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GIPSY: Joining Spatial Datasets with Contrasting Density

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Data-intensive systems are the backbone of today's computing and are responsible for shaping data centers. Over the years, cloud providers have relied on three principles to maintain cost-effective data systems: use disaggregation to decouple scaling, use ...

Assoc Computing Machinery2023

Data and code associated with the paper 'Mode-Specific Coupling of Nanoparticle-on-Mirror Cavities with Cylindrical Vector Beams'

Christophe Marcel Georges Galland, Philippe Andreas Rölli, Sachin Suresh Verlekar, Valeria Vento

Data and code associated with the following paper: V. Vento et al, Nano Lett. 2023 A thorough explanation of the experiment performed is available there. The name of each sub-folder and file in Maps_data_code.zip indicates the correspondin ...

Zenodo2023

ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

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We study the energy-critical nonlinear Schrodinger equation with randomised initial data in dimensions d > 6. We prove that the Cauchy problem is almost surely globally well-posed with scattering for randomised supercritical initial data in H-s(Rd) wheneve ...

Amer Inst Mathematical Sciences-Aims2023

Data and Workflow to: Three-dimensional buoyant hydraulic fractures: finite volume release (Möri and Lecampion, (2023))

Andreas Möri, Brice Tanguy Alphonse Lecampion

This upload contains the relevant scripts, notebooks, and datasets to reproduce the numerically obtained results of the Journal article "Three-dimensional buoyant hydraulic fractures: finite volume release" by Möri and Lecampion, (2023). ...

Zenodo2023

Shared metadata for data-centric materials science

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The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

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Reinforcement Learning for Joint Design and Control of Battery-PV Systems

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The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

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Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

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Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

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On Artificial Intelligence and Manipulation

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The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about ne ...

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Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

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Exploiting the recent advancements in artificial intelligence, showcased by ChatGPT and DALL-E, in real-world applications necessitates vast, domain-specific, and publicly accessible datasets. Unfortunately, the scarcity of such datasets poses a significan ...

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