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Digital Shadows as the aggregation, linkage and abstraction of data relating to physical objects are a central vision for the future of production. However, the majority of current research takes a technocentric approach, in which the human actors in production play a minor role. Here, the authors present an alternative anthropocentric perspective that highlights the potential and main challenges of extending the concept of Digital Shadows to humans. Following future research methodology, three prospections that illustrate use cases for Human Digital Shadows across organizational and hierarchical levels are developed: human-robot collaboration for manual work, decision support and work organization, as well as human resource management. Potentials and challenges are identified using separate SWOT analyses for the three prospections and common themes are emphasized in a concluding discussion.
Conventional EEG devices cannot be used in everyday life and
hence, past decade research has been focused on Ear-EEG for mobile,
at-home monitoring for various applications ranging from
emotion detection to sleep monitoring. As the area available for
electrode contact in the ear is limited, the electrode size and location
play a vital role for an Ear-EEG system. In this investigation, we
present a quantitative study of ear-electrodes with two electrode
sizes at different locations in a wet and dry configuration. Electrode
impedance scales inversely with size and ranges from 450 kΩ to
1.29 MΩ for dry and from 22 kΩ to 42 kΩ for wet contact at 10 Hz.
For any size, the location in the ear canal with the lowest impedance
is ELE (Left Ear Superior), presumably due to increased contact
pressure caused by the outer-ear anatomy. The results can be used
to optimize signal pickup and SNR for specific applications. We
demonstrate this by recording sleep spindles during sleep onset
with high quality (5.27 μVrms).
The transition within transportation towards battery electric vehicles can lead to a more sustainable future. To account for the development goal ‘climate action’ stated by the United Nations, it is mandatory, within the conceptual design phase, to derive energy-efficient system designs. One barrier is the uncertainty of the driving behaviour within the usage phase. This uncertainty is often addressed by using a stochastic synthesis process to derive representative driving cycles and by using cycle-based optimization. To deal with this uncertainty, a new approach based on a stochastic optimization program is presented. This leads to an optimization model that is solved with an exact solver. It is compared to a system design approach based on driving cycles and a genetic algorithm solver. Both approaches are applied to find efficient electric powertrains with fixed-speed and multi-speed transmissions. Hence, the similarities, differences and respective advantages of each optimization procedure are discussed.
Through a mirror darkly – On the obscurity of teaching goals in game-based learning in IT security
(2021)
Teachers and instructors use very specific language communicating teaching goals. The most widely used frameworks of common reference are the Bloom’s Taxonomy and the Revised Bloom’s Taxonomy. The latter provides distinction of 209 different teaching goals which are connected to methods. In Competence Developing Games (CDGs - serious games to convey knowledge) and in IT security education, a two- or three level typology exists, reducing possible learning outcomes to awareness, training, and education. This study explores whether this much simpler framework succeeds in achieving the same range of learning outcomes. Method wise a keyword analysis was conducted. The results were threefold: 1. The words used to describe teaching goals in CDGs on IT security education do not reflect the whole range of learning outcomes. 2. The word choice is nevertheless different from common language, indicating an intentional use of language. 3. IT security CDGs use different sets of terms to describe learning outcomes, depending on whether they are awareness, training, or education games. The interpretation of the findings is that the reduction to just three types of CDGs reduces the capacity to communicate and think about learning outcomes and consequently reduces the outcomes that are intentionally achieved.
Purpose Vascular risk factors and ocular perfusion are heatedly discussed in the pathogenesis of glaucoma. The retinal vessel analyzer (RVA, IMEDOS Systems, Germany) allows noninvasive measurement of retinal vessel regulation. Significant differences especially in the veins between healthy subjects and patients suffering from glaucoma were previously reported. In this pilot-study we investigated if localized vascular regulation is altered in glaucoma patients with altitudinal visual field defect asymmetry. Methods 15 eyes of 12 glaucoma patients with advanced altitudinal visual field defect asymmetry were included. The mean defect was calculated for each hemisphere separately (-20.99 ± 10.49 pro- found hemispheric visual field defect vs -7.36 ± 3.97 dB less profound hemisphere). After pupil dilation, RVA measurements of retinal arteries and veins were conducted using the standard protocol. The superior and inferior retinal vessel reactivity were measured consecutively in each eye. Results Significant differences were recorded in venous vessel constriction after flicker light stimulation and overall amplitude of the reaction (p \ 0.04 and p \ 0.02 respectively) in-between the hemispheres spheres. Vessel reaction was higher in the hemisphere corresponding to the more advanced visual field defect. Arterial diameters reacted similarly, failing to reach statistical significance. Conclusion Localized retinal vessel regulation is significantly altered in glaucoma patients with asymmetri altitudinal visual field defects. Veins supplying the hemisphere concordant to a less profound visual field defect show diminished diameter changes. Vascular dysregulation might be particularly important in early glaucoma stages prior to a significant visual field defect.
Experimental and numerical investigation on the effect of pressure on micromix hydrogen combustion
(2021)
The micromix (MMX) combustion concept is a DLN gas turbine combustion technology designed for high hydrogen content fuels. Multiple non-premixed miniaturized flames based on jet in cross-flow (JICF) are inherently safe against flashback and ensure a stable operation in various operative conditions.
The objective of this paper is to investigate the influence of pressure on the micromix flame with focus on the flame initiation point and the NOx emissions. A numerical model based on a steady RANS approach and the Complex Chemistry model with relevant reactions of the GRI 3.0 mechanism is used to predict the reactive flow and NOx emissions at various pressure conditions. Regarding the turbulence-chemical interaction, the Laminar Flame Concept (LFC) and the Eddy Dissipation Concept (EDC) are compared. The numerical results are validated against experimental results that have been acquired at a high pressure test facility for industrial can-type gas turbine combustors with regard to flame initiation and NOx emissions.
The numerical approach is adequate to predict the flame initiation point and NOx emission trends. Interestingly, the flame shifts its initiation point during the pressure increase in upstream direction, whereby the flame attachment shifts from anchoring behind a downstream located bluff body towards anchoring directly at the hydrogen jet. The LFC predicts this change and the NOx emissions more accurately than the EDC. The resulting NOx correlation regarding the pressure is similar to a non-premixed type combustion configuration.
This study investigates the influence of pressure on the temperature distribution of the micromix (MMX) hydrogen flame and the NOx emissions. A steady computational fluid dynamic (CFD) analysis is performed by simulating a reactive flow with a detailed chemical reaction model. The numerical analysis is validated based on experimental investigations. A quantitative correlation is parametrized based on the numerical results. We find, that the flame initiation point shifts with increasing pressure from anchoring behind a downstream located bluff body towards anchoring upstream at the hydrogen jet. The numerical NOx emissions trend regarding to a variation of pressure is in good agreement with the experimental results. The pressure has an impact on both, the residence time within the maximum temperature region and on the peak temperature itself. In conclusion, the numerical model proved to be adequate for future prototype design exploration studies targeting on improving the operating range.
The term ocular rigidity is widely used in clinical ophthalmology. Generally it is assumed as a resistance of the whole eyeball to mechanical deformation and relates to biomechanical properties of the eye and its tissues. Basic principles and formulas for clinical tonometry, tonography and pulsatile ocular blood flow measurements are based on the concept of ocular rigidity. There is evidence for altered ocular rigidity in aging, in several eye diseases and after eye surgery. Unfortunately, there is no consensual view on ocular rigidity: it used to make a quite different sense for different people but still the same name. Foremost there is no clear consent between biomechanical engineers and ophthalmologists on the concept. Moreover ocular rigidity is occasionally characterized using various parameters with their different physical dimensions. In contrast to engineering approach, clinical approach to ocular rigidity claims to characterize the total mechanical response of the eyeball to its deformation without any detailed considerations on eye morphology or material properties of its tissues. Further to the previous chapter this section aims to describe clinical approach to ocular rigidity from the perspective of an engineer in an attempt to straighten out this concept, to show its advantages, disadvantages and various applications.
The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.
Multi-attribute relation extraction (MARE): simplifying the application of relation extraction
(2021)
Natural language understanding’s relation extraction makes innovative and encouraging novel business concepts possible and facilitates new digitilized decision-making processes. Current approaches allow the extraction of relations with a fixed number of entities as attributes. Extracting relations with an arbitrary amount of attributes requires complex systems and costly relation-trigger annotations to assist these systems. We introduce multi-attribute relation extraction (MARE) as an assumption-less problem formulation with two approaches, facilitating an explicit mapping from business use cases to the data annotations. Avoiding elaborated annotation constraints simplifies the application of relation extraction approaches. The evaluation compares our models to current state-of-the-art event extraction and binary relation extraction methods. Our approaches show improvement compared to these on the extraction of general multi-attribute relations.
For typical cases of non-isolated lightning
protection systems (LPS) the impulse currents are investigated which may flow through a human body directly touching a structural part of the LPS. Based on a basic LPS model with conventional down-conductors especially the cases of external and internal steel columns and metal façades are considered and compared. Numerical simulations of the line quantities voltages and currents in the time domain are performed with an equivalent circuit of the entire LPS.
As a result it can be stated that by increasing the number of conventional down-conductors and external steel columns the threat for a human being can indeed be reduced, but not down to an acceptable limit. In case of internal steel columns used as natural down-conductors the threat can be reduced sufficiently, depending on the low-resistive connection of the steel columns to the lightning equipotential bonding or the earth termination system, resp. If a metal façade is used the threat for human beings touching is usually very low, if the façade is sufficiently interconnected and multiply connected to the lightning equipotential bonding or the earth termination system, resp.
The coupling of ligand-stabilized gold nanoparticles with field-effect devices offers new possibilities for label-free biosensing. In this work, we study the immobilization of aminooctanethiol-stabilized gold nanoparticles (AuAOTs) on the silicon dioxide surface of a capacitive field-effect sensor. The terminal amino group of the AuAOT is well suited for the functionalization with biomolecules. The attachment of the positively-charged AuAOTs on a capacitive field-effect sensor was detected by direct electrical readout using capacitance-voltage and constant capacitance measurements. With a higher particle density on the sensor surface, the measured signal change was correspondingly more pronounced. The results demonstrate the ability of capacitive field-effect sensors for the non-destructive quantitative validation of nanoparticle immobilization. In addition, the electrostatic binding of the polyanion polystyrene sulfonate to the AuAOT-modified sensor surface was studied as a model system for the label-free detection of charged macromolecules. Most likely, this approach can be transferred to the label-free detection of other charged molecules such as enzymes or antibodies.