Sökning: "Data provenance"

Visar resultat 1 - 5 av 30 uppsatser innehållade orden Data provenance.

1. 1. Data streaming provenance in advanced metering infrastructures

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Zozk Mohamed; [2023-11-24]
   Nyckelord :Advanced Metering Infrastructure; Ananke; Apache Flink; Göteborg Energi; Provenance; Stream processing; Stream Processing Engine;

   Sammanfattning : Increasing volumes of data in digital systems have made the traditional approach of gathering and storing all the data while analyzing it in bulks at periodic intervals challenging and costly. One such field is the electric grid market, which has started modernizing its aging grids into smart grids where Advanced Metering Infrastructures (AMIs) play a vital role. LÄS MER

3. 2. Cyber Threat Detection using Machine Learning on Graphs : Continuous-Time Temporal Graph Learning on Provenance Graphs

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jakub Reha; [2023]
   Nyckelord :Graph neural networks; Temporal graphs; Benchmark datasets; Anomaly detection; Heterogeneous graphs; Provenance graphs; Grafiska neurala nätverk; temporala grafer; benchmark-datauppsättningar; anomalidetektering; heterogena grafer; härkomstgrafer;

   Sammanfattning : Cyber attacks are ubiquitous and increasingly prevalent in industry, society, and governmental departments. They affect the economy, politics, and individuals. LÄS MER

4. 3. Risk Assessment of Digital Assets – Insurance Applications in Cryptocurrencies and NFTs

   Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

   Författare :Roberto Delgado Ferrezuelo; [2023]
   Nyckelord :Blockchain; NFTs; private key; phishing; floor price; rarity; cold wallet; hot wallet; risk premium; Technology and Engineering;

   Sammanfattning : The aim of the project is to develop a framework for an insurance policy for digital assets. The project comprised several stages, starting with the identification of risks associated with these assets. Policyholders were then categorized into two groups based on a predefined rating factor. LÄS MER

5. 4. Manufacturing Knowledge Management Using a Virtual Factory-Based Ontology Implemented in a Graph Database

   Magister-uppsats, Högskolan i Skövde/Institutionen för ingenjörsvetenskap

   Författare :Mehran Ghorbani Tajani; [2022]
   Nyckelord :Knowledge Management; Ontology; Graph database; Graph theory; Virtual Factory; Knowledge-Driven Optimization;

   Sammanfattning : Ontology-based technologies like Semantic Web and Knowledge Graphs are promising for knowledge management in manufacturing industries. In the literature there are abundant of publications related to using ontologies to represent and capture knowledge in manufacturing. LÄS MER

7. 5. Increasing Reproducibility Through Provenance, Transparency and Reusability in a Cloud-Native Application for Collaborative Machine Learning

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för datorteknik

   Författare :Adam Ekström Hagevall; Carl Wikström; [2021]
   Nyckelord :Machine Learning; MLOps; STACKn; Reproducibility; Replicability; Provenance; Transparency; Reusability; Kubernetes; Cloud-Native; Open Source; Software Engineering;

   Sammanfattning : The purpose of this thesis paper was to develop new features in the cloud-native and open-source machine learning platform STACKn, aiming to strengthen the platform's support for conducting reproducible machine learning experiments through provenance, transparency and reusability. Adhering to the definition of reproducibility as the ability of independent researchers to exactly duplicate scientific results with the same material as in the original experiment, two concepts were explored as alternatives for this specific goal: 1) Increased support for standardized textual documentation of machine learning models and their corresponding datasets; and 2) Increased support for provenance to track the lineage of machine learning models by making code, data and metadata readily available and stored for future reference. LÄS MER