Buchbeitrag

Dieser Artikel expliziert ein verbreitetes Paradigma der Maschinenethik, das Nebenbedingungsparadigma. Gemäß diesem Paradigma werden künstliche moralische Akteure1 geschaffen, um das durch komplexe und selbständige Systeme entstehende Risiko zu begrenzen. [...]

We provide the first method allowing to retrieve spaceborne SIF maps at 30 m ground resolution with a strong correlation (r$^2$ = 0.6) to high-quality airborne estimates of sun-induced fluorescence (SIF) ̇SIF estimates can provide explanatory information for many tasks related to agricultural management and physiological studies. While SIF products from airborne platforms are accurate and spatially well resolved, the data acquisition of such products remains science-oriented and limited to temporally constrained campaigns [...]

Ontological models empower stakeholders to establish shared ontological commitments for achieving objectives,including (1) fostering domain-specific understanding; (2) formalizing communication between stakeholdersand modelers; and (3) enabling knowledge inference through formal rule-based systems. A significantchallenge arises as conceptual modeling transitions from single-organizational contexts to heterogeneous,multi-perspective environments, raising questions about how quasi-universal conceptualizations can ensuredata interoperability. [...]

We introduce a correlative in situ platform for electro-thermal studies in both TEM and SEM using the same MEMS-based Nano-Chip. Equipped with up to eight electrodes, the chip enables precise electrical biasing and localized heating of as prepared samples under real operating conditions. [...]

The spatial derivatives in Hamilton-Jacobi partial differential equations for the definition of morphological operations such as dilation and erosion for grey-value images are replaced by fractional derivatives of arbitrary positive order. Focus is laid on geometric invariance with respect to reflections and rotations so that directional bias towards the coordinate directions is avoided. [...]

Understanding information propagation and computational capabilities in large-scale brain models is crucial for advancing both neuroscience and neuro-inspired computing. It remains unknown how complexity affects the performance of simulated biological networks in predicting non-linear dynamics. [...]