Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Zoran Obradov"'
Autor:
Jovan Andjelkovic, Branimir Ljubic, Ameen Abdel Hai, Marija Stanojevic, Martin Pavlovski, Wilson Diaz, Zoran Obradovic
Publikováno v:
Informatics in Medicine Unlocked, Vol 30, Iss , Pp 100928- (2022)
Cancer is one of the most common causes of death in the world. It is characterized by the multi-stage transformation of normal cells into tumor cells. Early cancer detection can significantly reduce its consequences, which was the objective of many m
Externí odkaz:
https://doaj.org/article/33b5b87248674745bea52af47dd867e5
Autor:
Zoran Obradović, Goran Kasum
Publikováno v:
Sport Mont, Vol III, Iss 6-7, Pp 141-149 (2005)
In the topic, wrestling has been observed through medical and educational aspects. In that point of view, observation of the best wrestling characteristics has been made. Using these, we can make an influence on educational and health state within yo
Externí odkaz:
https://doaj.org/article/449bde9691be48e08233056396d294b0
Publikováno v:
IEEE Access, Vol 11, Pp 125883-125896 (2023)
This study investigates severe weather events that lead to power outages. Despite extensive research on using social media during disasters, little work has focused on combining social media information with power outage data. To address this limitat
Externí odkaz:
https://doaj.org/article/0873341429ca4d6db2114d1a9963f640
Autor:
Mohammad Alqudah, Zoran Obradovic
Publikováno v:
IEEE Access, Vol 11, Pp 94840-94851 (2023)
Electric grid continually monitors spatiotemporal data from sparse service areas. As power systems grow and get more complex, and with the deployment of more sensors and data collection capabilities, monitoring and analyzing data streams for outage p
Externí odkaz:
https://doaj.org/article/8508fe1549a44d0187bf2d3ffd27c979
Publikováno v:
Network Neuroscience, Vol 7, Iss 1, Pp 22-47 (2023)
AbstractRepresentation learning is a core component in data-driven modeling of various complex phenomena. Learning a contextually informative representation can especially benefit the analysis of fMRI data because of the complexities and dynamic depe
Externí odkaz:
https://doaj.org/article/5c05dd6a27d0445f8620f7099e812e44
Publikováno v:
IEEE Access, Vol 11, Pp 18900-18909 (2023)
Disagreement among text annotators as a part of a human (expert) labeling process produces noisy labels, which affect the performance of supervised learning algorithms for natural language processing. Using only high agreement annotations introduces
Externí odkaz:
https://doaj.org/article/d79a24bc9a884c6bbed300a6a916642e
Publikováno v:
IEEE Access, Vol 11, Pp 7283-7296 (2023)
Electric power system operators monitor large multi-modal data streams from wide service areas. The current data setups stand to get more complex as utilities add more smart-grid sensors to collect additional data from power system substations and ot
Externí odkaz:
https://doaj.org/article/e20cdcd9e91147fab4377d6da2f6bd72
Publikováno v:
IEEE Access, Vol 11, Pp 4373-4380 (2023)
Electric grids are vulnerable to the impacts of extreme weather. Utility companies face the necessity to reduce the number of power outages caused by weather. This paper expands the approach of predicting weather outages in the distribution grid by i
Externí odkaz:
https://doaj.org/article/6749b275964a48cd83f941b21b038da7
Publikováno v:
BMC Nephrology, Vol 23, Iss 1, Pp 1-12 (2022)
Abstract Background Hemodialysis clinic patient social networks may reinforce positive and negative attitudes towards kidney transplantation. We examined whether a patient’s position within the hemodialysis clinic social network could improve machi
Externí odkaz:
https://doaj.org/article/b125d34307624030868e9a436e05a61c
Publikováno v:
Ekonomika Poljoprivrede (1979), Vol 70, Iss 2 (2023)
In the current situation of war conflicts, but also as a consequence of the COVID-19 pandemics, the economic crisis caused by the lack of goods, primarily food, energy sources, weapons and military equipment and multiple other products and services,
Externí odkaz:
https://doaj.org/article/0ad88233374648a096fc7d8fdc95d076