Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Bindiya M. Varghese"'
Autor:
M D Saju, Bindiya M Varghese, Lorane Scaria, Anuja Maria Benny, Shilpa V Yohannan, Natania Cheguvera, S P Rajeev, Amuthavalli Thiyagarajan Jotheeswaran
Publikováno v:
BMC Family Practice, Vol 22, Iss 1, Pp 1-10 (2021)
Abstract Background Kerala is known as the diabetes mellitus (DM) and hypertension (HTN) capital of the world, thus compelling health professionals to model strategies, addressing their social, behavioural, and cognitive risk factors and eliminating
Externí odkaz:
https://doaj.org/article/ef52b45b281e47d2a1cb2294985b4d9f
Autor:
Saju M D, Lovakanth Nukala, Rameela Shekhar, Keith Gomez, Bindiya M Varghese, Sphoorthi Prabhu, Amuthavalli Thiyagarajan Jotheeswaran
Publikováno v:
BMJ Open, Vol 10, Iss 3 (2020)
PurposeIn response to the need for more advanced and longitudinal data concerning chronic diseases, behavioural risk factors and social support systems in India, the SWADES (Social Well-being and Determinants of Health Study) was established.Particip
Externí odkaz:
https://doaj.org/article/4b1a7260de16455daa487cdc924aa25b
Publikováno v:
2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies (TQCEBT).
Publikováno v:
Multimedia Tools and Applications. 80:20527-20545
In today’s digitalized age and generation, where there is need of secure storage and transmission of data, the need of hiding information becomes a pre-requisite. In like situations, when we desire to send across data through images, we require an
Autor:
M. D. Saju, Bindiya M. Varghese, Natania Cheguvera, Shilpa V. Yohannan, S.P. Rajeev, Lorane Scaria, Amuthavalli Thiyagarajan Jotheeswaran, Anuja Maria Benny
Publikováno v:
BMC Family Practice
BMC Family Practice, Vol 22, Iss 1, Pp 1-10 (2021)
BMC Family Practice, Vol 22, Iss 1, Pp 1-10 (2021)
Background Kerala is known as the diabetes mellitus (DM) and hypertension (HTN) capital of the world, thus compelling health professionals to model strategies, addressing their social, behavioural, and cognitive risk factors and eliminating various b
Publikováno v:
Procedia Technology. 24:1311-1316
A data hiding technique embeds secret information into a cover image. Cover image and the stego image look similar due to which the hackers fail to detect the presence of the hidden secret data. In this paper we propose a two stage data hiding techni
Publikováno v:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN: 9783319589664
BDTA
BDTA
The ability to present data or information in a pictorial format makes data visualization, one of the major requirement in all data mining efforts. A thorough study of techniques, which presents visualization, it was observed that many of the describ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d7b0c7caafae0f84a02531831720e6b
https://doi.org/10.1007/978-3-319-58967-1_1
https://doi.org/10.1007/978-3-319-58967-1_1
Publikováno v:
Communications in Computer and Information Science ISBN: 9783642257339
Spatial Mining differs from regular data mining in parallel with the difference in spatial and non-spatial data. The attributes of a spatial object is influenced by the attributes of the spatial object and moreover by the spatial location. A new algo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efbe9fddabaee8a6b85a6f94858284aa
https://doi.org/10.1007/978-3-642-25734-6_17
https://doi.org/10.1007/978-3-642-25734-6_17
Publikováno v:
International Journal of Advanced Computer Science and Applications. 1
Over the years the academic records of thousands of students have accumulated in educational institutions and most of these data are available in digital format. Mining these huge volumes of data may gain a deeper insight and can throw some light on
Autor:
Bindiya M. Varghese, A. Unnikrishnan
Publikováno v:
CW
Data mining is an analytic process designed to explore data in search of consistent patterns or systematic relationships between variables. To build a model for data mining, both supervised and unsupervised learning techniques are used. In this paper