STYLE: Style Transfer for Synthetic Training of a YoLo6D Pose Estimator

Supervised training of deep neural networks requires a large amount of training data. Since labeling is time-consuming and error prone and many applications lack data sets of adequate size, research soon became interested in generating this data synthetically, e.g. by rendering images, which makes the annotation free and allows utilizing other sources of available data, for example, CAD models. However, unless much effort is invested, synthetically generated data usually does not exhibit the exact same properties as real-word data. In context of images, there is a difference in the distribution of image features between synthetic and real imagery, a domain gap. This domain gap reduces the transfer-ability of synthetically trained models, hurting their real world inference performance. Current state-of-the-art approaches trying to mitigate this problem concentrate on domain randomization: Overwhelming the model’s feature extractor with enough variation to force it to learn more meaningful features, effectively rendering real-world images nothing more but one additional variation. The main problem with most domain randomization approaches is that it requires the practitioner to decide on the amount of randomization required, a fact research calls "blind" randomization. Domain adaptation in contrast directly tackles the domain gap without the assistance of the practitioner, which makes this approach seem superior. This work deals with training of a DNN-based object pose estimator in three scenarios: First, a small amount of real-world images of the objects of interest is available, second, no images are available, but object specific texture is given, and third, no images and no textures are available. Instead of copying successful randomization techniques, these three problems are tackled mainly with domain adaptation techniques. The main proposition is the adaptation of general-purpose, widely-available, pixel-level style transfer to directly tackle the differences in features found in images from different domains. To that end several approaches are introduced and tested, corresponding to the three different scenarios. It is demonstrated that in scenario one and two, conventional conditional GANs can drastically reduce the domain gap, thereby improving performance by a large margin when compared to non-photo-realistic renderings. More importantly: ready-to-use style transfer solutions improve performance significantly when compared to a model trained with the same degree of randomization, even when there is no real-world data of the target objects available (scenario three), thereby reducing the reliance on domain randomization

Early deformation mechanisms in the shear affected region underneath a copper sliding contact

Dislocation mediated plastic deformation decisively influences the friction coefficient and the microstructural changes at many metal sliding interfaces during tribological loading. This work explores the initiation of a tribologically induced microstructure in the vicinity of a copper twin boundary. Two distinct horizontal dislocation traces lines (DTL) are observed in their interaction with the twin boundary beneath the sliding interface. DTL formation seems unaffected by the presence of the twin boundary but the twin boundary acts as an indicator of the occurring deformation mechanisms. Three concurrent elementary processes can be identified: simple shear of the subsurface area in sliding direction, localized shear at the primary DTL and crystal rotation in the layers above and between the DTLs around axes parallel to the transverse direction. Crystal orientation analysis demonstrates a strong compatibility of these proposed processes. Quantitatively separating these different deformation mechanisms is crucial for future predictive modeling of tribological contacts

Measuring innovation in the bioeconomy - Conceptual discussion and empirical experiences

Innovations in the bioeconomy are expected to provide new solutions to major economic, societal and ecological challenges like resource depletion, food insecurity or climate change. However, information about innovation activities in the bioeconomy and its outcomes is scattered and more systematic measurement efforts are useful for policy making to assess its impact and whether objectives are met. This article provides an overview of information needs and data availability for innovation indicators. Furthermore, data for key input and throughput indicators are presented and discussed for the bioeconomy in Germany. The data indicates a rather strong role of Germany for publications and patents. However, the commercial success remains unclear, because of current limitations in information availability about the output and outcome of innovations efforts. Here, the most critical information gap in exist. In order to improve this situation additional data collection such as innovation survey for the bioeconomy would be needed

Fabrication and functional properties of additively manufactured NiTi lattice structures using adaptive scanning strategies: Presentation held at The World comes here, TMS 2020, 149th Annual Meeting & Exhibition, co-located 9th International Symposium on Lead and Zinc Processsing, PbZn 2020, February 23-27, 2020, San Diego, California

Near-equiatomic NiTi-alloys are attractive materials for medical applications due to their functional properties (pseudoelasticity). However, most of the manufacturing steps needed for processing of NiTi are challenging. Thus, laser beam melting (LBM) was used and identified as a suitable method for the fabrication of a wide range of complex NiTi structures with low impurity pick up and good functional properties. Besides obtaining as-built parts with pronounced shape-recovery, efforts have been made to improve the quality of the processed specimens (e.g. accuracy). In our work, we demonstrate that delicate NiTi lattice structures can be manufactured on a conventional LBM machine using point scanning strategies. Process parameters and the type of point exposure have been optimized to obtain struts (below 200 microns) with high evenness and smooth surfaces. Due to this reason, the use of point scanning strategies is a promising approach for LBM of NiTi lattices with improved mechanical properties

Electron Channeling Contrast Imaging Investigation of Stacking Fault Pyramids in GaP on Si Nucleation Layers

Thin gallium phosphide layers were deposited on (0 0 1) Silicon surfaces via organometallic vapor phase epitaxy and characterized by electron channeling contrast imaging (ECCI). Stacking fault pyramids at a density of up to 6 × 107 cm−2 were identified in the GaP nucleation layer by varying the diffraction conditions. We show that these defects originate at the GaP/Si interface and propagate on all four {1 1 1} planes. We observed that such stacking fault pyramids interact with the gliding of misfit dislocations during lattice-mismatched growth and enhance the threading dislocation density. The initial pulsing of TEGa and TBP during the nucleation of GaP on Silicon has been found to strongly influence the formation of those pyramidal defects. Changing the number of pulse cycles allowed us to lower their density by two orders of magnitude from 6 × 107 cm−2 to 4 × 105 cm−2

Feinstzerkleinerung von CFK-Abfällen und Charakterisierung der Zerkleinerungsprodukte

The comminution of carbon fiber reinforced plastics (CFRP) is a central process step for almost all recycling processes. Size reduction creates a specific surface that serves as a measure in particular of the size reduction success of fines. The article shows the comminution from 1 m edge length in the feed material down to a target product size of less than 100 µm by means of three‐stage comminution. The challenges of granulometric characterization of the comminution products and the associated evaluation of the comminution success are specifically addressed

Fiber laser-driven gas plasma-based generation of THz radiation with 50-mW average power

We present on THz generation in the two-color gas plasma scheme driven by a high-power, ultrafast fiber laser system. The applied scheme is a promising approach for scaling the THz average power but it has been limited so far by the driving lasers to repetition rates up to 1 kHz. Here, we demonstrate recent results of THz generation operating at a two orders of magnitude higher repetition rate. This results in a unprecedented THz average power of 50 mW. The development of compact, table-top THz sources with high repetition rate and high field strength is crucial for studying nonlinear responses of materials, particle acceleration or faster data acquisition in imaging and spectroscopy

ECU-Secure: Characteristic Functions for In-Vehicle Intrusion Detection

Growing connectivity of vehicles induces increasing attack surfaces and thus the demand for a sophisticated security strategy. One part of such a strategy is to accurately detect intrusive behavior in an in-vehicle network. Therefore, we built a log analyzer in C that focused on payload bytes having either a small set of different values or a small set of possible changes. While being an order of magnitude faster, the accuracy of the results obtained is at least comparable with results obtained using standard machine learning techniques. Thus, this approach is an interesting option for implementation within in-vehicle embedded systems. Another important aspect is that the explainability of the results is better compared to deep learning systems