31. Machine learning models for government to predict COVID-19 outbreakRajan Gupta, Gaurav Pandey, Poonam Chaudhary, Saibal K. Pal, 2020, izvirni znanstveni članek Opis: The COVID-19 pandemic has become a major threat to the whole world. Analysis of this disease requires major attention by the government in all countries to take necessary steps in reducing the effect of this global pandemic. In this study, outbreak of this disease has been analysed and trained for Indian region till 10th May, 2020, and testing has been done for the number of cases for the next three weeks. Machine learning models such as SEIR model and Regression model have been used for predictions based on the data collected from the official portal of the Government of India in the time period of 30th January, 2020, to 10th May, 2020. The performance of the models was evaluated using RMSLE and achieved 1.52 for SEIR model and 1.75 for the regression model. The RMSLE error rate between SEIR model and Regression model was found to be 2.01. Also, the value of R0, which is the spread of the disease, was calculated to be 2.84. Expected cases are predicted around 175K--200K in the three-week time period of test data, which is very close to the actual numbers. This study will help the government and doctors in preparing their plans for the future. Ključne besede: COVID-19, India, spread exposed infected recovered model, regression model, machine learning, predictions, forecasting Objavljeno v RUNG: 01.04.2021; Ogledov: 2256; Prenosov: 83 Povezava na celotno besedilo Gradivo ima več datotek! Več... |
32. When art gets more rigorous than science2020, radijska ali televizijska oddaja, podkast, intervju, novinarska konferenca Ključne besede: research, ethics, bioart, anthropocene, methodologies, mixed research, temporal community, learning by sharing, sonic film, sound art Objavljeno v RUNG: 25.02.2021; Ogledov: 2219; Prenosov: 24 Povezava na celotno besedilo |
33. Action Learning Sets - EmindS Training MaterialsPetroula Mavrkiou, Peter Purg, Kirsi Maasalo, Dimitrios Doukas, Haris Tsitouras, Maria Koutiva, Christiana Knais, univerzitetni, visokošolski ali višješolski učbenik z recenzijo Ključne besede: action learning, materials, entrepreneurship, interdisciplinary, entrecomp Objavljeno v RUNG: 05.01.2021; Ogledov: 2241; Prenosov: 0 Gradivo ima več datotek! Več... |
34. Creating better models of data work through big exercises of imagination2020, radijska ali televizijska oddaja, podkast, intervju, novinarska konferenca Ključne besede: predictive economies, data, social tech, machine learning, autonomy, data worker, trade union, solidarity, labour extraction, data labour rights Objavljeno v RUNG: 08.12.2020; Ogledov: 2425; Prenosov: 27 Povezava na celotno besedilo |
35. Air-Shower Reconstruction at the Pierre Auger Observatory based on Deep LearningJonas Glombitza, Andrej Filipčič, Gašper Kukec Mezek, Samo Stanič, Marta Trini, Serguei Vorobiov, Lili Yang, Danilo Zavrtanik, Marko Zavrtanik, Lukas Zehrer, 2019, objavljeni znanstveni prispevek na konferenci Ključne besede: Pierre Auger Observatory, extensive air showers, event reconstruction, deep learning Objavljeno v RUNG: 16.06.2020; Ogledov: 2645; Prenosov: 80 Celotno besedilo (1,16 MB) |
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39. Pregnancy and delivery in online communities: new ownership practices, new forms of technoscientific citizenshipGiulia Annovi, Yurji Castelfranchi, Chiara Saviane, Elena Bellio, Donatella Fontanot, Luca Buccoliero, Nico Pitrelli, Gianluigi Scannapieco, 2017, izvirni znanstveni članek Ključne besede: knowledge, expertise, collective learning, web, technoscientific citizenship Objavljeno v RUNG: 23.08.2019; Ogledov: 2468; Prenosov: 0 Gradivo ima več datotek! Več... |
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