A Computer Vision-Based Standalone System for Automated Operational Data Collection at Non-Towered Airports

Autor: Mohammad Farhadmanesh, Abbas Rashidi, Abhishek Kumar Subedi, Nikola Markovic

Publikováno v: IEEE Access, Vol 12, Pp 95245-95264 (2024)

The accurate collection of operational data at airports is essential for ensuring the fair distribution of national funds. However, many U.S. airports lack control towers, which forces planners to rely on sound, radio, and transponder-based systems f

Externí odkaz: https://doaj.org/article/4c9ca53f16834081bf0d127954681867

Hybrid Condition Monitoring for Power Converters: Learning-Based Methods With Statistical Guarantees

Autor: Nikola Markovic, Thomas Stoetzel, Volker Staudt, Dorothea Kolossa

Publikováno v: IEEE Access, Vol 11, Pp 31855-31865 (2023)

In this paper, a new learning-based method is proposed for the early detection of changes of parameters in power converters. It circumvents the pertinent shortcomings of previous model-based methods, such as their need for acquiring switching signals

Externí odkaz: https://doaj.org/article/c42092bedd1d4f28bcc9b187bb8583bc

Introduction of a method to calculate cumulative age- and gender-specific lifetime attributable risk (LAR) of cancer in populations after a large-scale nuclear power plant accident.

Autor: Christopher Rääf, Nikola Markovic, Martin Tondel, Robert Wålinder, Mats Isaksson

Publikováno v: PLoS ONE, Vol 15, Iss 2, p e0228549 (2020)

The effect of age and gender in risk estimates related to long-term residence in areas contaminated by nuclear power plant fallout was evaluated by applying the lifetime attributable risk (LAR) concept to an existing exposure model that was previousl

Externí odkaz: https://doaj.org/article/856157302235477c96aabd357a72ca35

POLARIS

Autor: Goran Lukic, Vukasin Stefanovic, Srikumar Rangarajan, Ioannis Alagiannis, Marko Zivanovic, Marko Milojevic, Aleksandar Vujic, Nikola Markovic, Steve Toscano, Nikola Vujic, Milos Radic, Josep Aguilar-Saborit, Cesar A. Galindo-Legaria, Djordje Trifunovic, José A. Blakeley, Dragan Tomic, Milan Simic, Girish Dasarathy, Ana Manic, Alan Halverson, Nemanja Djurkic, Maja Stikic, Maja Damjanic, Lazar Davidovic, Bosko Mihic, Krish Srinivasan, Marko Sosic, Djordje Maksimovic, Kevin Bocksrocker, Igor Stanko, Ugljesa Milic, Marko Vukovic, Aleksandar Tomic, Slobodan Djunic, Moe Shafiei, Milos Sukovic, Bozidar Radivojevic, Sumeet Dash, Charles Feddersen, Tapas Kumar Nayak, Tomer Verona, Mahadevan Sankara, Milana Kovacevic, Nikola Kicovic, Sasa Stanojkov, Milan Ruzic, Raghu Ramakrishnan, Milan Potocnik, Veljko Vasic

Publikováno v: Proceedings of the VLDB Endowment. 13:3204-3216

In this paper, we describe the Polaris distributed SQL query engine in Azure Synapse. It is the result of a multi-year project to re-architect the query processing framework in the SQL DW parallel data warehouse service, and addresses two main goals:

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6eeca344ada35eb9b0f5d869a7a9535d
https://doi.org/10.14778/3415478.3415545

General Guide to Applying Machine Learning to Computer Architecture

Autor: Nikola Markovic, Osman Unsal, Tugberk Arkose, Mateo Valero, Mario Nemirovsky, Adrian Cristal, Daniel Nemirovsky

Publikováno v: Recercat. Dipósit de la Recerca de Catalunya
instname
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

The resurgence of machine learning since the late 1990s has been enabled by significant advances in computing performance and the growth of big data. The ability of these algorithms to detect complex patterns in data which are extremely difficult to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf1b5f5cd07d66d1dfd240a3169cdd9a
https://doi.org/10.14529/jsfi180106