Artificial Intelligence : Potenziale und Anwendungsbereiche für den Einsatz bei einer mittelgrossen Schweizer Krankenversicherung - der Sympany

Artificial Intelligence (AI) hat sich in den vergangenen 5-10 Jahren in vielen Anwendungsbereichen vom theoretischen Konzept zum praxistauglichen und entscheidenden Wettbewerbsfaktor entwickelt. Beschleunigt wurde dies durch das exponentielle Wachstum von verfügbaren Daten und kostengünstiger Rechenleistung. Obwohl es in der Versicherungsbranche einen allgemeinen Konsens über die strategische Bedeutung und die Wichtigkeit von AI-Technologien gibt, schreitet die Nutzung bisher nur langsam voran. Gerade für kleine und mittelgrosse Versicherungen, mit kleineren Budgets für Investitionen als grosse Marktteilnehmer, stellt sich die Frage, in welchen Anwendungsbereichen der Einsatz von Artificial Intelligence Potenzial bietet. Für die mittelgrosse Schweizer Krankenversicherung Sympany wurde diese Frage im Rahmen dieser Masterarbeit sorgfältig untersucht und beantwortet

Comparison of computational methods for the electrochemical stability window of solid-state electrolyte materials

Superior stability and safety are key promises attributed to all-solid-state batteries (ASSBs) containing solid-state electrolyte (SSE) compared to their conventional counterparts utilizing liquid electrolyte. To unleash the full potential of ASSBs, SSE materials that are stable when in contact with the low and high potential electrodes are required. The electrochemical stability window is conveniently used to assess the SSE-electrode interface stability. In the present work, we review the most important methods to compute the SSE stability window. Our analysis reveals that the stoichiometry stability method represents a bridge between HOMO-LUMO method and phase stability method (grand canonical phase diagram). Moreover, we provide computational implementations of these methods for SSE material screening. We compare their results for the relevant Li- and Na-SSE materials LGPS, LIPON, LLZO, LLTO, LATP, LISICON, and NASICON, and we discuss their relation to published experimental stability windows

Hommage à Matthieu Giroud

Echogéo a publié deux fois dans la rubrique Sur l’écrit, des contributions de Matthieu Giroud, l’une portant sur la place des commerçants dans les quartiers populaires affectés par un changement social et urbain (Berroir et al., 2015) et l’autre étant une interview retraçant les conditions de publication de la traduction qu’il a coordonnée d’un ouvrage incontournable de David Harvey, Paris, capitale de la modernité (Weber, 2013). La revue Echogéo a souhaité lui rendre à son tour hommage, au l..

SPARKLINE HISTOGRAMS FOR COMPARING EVOLUTIONARY OPTIMIZATION METHODS

Abstract: Comparing evolutionary optimization methods is a difficult task. As more and more of articles are published in this field, the readers and reviewers are swamped with information that is hard to decipher. We propose the use of sparkline histograms that allow compact representation of test data in a way which is extremely fast to read and more informative than usually given metrics

Meta-Lamarckian learning in three stage optimal memetic exploration

The file attached to this record is the authors final peer reviewed version. The publisher's final version can be found by following the DOI link.Three Stage Optimal Memetic Exploration (3SOME) is a single-solution optimization algorithm where the coordinated action of three distinct operators progressively perturb the solution in order to progress towards the problem's optimum. In the fashion of Memetic Computing, 3SOME is designed as an organized structure where the three operators interact by means of a success/failure logic. This simple sequential structure is an initial example of Memetic Computing approach generated by means of a bottom-up logic. This paper compares the 3SOME structure with a popular adaptive technique for Memetic Algorithms, namely Meta-Lamarckian learning. The resulting algorithm, Meta-Lamarckian Three Stage Optimal Memetic Exploration (ML3SOME) is thus composed of the same three 3SOME operators but makes use a different coordination logic. Numerical results show that the adaptive technique is overall efficient also in this Memetic Computing context. However, while ML3SOME appears to be clearly better than 3SOME for low dimensionality values, its performance appears to suffer from the curse of dimensionality more than that of the original 3SOME structure

An electronic nematic liquid in BaNi2_2As2_2

Understanding the organizing principles of interacting electrons and the emergence of novel electronic phases is a central endeavor of condensed matter physics. Electronic nematicity, in which the discrete rotational symmetry in the electron fluid is broken while the translational one remains unaffected, is a prominent example of such a phase. It has proven ubiquitous in correlated electron systems, and is of prime importance to understand Fe-based superconductors. Here, we find that fluctuations of such broken symmetry are exceptionally strong over an extended temperature range above phase transitions in BaNi$_2$(As$_{1−x}$P$_x$)$_2$, the nickel homologue to the Fe-based systems. This lends support to a type of electronic nematicity, dynamical in nature, which exhibits a particularly strong coupling to the underlying crystal lattice. Fluctuations between degenerate nematic configurations cause splitting of phonon lines, without lifting degeneracies nor breaking symmetries, akin to spin liquids in magnetic systems

Nanometric 3D Printing of Functional Materials by Atomic Layer Deposition

Atomic layer deposition (ALD) is a chemical vapour deposition (CVD) method that allows the layer-by-layer growth of functional materials by exposing a surface to different precursors in an alternative fashion. Thus, thanks to gas-solid reactions that are substrate-limited and self-terminating, precise control over thickness below the nanometer level can be achieved. While ALD was originally developed to deposit uniform coatings over large areas and on high-aspect-ratio features, in recent years the possibility to perform ALD in a selective fashion has gained much attention, in what is known as area-selective deposition (ASD). ASD is indeed a novel 3D printing approach allowing the deposition of functional materials (for example metals to oxides, nitrides or sulfides) with nanometric resolution in Z. The chapter will present an introduction to ALD, which will be followed by the description of the different approaches currently being developed for the ASD of functional materials (including initial approaches such as surface pre-patterning or activation, and newer concepts based on spatial CVD/ALD). The chapter will also include a brief overview of recent works involving the use of ALD to tune the properties of 3D printed parts

Optical properties of ZnO deposited by atomic layer deposition (ALD) on Si nanowires

International audienceIn this work, we report proof-of-concept results on the synthesis of Si core/ ZnO shell nanowires (SiNWs/ZnO) by combining nanosphere lithography (NSL), metal assisted chemical etching (MACE) and atomic layer deposition (ALD). The structural properties of the SiNWs/ZnO nanostructures prepared were investigated by X-ray diffraction, Raman spectroscopy, scanning and transmission electron microscopies. The X-ray diffraction analysis revealed that all samples have a hexagonal wurtzite structure. The grain sizes are found to be in the range of 7-14 nm. The optical properties of the samples were investigated using reflectance and photoluminescence spectroscopy. The study of photoluminescence (PL) spectra of SiNWs/ZnO samples showed the domination of defect emission bands, pointing to deviations of the stoichiometry of the prepared 3D ZnO nanostructures. Reduction of the PL intensity of the SiNWs/ZnO with the increase of SiNWs etching time was observed, depicting an advanced light scattering with the increase of the nanowire length. These results open up new prospects for the design of electronic and sensing devices

Round Robin Testing: Exploring Experimental Uncertainties through a Multifacility Comparison of a Hinged Raft Wave Energy Converter

The EU H2020 MaRINET2 project has a goal to improve the quality, robustness and accuracy of physical modelling and associated testing practices for the offshore renewable energy sector. To support this aim, a round robin scale physical modelling test programme was conducted to deploy a common wave energy converter at four wave basins operated by MaRINET2 partners. Test campaigns were conducted at each facility to a common specification and test matrix, providing the unique opportunity for intercomparison between facilities and working practices. A nonproprietary hinged raft, with a nominal scale of 1:25, was tested under a set of 12 irregular sea states. This allowed for an assessment of power output, hinge angles, mooring loads, and six-degree-of-freedom motions. The key outcome to be concluded from the results is that the facilities performed consistently, with the majority of variation linked to differences in sea state calibration. A variation of 5–10% in mean power was typical and was consistent with the variability observed in the measured significant wave heights. The tank depth (which varied from 2–5 m) showed remarkably little influence on the results, although it is noted that these tests used an aerial mooring system with the geometry unaffected by the tank depth. Similar good agreement was seen in the heave, surge, pitch and hinge angle responses. In order to maintain and improve the consistency across laboratories, we make recommendations on characterising and calibrating the tank environment and stress the importance of the device–facility physical interface (the aerial mooring in this case).</jats:p