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Memento mori!
(2022)
Das plötzliche Ende des romantischen Komponisten Felix Mendelssohn Bartholdy (1809–1847) gibt uns auch heute noch Rätsel auf. Einiges deutet auf ein rupturiertes zerebrales Aneurysma mit konsekutiver Subarachnoidalblutung hin. Das Quellenmaterial zu den Symptomen seiner Todeskrankheit wird in dieser Arbeit ausführlich vorgestellt und diskutiert. Eine mögliche familiäre Disposition im Sinne eines Ehlers-Danlos-Syndroms Typ IV wird erörtert.
Dieser Beitrag beschreibt, wie mit Campbells Schema der „Heldenreise“ personalisierte Narrative der obersten Führungsebene aufgebaut werden können, um für interne und externe Stakeholder eine Orientierung zu bieten und die Unternehmenskultur bewusst zu prägen und zu beeinflussen. Das Beispiel der Preisträgerportraits des Manager Magazins zeigt, dass diese Methode breite Anwendung findet und dabei auch unterschiedliche funktionale Zuschreibungen der Führungsrolle erfolgen können.
Heat generation that is coupled with electricity usage, like combined heat and power generators or heat pumps, can provide operational flexibility to the electricity sector. In order to make use of this in an optimized way, the flexibility that can be provided by such plants needs to be properly quantified. This paper proposes a method for quantifying the flexibility provided through a cluster of such heat generators. It takes into account minimum operational time and minimum down-time of heat generating units. Flexibility is defined here as the time period over which plant operation can be either delayed or forced into operation, thus providing upward or downward regulation to the power system on demand. Results for one case study show that a cluster of several smaller heat generation units does not provide much more delayed operation flexibility than one large unit with the same power, while it more than doubles the forced operation flexibility. Considering minimum operational time and minimum down-time of the units considerably limits the available forced and delayed operation flexibility, especially in the case of one large unit.
Purpose: Participation and accessibility issues faced by gamers with multi-sensory disabilities are themes yet to be fully understood by accessible technology researchers. In this work, we examine the personal experiences and perceptions of individuals with deafblindness who play games despite their disability, as well as the reasons that lead some of them to stop playing games.
Materials and methods: We conducted 60 semi-structured interviews with individuals living with deafblindness in five European countries: United Kingdom, Germany, Netherlands, Greece and Sweden.
Results: Participants stated that reasons for playing games included them being a fun and entertaining hobby, for socialization and meeting others, or for occupying the mind. Reasons for stop playing games included essentially accessibility issues, followed by high cognitive demand, changes in gaming experience due their disability, financial reasons, or because the accessible version of a specific game was not considered as fun as the original one.
Conclusions: We identified that a considerable number of individuals with deafblindness enjoy playing casual mobile games such as Wordfeud and Sudoku as a pastime activity. Despite challenging accessibility issues, games provide meaningful social interactions to players with deafblindness. Finally, we introduce a set of user-driven recommendations for making digital games more accessible to players with a diverse combination of sensory abilities.
IMPLICATIONS FOR REHABILITATION
- Digital games were considered a fun and entertaining hobby by participants with deafblindness. Furthermore, participants play games for socialization and meeting others, or for occupying the mind.
- Digital games provide meaningful social interactions and past time to persons with deafblindness.
- On top of accessibility implications, our findings draw attention to the importance of the social element of gaming for persons with deafblindness.
- Based on interviews, we introduce a set of user-driven recommendations for making digital games more accessible to players with a diverse combination of sensory abilities.
Surface acoustic waves are propagated toward the edge of an anisotropic elastic medium (a silicon crystal), which supports leaky waves with a high degree of localization at the tip of the edge. At an angle of incidence corresponding to phase matching with this leaky wedge wave, a sharp peak in the reflection coefficient of the surface wave was found. This anomalous reflection is associated with efficient excitation of the leaky wedge wave. In laser ultrasound experiments, surface acoustic wave pulses were excited and their reflection from the edge of the sample and their partial conversion into leaky wedge wave pulses was observed by optical probe-beam deflection. The reflection scenario and the pulse shapes of the surface and wedge-localized guided waves, including the evolution of the acoustic pulse traveling along the edge, have been confirmed in detail by numerical simulations.
Properties of higher-order surface acoustic wave modes in Al(1-x)Sc(x)N / sapphire structures
(2021)
In this work, surface acoustic wave (SAW) modes and their dependence on propagation directions in epitaxial Al0.68Sc0.32N(0001) films on Al2O3(0001) substrates were studied using numerical and experimental methods. In order to find optimal propagation directions for higher-order SAW modes, phase velocity dispersion branches of Al0.68Sc0.32N on Al2O3 with Pt mass loading were computed for the propagation directions <11-20> and <1-100> with respect to the substrate. Experimental investigations of phase velocities and electromechanical coupling were performed for comparison with the numerical results. Simulations carried out with the finite element method (FEM) and with a Green function approach allowed identification of each wave type, including Rayleigh, Sezawa and shear horizontal wave modes. For the propagation direction <1-100>, significantly increased wave guidance of the Sezawa mode compared to other directions was observed, resulting in enhanced electromechanical coupling (k2eff = 1.6 %) and phase velocity (vphase = 6 km/s). We demonstrated, that selecting wave propagation in <1-100> with high mass density electrodes results in increased electromechanical coupling without significant reduction in phase velocities for the Sezawa wave mode. An improved combination of metallization, Sc concentration x, and SAW propagation direction is suggested which exhibits both high electromechanical coupling (k2eff > 6 %) and high velocity (vphase = 5.5 km/s) for the Sezawa mode.
It is important to minimize the unscheduled downtime of machines caused by outages of machine components in highly automated production lines. Considering machine tools such as, grinding machines, the bearing inside of spindles is one of the most critical components. In the last decade, research has increasingly focused on fault detection of bearings. In addition, the rise of machine learning concepts has also intensified interest in this area. However, up to date, there is no single one-fits-all solution for predictive maintenance of bearings. Most research so far has only looked at individual bearing types at a time.
This paper gives an overview of the most important approaches for bearing-fault analysis in grinding machines. There are two main parts of the analysis presented in this paper. The first part presents the classification of bearing faults, which includes the detection of unhealthy conditions, the position of the error (e.g. at the inner or at the outer ring of the bearing) and the severity, which detects the size of the fault. The second part presents the prediction of remaining useful life, which is important for estimating the productive use of a component before a potential failure, optimizing the replacement costs and minimizing downtime.
In the last decade, deep learning models for condition monitoring of mechanical systems increasingly gained importance. Most of the previous works use data of the same domain (e.g., bearing type) or of a large amount of (labeled) samples. This approach is not valid for many real-world scenarios from industrial use-cases where only a small amount of data, often unlabeled, is available.
In this paper, we propose, evaluate, and compare a novel technique based on an intermediate domain, which creates a new representation of the features in the data and abstracts the defects of rotating elements such as bearings. The results based on an intermediate domain related to characteristic frequencies show an improved accuracy of up to 32 % on small labeled datasets compared to the current state-of-the-art in the time-frequency domain.
Furthermore, a Convolutional Neural Network (CNN) architecture is proposed for transfer learning. We also propose and evaluate a new approach for transfer learning, which we call Layered Maximum Mean Discrepancy (LMMD). This approach is based on the Maximum Mean Discrepancy (MMD) but extends it by considering the special characteristics of the proposed intermediate domain. The presented approach outperforms the traditional combination of Hilbert–Huang Transform (HHT) and S-Transform with MMD on all datasets for unsupervised as well as for semi-supervised learning. In most of our test cases, it also outperforms other state-of-the-art techniques.
This approach is capable of using different types of bearings in the source and target domain under a wide variation of the rotation speed.
Mit zunehmender Datenverfügbarkeit wird der Einsatz Maschinellen Lernens zur Steuerung und Optimierung von Supply Chains attraktiver, da die Qualität der Datenauswertung erhöht und gleichzeitig der Aufwand gesenkt werden kann. Anhand des SCOR-Modells werden exemplarische Ansätze als Orientierungshilfe eingeordnet und dazu passende Verfahren des Maschinellen Lernens vorgestellt.