Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Pawel Marcinek"'
Publikováno v:
IEEE Access, Vol 6, Pp 12951-12965 (2018)
Social network patient data for comorbid studies is a sparsely explored avenue. This can provide unprecedented insight into disease conditions and their progression, hence facilitating improvement of healthcare and public health services. Structuring
Externí odkaz:
https://doaj.org/article/774900f31f37483794343dbbb5848a2d
Publikováno v:
Electronic Journal of Differential Equations, Vol 2017, Iss 301,, Pp 1-42 (2017)
This work models, analyses and simulates a one-dimensional process of debonding of a structure made of two viscoelastic bonded slabs that is described by a rod-beam system. It is motivated, primarily, by the degradation of adhesively bonded plates
Externí odkaz:
https://doaj.org/article/9636aaaf06bd4c099a2745a4baf82c77
Publikováno v:
IEEE Access, Vol 6, Pp 12951-12965 (2018)
Social network patient data for comorbid studies is a sparsely explored avenue. This can provide unprecedented insight into disease conditions and their progression, hence facilitating improvement of healthcare and public health services. Structuring
Publikováno v:
ICISDM
Android applications pose many security risks that affect the security and privacy of their users. Adversaries construct different types' Android applications pose many security risks that affect the security and privacy of their users. Adversaries c
Publikováno v:
ASONAM
Ruptured intracranial aneurysms are associated with a high rate of mortality and disability due to the difficulty in predicting the rupture and complexity of the condition itself. Clinical narratives such as progress summaries and radiological report
Publikováno v:
2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).
Publikováno v:
International Journal of Computational Vision and Robotics. 8:476
Recognition of arbitrary shaped clusters is a highly active research topic in data mining and cluster analysis. In this paper, we consider the problem of data clustering of arbitrary shaped clusters as a random evolutionary process. We propose a new