2 Search Results for "Morales, David"

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DOI: 10.4230/TGDK.2.1.2
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1

Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.
Cite as

Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
DOI: 10.4230/OASIcs.WCET.2016.9
Measurement-Based Timing Analysis of the AURIX Caches

Authors: Leonidas Kosmidis, Davide Compagnin, David Morales, Enrico Mezzetti, Eduardo Quinones, Jaume Abella, Tullio Vardanega, and Francisco J. Cazorla

Published in: OASIcs, Volume 55, 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016)

Abstract
Cache memories are one of the hardware resources with higher potential to reduce worst-case execution time (WCET) costs for software programs with tight real-time constraints. Yet, the complexity of cache analysis has caused a large fraction of real-time systems industry to avoid using them, especially in the automotive sector. For measurement-based timing analysis (MBTA) - the dominant technique in domains such as automotive - cache challenges the definition of test scenarios stressful enough to produce (cache) layouts that causing high contention. In this paper, we present our experience in enabling the use of caches for a real automotive application running on an AURIX multiprocessor, using software randomization and measurement-based probabilistic timing analysis (MBPTA). Our results show that software randomization successfully exposes - in the experiments performed for timing analysis - cache related variability, in a manner that can be effectively captured by MBPTA.
Cite as

Leonidas Kosmidis, Davide Compagnin, David Morales, Enrico Mezzetti, Eduardo Quinones, Jaume Abella, Tullio Vardanega, and Francisco J. Cazorla. Measurement-Based Timing Analysis of the AURIX Caches. In 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016). Open Access Series in Informatics (OASIcs), Volume 55, pp. 9:1-9:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{kosmidis_et_al:OASIcs.WCET.2016.9,
  author =	{Kosmidis, Leonidas and Compagnin, Davide and Morales, David and Mezzetti, Enrico and Quinones, Eduardo and Abella, Jaume and Vardanega, Tullio and Cazorla, Francisco J.},
  title =	{{Measurement-Based Timing Analysis of the AURIX Caches}},
  booktitle =	{16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016)},
  pages =	{9:1--9:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-025-5},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{55},
  editor =	{Schoeberl, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2016.9},
  URN =		{urn:nbn:de:0030-drops-69028},
  doi =		{10.4230/OASIcs.WCET.2016.9},
  annote =	{Keywords: WCET, caches, AURIX, Automotive}
}
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