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

Anastasia Ailamaki, Viktor Sanca

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 ...

2023

LAQy: Efficient and Reusable Query Approximations via Lazy Sampling

Anastasia Ailamaki, Viktor Sanca, Periklis Chrysogelos

Modern analytical engines rely on Approximate Query Processing (AQP) to provide faster response times than the hardware allows for exact query answering. However, existing AQP methods impose steep performance penalties as workload unpredictability increase ...

2023

When is it safe to run a transactional workload under Read Committed?

Christoph Koch, Bas Ketsman

The popular isolation level multiversion Read Committed (RC) exchanges some of the strong guarantees of serializability for increased transaction throughput. Nevertheless, transaction workloads can sometimes be executed under RC while still guaranteeing se ...

ASSOC COMPUTING MACHINERY2023

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

Colin Neil Jones, Roland Schwan, Melanie Nicole Zeilinger, Xuan Truong Nghiem

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 ...

IEEE2023

Using Cloud Functions as Accelerator for Elastic Data Analytics

Anastasia Ailamaki, Haoqiong Bian, Tiannan Sha

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

ACM2023

Determining an optimum quantity of interleaved instruction streams of defined coroutines

Anastasia Ailamaki, Georgios Psaropoulos

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 ...

2023

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

Paolo Benettin

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 ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

E-Scan: Consuming Contextual Data with Model Plugins

Anastasia Ailamaki, Viktor Sanca

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 ...

2023

AIDRES: A database for the decarbonisation of the heavy industry in Europe

François Maréchal, Luc Girardin, Daniel Alexander Florez Orrego, Ivan Daniel Kantor, Shivom Sharma, Julia Granacher, Meire Ellen Gorete Ribeiro Domingos, Rafael Amorim Leandro De Castro Amoedo, Yi Zhao

The AIDRES database aims to support the long-term objective of a fully integrated industrial strategy in the EU 27, providing a service to the European Commission and a catalogue for industries to understand the effectiveness, efficiency and cost of potent ...

Universidad de Las Palmas de Gran Canaria2023