Biblio

Filters: Author is Muller, A.  [Clear All Filters]
2021-11-29
Nicoloiu, A., Nastase, C., Zdru, I., Vasilache, D., Boldeiu, G., Ciornei, M. C., Dinescu, A., Muller, A..  2021.  Novel ScAlN/Si SAW-type devices targeting surface acoustic wave/spin wave coupling. 2021 International Semiconductor Conference (CAS). :67–70.
This paper reports high frequency surface acoustic wave (SAW) devices developed on Sc doped (30%) AlN on high resistivity Si for demonstrating surface acoustic wave – spin wave coupling. Enhanced Q-factors were found for both propagation modes – Rayleigh (4.7 GHz) and Sezawa (8 GHz). SAW/SW (spin wave) coupling is proven for two-ports SAW structures having a magnetostrictive layer of Ni between the two interdigitated transducers (IDTs). A decrease of 3.42 dB was observed in the amplitude of the transmission parameter, at resonance, when the magnetic field was applied. The angle between the applied magnetic field and the SAW propagation direction is π/4.
2015-05-05
Koch, S., John, M., Worner, M., Muller, A., Ertl, T..  2014.  VarifocalReader #x2014; In-Depth Visual Analysis of Large Text Documents. Visualization and Computer Graphics, IEEE Transactions on. 20:1723-1732.

Interactive visualization provides valuable support for exploring, analyzing, and understanding textual documents. Certain tasks, however, require that insights derived from visual abstractions are verified by a human expert perusing the source text. So far, this problem is typically solved by offering overview-detail techniques, which present different views with different levels of abstractions. This often leads to problems with visual continuity. Focus-context techniques, on the other hand, succeed in accentuating interesting subsections of large text documents but are normally not suited for integrating visual abstractions. With VarifocalReader we present a technique that helps to solve some of these approaches' problems by combining characteristics from both. In particular, our method simplifies working with large and potentially complex text documents by simultaneously offering abstract representations of varying detail, based on the inherent structure of the document, and access to the text itself. In addition, VarifocalReader supports intra-document exploration through advanced navigation concepts and facilitates visual analysis tasks. The approach enables users to apply machine learning techniques and search mechanisms as well as to assess and adapt these techniques. This helps to extract entities, concepts and other artifacts from texts. In combination with the automatic generation of intermediate text levels through topic segmentation for thematic orientation, users can test hypotheses or develop interesting new research questions. To illustrate the advantages of our approach, we provide usage examples from literature studies.