates from 26.10.2023. The latest version can be found at: https://github.com/cl-finger/B3Ampy A Matlab Version of this code can be found at https://github.com/katrinloer/B3AM
B3AMpy: Beamforming Toolbox for three-component ambient seismic noise
Fish motion is a very important indicator of various health conditions of fish swarms in the fish farming industry. Many researchers have successfully analyzed fish motion information with the help of special sensors or computer vision, but their research results were either limited to few robotic fishes for ground-truth reasons or restricted to 2D space. Therefore, there is still a lack of methods that can accurately estimate the motion of a real fish swarm in 3D space. Here we present our Fish Motion Estimation (FME) algorithm that uses multi-object tracking, monocular depth estimation, and our novel post-processing approach to estimate fish motion in the world coordinate system. Our results show that the estimated fish motion approximates the ground truth very well and the achieved accuracy of 81.0% is sufficient for the use case of fish monitoring in fish farms.
Fish Motion Approximation using ML-based Relative Depth Estimation and Object Tracking
Verbundvorhaben KETEC: Forschungsplattform Kälte- und Energietechnik
Scripts for calculating adsorption chillers and adsorptive heat transformers with basic adsorption heat exchanger theory equations including examples. Scripts may be used with R 4.3.0 https://cran.r-project.org/bin/windows/base/ in combination with RStudio https://posit.co/products/open-source/rstudio/
Dazugehöriges Paper noch nicht erschienen. Eingereicht bei "Energy conversion and management" mit dem Titel "Utilizing Waste Heat from Data Centers with Adsorptive Heat Transformation"
Adsorptive Heat Transformation Calculation Scripts
Microphone raw data of the R134a detector
Miniaturized photoacoustic detection of organofluorine-based refrigerants
Maschinelle Lernverfahren für Stochastisch-Deterministische Sensorsignale
The dataset was created in order to be able to train machine learning models in the domain of wind energy, especially for the use cases of predictive maintenance / condition monitoring and anomaly detection. In the wind energy domain, one usually suffers from two main problems: Firstly, the lack of sufficiently many labeled data instances, especially for rarely occurring anomalous states. Secondly, the stochastic nature of the resulting measurements, as changing and turbulent environmental conditions lead to a lot of noise in the recorded sensor signals, which in turn makes the analysis of the data very hard. To this end, a synthetic wind turbine dataset has been created, which addresses these issues. The dataset allows to obtain a more controlled view than measurements in the field would yield, since for different fixed conditions of the wind turbine, simulations have been carried out for a various number of environmental conditions. The goal is to be able to learn data representations for different states of the wind turbine from the simulated data, which would not be possible on real measurements. Moreover, as the simulations can be carried out with a very high number of different sensor outputs, the dataset offers a possibility to uncover relations between different measurements / components of the wind turbine, which are not known yet. The dataset consists strictly of highdimensional time series as output of certain setups of a 5MW wind turbine. They represent various measurements of important characteristics, such as acceleration or bending moments, on the blades, the nacelle, or different parts of the wind turbine. The dataset is created to resemble different locations and degrees of mass imbalance on one of the three wind turbine blades.
FAST Wind Turbine simulations for mass and aerodynamic imbalance detection
Light-field (LF) imaging has various advantages over the traditional 2D photography, providing angular information of the real world scene by separately recording light rays in different directions. Despite the directional light information which enables new capabilities such as depth estimation, post-capture refocusing, and 3D modelling, currently available light-field datasets are very restricted in terms of spatial-resolution and dynamic range. In this work, we address this problem by capturing a novel light-field dataset featuring both a high spatial resolution and a high dynamic range (HDR). This dataset should enable the community to research and develop efficient reconstruction and tone-mapping algorithms for a hyper-realistic visual experience. The dataset consists of four static light-fields that are captured by a high-quality digital camera mounted on two precise linear axes using exposure bracketing at each view point.
TEDDY: A High-Resolution High Dynamic Range Light-Field Dataset
Dieser Datensatz enthält die Validierung einer Implementierung eines 5G-Systems als Wireless-Bridge in eine Time-Sensitive Networking (TSN) Infrastruktur. Diser Prototyp einer Integration von 5G in ein TSN-Netzwerk wurde erstellt, um die Leistung von 5G-TSN für industrielle Anwendungen zu bewerten. Der Aufbau wird im Paper »Prototype of 5G Integrated with TSN for Edge-Controlled Mobile Robotics« ausführlich erläutert.
This dataset presents a validation of an implementation of a 5G system with Time-Sensitive Networking (TSN). A prototype setup integrating 5G in a TSN network has been completed to evaluate the 5G-TSN performance for industrial applications. The setup is explained in details in the paper "Prototype of 5G Integrated with TSN for Edge-Controlled Mobile Robotics".
Prototyp zur Integration von 5G in TSN. Datenset
The three files are supplementary material to the study "Exploring residential space use patterns: Findings from a multi-country survey". They contain the survey questions, the validation process of the collected sample and the results of the hierarchical clustering.
Supplementary material to the study on exploring residential space use patterns
The published code performs a metal forming process simulation. The process consists of subsequent steps of uniaxial tension and compression, arbitrarily oriented to a reference coordinate system. The simulation is based on a Taylor-type crystal plasticity model. To run the simulation, Intel Fortran libraries are needed.
Simulation of texture evolution for a multi-step metal forming process
Shared IoT Security, Teilvorhaben Entwurf und Entwicklung von Tools für drahtlose Netzwerksicherheit von IoT
Automated spectrum analysis serves as a troubleshooting tool that helps to diagnose faults in wireless networks like difficult signal propagation conditions as well as coexisting wireless networks. It provides a higher monitoring coverage while requiring less expertise compared to manual spectrum analysis. In this publication, we introduce a data set that can be used to train and evaluate a deep learning model, capable to detect frames of different wireless standards as well as interference between single frames. Since manually labelling a high variety of frames in different environments is too challenging, an artificial data generation pipeline has been developed. The data set consists of 20000 augmented signal segments, each containing a random number of different Wi-Fi and Bluetooth frames, their spectral image representations and labels that describe the position and type of frame within the spectrogram. The dataset contains results of intermediate processing steps that enables the research or teaching community to create new datasets for specific requirements or to provide new interesting examination examples.
Spectrogram Data Set for Deep Learning Based RF-Frame Detection
The Folgar Tucker model is an analytical model to predict the orientation of embedded particles within suspension under various kinds of deformation. The accuracy of the model is affected by a model parameter - the Folgar Tucker parameter. This dataset includes Folgar Tucker parameter that have been fitted against numerical simulations of suspension under three types of deformation that are shear, elongation or a combination of both. The simulations are performed in 2D with Smoothed Particle Hydrodynamic applying a two-way-coupling between the fluid and the solid phase. The suspension includes two types of different geometries that have either a disk shape or fiber shape. The suspension composition has been altered in terms of filling fractions of disks and fibers, size of the disks and the aspect ratio of the fibers. The Folgar Tucker model itself is precisely formulated but allows a certain degree of freedom with respect to the computation of the fourth order tensor. This fourth order tensor is often computed by a closure approximation. We show the fitted parameters for two closure approximations – the quadratic and hybrid closure.
Folgar Tucker constants fitted against simulations of various suspensions under shear and/or elongation
RGB Images of Post-Consumer LWP Waste in a Realistic Sorting Plant Setting
Supplementary datasets to the journal paper in excel format for results and GIS-datasets (raster and vector) for datasets
This survey is aimed at employees in the hotel, catering and tourism industries and deals with the opportunities offered by innovative technologies in specific work situations with a view to the next 3-5 years. The survey described possible applications of the technologies in pre-employment, employment, and post-employment phase. Respondents were asked to evaluate each application according to their personal opinion. They were asked to mentally put themselves in the specific situations.
Im Moment wird viel darüber gesprochen, wie Roboter und die Digitalisierung, die Arbeit in der Zukunft verändern werden. Technologien können viele neue Möglichkeiten bringen. Auch wenn wir heute immer noch an ganz normalen Arbeitsplätzen arbeiten, bieten uns die virtuellen Welten, also Computerwelten, ganz neue und interessante Wege, wie wir in der Zukunft arbeiten können. Diese Umfrage richtet sich an Mitarbeitende in Hotellerie, Gastronomie und im Tourismus und behandelt die Chancen von innovativen Technologien in konkreten Arbeitssituationen mit Blick auf die nächsten 3-5 Jahre.
Eine Umfrage des Fraunhofer IAO zu den Chancen von Technologieeinsatz für innovative Arbeitswelten in virtuellen Umgebungen
Umfrage zur Arbeitswelt der Zukunft – Neue Arbeitssituationen in Hotellerie, Gastronomie und Tourismus mithilfe innovativer Technologien
Survey on the future world of work – New work situations in the hotel, catering, and tourism industries with the help of innovative technologies
This geospatial dataset presents real-world locations (latitude, longitude) of potential heavy-duty truck parking locations in Europe (EU-27, EFTA, UK). Coverage and completeness varies among countries. GPS coordinates may not match exact locations but should be considered as reference point for detailed local analyses of ambient conditions and truck parking suitability. Fraunhofer ISI does not assume any liability for completeness, correctness and accuracy of the information. Such a real-world dataset is invaluable when designing future European infrastructures for low-carbon road freight transport, particularly charging infrastructure networks for battery-electric trucks in long-haul operation but also hydrogen refuelling station networks. Therefore, it is a valuable resource for researchers, industry representatives such as charging point operators and grid network operators, or public authorities. Details and references are provided in the .pdf document. More information is available upon request.
Hochtechnologien für das 21. Jahrhundert
Aktive, theranostische Blasenschließmuskeltechnologie
This dataset contains experimental data as a characterisation of piezoelectric micropumps and microvalves. Measurement data includes the actuator stroke measured using white light profilometry, as well as fluidic measurements of generated flow, passive flow, and leakage measured using coriflow flowmeters. Flow measurement data of normally open valves before and after 10^6 actuation cycles is supplied. An ANSYS 2019 R1 project file is given as part of an evaluation of a normally closed valve's spring foil. Associated with the simulation is experimental data of the pressure-dependant stroke of the normally closed valve's spring foil.
Experimental Characterisation and Simulation of Piezoelectric Titanium Micropumps and Titanium Microvalves
Experimentelle Charakterisierung und Simulation von piezoelektrischen Mikropumpen und Mikroventilen aus Titan
Regenerative und energieeffiziente Wärme- und Kältenutzung
Nachhaltige und zukunftssichere Wärmeversorgung für Gewächshäuser mit Wärmepumpen
This dataset is linked to the article submitted at ISEC 2024 "Sustainable Heat Supply for Greenhouses with Heatpumps". It contains: 1. weather data (hourly) from Test Reference Year 2011 in Straelen and 2. the hourly heat demand profile of the greenhouse that were used to simulate the different scenarios. The heat demand profile was calculated with Hortex using the same weather data and summarizes all 18 greenhouses of the considered company together in one value.
Sustainable Heat Supply for Greenhouses with Heatpumps presented at ISEC 2024 (DOI not yet available)
Sustainable Heat Supply for Greenhouses with Heatpumps - Dataset for the simulation
Die Umfrage befasst sich mit Sensoren im öffentlichen Raum wie bspw. Verkehrssensoren, Umweltsensoren oder Videokameras auf Plätzen oder Straßen. Teilnehmende bewerten ihre generelle Haltung gegenüber Sensoren und werden zu deren Wahrnehmung im öffentlichen Raum sowie zu ihrem Wissen über deren Arten und Funktionsweisen befragt. Ein besonderer Fokus liegt auf Kameras im öffentlichen Raum: Hierzu werden Meinungen zu Videoüberwachung, Sicherheit, Datenschutz und der Nutzung von Bilddaten erkundet. Themen wie die gewünschte Anzahl der Sensoren im öffentlichen Raum, die Bewertung von Maßnahmen um die Zustimmung zu Sensoren zu beeinflussen, sowie die Einstellung gegenüber und Nutzung von Wearables und Corona-bezogenen Apps werden ebenfalls behandelt. Die Umfrage endet mit Fragen zu persönlichen Erfahrungen und der Einschätzung der Nützlichkeit von Videoüberwachung in bestimmten Situationen. Für die Umfrage wird neben dem Datensatz (in zwei Versionen: sowohl mit Werten als auch mit Label) auch der Fragebogen mit dem Codeschema bereitgestellt. Zusätzlich werden die vom Dienstleister verfügbaren Angaben zu den Methoden der Datenvalidierung, Bereinigung und Gewichtung der Datensätze bereitgestellt.
European Training Network on Full Parallax Imaging
Light-field imaging provides full spatio-angular information of the real world by capturing the light rays in various directions. This allows image processing algorithms to result in immersive user experiences such as VR. To evaluate, and develop reconstruction algorithms, a precise and dense light-field dataset of the real world that can be used as ground truth is desirable. Fraunhofer IIS presents a dataset that includes two scenes that are captured by an accurate industrial robot with an attached color camera such that the camera is looking outward. The arm moves on a cylindrical path for a field of view of 125 degrees with angular step size of 0,01 degrees. The images are pre-processed in different steps. The disparity between two adjacent views with resolution of 5168x3448 is less than 1,6 pixels; the parallax between the foreground and the background objects is less than 0,6 pixels. The dataset is based on the paper "Non-planar inside-out dense light-field dataset and reconstruction pipeline" by Faezeh Sadat Zakeri, Ahmed Durmush, Matthias Ziegler, Michel Bätz, and Joachim Keinert.
Non-planar inside-out dense light-field dataset and reconstruction pipeline
SPELL - Semantische Plattform zur intelligenten Entscheidungs- und Einsatzunterstützung in Leitstellen und Lagezentren
The aim of the present study is to survey the technology commitment of dispatchers in fire and emergency centers, physicians and EMS professionals, and to develop a short scale for specific Technology Commitment with regard to intelligent systems, as they are to be developed and implemented in the SPELL project.
Technology commitment of high responsibility teams
The following data set contains meteorological data measured at the Fraunhofer Institute for Chemical Technology ICT in Pfinztal, Germany. The measured values are available with a resolution of 15 minutes and grouped by year. The measurements were taken with a certified WS700 weather station from Lufft. The individual measurements, their ranges and the corresponding units are described below. The station is used at the ICT for monitoring weather conditions during outdoor experiments. Each day's measurements are automatically stored as individual csv files on a data server. A manual download of the data sets took place on 06.06.2024. For better usability, the individual measurements were combined into a single dataset for an entire year. This was done using a Python script.
Wetterdaten des Fraunhofer Institute for Chemical Technology ICT in Pfinztal, Germany
Meteorological data from Fraunhofer Institute for Chemical Technology ICT in Pfinztal, Germany
Maschine Lernverfahren für Stochastisch-Deterministische Multi-Sensor Signale
This dataset consists of simulated acceleration signals representing the vibration response of a generic geared-rotor bearing system made of a rigid gearbox with a spur gear pair mounted on flexible shafts supported by rolling element bearings. The signals include a stochastic component simulating the varying load condition caused by wind turbulence. The data have been generated simulating two distinct gearbox health scenarios and two wind speed conditions. Specifically, signals represent a situation in which a perfectly healthy gearbox is modelled or a scenario in which one of the gears is damaged. The simulated damage consists of a cracked tooth in one of the two gears. Moreover, independently of the gearbox's health condition, we consider the two wind speed scenarios of 5 m/s and 13m/s. Further information on the data can be found in the 'Readme.md' file.
Bayerisches Staatsministerium für Wirtschaft, Landesentwicklung und Energie StMWi
Results for autonomous driving scenarios simulated with CARLA under different environment conditions.
Assured Resilience in Autonomous Systems – Supplementary Material
Alle während des BSFood-Projekts erhobenen Daten.
KI-Labor Systemdesign für Maschinelles Lernen in Anwendungen der Signalverarbeitung
This dataset is composed from three different scenes with a varying number of takes per scene. The images have been generated using CARLA, a framework for autonomeous driving. In the dataset, an autonomeous car is exploring an urban area under different lighting and weather conditions. In each take, the car is equipped with three front-facing cameras capturing the scenery. Besides pure RGB image data, the dataset features ground-truth depth information encoded as described here: https://carla.readthedocs.io/en/latest/ref_sensors/#depth-camera The camera parameters and capture setup is as follows: Field of view: 110° Resolution: 1920 x 1080 Number of takes: Scene 1: 41 Scene 2: 23 Scene 3: 20 Camera baseline Scene 1: 0.280833m (2.17m/12) Scene 2 and 3: 0.1m
Dataset for multi-camera depth reconstruction
List of available and outdated software solutions for life data analysis
Software solution for life data analysis
DeepQuali - Anwendung von Deep Learning auf Software-Repositories zur Qualitätsbewertung
This is the data for the paper "Can Large Language Models (LLMs) Compete with Human Requirements Reviewers? – Replication of an Inspection Experiment on Requirements Documents". It contains the source code of the experiment to make our work transparent and reproducible. Furthermore, it contains the evaluation results.
Can Large Language Models (LLMs) compete with Human Requirement Reviewers? - Replication of an Inspection Experiment on Requirements Documents
PCAPs of the paper "CrossTest: A cross-domain physical testbed environment for cybersecurity performance evaluations".
A cross-domain physical testbed environment for cybersecurity performance evaluations
Retrieval Augmented Generation (RAG) works as a backbone for interacting with an enterprise's own data via Conversational Question Answering (ConvQA). In a RAG system, a retriever fetches passages from a collection in response to a question, which are then included in the prompt of a large language model (LLM) for generating a natural language (NL) answer. However, several RAG systems today suffer from two shortcomings: (i) retrieved passages usually contain their raw text and lack appropriate document context, negatively impacting both retrieval and answering quality; and (ii) attribution strategies that explain answer generation typically rely only on similarity between the answer and the retrieved passages, thereby only generating plausible but not causal explanations. In this work, we demonstrate RAGONITE, a RAG system that remedies the above concerns by: (i) contextualizing evidence with source metadata and surrounding text; and (ii) computing counterfactual attribution, a causal explanation approach where the contribution of an evidence to an answer is determined by the similarity of the original response to the answer obtained by removing that evidence. To evaluate our proposals, we release a new benchmark ConfQuestions: it has 300 hand-created conversational questions, each in English and German, coupled with ground truth URLs, completed questions, and answers from 215 public Confluence pages. These documents are typical of enterprise wiki spaces with heterogeneous elements. Experiments with RAGONITE on ConfQuestions show the viability of our ideas: contextualization improves RAG performance, and counterfactual explanations outperform standard attribution.
Evidence Contextualization and Counterfactual Attribution for Conversational QA over Heterogeneous Data with RAG Systems
Piezoelektrische Metall-Mikromembranpumpe für Flüssigkeiten und Gase
This dataset contains experimental data as a characterisation of piezoelectric microvalves. Measurement data includes the actuator stroke measured using white light profilometry, as well as fluidic measurements of generated flow, passive flow, and leakage measured using coriflow flowmeters. Experimental data before and after 10^6 actuation cycles fatigue test is supplied. An COMSOL Multiphysics project file is given as part of an evaluation of a design parameter study as well as simulation results in form of csv data. Analytical modelling of leakage rates is implemented in python scripts and associated text files contain calculation results.
Experimental Characterization, FEA Simulation, and Analytical Modelling of Piezoelectric Microvalve with multiple Valve Seat Trenches
Experimentelle Charakterisierung, FEM Simulation und analytische Modellierung einer piezoelektrischen Mikroventils mit mehreren Ventilsitzgräben
The identification and location of critical defects inside battery cells before the performance decreases or safety issues arise remains a challenge. Here we show images acquired from Scanning Acoustic Microscopy (SAM) as a non-destructive testing methods for the 3D visualization of defects at different depths inside a pouch battery cell. A manufactured dummy pouch cell with 8 cathode sheets is used for this investigation. SAM using a 15 MHz transducer in reflection mode can detect defects with a lateral resolution of 150 µm in 2 min. The time intervals of each micrograph have a length of 30 ns. The images are acquired with a resolution of with a pixel dimension of 50 x 50 μm²/ pixel.
Scanning acoustic microscope images for the localization of defects inside dummy pouch cells
Optimizing neural 3D reconstruction rendering quality for small-sized objects
Neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS) use volumetric scene representations to achieve impressive visual results in the field of novel-view synthesis. However, traditional 3D pipelines are dominated by textured meshes, supported by hardware assisted rendering and a huge software ecosystem. We show that mesh-based workflows can also profit from those novel reconstruction methods by evaluating mesh reconstruction algorithms paired with view-dependent textures in terms of texture sharpness, surface accuracy and real-time rendering performance. For that purpose, we employ a modular 3D reconstruction pipeline and use it to benchmark not only publicly available data sets, but additionally four new high-quality data sets of our own. These data sets capture different objects containing both reflective and uniform surface characteristics.
Benchmarking Learnable Mesh and Texture Representations for Immersive Digital Twins
Complementary data for the paper "Bringing Light into the Darkness: Leveraging Hidden Markov Models for Blackbox Fuzzing" published at the 6th ACM/IEEE International Conference on Automation of Software Test (AST 2025). A Jupyter notebook for visualizing the data can be found here: https://github.com/anneborcherding/palpebratum
Bringing Light into the Darkness: Leveraging Hidden Markov Models for Blackbox Fuzzing
XPS / tribometer / mass spectrometer raw data supporting the publication "Gas phase lubrication study with an organic friction modifier"
Raw Data: Gas phase lubrication study with an organic friction modifier
Highly immersive virtual realities (VR) offer a variety of opportunities for simulation training. This article presents the approach of integrating a VR simulation environment into the practice of emergency paramedic education. The article concludes with the presentation of the results from an evaluation study.
Hochimmersive virtuelle Realitäten (VR) bieten vielfältige Möglichkeiten für das Simulationstraining. In diesem Beitrag wird die Vorgehensweise der Integration einer VR-Simulationsumgebung in die Praxis der Notfallsanitäterausbildung vorgestellt. Der Fachbeitrag schließt mit der Darstellung der Ergebnisse aus der Praxisstudie ab.
Virtual-Reality-Simulationstraining in der Notfallsanitäterausbildung
The research data refer to a formative project evaluation in the BMBF-funded project ViTAWiN.In addition to socio-demographic data from 41 participants, presence (Igroup Presence Questionnaire, Schubert et al.), simulator sickness (Sim. Sickn. Quest., Kennedy), situational motivation (Situational Motivation Scale, Guay) and usability (System Usability Scale, Brook) are recorded.
Multiprofessionelle Evaluation des Trainings von Auszubildenden im Beruf Notfallsanitäter:in und Teilnehmenden der Fachweiterbildung Notfallpflege in Extended Reality
Multi-professional evaluation of the training of paramedic trainees and participants of the advanced training in emergency care in extended reality
Sonderfinanzierung (Anschubfinanzierung)
Prototyping- und Test-Zentrum für Systeme der Künstlichen Intelligenz am Fraunhofer-Institutsteil Entwicklung Adaptiver Systeme (EAS) Dresden
This dataset represents a triaxial vibration dataset acquired during a face‑milling process under two distinct tool conditions (sharp and worn). Experiments were conducted on a 3‑axis CNC milling machine (VECTOR 850 M SI) using a 10 mm solid carbide end mill with 6 flutes, machining a flat steel workpiece in conventional face milling. The milling feed direction was aligned with the machine x‑axis. Cutting parameters were kept constant across both tool conditions: 60 % radial depth of cut, 2 mm axial depth of cut, spindle speed of 3500 rpm, and feed rate of 600 mm/min. Vibrations were measured with a Bosch BMI270 MEMS accelerometer mounted on the spindle housing. The sensor axes were aligned with the machine coordinate system (x: feed direction, y: transverse in‑plane, z: spindle axis). Triaxial acceleration signals were recorded as raw time series at a sampling frequency of 1600 Hz and are provided in units of g. The dataset consists of two NumPy .npy files, one for each tool condition: SharpTool_1600Hz_xyz.npy (sharp tool) and WornTool_1600Hz_xyz.npy (worn tool). Each file contains a 2D NumPy array of shape (n_samples, 3), corresponding to time samples and the three acceleration components (x, y, z). No additional label files are required, as the tool condition is encoded in the file name. The dataset is intended for developing and benchmarking signal processing and machine learning methods for tool wear detection and related diagnostics in milling operations.
Triaxial Vibration Data of a Milling Process: Sharp and Blunt Tool Condition
Files containing acceleration signals, representing the vibration response of the modelled gearbox for three full rotations of the shaft. S={5,13} indicates the wind (W) speed considered in the simulation, while X={h,cr} indicates the health condition. 'cr' indicates that the simulation includes the cracked tooth. On the contrary, 'h' indicates that the signal has been produced considering a healthy gearbox and not including damage. Y= {1,2,3} indicates the set of excitation parameters chosen to simulate the signal. The three different excitation parameters (ep) settings used for the experiments can be consulted in Table 4 of the paper. Z={10,13,16} relates to the different crack lengths simulated. Specifically, it indicates the percentage of the dimensionless stiffness function's decrease applied to simulate the tooth crack (tc).
Bundesministerium für Digitales und Verkehr BMDV (Deutschland)
CherrySet encompasses a collection of 2D images covering three sweet cherry trees at more than 10 distinct time points, spanning from dormancy in March through blooming and growth until harvest in July 2023. In addition to the image data, CherrySet offers manually recorded ground truth information obtained from reference branches throughout the growing season, which includes comprehensive bud, blossoms and fruit counts during all vegetation phases, as well as the total number of cherries gathered at harvest.
CherrySet - A comprehensive dataset of three cherry trees throughout the 2023 season
Übersicht über die einzelnen Prozessschritte des Datenmanagements sowie über die zugehörigen Arbeitshilfen.
Purpose: Anthropogenic activities are a major driver of soil and land degradation. Due to the spatial heterogeneity of soil properties and the global nature of most value chains, the modelling of the impacts of land use on soil quality for application in Life Cycle Assessment (LCA) requires a regionalised assessment with global coverage. This paper proposes an approach to quantify the impacts of land use, based on changes in soil organic carbon (SOC) stocks, following the latest recommendation of the Life Cycle Initiative. Methods: An operational set of SOC-based characterisation factors for land occupation and land transformation were derived using spatial datasets (1 km resolution) and aggregated at national and global level, by adopting an aggregation approach excluding those areas where a certain land use activity was not indicated in land use maps, to avoid the introduction of bias. The developed characterisation factors were tested by means of a case study analysis, investigating the impact on soil quality caused by land use activities necessary to provide three alternative energy supply systems for passenger car transport (biomethane, ethanol, and solar electricity). Results obtained by applying characterisation factors at local, regional and national level were compared, to investigate the role of the level of regionalisation on the resulting impacts. Results and discussion: Global maps of characterisation factors are presented for the 56 land use types commonly used in LCA databases, together with national and global values. Urban and industrial land uses present the highest impacts on SOC stocks, followed by severely degraded pastures and intensively managed arable lands. Instead, values obtained for extensive pastures, flooded crops, and urban green areas often report an increase in SOC stocks. Results show that the ranking of impacts of the three energy systems considered in the case study analysis is not affected by the level of regionalisation of the analysis. In the case of biomethane energy supply, impacts assessed using national characterisation factors are more than double those obtained with local characterisation factors, with less significant differences in the other two cases. Conclusions: The integration of soil quality aspects in life cycle impact assessment methods is a crucial challenge due to the key role of soil conservation in ensuring food security and environmental protection. This approach allows the quantification of land use impacts on SOC stocks, taken as a proxy of soil quality. Further research needs to improve the assessment of land use impacts in LCA are identified, such as the ability to reflect the effects of agricultural and forestry management practices.
Soil organic carbon of land use impacts in life cycle assessment
The data set comprises data from a representative empirical survey, in which the investment behaviour of private individuals (homeowners) in PV battery systems was investigated. A combination of questionnaire and Discrete Choice Experiment (DCE) was chosen. The DCE differentiated between persons who already own a PV system but no battery storage and persons without a PV system. The DCE was analyzed using Hierarchical Bayes. The values in the DCE Excel sheets are individual (partial) utility values. In addition to investment-relevant factors, data on personal attitudes and barriers to investment were collected.
Der Datensatz umfasst Daten einer repräsentativen empirischen Erhebung, bei der das Investitionsverhalten von Privatpersonen (Hauseigentümer*innen) in PV-Batteriesysteme untersucht wurde. Es wurde eine Kombination aus Fragebogen und Discrete Choice Experiment (DCE) gewählt. Dabei wurde im DCE in Personen, die bereits eine PV-Anlage aber keinen Batteriespeicher besitzen und Personen ohne PV-Anlage unterschieden. Das DCE wurde mittels Hierarchical Bayes ausgewertet. Die Werte in den DCE Excelblättern sind individuelle (Teil-) Nutzenwerte. Neben investitionsrelevanter Faktoren wurden Daten zu persönlichen Einstellungen und Hemmnissen bzgl. einer Investition erfasst.
Representative empirical survey and choice experiment on willingness to invest in PV battery systems
Repräsentative empirische Erhebung zur Investitionsbereitschaft in PV-Batteriesysteme
Measured microphone and NDIR detector signals
Towards a miniaturized photoacoustic sensor for application in transcutaneous CO2 monitoring
Visual surface inspection images of aluminum plates with defects and impurities present. Dataset was used to support study of influence of impurities on defect detection. Plates were inspected using a ring light and grayscale camera monted on a robotic manipulator.
Sequential PatchCore: Anomaly Detection for Surface Inspection using Synthetic Impurities
This data set contains the results of 9999 finite element simulations of cup drawing processes that are conducted using the commercial software Abaqus/Explicit. For each process simulation, the input parameters (material dependent parameters and process parameters) were varied randomly. The material parameters were chosen based on typical fluctuations in DC04 steel sheets and possible process parameter settings following literature and norms.
Simulation data set for deep drawing cups of DC04 steel sheets
Raw data and analysis results of the six experts of the analytical hierarchy process (AHP) expert survey. The expert survey was conducted for prioritising sub-criteria of the Simulation Decision Matrix (SDM). The SDM is primarily used for prioritising quality-critical product parameters of hydrogen technologies for simulation applications in their production process.
Simulation Decision Matrix_Analytical Hierarchy Process_data_expert survey
Test data for interlaminar shear strength (ILSS) tests conducted as per DIN EN ISO 14130 on Aluminium-CFRP hybrid specimens. The specimens were manufactured by bonding Aluminium plate and thermoplastic CFRP tapes together in a hot press process. An adhesion promoter was applied on the Aluminium surface to facilitate bonding process. The hybrid material plates such manufactured were then conditioned in a cyclic climatic test according to standard PV1200. Finally the specimens were cut in standard sizes with water jet cutting and tested for their interlaminar shear strength.
Interlaminar Shear Strength (ILSS) test results for aged Aluminium-CFRP (thermoplastic) hybrid specimens
This publication contains three exemplary data sets generated via active learning and numerical simulations. The active learning approach used is query-by-committee. For comparison, data is also generated using classical sampling approachs. The first data set originates from a toy example that is based on an appoximated Dirac delta function, for which data was generated randomly and via query-by-committee. The second example is part of a parameter identification problem in materials modeling, for which data was generated via Latin Hypercube design, a knowledge-based approach and query-by-committee. The third example is about generating artificial bcc rolling textures, for which data was generated via Latin Hypercube design, query-by-committee and an extended query-by-committee approach that prevents sampling in regions out of scope.
Sets of exemplary microstructure-property data generated via active learning and numerical simulations
NG2: StacIE Stack Scale up – Industrialisierung PEM Elektrolyse
This data set implies measurement data of two measurements done with laser ablation reference electrodes in a segmented Along the Channel cell for PEM water electrolysis.
Messdaten - Referenzelektroden in einer segmentierten Along the Channel PEM-Wasser-Elektrolysezelle
Measurement Data - Reference Electrodes in a segmented Along the Channel PEM Water Electrolysis Cell
The two datasets are supplement to the publication Manz, Pia; Fleiter, Tobias; Eichhammer, Wolfang: "The effect of low-carbon processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis" (to be published). Excess heat from industrial processes can be utilized in district heating networks, thereby reducing the primary energy demand and possibly CO2 emissions for district heating generation. Many studies found a substantial potential of industrial excess heat; however, they did not systematically consider the potential future changes in the energy system that will affect the potential excess heat utilization. Industrial production will transform to low-carbon processes and district heating needs to be generated without fossil fuels. Here, we quantify industrial excess heat by spatial matching for the EU-27, considering the impact of the transformation to a climate-neutral energy system. In a first step, excess heat potentials from energy-intensive industries are identified as point sources, taking into account process changes. In a subsequent step, the excess heat potentials are spatially matched to district heating areas with a GIS-based approach. The results show, that available excess heat will reduce significantly due to industry transformation. At the same time, the utilization potential could be increased by lower district heating system temperatures and by an expansion of district heating areas, resulting in 3 - 36 TWh/a. Locally, there is a significant contribution of industrial excess heat in the future, even though the major share will need to be supplied by renewables.
Journal paper publication: Manz, P; Fleiter, T.; Eichhammer, W.: The effect of climate-neutral processes on industrial excess heat potentials for district heating in the EU: a GIS-based analysis, Smart Energy, 2023 [under review]
Transparente und Selbstbestimmte Ausgestaltung der Datennutzung im Unternehmen
Nationales Referenzprojekt zur IT-Sicherheit in der Industrie 4.0
Results (primary data) of the experiment on matching user types of Dupree to different policy specification paradigms for achieving better effectiveness, efficiency and satisfaction in the context of privacy settings for SRA services.
Data for "Machine learning-based sampling of virtual experiments within the full stress state" by Alexander Wessel, Lukas Morand, Alexander Butz, Dirk Helm and Wolfram Volk.
Data for "Machine learning-based sampling of virtual experiments within the full stress state"
In der Umfrage zu Digitalpolitik und digitalem Engagement geht es um den digitalen Wandel und die Einschätzungen der Bevölkerung zur politischen Ausgestaltung der Digitalisierung. Es werden dabei verschiedene digitalpolitische Themen nach ihrer Relevanz bewertet und Ablehnung und Zustimmung zu verschiedenen digitalpolitischen Themen abgefragt. Im zweiten Teil der Umfrage folgen Fragen zu digitalem bürgerschaftlichem Engagement. Das Kompetenzzentrum Öffentliche Informationstechnologie (ÖFIT) versteht sich als Ansprechpartner und Denkfabrik für Fragen der öffentlichen IT und untersucht staatliche Gestaltungs- und Regulierungsanforderungen zur Digitalisierung im öffentlichen Raum. Es handelt sich bei dieser Veröffentlichung um Daten einer Bevölkerungsumfrage zu Digitalpolitik und digitalem Engagement, die von der GMS Dr. Jung GmbH Gesellschaft für Markt- und Sozialforschung im Auftrag des Kompetenzzentrums Öffentliche IT (ÖFIT) von November bis Dezember 2017 durchgeführt wurden. Mit der Veröffentlichung der Umfragedaten wollen wir diese der Forschungsgemeinschaft zur Nachnutzung für weitere Forschungszwecke bereitstellen.
The research data refer to a formative project evaluation in the BMBF-funded project ViTAWiN. In addition to socio-demographic data, presence (Igroup Presence Questionnaire, Schubert et al.), simulator sickness (Sim. Sickn. Quest. Kennedy), task and cognitive load (NASA TLX, Hart & Staveland), situational motivation (Situational Motivation Scale), Training Evaluation (Training Evaluation Inventory, Ritzmann et al.) and usability (System Usability Scale according to Brooke) are recorded.
Interprofessionelle Evaluation des Trainings von Auszubildenden im Beruf Notfallsanitäter:in und Teilnehmenden der Fachweiterbildung Notfallpflege in Extended Reality
Interprofessional evaluation of the training of paramedic trainees and participants of the advanced training in emergency care in extended reality
This source code is meant to support the understanding of our paper Improved FRQI on superconducting processors and its restrictions in the NISQ era. In image processing, the amount of data to be processed grows rapidly, in particular when dealing with images of more than two dimensions or time series of images. Thus, efficient processing is a challenge, as data sizes may push even supercomputers to their limits. Quantum image processing promises to encode images with logarithmically less qubits than classical pixels in the image. In theory, this is a huge progress, but so far not many experiments have been conducted in practice, in particular on real backends. Often, the precise conversion of classical data to quantum states, the exact implementation, and the interpretation of the measurements in the classical context are challenging. We investigate these practical questions in this paper. In particular, we study the feasibility of the flexible representation of quantum images (FRQI). Furthermore, we check experimentally the limit in the current noisy intermediate-scale quantum era, i.e., up to which image size an image can be encoded, both on simulators and on real backends. Finally, we propose a method for simplifying the circuits needed for the FRQI. With our alteration, the number of gates can be reduced, especially the one of the error-prone controlled-NOT gates. As a consequence, the size of manageable images increases.
Improved FRQI on superconducting processors and its restrictions in the NISQ era
We present a continuous seismic waveform dataset created with the rotated staggered-grid finite-difference simulator HeidimodX (Saenger et al., 2000). The aim of the dataset is to recreate the random nature of ambient seismic noise using numerous synthetic point sources with arbitrary source parameters and locations. Three-component waveforms are recorded at the free surface of a three-dimensional model with two different velocity structures. This dataset can be used to benchmark and test robustness of different methodologies typically applied to ambient noise data.
Synthetic ambient seismic noise dataset for testing ambient-noise methods
Neue Elektroniksysteme für intelligente Medizintechnik (Smart Health)
Mit dem in der Publikation beschriebenen Messsystemen generierte Rohdaten
Novel Test Bench for Inhaler Characterization Including Real-Time Determination of Output, Output Rate, and Liquid Water Content of Delivered Aerosols
The archive contains primary data for the doctoral dissertation "Scenario-based Derivation of Digital Ecosystem Requirements" by Matthias Koch. The data consists of study material and raw data of study results. Additionally, the source code for the tooling is included.
Archive of Primary Data for Doctoral Dissertation "Scenario-based Derivation of Digital Ecosystem Requirements"
The Industrial Objects in Varied Contexts (InVar) dataset was internally produced by our team and contains 100 objects in 20800 total images (208 images per class). The objects consist of common automotive, machine and robotics lab parts. Each class contains 4 sub-categories (52 images each) with different attributes and visual complexities. White background (Dwh): The object is against a clean white background and the object is clear, centred and in focus. Stationary Setup (Dst): These images are also taken against a clean background using a stationary camera setup, with uncentered objects at a constant distance. The images have lower DPI resolution with occasional cropping. Handheld (Dha): These images are taken with the user holding the objects, with occasional occluding. Cluttered background (Dcl): These images are taken with the object placed along with other objects from the lab in the background and with no occlusion. The dataset was produced to simulate the miscellaneous issues in industrial setups as discussed. The dataset was produced by our staff at different workstations and labs in Berlin. More details regarding the objects used for digitisation are available in the metadata file.
InVar-100: Industrial Objects in Varied Contexts Dataset
The compound [Ca24Al28O64]4+(4e-) named as C12A7:e- has outstanding properties because of a low work function (2.4-2.6 eV) and high electron conductivity due to a cage-like crystal structure. For the application of the material as hollow cathodes in small satellite propulsion systems, its preparation as sinterable glass-ceramics via the powder route is purposeful. The coefficient of thermal expansion CTE is between 4.2 and 6.0 × 10−6 K−1 (RT-1000°C).
Coefficient of thermal expansion (CTE) of C12A7:e- ceramic
Comparison of inline crack detection systems for multicrystalline silicon solar cells
Unternehmenslabore für Transformation und Change im Zusammenhang mit Künstlicher Intelligenz in der Arbeitswelt
Bundesministerium für Arbeit und Soziales BMAS (Deutschland)
Die vorliegenden Templates sind leichtgewichtige, praxisorientierte Werkzeuge für das Projektmanagement in datenbasierten Projekten. Sie ergänzen insbesondere den "Leitfaden zur Durchführung von KI-Projekten".
Templates zum Leitfaden zur Durchführung von KI-Projekten
Highly Accelerated Pitch Bearing Tests 2
This data set contains time series and additional information for a test program for pitch bearings of wind turbines. The program covers two distinct operational scenarios: the standstill of the bearing under rated speed and the active pitch cycles caused by the IPC. It is designed for rollerr-type pitch bearings, but can be applied to toher pitch bearings as well. It bases upon the aero-elastic simulation time series (see links).
Time Series of wear test for roller-type pitch bearings of wind turbines
A miter saw was equipped with a sensor node consisting of a wideband MEMS microphone, an accelerometer and an ultrasound transducer. Data has been collected for 4 different saw blades: two different sharp blades, one blunt and one demolished. There is reference data measured when the saw it off and when the saw is actively rotating, but not inside wood. The sawing data consists of dataset with narrow and wide wooden laths.
Eine Kappsäge wurde mit einem Sensorknoten aus Mikrofon, Accelerometer und Ultraschallsender ausgestattet. Es wurde Daten für 4 unterschiedliche Sägeblätter gesammelt: 2 neue, scharfe Blätter, 1 stumpfes und 1 durch einen Hammer demoliertes. Es wurden Referenzdaten für den Fall, dass die Säge aus ist und für den Fall, dass sich die Säge in der Luft dreht. Weiter wurden Schnitte an dünnen und breiten Holzlatten durchgeführt.
Dataset for AI-assisted classification of damaged saw blades on a miter saw using microphone, accelerometer and ultrasonic data
Datensatz zur KI-gestützten Klassifizierung von defekten Sägeblättern an einer Kappsäge mit Mikrofon-, Accelerometer- und Ultraschalldaten
Semantische Plattform zur intelligenten Entscheidungs- und Einsatzunterstützung
Introduction: AI is transforming various industries, especially healthcare and emergency services. For example, AI helps with clinical decision support, detects cardiac arrest and stroke during calls, and manages text-to-speech translation. On the human-centered side, the societal and personal impacts of AI and other technologies are significant but under-researched. Therefore, this study examines the belief systems of emergency dispatchers regarding AI applications. Methods: From September 2021 to September 2023, eight extensive interviews were conducted with a total of 31 individuals, lasting over 619 minutes. Following grounded theory, the interview guide was iteratively adapted to support theory development. Results: The interviews revealed a high level of commitment to their profession and a strong appreciation and interest in research. While many issues within public safety and answering points (PSAPs) and the healthcare system were identified, few concrete ideas for AI-based solutions were mentioned. In addition to the common assumption of high mental workload in emergency call centers and the need for AI systems to be understandable, there are notable differences in the belief systems of dispatchers and other experts. These differences often lead to a more negative attitude towards AI, which is influenced by job status, AI knowledge and qualifications. However, the ability to reflect can mitigate these limitations. AI can support dispatchers who have to handle complex tasks under time pressure, information deficits and uncertainty. Conclusion: In addition to the assumption of high mental workload and the need for understandable AI systems, dispatchers and other experts have different belief systems. These can lead to a negative attitude towards AI, which is influenced by job status, AI knowledge and qualifications, although reflection can help to mitigate this. AI can support dispatchers to handle complex tasks under pressure, information deficits and uncertainty. To prevent rejection of AI and raise awareness of its opportunities and risks, a comprehensive package of measures such as the one we have introduced is needed.
Attitude of Emergency Dispatchers Towards Artificial Intelligence – A Black Box of Expectations
The decomposition of an anhydride-cured epoxy resin by subcritical hydrolysis was studied under variation of reaction temperature, decomposition duration and water volume.
Analysis of the decomposition of an anhydride-cured epoxy resin by subcritical hydrolysis
Ablative Fast Pyrolysis (AFP) is the first step in the BioMates-concept to convert herbaceous biomass into co-feed with reliable properties for conventional refineries (www.biomates.eu). The document provides the coding behind the identifiers used for samples and sample blends produced by Fraunhofer UMSICHT via AFP within the H2020-project BioMates.
BioMates - Coding of identifiers for WP1-samples and -blends
This paper investigates the role of various sensors in estimating shoulder loads during manual manipulation tasks in the context of exoskeleton control. The sensors examined include textile-integrated electromyography (EMG) sensors forthe trapezius, deltoids, biceps, and forearm muscles; inertial measurement units (IMUs) on key body segments such as the pelvis, shoulder, upper arm, and forearm; and pressure-sensing insoles. The objective is to reduce the sensor configuration for predicting the internal torque exerted on the shoulder in the sagittal plane. To achieve this, a study involving nine subjects manipulating dumbbells in the sagittal plane was conducted. The protocol encompasses four static positions as well as isolated elbow and shoulder flexions. Further, four distinct machine learning model architectures were trained, systematically omitting one sensor at a time. The significance of each sensor was evaluated by assessing the impact of its omission on the predictive correlation using cross-validated R2 scores. Consequently, a top-five sensor configuration was identified and compared against configurations based solely on domain knowledge and the full sensor array. The configuration proposed in this study achieved a correlation of R2 = 0.83 in predicting shoulder loads, slightly surpassing the performance of the full sensor setup (R2 = 0.82) and outperforming the domain knowledge-based (DKB) setup (R2 = 0.63). All metrics are determined in a leave-one-subject-out cross-validation (loso-cv) training strategy.
Dataset for 'Reducing Sensor Configuration for Data-Driven Shoulder Load Estimation for Exoskeleton Control'
Verbundvorhaben: Open source Energiesystemmodellierung – Einfluss von soziokulturellen Faktoren auf Transformationspfade des deutschen Energiesystems (Sozio-E2S)
The data set includes results of a survey on flight behaviour on domestic German and European distances. 2530 persons participated in the study, which is representative for Germany with regard to the following parameters: gender, age, educational background, size of town and federal state. The data set includes questions on mobility behaviour, attractiveness of air travel, personal attitudes towards travel, environmental aspects, intergenerational justice and national and global identity. In addition, an experimental, single factor study design (4 levels) was chosen to investigate the impact of various information (vs. no information) regarding the environmental impact of air travel, global equity and subsidies on the support of political measures and personal flight intentions.
Der Datensatz umfasst Ergebnisse einer Befragung zum Flugverhalten auf innerdeutschen und innereuropäischen Distanzen. 2530 Personen haben an der Studie teilgenommen, die repräsentativ für Deutschland bzgl. folgender Kennwerte ist: Geschlecht, Alter, Schulabschluss, Ortsgröße sowie Bundesland. Der Datensatz umfasst Fragen zu Mobilitätsverhalten, Attraktivität des Flugverkehrs, persönlichen Einstellungen bzgl. Reisens, Umweltaspekte, intergenerationaler Gerechtigkeit sowie nationaler und globaler Identität. Außerdem wurde ein experimentelles, einfaktorielles Untersuchungsdesign (4-stufig) gewählt, um die Auswirkungen verschiedener Informationen (vs. keine information) zur Umweltwirkung des Flugverkehrs, globaler Gerechtigkeit sowie von Subventionen auf die Unterstützung politischer Maßnahmen und persönliche Flugabsichten zu untersuchen.
Survey on individual flight behaviour within Germany and Europe
Befragung zum individuellen Flugverhalten innerhalb Deutschlands und Europas
This dataset presents the results of a 3D geomechanical-numerical model of the in situ stress state of the Ruhr region. The modelled three-dimensional in situ stress state is provided for each of the six components of the full stress tensor as well as for the three components of the principal stress tensor. Presented in situ stress magnitudes represent total stresses i.e., a sum of effective in situ stresses and pore pressure field accounting for the Biot’s coefficient of the rock mass. In addition to the full and principal stress tensor, scalar properties of the major fault zones located within the model volume such as shear stress, normal effective stress, Coulomb Failure Function, slip tendency, and dilation tendency are presented.
Modelled three-dimensional in situ stress state and fault reactivation risk in the Ruhr region
Intelligent data-guided process design for fatigue-resistant steel components using the example of bainitic microstructure
This repository contains named-entity recognition (NER) datasets for four materials science and engineering (MSE) publications and utility functions to handle the data. The scope of the scholarly articles used as a basis is crystallographic defects, microstructure, mechanical properties in particular fatigue. Each annotation corresponds to a class in a materials science domain ontology called materials mechanics ontology. This should prospectively enable linking materials knowledge and data to facilitate training neurosymbolic machine learning models. Two dataset variants are published: coarse-granular named-entity recognition (CG-NER) where the annotated concepts are high-level ontological classes fine-granular named-entity recognition (FG-NER) where the annotated concepts are low-level ontological classes Aside from the link to the ontology a characteristic of the dataset is its high degree of of annotation. Namely, 179 distinct ontological classes and 27% of all tokens are annotated in the fine-granular dataset.
MaterioMiner - An ontology-based text mining dataset for extraction of process-structure-property entities
Gewichtsreduzierung in Leichtbaustukturen dynamisch belasteter Systeme durch neue energirdissipative Elemente
Der Datensatz enthält die ausgewerteten Ergebnisse von mehreren Frettingexperimenten mit verschieden Materialpaarungen. Außerdem enthalten sind chemische Analysen der gelaufenen Proben. Von jeder Metallpaarung gibt es eine XPS-Analyse der Reibpartner neben und in der Verschleißspur. Von einer Polymerprobe gibt es Daten zu je einer Ramanmessung in und neben der Verschleißspur.
The data set contains the analysed results of several fretting experiments with different material pairings. Chemical analyses of the worn samples are also included. For each metal pairing there is an XPS analysis of the friction partners inside and outside of the wear track. For one polymer sample, there is data of Raman measurements inside and outside of the wear track.
Fretting data of different materials and chemical analysis of the tribological layer with XPS and Raman
Fretting Daten unterschiedlicher Materialien und chemische Analyse der Triboschicht mittels XPS und Raman
Pressure-based OpenFOAM solver for the stationary "extended Navier-Stokes equations".
An OpenFOAM solver for the extended Navier-Stokes equations (rhoSimpleEnseFoam)
This repository contains named-entity recognition (NER) datasets for four materials science and engineering (MSE) publications and utility functions to handle the data. The scope of the scholarly articles used as a basis is crystallographic defects, microstructure, mechanical properties in particular fatigue. Each annotation corresponds to a class in a materials science domain ontology called materials mechanics ontology. This should prospectively enable linking materials knowledge and data to facilitate training neurosymbolic machine learning models. Two dataset variants are published: coarse-grained named-entity recognition (CG-NER) where the annotated concepts are high-level ontological classes fine-grained named-entity recognition (FG-NER) where the annotated concepts are low-level ontological classes Aside from the link to the ontology a characteristic of the dataset is its high degree of of annotation. Namely, 179 distinct ontological classes and 27% of all tokens are annotated in the fine-granular dataset.
The LUCID Dataset consists of labeled data for 100~scenarios with about 1.1h of drive time, 40.000 frames and 500.000 bounding boxes and will be publicly available from now. We employed the Eclipse MOSAIC simulation framework in conjunction with the SUMO simulator for routes and traffic densities as well as CARLA for simulation of sophisticated LIDAR sensors and environments.
LIDAR Utilization for Cross-Data Integration and Diversity
LIDAR-Anwendung für datenübergreifende Integration und Diversität