Semantic validation in spatio-temporal schema integration

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One of the primary causes of non-uniform snowfall deposition on the ground in mountainous regions is the preferential deposition of snow, which results from the interaction of near-surface winds with topography and snow particles. However, producing high-r ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...

In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

We study the proof theory and algorithms for orthologic, a logical system based on ortholattices, which have shown practical relevance in simplification and normalization of verification conditions. Ortholattices weaken Boolean algebras while having polyno ...

Combined high-fusion performance and long-pulse operation is one of the key integration challenges for fusion energy development in magnetic devices. Addressing these challenges requires an integrated vision of physics and engineering aspects with the purp ...

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

A method for optimizing memory access for database operations is provided. The method may include performing a first database operation by at least executing a first instruction stream associated with the first database operation. The first database opera ...

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

In this thesis we study a problem of searching in a space of objects using comparisons. To navigate through the space to the target object

t

, we ask a sequence of questions of the form ``which object

i

j

is closer to

t

?'' for which we observe no ...

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

Various endeavours into semantic web technologies and ontology engineering have been made within the organisation of cultural data, facilitating public access to digital assets. Although models for conceptualising objects have reached a certain level of ma ...

As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such formats a ...

Time series of hydrochemical parameters support the investigation of dominant karst hydrological processes and conceptual model structures. Nevertheless, high costs for sample collection and analyses cause hydrochemical data to be rarely available at a suf ...

Functional materials that enable many technological applications in our everyday lives owe their unique properties to defects that are carefully engineered and incorporated into these materials during processing. However, optimizing and characterizing thes ...

Driven by the rising popularity of chatbots such as ChatGPT, there is a budding line of research proposing guidelines for chatbot design, both in general and specifically for digital education. Nevertheless, few researchers have focused on providing concep ...

Semantic validation in spatio-temporal schema integration

Chattez avec Graph Search

Snowfall deposition in mountainous terrain: a statistical downscaling scheme from high-resolution model data on simulated topographies

Extensions of Peer Prediction Incentive Mechanisms

A semantic model-based systems engineering approach for assessing the operational performance of metal forming process

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Orthologic with Axioms

Long plasma duration operation analyses with an international multi-machine (tokamaks and stellarators) database

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Determining an optimum quantity of interleaved instruction streams of defined coroutines

E-Scan: Consuming Contextual Data with Model Plugins

Stochastic Models for Comparison-based Search

Data-driven modeling of beam loss in the LHC

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Building a Knowledge Graph of Chinese Kung Fu Masters From Heterogeneous Bilingual Data

Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics

Deriving Major Ion Concentrations at High Resolution from Continuous Electrical Conductivity Measurements in Karst Systems

AiiDA-defects: an automated and fully reproducible workflow for the complete characterization of defect chemistry in functional materials

TRACE: A Conceptual Model to Guide the Design of Educational Chatbots