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Modern Franciscan Leadership
(2020)
This article combines two important areas of practical theology: Monastic rules and leadership in a cloistral organisation, using the Rule of Saint Francis as a prominent example. The aim of this research is to examine how living Christian tradition in a monastic order affects leadership today, discovering how the Rule and Franciscan spirituality impact managing a convent. The research question is answered within this inductive research applying the methodology of the ‘theology in four voices.’ Based on the results, it is possible to build a coherent leadership system based on Biblical and Franciscan sources.
Experimental Investigation of the Air Exchange Effectiveness of Push-Pull Ventilation Devices
(2020)
The increasing installation numbers of ventilation units in residential buildings are driven by legal objectives to improve their energy efficiency. The dimensioning of a ventilation system for nearly zero energy buildings is usually based on the air flow rate desired by the clients or requested by technical regulations. However, this does not necessarily lead to a system actually able to renew the air volume of the living space effectively. In recent years decentralised systems with an alternating operation mode and fairly good energy efficiencies entered the market and following question was raised: “Does this operation mode allow an efficient air renewal?” This question can be answered experimentally by performing a tracer gas analysis. In the presented study, a total of 15 preliminary tests are carried out in a climatic chamber representing a single room equipped with two push-pull devices. The tests include summer, winter and isothermal supply air conditions since this parameter variation is missing till now for push-pull devices. Further investigations are dedicated to the effect of thermal convection due to human heat dissipation on the room air flow. In dependence on these boundary conditions, the determined air exchange efficiency varies, lagging behind the expected range 0.5 < εa < 1 in almost all cases, indicating insufficient air exchange including short-circuiting. Local air exchange values suggest inhomogeneous air renewal depending on the distance to the indoor apertures as well as the temperature gradients between in- and outdoor. The tested measurement set-up is applicable for field measurements.
In this paper, we describe the PALM model system 6.0. PALM (formerly an abbreviation for Parallelized Large-eddy Simulation Model and now an independent name) is a Fortran-based code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. This is a follow-up paper to the PALM 4.0 model description in Maronga et al. (2015). During the last years, PALM has been significantly improved and now offers a variety of new components. In particular, much effort was made to enhance the model with components needed for applications in urban environments, like fully interactive land surface and radiation schemes, chemistry, and an indoor model. This paper serves as an overview paper of the PALM 6.0 model system and we describe its current model core. The individual components for urban applications, case studies, validation runs, and issues with suitable input data are presented and discussed in a series of companion papers in this special issue.
Purpose
This work presents a new monocular peer-to-peer tracking concept overcoming the distinction between tracking tools and tracked tools for optical navigation systems. A marker model concept based on marker triplets combined with a fast and robust algorithm for assigning image feature points to the corresponding markers of the tracker is introduced. Also included is a new and fast algorithm for pose estimation.
Methods
A peer-to-peer tracker consists of seven markers, which can be tracked by other peers, and one camera which is used to track the position and orientation of other peers. The special marker layout enables a fast and robust algorithm for assigning image feature points to the correct markers. The iterative pose estimation algorithm is based on point-to-line matching with Lagrange–Newton optimization and does not rely on initial guesses. Uniformly distributed quaternions in 4D (the vertices of a hexacosichora) are used as starting points and always provide the global minimum.
Results
Experiments have shown that the marker assignment algorithm robustly assigns image feature points to the correct markers even under challenging conditions. The pose estimation algorithm works fast, robustly and always finds the correct pose of the trackers. Image processing, marker assignment, and pose estimation for two trackers are handled in less than 18 ms on an Intel i7-6700 desktop computer at 3.4 GHz.
Conclusion
The new peer-to-peer tracking concept is a valuable approach to a decentralized navigation system that offers more freedom in the operating room while providing accurate, fast, and robust results.
Diffracted waves carry high‐resolution information that can help interpreting fine structural details at a scale smaller than the seismic wavelength. However, the diffraction energy tends to be weak compared to the reflected energy and is also sensitive to inaccuracies in the migration velocity, making the identification of its signal challenging. In this work, we present an innovative workflow to automatically detect scattering points in the migration dip angle domain using deep learning. By taking advantage of the different kinematic properties of reflected and diffracted waves, we separate the two types of signals by migrating the seismic amplitudes to dip angle gathers using prestack depth imaging in the local angle domain. Convolutional neural networks are a class of deep learning algorithms able to learn to extract spatial information about the data in order to identify its characteristics. They have now become the method of choice to solve supervised pattern recognition problems. In this work, we use wave equation modelling to create a large and diversified dataset of synthetic examples to train a network into identifying the probable position of scattering objects in the subsurface. After giving an intuitive introduction to diffraction imaging and deep learning and discussing some of the pitfalls of the methods, we evaluate the trained network on field data and demonstrate the validity and good generalization performance of our algorithm. We successfully identify with a high‐accuracy and high‐resolution diffraction points, including those which have a low signal to noise and reflection ratio. We also show how our method allows us to quickly scan through high dimensional data consisting of several versions of a dataset migrated with a range of velocities to overcome the strong effect of incorrect migration velocity on the diffraction signal.
Extracting horizon surfaces from key reflections in a seismic image is an important step of the interpretation process. Interpreting a reflection surface in a geologically complex area is a difficult and time-consuming task, and it requires an understanding of the 3D subsurface geometry. Common methods to help automate the process are based on tracking waveforms in a local window around manual picks. Those approaches often fail when the wavelet character lacks lateral continuity or when reflections are truncated by faults. We have formulated horizon picking as a multiclass segmentation problem and solved it by supervised training of a 3D convolutional neural network. We design an efficient architecture to analyze the data over multiple scales while keeping memory and computational needs to a practical level. To allow for uncertainties in the exact location of the reflections, we use a probabilistic formulation to express the horizons position. By using a masked loss function, we give interpreters flexibility when picking the training data. Our method allows experts to interactively improve the results of the picking by fine training the network in the more complex areas. We also determine how our algorithm can be used to extend horizons to the prestack domain by following reflections across offsets planes, even in the presence of residual moveout. We validate our approach on two field data sets and show that it yields accurate results on nontrivial reflectivity while being trained from a workable amount of manually picked data. Initial training of the network takes approximately 1 h, and the fine training and prediction on a large seismic volume take a minute at most.
Ecological concerns on the climatic effects of the emissions from electricity production stipulate the remuneration of electricity grids to accept growing amounts of intermittent regenerative electricity feed-in from wind and solar power. Germany’s eager political target to double regenerative electricity production by 2030 puts pressure on grid operators to adapt and restructure their transmission and distribution grids. The ability of local distribution grids to operate autonomous of transmission grid supply is essential to stabilize electricity supply at the level of German federal states. Although congestion management and collaboration at the distribution system operator (DSO) level are promising approaches, relatively few studies address this issue. This study presents a methodology to assess the electric energy balance for the low-voltage grids in the German federal state of Baden-Württemberg, assuming the typical load curves and the interchange potential among local distribution grids by means of linear programming of the supply function and for typical seasonal electricity demands. The model can make a statement about the performance and development requirements for grid architecture for scenarios in 2035 and 2050 when regenerative energies will—according to present legislation—account for more than half of Germany’s electricity supply. The study details the amendment to Baden-Württemberg’s electricity grid required to fit the system to the requirements of regenerative electricity production. The suggested model for grid analysis can be used in further German regions and internationally to systematically remunerate electricity grids for the acceptance of larger amounts of regenerative electricity inflows. This empirical study closes the research gap of assessing the interchange potential among DSO and considers usual power loads and simultaneously usual electricity inflows.
Background: This paper presents a novel approach for a hand prosthesis consisting of a flexible, anthropomorphic, 3D-printed replacement hand combined with a commercially available motorized orthosis that allows gripping.
Methods: A 3D light scanner was used to produce a personalized replacement hand. The wrist of the replacement hand was printed of rigid material; the rest of the hand was printed of flexible material. A standard arm liner was used to enable the user’s arm stump to be connected to the replacement hand. With computer-aided design, two different concepts were developed for the scanned hand model: In the first concept, the replacement hand was attached to the arm liner with a screw. The second concept involved attaching with a commercially available fastening system; furthermore, a skeleton was designed that was located within the flexible part of the replacement hand.
Results: 3D-multi-material printing of the two different hands was unproblematic and inexpensive. The printed hands had approximately the weight of the real hand. When testing the replacement hands with the orthosis it was possible to prove a convincing everyday functionality. For example, it was possible to grip and lift a 1-L water bottle. In addition, a pen could be held, making writing possible.
Conclusions: This first proof-of-concept study encourages further testing with users.
Fully Printed Inverters using Metal‐Oxide Semiconductor and Graphene Passives on Flexible Substrates
(2020)
Printed and flexible metal‐oxide transistor technology has recently demonstrated great promise due to its high performance and robust mechanical stability. Herein, fully printed inverter structures using electrolyte‐gated oxide transistors on a flexible polyimide (PI) substrate are discussed in detail. Conductive graphene ink is printed as the passive structures and interconnects. The additive printed transistors on PI substrates show an on/off ratio of 106 and show mobilities similar to the state‐of‐the‐art printed transistors on rigid substrates. Printed meander structures of graphene are used as pull‐up resistances in a transistor–resistor logic to create fully printed inverters. The printed and flexible inverters show a signal gain of 3.5 and a propagation delay of 30 ms. These printed inverters are able to withstand a tensile strain of 1.5% following more than 200 cycles of mechanical bending. The stability of the electrical direct current (DC) properties has been observed over a period of 5 weeks. These oxide transistor‐based fully printed inverters are relevant for digital printing methods which could be implemented into roll‐to‐roll processes.
In this study, a facile method to fabricate a cohesive ion‐gel based gate insulator for electrolyte‐gated transistors is introduced. The adhesive and flexible ion‐gel can be laminated easily on the semiconducting channel and electrode manually by hand. The ion‐gel is synthesized by a straightforward technique without complex procedures and shows a remarkable ionic conductivity of 4.8 mS cm−1 at room temperature. When used as a gate insulator in electrolyte‐gated transistors (EGTs), an on/off current ratio of 2.24×104 and a subthreshold swing of 117 mV dec−1 can be achieved. This performance is roughly equivalent to that of ink drop‐casted ion‐gels in electrolyte‐gated transistors, indicating that the film‐attachment method might represent a valuable alternative to ink drop‐casting for the fabrication of gate insulators.
Hybrid low-voltage physical unclonable function based on inkjet-printed metal-oxide transistors
(2020)
Modern society is striving for digital connectivity that demands information security. As an emerging technology, printed electronics is a key enabler for novel device types with free form factors, customizability, and the potential for large-area fabrication while being seamlessly integrated into our everyday environment. At present, information security is mainly based on software algorithms that use pseudo random numbers. In this regard, hardware-intrinsic security primitives, such as physical unclonable functions, are very promising to provide inherent security features comparable to biometrical data. Device-specific, random intrinsic variations are exploited to generate unique secure identifiers. Here, we introduce a hybrid physical unclonable function, combining silicon and printed electronics technologies, based on metal oxide thin film devices. Our system exploits the inherent randomness of printed materials due to surface roughness, film morphology and the resulting electrical characteristics. The security primitive provides high intrinsic variation, is non-volatile, scalable and exhibits nearly ideal uniqueness.
Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques
(2020)
This study evaluates four machine learning (ML) techniques (Decision Trees (DT), Random Forests (RF), Neural Networks (NN) and Probabilistic Neural Networks (PNN)) on their ability to accurately predict export credit insurance claims. Additionally, we compare the performance of the ML techniques against a simple benchmark (BM) heuristic. The analysis is based on the utilisation of a dataset provided by the Berne Union, which is the most comprehensive collection of export credit insurance data and has been used in only two scientific studies so far. All ML techniques performed relatively well in predicting whether or not claims would be incurred, and, with limitations, in predicting the order of magnitude of the claims. No satisfactory results were achieved predicting actual claim ratios. RF performed significantly better than DT, NN and PNN against all prediction tasks, and most reliably carried their validation performance forward to test performance.
A disturbed synchronization of the ventricular contraction can cause a highly developed systolic heart failure in affected patients with reduction of the left ventricular ejection fraction, which can often be explained by a diseased left bundle branch block (LBBB). If medication remains unresponsive, the concerned patients will be treated with a cardiac resynchronization therapy (CRT) system. The aim of this study was to integrate His-bundle pacing into the Offenburg heart rhythm model in order to visualize the electrical pacing field generated by His-Bundle-Pacing. Modelling and electrical field simulation activities were performed with the software CST (Computer Simulation Technology) from Dessault Systèms. CRT with biventricular pacing is to be achieved by an apical right ventricular electrode and an additional left ventricular electrode, which is floated into the coronary vein sinus. The non-responder rate of the CRT therapy is about one third of the CRT patients. His- Bundle-Pacing represents a physiological alternative to conventional cardiac pacing and cardiac resynchronization. An electrode implanted in the His-bundle emits a stronger electrical pacing field than the electrical pacing field of conventional cardiac pacemakers. The pacing of the Hisbundle was performed by the Medtronic Select Secure 3830 electrode with pacing voltage amplitudes of 3 V, 2 V and 1,5 V in combination with a pacing pulse duration of 1 ms. Compared to conventional pacemaker pacing, His-bundle pacing is capable of bridging LBBB conduction disorders in the left ventricle. The His-bundle pacing electrical field is able to spread via the physiological pathway in the right and left ventricles for CRT with a narrow QRS-complex in the surface ECG.
For the standard ISO 16842 cruciform test specimen, stresses obtained from the gauge area are far below the ultimate tensile strength due to high stress concentrations at the slit ends which lead to premature failure. Objective: To introduce a new cruciform specimen design which has been optimized with respect to the determination of yield surfaces. Methods: The proposed design differs from the ISO standard by an additional thinning of the gauge area and wider slits in the arms to avoid stress singularities. Compared to other cruciform test piece designs found in the literature, the stress distribution is still homogeneous and there is no need to reduce the size of the gauge area, thanks to the specimen’s well-balanced proportions. Results: Biaxial tensile tests have been conducted with aluminium 5754 alloy samples of different thicknesses. For the standard cruciform test piece, the maximum strain achieved at the gauge area is only 25% of the fracture strain. The optimized cruciform test piece can attain about 66% of the fracture strain before breaking. Conclusions: The optimized specimen design enables the measurement of yield surfaces at higher stress levels. In case of other materials such as elastomers, the slit length has be to adjusted accordingly.
Cooling towers or recoolers are one of the major consumers of electricity in a HVAC plant. The implementation and analysis of advanced control methods in a practical application and its comparison with conventional controllers is necessary to establish a framework for their feasibility especially in the field of decentralised energy systems. A standard industrial controller, a PID and a model based controller were developed and tested in an experimental set-up using market-ready components. The characteristics of these controllers such as settling time, control difference, and frequency of control actions are compared based on the monitoring data. Modern controllers demonstrated clear advantages in terms of energy savings and higher accuracy and a model based controller was easier to set-up than a PID.
Knight Götz von Berlichingen (1480–1562) lost his right hand distal to the wrist due to a cannon ball splinter injury in 1504 in the Landshut War of Succession at the age of 24. Early on, Götz commissioned a gunsmith to build the first “Iron Hand,” in which the artificial thumb and two finger blocks could be moved in their basic joints by a spring mechanism and released by a push button. Some years later, probably around 1530, a second “Iron Hand” was built, in which the fingers could be moved passively in all joints. In this review, the 3D computer-aided design (CAD) reconstructions and 3D multi-material polymer replica printings of the first “Iron hand“, which were developed in the last few years at Offenburg University, are presented. Even by today’s standards, the first “Iron Hand”—as could be shown in the replicas—demonstrates sophisticated mechanics and well thought-out functionality and still offers inspiration and food for discussion when it comes to the question of an artificial prosthetic replacement for a hand. It is also outlined how some of the ideas of this mechanical passive prosthesis can be translated into a modern motorized active prosthetic hand by using simple, commercially available electronic components.
In the field of neuroprosthetics, the current state-of-the-art method involves controlling the prosthesis with electromyography (EMG) or electrooculography/electroencephalography (EOG/EEG). However, these systems are both expensive and time consuming to calibrate, susceptible to interference, and require a lengthy learning phase by the patient. Therefore, it is an open challenge to design more robust systems that are suitable for everyday use and meet the needs of patients. In this paper, we present a new concept of complete visual control for a prosthesis, an exoskeleton or another end effector using augmented reality (AR) glasses presented for the first time in a proof-of-concept study. By using AR glasses equipped with a monocular camera, a marker attached to the prosthesis is tracked. Minimal relative movements of the head with respect to the prosthesis are registered by tracking and used for control. Two possible control mechanisms including visual feedback are presented and implemented for both a motorized hand orthosis and a motorized hand prosthesis. Since the grasping process is mainly controlled by vision, the proposed approach appears to be natural and intuitive.
In this editorial, a topic for general discussion in the field of neuroprosthetics of the upper limb is addressed: which way—invasive or non-invasive—is the right one for the future in the development of neuroprosthetic concepts. At present, two groups of research priorities (namely the invasive versus the non-invasive approach) seem to be emerging, without taking a closer look at the wishes but also the concerns of the patients. This piece is intended to stimulate the discussion on this.
Silicon (Si) has turned out to be a promising active material for next‐generation lithium‐ion battery anodes. Nevertheless, the issues known from Si as electrode material (pulverization effects, volume change etc.) are impeding the development of Si anodes to reach market maturity. In this study, we are investigating a possible application of Si anodes in low‐power printed electronic applications. Tailored Si inks are produced and the impact of carbon coating on the printability and their electrochemical behavior as printed Si anodes is investigated. The printed Si anodes contain active material loadings that are practical for powering printed electronic devices, like electrolyte gated transistors, and are able to show high capacity retentions. A capacity of 1754 mAh/gSi is achieved for a printed Si anode after 100 cycles. Additionally, the direct applicability of the printed Si anodes is shown by successfully powering an ink‐jet printed transistor.
Fast charging of lithium-ion batteries remains one of the most delicate challenges for the automotive industry, being seriously affected by the formation of lithium metal in the negative electrode. Here we present a physicochemical pseudo-3D model that explicitly includes the plating reaction as side reaction running in parallel to the main intercalation reaction. The thermodynamics of the plating reaction are modeled depending on temperature and ion concentration, which differs from the often-used assumption of a constant plating condition of 0 V anode potential. The reaction kinetics are described with an Arrhenius-type rate law parameterized from an extensive literature research. Re-intercalation of plated lithium was modeled to take place either via reverse plating (solution-mediated) or via an explicit interfacial reaction (surface-mediated). At low temperatures not only the main processes (intercalation and solid-state diffusion) become slow, but also the plating reaction itself becomes slower. Using this model, we are able to predict typical macroscopic experimental observables that are indicative of plating, that is, a voltage plateau during discharge and a voltage drop upon temperature increase. A spatiotemporal analysis of the internal cell states allows a quantitative insight into the competition between intercalation and plating. Finally, we calculate operation maps over a wide range of C-rates and temperatures that allow to assess plating propensity as function of operating condition.
A new concept for robust non-invasive optical activation of motorized hand prostheses by simple and non-contactcommands is presented. In addition, a novel approach for aiding hand amputees is shown, outlining significantprogress in thinking worth testing. In this, personalized 3D-printed artificial flexible hands are combined withcommercially available motorized exoskeletons, as they are used e.g. in tetraplegics.
Embedded Analog Physical Unclonable Function System to Extract Reliable and Unique Security Keys
(2020)
Internet of Things (IoT) enabled devices have become more and more pervasive in our everyday lives. Examples include wearables transmitting and processing personal data and smart labels interacting with customers. Due to the sensitive data involved, these devices need to be protected against attackers. In this context, hardware-based security primitives such as Physical Unclonable Functions (PUFs) provide a powerful solution to secure interconnected devices. The main benefit of PUFs, in combination with traditional cryptographic methods, is that security keys are derived from the random intrinsic variations of the underlying core circuit. In this work, we present a holistic analog-based PUF evaluation platform, enabling direct access to a scalable design that can be customized to fit the application requirements in terms of the number of required keys and bit width. The proposed platform covers the full software and hardware implementations and allows for tracing the PUF response generation from the digital level back to the internal analog voltages that are directly involved in the response generation procedure. Our analysis is based on 30 fabricated PUF cores that we evaluated in terms of PUF security metrics and bit errors for various temperatures and biases. With an average reliability of 99.20% and a uniqueness of 48.84%, the proposed system shows values close to ideal.