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The laser-based directed energy deposition of polymers (DED-LB/P) is an additive manufacturing process which offers the possibility to build up 3D structures with a high level of individualization on free-form surfaces. In this article, an absorber free DED-LB/P process with a thulium-doped fiber laser is presented for the first time to produce dielectric image lines (DIL) consisting of polypropylene (PP) for high frequency applications. This type of transmission line has advantages over the commonly used stripline technology due to its low signal attenuation, especially at high frequencies, but is currently hardly found in mass-market applications because no suitable manufacturing technology has been established for it yet. The steadily increasing demand of higher bandwidth in telecommunication or increased resolution of radar sensors leads to higher application frequencies and alternative interconnect technologies will become more important as they significantly define the achievable overall system performance. Based on the fabricated low-loss DILs in this study, DED-LB/P could represent such an alternative manufacturing process for future RF-applications.

MRI-compatible robots provide a means of studying brain function involved in complex sensorimotor learning processes, such as adaptation. To properly interpret the neural correlates of behavior measured using MRI-compatible robots, it is critical to validate the measurements of motor performance obtained via such devices. Previously, we characterized adaptation of the wrist in response to a force field applied via an MRI-compatible robot, the MR-SoftWrist. Compared to arm reaching tasks, we observed lower end magnitude of adaptation, and reductions in trajectory errors beyond those explained by adaptation. Thus, we formed two hypotheses: that the observed differences were due to measurement errors of the MR-SoftWrist; or that impedance control plays a significant role in control of wrist movements during dynamic perturbations. To test both hypotheses, we performed a two-session counterbalanced crossover study. In both sessions, participants performed wrist pointing in three force field conditions (zero force, constant, random). Participants used either the MR-SoftWrist or the UDiffWrist, a non-MRI-compatible wrist robot, for task execution in session one, and the other device in session two. To measure anticipatory co-contraction associated with impedance control, we collected surface EMG of four forearm muscles. We found no significant effect of device on behavior, validating the measurements of adaptation obtained with the MR-SoftWrist. EMG measures of co-contraction explained a significant portion of the variance in excess error reduction not attributable to adaptation. These results support the hypothesis that for the wrist, impedance control significantly contributes to reductions in trajectory errors in excess of those explained by adaptation.

Deep neural networks (DNNs) have proven their capabilities in the past years and play a significant role in environment perception for the challenging application of automated driving. They are employed for tasks such as detection, semantic segmentation, and sensor fusion. Despite tremendous research efforts, several issues still need to be addressed that limit the applicability of DNNs in automated driving. The bad generalization of DNNs to unseen domains is a major problem on the way to a safe, large-scale application, because manual annotation of new domains is costly, particularly for semantic segmentation. For this reason, methods are required to adapt DNNs to new domains without labeling effort. This task is termed unsupervised domain adaptation (UDA). While several different domain shifts challenge DNNs, the shift between synthetic and real data is of particular importance for automated driving, as it allows the use of simulation environments for DNN training. We present an overview of the current state of the art in this research field. We categorize and explain the different approaches for UDA. The number of considered publications is larger than any other survey on this topic. We also go far beyond the description of the UDA state-of-the-art, as we present a quantitative comparison of approaches and point out the latest trends in this field. We conduct a critical analysis of the state-of-the-art and highlight promising future research directions. With this survey, we aim to facilitate UDA research further and encourage scientists to exploit novel research directions.

For the last two decades, an extensive transition in automotive X-in-the-loop activities from isolated electronic control units to real-time related, geographically distributed validation tasks has occurred. Benefits are strengthening frontloading, enabling concurrent engineering and reducing prototypes and testing efforts. As a downside, comprehensive system understanding and adequate simulation models must be provided. New technological trends like software-over-the-air-updates denote a continuous validation process even after the start of production. The present review focuses on the virtual validation of vehicle longitudinal dynamics. This exemplary field of application receives more and more attention as electrification of the vehicle powertrain accelerates, and this property directly influences the vehicle DNA. A systematic review process based on the PRISMA workflow has been conducted, focusing on drivability-related powertrain applications. The investigation reveals the following trends: First, increasing complexity of virtualisation methods and models for validation activities influenced by vehicle-to-everything and geographically distributed development. Second, missing standards for virtual validation and proof of representativeness for combined real-virtual testing. In addition, many studies only contemplate the advantages of hardware-in-the-loop-driven development, disregarding crucial limitations and risks for such approaches. In conclusion, there is no longer the question of whether to validate virtually but how to comprehensible realise virtual validation.

It is predicted that the number of autonomous vehicles will increase in the forthcoming years. In this context, this research deals with autonomous micro-mobiles, specifically autonomous cargo bikes. In the development of (partially) autonomous vehicles, it is important to consider the safety perspective of vulnerable road users, such as pedestrians, already during development to enhance acceptance and widespread use. We investigated the safety parameters of speed and distance. For this purpose, videos with varying distance and speed parameters were filmed from a third-person perspective. These were then distributed via online questionnaires and evaluated by subjects regarding the subjective perceived safety. The results show that perceived safety increases with increasing passing and yielding distance and decreasing passing speed. Even at very short distances and relatively high speeds, the behavior of the cargo bike was still considered safe. These results can serve as reference values in the development of autonomous micro-mobiles. Further, the high safety perception should encourage planners and decisionmakers to give these technologies a chance and boldly tackle the mobility revolution and test possible substitutes for motorized individual transport.

Inferring the network topology from the dynamics of interacting units constitutes a topical challenge that drives research on its theory and applications across physics, mathematics, biology, and engineering. Most current inference methods rely on time series data recorded from all dynamical variables in the system. In applications, often only some of these time series are accessible, while other units or variables of all units are hidden, i.e. inaccessible or unobserved. For instance, in AC power grids, frequency measurements often are easily available whereas determining the phase relations among the oscillatory units requires much more effort. Here, we propose a network inference method that allows to reconstruct the full network topology even if all units exhibit hidden variables. We illustrate the approach in terms of a basic AC power grid model with two variables per node, the local phase angle and the local instantaneous frequency. Based solely on frequency measurements, we infer the underlying network topology as well as the relative phases that are inaccessible to measurement. The presented method may be enhanced to include systems with more complex coupling functions and additional parameters such as losses in power grid models. These results may thus contribute towards developing and applying novel network inference approaches in engineering, biology and beyond.

Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and variations that need to be addressed before the tissues are analyzed. WSI preprocessing can significantly improve the performance of computational pathology systems and is often used to facilitate human or machine analysis. Color preprocessing techniques are frequently mentioned in the literature, while other areas are usually ignored. In this paper, we present a detailed study of the state-of-the-art in three different areas of WSI preprocessing: Artifacts detection, color variation, and the emerging field of pathology-specific data augmentation. We include a summary of evaluation techniques along with a discussion of possible limitations and future research directions for new methods.

The topographical information of a weld seam bears information about quality relevant characteristics such as humping or spatter. Optical coherence tomography (OCT) can be used for inline scanning the weld topography coaxially mounted at a laser scanning optic. Feature extraction from this topographical information is challenging due to finding mathematical representations for the identification of relevant features. Feature extraction based on scalable hypothesis tests (FRESH) allows for feature extraction by a combination of various time series characterization methods. FRESHs feature selection is supported with an automatically configured hypothesis test and hence allows for quick extraction of significant features from sensing data in laser welding processes. In this work, a proof-of-concept is demonstrated for weld result categorization from OCT data by feature extraction using the FRESH algorithm. Changes in weld topography are characterized in a vast variety of process parameters for weld categories such as spatter, deep penetration welding, humping and heat conduction welding. As a result, a quantified separation of weld categories is possible and shows the feasibility of the FRESH algorithm for future quality assessments with different sensing technologies in laser welding.

In addition to their main functionality of converting DC input power to AC output power, today’s photovoltaic inverters are generally required to be capable of providing reactive power. While there are well-established mathematical models that use the correlation between inverter losses and the transmitted active power to estimate inverter efficiency for any given active power operating point, the additional losses in the inverter due to the supply of reactive power are less well studied. In this work, the conversion efficiencies of three different photovoltaic inverters were measured for various active power and reactive power setpoints. Based on these measurements, two mathematical models are proposed to represent the conversion losses as a function of active and reactive output power. One model is of empirical nature and expands preexisting models to include terms that take the reactive power into consideration. The other model takes the dominant loss mechanisms in the conversion stage of inverters into account and considers the effect of reactive power provision on them. Both models were compared with a model variant proposed in literature. They are shown to perform with high accuracy over the entire operating range, while requiring only a small number of known efficiency values for parametrization. There are several fields of application for these new models: They allow photovoltaic park operators to precisely estimate the individual losses of a solar power plant that feeds reactive power into the grid. For grid operators, they enable a comparative loss analysis for different reactive power sources.

We report an in-well and barrier coupling pump scheme of semiconductor disk laser (SDL). An in-well-absorbed (940 nm) and a barrier-absorbed (808 nm) pump source were used to measure laser output characteristics. The output power of the coupling pump can be significantly improved compared to the in-well pump only scheme under similar thermal load conditions. The power scaling of the coupling pump SDL is caused by the interaction dynamics of the photoexcited carrier between quantum-well and barrier. The results are discussed with a rate equation model that considers the injected into the quantum-well carrier and the barrier carrier in the active region.

Integrated optofluidic biosensors can fill the need for sensitive, amplification-free, multiplex single molecule detection which is relevant for containing the spread of infectious diseases such as COVID-19. Here, we demonstrate a rapid sample-to-answer scheme that uses a field programmable gate array (FPGA) to enable live monitoring of single particle fluorescence analysis on an optofluidic chip. Fluorescent nanobeads flowing through a micro channel are detected with 99% accuracy and particle concentrations in clinically relevant ranges from 3.4x104 to 3.4 × 106/ml are determined within seconds to a few minutes without the need for post-experiment data extraction and analysis. In addition, other extract salient experimental parameters such as dynamic flow rate changes can be monitored in real time. The sensor is validated with real-time fluorescence detection of single bacterial plasmid DNA at attomolar concentrations, showing excellent promise for implementation as a point of care (POC) diagnostic tool.

The 3rd Generation Partnership Project (3GPP) is investing a notable effort to mitigate the endogenous stack and protocol delays (e.g., introducing new numerology, through preemptive scheduling or providing uplink granted free transmission) to attain to the heterogeneous Quality of Service (QoS) latency requirements for which the fifth generation technology standard for broadband cellular networks (5G) is envisioned. However, 3GPP’s goals may become futile if exogenous delays generated by the transport layer (e.g., bufferbloat) and the Radio Link Control (RLC) sublayer segmentation/reassembly procedure are not targeted. On the one hand, the bufferbloat specifically occurs at the Radio Access Network (RAN) since the data path bottleneck is located at the radio link, and contemporary RANs are deployed with large buffers to avoid squandering scarce wireless resources. On the other hand, a Resource Block (RB) scheduling that dismisses 5G’s packet-switched network nature, unnecessarily triggers the segmentation procedure at sender’s RLC sublayer, which adds extra delay as receiver’s RLC sublayer cannot forward the packets to higher sublayers until they are reassembled. Consequently, the exogenously generated queuing delays can surpass 5G’s stack and protocol endogenous delays, neutralizing 3GPP’s attempt to reduce the latency. We address RLC’s related buffer delays and present two solutions: (i) we enhance the 3GPP standard and propose a bufferbloat avoidance algorithm, and (ii) we propose a RB scheduler for circumventing the added sojourn time caused by the packet segmentation/reassembly procedure. Both solutions are implemented and extensively evaluated along with other state-of-the-art proposals in a testbed to verify their suitability and effectiveness under realistic conditions of use (i.e., by considering Modulation and Coding Scheme (MCS) variations, slices, different traffic patterns and off-the-shelf equipment). The results reveal current 3GPP deficits in its QoS model to address the bufferbloat and the contribution of the segmentation/reassembly procedure to the total delay.

Wireless solutions for on-board communications are gaining momentum in the aerospace industry with the aim to further improve flight safety, reduce aircraft costs, and lower environmental impact. Also passenger infotainment services are increasingly realized in a wireless way and call for high-rate connectivity to the Internet. There are many issues though, including security, coexistence, and power sustainability. We argue that ultra-wideband (UWB) technology is a promising implementation path for such intra-aircaft communications. From a power sustainability perspective, UWB attains a unique trade-off between power consumption and data rate that can become a key enabler. Experimental results from a proof-of-concept deployment of off-the-shelf UWB transceivers in an Airbus A319 support our discussion and shed light on the challenges ahead.

In this work, we present and analyze methods and mechanisms for interconnecting a network slice control and management system of the mobile network, with an IEEE Time-Sensitive Network (TSN) control plane. IEEE TSN is gaining momentum as a key technology that is able to provide network service guarantees for Ethernet-based communications. Although Ultra-Reliable Low-Latency Communications (URLLC) have been thoroughly investigated in 5G, incorporating TSN technologies in the Transport Network is expected to unleash the potential of end-to-end deterministic communications, especially in industrial environments and time-critical applications like factory automation.We elaborate on the concepts of a TSN-aware Xhaul network, present a novel architecture, and describe a set of amendments required in order to enable network slicing. With the devised approach, a slice-aware TSN-enabled transport network can be controlled and managed in an end-to-end orchestrated way. Implementation experience and evaluation results are reported using TSN-enabled prototype devices, OpenAirInterface (OAI), and JOX slice orchestrator.

Wearable devices are commonly used to monitor human movement since motor activity is a fundamental element in all phases of a person's life. Patients with motor disorders need to be monitored for a prolonged period and the battery life can be a limit for such a goal. Here the technique of harvesting energy from body heat to supply energy to wearable devices is investigated. A commercial flexible thermoelectric generator, equipped with an accelerometer, is placed on the lower leg above the ankle. The accelerometer serves to detect diverse motor activities carried out by ten students of VSB-Technical University of Ostrava involved in the execution of two tasks. To summarize, the motor activities analyzed in the proposed work are: “Sit”, “Walk”, “Rest”, “Go biking”, “Rest after biking”, and “Go down and up the stairs”. The maximum measured value of power density was 20.3 μW cm-2 for the “Walk” activity, corresponding to a gradient of temperature between the hot and cold side of the thermocouples constituting the flexible thermoelectric generator of 1.5 °C, while the minimum measured value of power density was 8.3 μW cm-2 for the “Sit” activity, corresponding to a gradient of temperature of 1.1 °C. Moreover, a mathematical model was developed for the recognition of motor activities carried out during the execution of the experiments. As a preliminary result, it is possible to state that semi-stationary parts of the signal generated by the thermoelectric generator can be traced back to the performance of an activity.

The TanDEM-X mission, formed by the TanDEM-X satellite in cooperation with its almost identical twin TerraSAR-X (TSX), has mainly been designed to acquire bistatic synthetic aperture radar (SAR) images of the Earth. Initiated in 2010, the primary mission objectives were to generate a global digital elevation model (DEM) to perform scientific measurements and to explore novel SAR techniques. Up to the present day, all these objectives have been completed with outstanding results. In addition, the satellites maintained a stable image quality from the start throughout their entire lifetime. The ground segment, which was tailored to the capabilities of the space segment, as well as an excellent design and manufacturing of the satellites were the key elements to achieve such a performance. In addition, the elaborate calibration concept and a careful treatment of the on-board resources enabled full operability up to the present day and allowed additional mission objectives such as the generation of a Change-DEM layer as an update to the global DEM. The stable bus and SAR payload performance as revealed by long-term system monitoring provide the basis for further extension of the TanDEM-X mission for several more years. In the following paper, these long-term system monitoring results are presented to provide an overview of the evolution of the radar system. The results and experience gained with more than a decade of TanDEM-X mission operation are a great value for both the scientific and commercial community and serve as a forerunner for the development of future SAR missions.

Due to load growth and various load types within the service territory, utilities need to enhance the utilization of substations. In any case, towards the coordinated substation design, the utilization of the transformers’ most total capacity cannot be reduced just because there is a lack of proper coordination between transmission and distribution systems. The transmission and distribution systems’ stability and safe operability must be investigated in a coordinated substation. The critical issues are the asymmetric fault currents on the high voltage and arc-related safety issues on the distribution switchgear at different dynamic loading scenarios. We found that when one 138 kV transmission line and two transformers are energized, with increased dynamic loading, from 40% and above, the substation, as a whole, gets gradually more stressed. Because of the highest amount of fault currents on the 138 kV bus, to avoid CT saturation, we need to consider that three transmission lines are connected, and all three transformers are running at 100% dynamic loading. At this value of dynamic loading, in the 13.2 kV switchgear, the incident energy is 2 cal/cm2, and the arc flash boundary is four feet, which ensures that all workers need to wear the proper arc-rated clothes to work on any de-energized cubicle of the switchgear.

Utility encounters situations like when one out of two power transformers in the substation requires maintenance and only one transformer remains in operation. To meet the load requirements of a maximum number of customers, if not all, the only transformer needs to be overloaded. Due to various load types within the service territory, utilities need to understand the customers' maximum dynamic loading amount to overload a transformer in an emergency. We propose the iteration process with real-world substation data, which considers the concept of a coordinated substation for optimal power flow. We found to what extent the only 138 kV//13.8 kV, 30/40/50 MVA transformer can be safely overloaded beyond its nameplate's maximum rating for a minimum time. Within that time, the utility personnel can work on the substation yard and switchgear room safely and comfortably to bring back the other transformer in operation. We found from the perspective of power flow that with increased dynamic loading, transformer secondary current increases. Therefore, under the maximum dynamic loading condition, we should calculate the asymmetric fault current on the 13.2 kV switchgear bus to select the suitable CTs and develop a protection scheme accordingly.

Mixed-criticality scheduling in modern deeply embedded mission and safety-critical systems needs to consider delivered service, that is, the runtime in low criticality mode. If the change into a higher criticality mode is triggered by the first overrunning job, the service is severely reduced. With earliest deadline first with virtual deadlines for single errors (EDF-VD-SE) we show how to reserve additional time to tolerate a single overrunning job by formulating and solving an optimization problem, and that EDF-VD-SE is feasible without assumptions about error probabilities for safety guarantees. We conduct extensive simulation experiments to report on average doubled service figures, and show how EDF-VD-SE results in a nearly constant acceptance rate of random task systems.

We discuss the potential of ultra-wideband (UWB) technology for realizing use cases in industry 4.0 and demonstrate the implementation of an UWB sensor network with off-the-shelf transceivers for machine vibration monitoring. We propose a flexible medium access layer tailored for industrial sensing and show how the choice of its parameters is affected by the propagation environment and hardware constraints. Our real-world experiments reveal that links up to 20 meters can be achieved in industrial environments with an average packet loss rate in the order of 10-6 for typical links. A comparison with a commercial vibration monitoring system based on IEEE 802.15.4 spread spectrum shows that UWB attains a twenty-times higher throughput for similar link ranges.

We propose P4-MACsec to protect network links between P4-based SDN switches through automated deployment of MACsec, a widespread IEEE standard for securing Layer 2 infrastructures. MACsec is supported by switches and routers from many manufacturers. On these devices, it has only little performance limitations compared to VPN technologies such as IPsec. P4-MACsec suggests a data plane implementation of MACsec including AES-GCM encryption and decryption directly on P4 targets. P4-MACsec features a two-tier control plane structure where local controllers running on the P4 targets interact with a central controller. We propose a novel secure link discovery mechanism that leverages protected LLDP frames and a two-tier control plane structure for secure and efficient management of a global link map. Automated deployment of MACsec creates secure channels, generates keying material, and configures the P4 targets for each detected link between two P4 targets. It detects link changes and performs rekeying to provide a secure, configuration-free operation of MACsec. In this paper, we review the technological background of P4-MACsec and explain its architecture. To demonstrate the feasibility of P4-MACsec, we implement it on the BMv2 P4 software target, validate the prototype through experiments, and evaluate its performance through experiments considering TCP goodput and round-trip time. We publish the prototype and experiment setup under the Apache v2 license on GitHub [7].

Developments in artificial intelligence (AI) and distributed ledger technology (DLT) currently lead to lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans. DLT has the potential to create consensus over data among a group of participants in untrustworthy environments. In recent research, both technologies are used in similar and even the same systems. This can lead to a convergence of AI and DLT, which in the past, has paved the way for major innovations of other information technologies. Previous work highlights several potential benefits of a convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. In this research, we review and synthesize extant research on integrating AI with DLT and vice versa to rigorously develop a future research agenda on the convergence of both technologies. In terms of integrating AI with DLT, we identified research opportunities in the areas of secure DLT, automated referee and governance, and privacy-preserving personalization. With regard to integrating DLT with AI, we identified future research opportunities in the areas of decentralized computing for AI, secure data sharing and marketplaces, explainable AI, and coordinating devices. In doing so, this research provides a four-fold contribution. First, it is not constrained to blockchain but instead investigates the broader phenomenon of DLT. Second, it considers the reciprocal nature of a convergence of AI and DLT. Third, it bridges the gap between theory and practice by helping researchers active in AI or DLT to overcome current limitations in their field, and practitioners to develop systems along with the convergence of both technologies. Fourth, it demonstrates the feasibility of applying the convergence concept to research on AI and DLT.

Automated manufacturing systems (AMSs) consist of computer-controlled interconnected manufacturing components (MCs) that are used to transport and process different product types. Each product type requires a certain sequence of processing steps in different MCs. Hereby, multiple product types can share processing steps on the same MC and the paths of different products types can overlap. In this paper we consider the modeling of AMSs in the scope of supervisory control for discrete event systems (DES). On the one hand, a suitable AMS model must allow the representation of sequential and concurrent processing steps in MCs. On the other hand, such model must be able to track different product types traveling through the AMS so as to process the products correctly. While previous work is commonly concerned with the first requirement, this paper identifies that the existing literature lacks a general treatment of the second requirement. Accordingly, we first introduce order-preserving (OP) languages that preserve the order of different product types in MCs and we propose a suitable finite state automaton model for OP languages. Then, we show that the composition of OP languages again leads to an OP language. That is, modeling MCs by OP languages, an OP model of a complete AMS that is suitable for supervisory control is obtained. In addition, it is possible to use both OP models and non-OP models for general AMSs, where MCs have different properties. We demonstrate the applicability of the proposed modeling technique by a flexible manufacturing system example.

In this work, we present P4-IPsec, a concept for IPsec in software-defined networks (SDN) using P4 programmable data planes. The prototype implementation features ESP in tunnel mode and supports different cipher suites. P4-capable switches are programmed to serve as IPsec tunnel endpoints. We also provide a client agent to configure tunnel endpoints on Linux hosts so that site-to-site and host-to-site application scenarios can be supported which are the base for virtual private networks (VPNs). While traditional VPNs require complex key exchange protocols like IKE to set up and renew tunnel endpoints, P4-IPsec benefits from an SDN controller to accomplish these tasks. One goal of this experimental work is to investigate how well P4-IPsec can be implemented on existing P4 switches. We present a prototype for the BMv2 P4 software switch, evaluate its performance, and publish its source code on GitHub [1]. We explain why we could not provide a useful implementation with the NetFPGA SUME board. For the Edgecore Wedge 100BF-32X Tofino-based switch, we presented two prototype implementations to cope with a missing crypto unit. As another contribution of this paper, we provide technological background of P4 and IPsec and give a comprehensive review of security applications in P4, IPsec in SDN, and IPsec data plane implementations. According to our knowledge, P4-IPsec is the first implementation of IPsec for P4-based SDN.

The subject of this paper is the computation of paths for mobile robots that navigate from a start position to a goal position in environments with static obstacles. Specifically, we focus on paths that are represented by straight lines. Such paths can for example directly be followed by omni-directional robots or can be used as an initial solution for path smoothing. In this context, the most common performance metrics are the path length, the obstacle clearance and the computation time. In this paper, we develop a new path planning algorithm that addresses all the stated performance metrics. Our method first determines all possible connections between the start position and goal position along the edges of the generalized Voronoi diagram (GVD) of a given obstacle map. The shortest connections are then refined using a balanced method for creating shortcuts along existing waypoints and introducing new waypoints in order to cut corners. As an important feature, our method reduces the number of required waypoints by iteratively adding new waypoints and then removing unnecessary waypoints along solution paths. Moreover, our method takes into account multiple start-goal connections, since the shortest start-goal connection along the edges of the GVD might not lead to the shortest solution path. A comprehensive computational evaluation for a large number of maps with different properties shows that the proposed method outperforms sampling-based algorithms such as Probabilistic Roadmaps (PRM) and exact methods such as Visibility Graphs (VG) by computing close-to-optimal solution paths with a specified minimum obstacle clearance in less time.