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pro vyhledávání: '"Avraham, Rinat"'
Publikováno v:
International Journal of Qualitative Studies on Health & Well-Being. Dec2024, Vol. 19 Issue 1, p1-11. 11p.
Akademický článek
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Autor:
Avraham, Rinat1 (AUTHOR) benamir@bgu.ac.il, Cohen, Tanya1 (AUTHOR), Artzi-Medvedik, Rada1 (AUTHOR), Hurvitz, Nancy1 (AUTHOR), Cohen, Odeya1 (AUTHOR)
Publikováno v:
BMC Nursing. 7/8/2023, Vol. 22 Issue 1, p1-9. 9p. 1 Diagram, 4 Charts, 1 Graph.
Publikováno v:
In Nurse Education Today August 2021 103
The discrete Fr\'echet distance is a useful similarity measure for comparing two sequences of points $P=(p_1,\ldots, p_m)$ and $Q=(q_1,\ldots,q_n)$. In many applications, the quality of the matching can be improved if we let $Q$ undergo some transfor
Externí odkaz:
http://arxiv.org/abs/1501.03724
Autor:
Ben-Avraham, Rinat, Henze, Matthias, Jaume, Rafel, Keszegh, Balázs, Raz, Orit E., Sharir, Micha, Tubis, Igor
We consider the RMS distance (sum of squared distances between pairs of points) under translation between two point sets in the plane, in two different setups. In the partial-matching setup, each point in the smaller set is matched to a distinct poin
Externí odkaz:
http://arxiv.org/abs/1411.7273
Publikováno v:
ACM Trans. Algorithms 11(4): 29 (2015)
The \emph{Fr\'echet distance} is a well studied similarity measures between curves. The \emph{discrete Fr\'echet distance} is an analogous similarity measure, defined for a sequence $A$ of $m$ points and a sequence $B$ of $n$ points, where the points
Externí odkaz:
http://arxiv.org/abs/1310.5245
The Fr\'echet distance is a similarity measure between two curves $A$ and $B$: Informally, it is the minimum length of a leash required to connect a dog, constrained to be on $A$, and its owner, constrained to be on $B$, as they walk without backtrac
Externí odkaz:
http://arxiv.org/abs/1204.5333
Let P be a set of n points in R^3. The 2-center problem for P is to find two congruent balls of minimum radius whose union covers P. We present two randomized algorithms for computing a 2-center of P. The first algorithm runs in O(n^3 log^5 n) expect
Externí odkaz:
http://arxiv.org/abs/1012.2694
Publikováno v:
In Teaching and Learning in Nursing October 2018 13(4):258-262