Nutzung von Social-Media-Analysen zur Erkennung von Nachhaltigkeitstrends in Saudi-Arabiens sich entwickelnder Markt
Saudi-Arabiens schnelles Wirtschaftswachstum und soziale Entwicklung unter Vision 2030 bieten eine einzigartige Gelegenheit, aufkommende Trends in Echtzeit zu verfolgen. Uncovering trends in real time can open up new avenues for business and investment opportunities. This paper explores how AI...
Navigieren im Zustand des kognitiven Flusses: Kontextbewusste KI-Interventionen für effektive Argumentationsunterstützung
Flow theory describes an optimal cognitive state where individuals experience deep focus and intrinsic motivation when a task’s difficulty aligns with their skill level. In AI-augmented reasoning, interventions that disrupt the state of cognitive flow can hinder rather than enhance decision-making. Das...
Non-Renormalizable SU(5) GUTs: Leptoquark-Induced Neutrino Masses
We revisit the doublet-triplet splitting problem within the $SU(5)$ gauge group framework to advocate a viable regime with the light scalar leptoquark of the doublet-triplet splitting notoriety that is compatible with the current experimental bounds on partial proton decay lifetimes. We explicitly...
EnsAI: An Emulator for Atmospheric Chemical Ensembles
Ensemble-based methods for data assimilation and emission inversions are a popular way to encode flow-dependency within the model error covariance. While most ensemble methods do not require the use of an adjoint model, the need to repeatedly run a geophysical model to...
Modellierung von Gezeitenstörungen mit dynamischen Gezeiten
Tidal disruption events (TDEs) occur when stars pass close enough to supermassive black holes to be torn apart by tidal forces. Traditionally, these events are studied with computationally intensive hydrodynamical simulations. In diesem Papier, we present a fast, physically motivated two-stage model...
LiveCC: Lernen von Video-LLM mit skalierter Streaming-Sprachtranskription
Aktuelle Video-Großsprachmodelle (Video-LLMs) often depend on costly human annotations or proprietary model APIs (z.B., GPT-4o) Trainingsdaten zu erstellen, was ihre Ausbildung im großen Maßstab einschränkt. In diesem Papier, we explore large-scale training for Video LLM with cheap automatic...
LLMs treffen auf Federated Learning für skalierbares und sicheres IoT-Management
The rapid expansion of IoT ecosystems introduces severe challenges in scalability, security, and real-time decision-making. Traditional centralized architectures struggle with latency, privacy concerns, and excessive resource consumption, making them unsuitable for modern large-scale IoT deployments. This paper presents a novel Federated Learning-driven...
$η$-Einstein Sasakian Lie algebras
We study $\eta$-Einstein Sasakian structures on Lie algebras, das heißt, Sasakian structures whose associated Ricci tensor satisfies an Einstein-like condition. We divide into the cases in which the Lie algebra’s centre is non-trivial (and necessarily one-dimensional) and those where it is zero....
LHCspin: a Polarized Gas Target for LHC
The goal of the LHCspin project is to develop innovative solutions for measuring the 3D structure of nucleons in high-energy polarized fixed-target collisions at LHC, exploring new processes and exploiting new probes in a unique, previously unexplored, kinematic regime. A precise multi-dimensional...
Rotational ultrasound and photoacoustic tomography of the human body
Imaging the human body’s morphological and angiographic information is essential for diagnosing, monitoring, and treating medical conditions. Ultrasonography performs the morphological assessment of the soft tissue based on acoustic impedance variations, whereas photoacoustic tomography (PAT) can visualize blood vessels based on intrinsic...