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  1. Automatic Anomaly Detection over Sliding Windows: Grand Challenge. Pages 310 - 314. PREVIOUS CHAPTER. Runtime Anomaly Detection Method in Smart Factories using Machine Learning on RDF Event Streams. ... Automatic Anomaly Detection over Sliding Windows: Grand Challenge. Computer systems organization. Architectures. Distributed architectures.
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  3. 2017.debs.org

    Grand Challenge: Automatic Anomaly Detection over Sliding Windows Problem • Real-time anomaly detection based on the observation of a stream of events. ... (TT) grant No 731932 and Big Data Value ecosystem (BDVe) grant No 732630. Architecture •Sequential approach performs
  4. researchgate.net

    The ACM DEBS Grand Challenge 2017 focuses on real-time anomaly detection for manufacturing equipments based on the observation of a stream of measurements generated by embedded digital and ...
  5. edwardcurry.org

    alies over a sliding time window and sorts them based on their timestamp. Yet at a high level of parallelism, an event with an earlier timestamp than the events in the current window might appear in the next window slide; hence, we only forward the event holding the earliest timestamp in the current window. 3 ANOMALY DETECTION SOLUTION
  6. researchrepository.universityofgalway.ie

    The ACM DEBS Grand Challenge 2017 focuses on real-time anomaly detection for manufacturing equipments based on the observation of a stream of measurements generated by embedded digital and analogue sensors. ... we present our solution to the challenge leveraging the Apache Flink stream processing framework and anomaly ordering based on sliding ...
  7. mural.maynoothuniversity.ie

    MURAL - Maynooth University Research Archive Library

    https://mural.maynoothuniversity.ie › 16007

    The ACM DEBS Grand Challenge 2017 focuses on real-time anomaly detection for manufacturing equipments based on the observation of a stream of measurements generated by embedded digital and analogue sensors. ... Automatic Anomaly Detection over Sliding Windows: Grand Challenge ... Souleiman and ul Hassan, Umair and Curry, Edward (2017) Automatic ...
  8. academia.edu

    Grand Challenge: Automatic Anomaly Detection over Sliding Windows Tarek Zaarour Niki Pavlopoulou Souleiman Hasan Insight Centre for Data Analytics, NUI, Galway tarek.zaarour@insight-centre.org Insight Centre for Data Analytics, NUI, Galway niki.pavlopoulou@insight-centre.org Lero - The Irish Software Research Centre, NUI, Galway souleiman.hasan ...
  9. edwardcurry.org

    The ACM DEBS Grand Challenge 2017 focuses on real-time anomaly detection for manufacturing equipments based on the observation of a stream of measurements generated by embedded digital and analogue sensors. ... Edward Curry, "Automatic Anomaly Detection over Sliding Windows", In Proceedings of the 11th ACM International Conference on ...
  10. mural.maynoothuniversity.ie

    MURAL - Maynooth University Research Archive Library

    https://mural.maynoothuniversity.ie › id › eprint › 16007

    With the advances in the Internet of Things and rapid generation of vast amounts of data, there is an ever growing need for leveraging and evaluating event-based systems as a basis for building realtime data analytics applications. The ability to detect, analyze, and respond to abnormal patterns of events in a timely manner is as challenging as it is important.
  11. Automatic Anomaly Detection over Sliding Windows: Grand Challenge: Publication Type: Conference Paper: Year of Publication: 2017: Authors: Zaarour T, Pavlopoulou N, Hasan S, Hassan Uul, Curry E: Conference Name: Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems: Publisher: ACM: Conference Location: New ...

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