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Measuring data quality across open government datasets
Rajan Gupta, Sushmita Yadav, Avinash Prasad, Saibal K. Pal, 2019, published scientific conference contribution

Abstract: Data Quality has become the base for any analytical operation or modelling. Poor Quality of data can lead to poor analytical modeling, which in turn can lead to poor decision making and predictions, which can finally impact the revenue and working of an organization. This is true for both public and private sector organizations. With rise in E-Governance, lot of nations and their respective public sector units are making use of publicly available datasets. But are these datasets reliable and have good quality. This is the major research question studied in this paper. The study collected publicly available datasets from Open Government Data platforms across 8 different nations around the world. More than 300 datasets having roughly 3.5 million rows were assessed for various data quality measures. The various parameters studied for the data were valid data types, correctness, completeness, statistical features, variability, comparability, duplicacy and the likes. Script was written in R to check the value for various measures. It was found that different countries had advantages on different parameters. Not one country was found to have all the parameters to be of high quality. Different ranges were found for the dataset for various parameters which was helpful in determining the overall quality of the dataset. This will be helpful for various public and private sector organizations in assessing the quality of datasets they intend to work on. Substantial efforts and resources can be saved on Advanced Analytics if the quality of dataset can be determined in advance. The proposed data quality assessment model can be applied on any private or public dataset. Different industry and organizations can set different threshold values for the parameters to benchmark their analytical process. Both practitioners and researchers can be benefitted from this research work.
Keywords: data quality assessment, open government datasets, e-governance, data quality measures
Published in RUNG: 05.04.2021; Views: 2023; Downloads: 0
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Studying TDEs in the era of LSST
Katja Bricman, Andreja Gomboc, 2019, published scientific conference contribution abstract

Keywords: The observing strategy with continuous scanning and large sky coverage of the upcoming ground-based Large Synoptic Survey Telescope (LSST) will make it a perfect tool in search of rare transients, such as Tidal Disruption Events (TDEs). Bright optical flares resulting from tidal disruption of stars by their host supermassive black hole (SMBH) can provide us with important information about the mass of the SMBH involved in the disruption and thus enable the study of quiescent SMBHs, which represent a large majority of SMBHs found in centres of galaxies. These types of transients are extremely rare, with only about few tens of candidates discovered so far. It is expected that the LSST will provide a large sample of new TDE light curves. Here we present simulations of TDE observations using an end-to-end LSST simulation framework. Based on the analysis of simulated light curves we estimate the number of TDEs with good quality light curves the LSST is expected to discover in 10 years of observations. In addition, we investigate whether TDEs observed by the LSST could be used to probe the SMBH mass distribution in the universe. The participation at this conference is supported by the Action CA16104 Gravitational waves, black holes and fundamental physics (GWverse), supported by COST (European Cooperation in Science and Technology).
Published in RUNG: 04.01.2021; Views: 2533; Downloads: 0

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Air quality and climate change - how smart can the cities be?
Griša Močnik, Matevž Lenarčič, 2020, unpublished invited conference lecture

Abstract: What starts as an air quality problem in urban areas, ends up as a climate change problem globally. Emissions from cities and the power generating facilities powering the cities have local, regional and global effects. We show examples spanning these scales with very practical advice on how to start abatement locally.
Keywords: air quality, climate change, black carbon, aerosol, co2, smart city
Published in RUNG: 11.09.2020; Views: 3091; Downloads: 0
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OBJECTIVE AND PERCEIVED ENVIRONMENTAL QUALITY IN THE TOWNS OF ZENICA AND MARIBOR : GROUP PROJECT FINAL REPORT
Ivana Pandža, Katja Belec, Matjaž Žvokelj, Merima Vrškić, Tajda Huber, Ula Urbas, 2020, treatise, preliminary study, study

Abstract: In this study, we measured the concentrations of specific heavy metals in the soil and sediment samples taken on different locations of the cities of Maribor (Slovenia), and Zenica (Bosnia and Herzegovina). The report also includes a questionnaire regarding the residents’ views about the environmental quality of the city they live in.
Keywords: Soil, sediments, heavy metals, AAS, pollution, questionnaire, environmental quality.
Published in RUNG: 11.09.2020; Views: 2643; Downloads: 0
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A new optical-based technique for real-time measurements of mineral dust concentration in PM10 using a virtual impactor
Luka Drinovec, Jean Sciare, IASONAS STAVROULAS, S. Bezantakos, Michael Pikridas, FLORIN UNGA, Chrysanthos Savvides, Bojana Višnjić, Maja Remškar, Griša Močnik, 2020, original scientific article

Abstract: Atmospheric mineral dust influences Earth’s radiative budget, cloud formation, and lifetime; has adverse health effects; and affects air quality through the increase of regulatory PM10 concentrations, making its real-time quantification in the atmosphere of strategic importance. Only few near-real-time techniques can discriminate dust aerosol in PM10 samples and they are based on the dust chemical composition. The online determination of mineral dust using aerosol absorption photometers offers an interesting and competitive alternative but remains a difficult task to achieve. This is particularly challenging when dust is mixed with black carbon, which features a much higher mass absorption cross section. We build on previous work using filter photometers and present here for the first time a highly timeresolved online technique for quantification of mineral dust concentration by coupling a high-flow virtual impactor (VI) sampler that concentrates coarse particles with an aerosol absorption photometer (Aethalometer, model AE33). The absorption of concentrated dust particles is obtained by subtracting the absorption of the submicron (PM1) aerosol fraction from the absorption of the virtual impactor sample (VIPM1 method). This real-time method for detecting desert dust was tested in the field for a period of 2 months (April and May 2016) at a regional background site of Cyprus, in the Eastern Mediterranean. Several intense desert mineral dust events were observed during the field campaign with dust concentration in PM10 up to 45 μgm
Keywords: aerosol absorption, mineral dust, on-line detection, air quality
Published in RUNG: 20.07.2020; Views: 2655; Downloads: 0
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