let $g$ be a simple graph with an orientation $sigma$‎, ‎which ‎assigns to each edge a direction so that $g^sigma$ becomes a‎ ‎directed graph‎. ‎$g$ is said to be the underlying graph of the‎ ‎directed graph $g^sigma$‎. ‎in this paper‎, ‎we define a weighted skew‎ ‎adjacency matrix with rand'c weight‎, ‎the skew randi'c matrix ${bf‎ ‎r_s}(g^sigma)$‎, ‎of $g^sigma$ as the real skew symmetric mat...

Differences in activity between infective juveniles (IJ) of the entomopathogenic nematode Steinernema carpocapsae that emerged directly from cadavers onto either a sand or agar substrate compared with those emerging from a cadaver into water and then being placed on the same substrate are known to occur. Differences between S. carpocapsae IJ that emerged directly from a cadaver vs. those that e...

In the heart, the rapid propagation and synchronization of action potentials necessary for a normal heart rhythm and an effective cardiac output are mediated by specialized ionic channels that link adjacent cells and are known collectively as gap junctions. Cardiac gap junctions are gated by various physiological and pharmacological agents, but the role of voltage in their gating is unclear. Wh...

In this paper we study the fuzzy c-mean clustering algorithm combined with principal components method. Demonstratively analysis indicate that the new clustering method is well rather than some clustering algorithms. We also consider the validity of clustering method. Keywords—FCM algorithm, Principal Components Analysis, ClusI. FUZZY SET THEORETIC SIMILARITY MEASURES ONE of the most important ...

Abstract We study the statistical estimation problem of orthogonal group synchronization and rotation synchronization. The model is $Y_{ij} = Z_i^* Z_j^{*T} + \sigma W_{ij}\in{\mathbb{R}}^{d\times d}$ where $W_{ij}$ a Gaussian random matrix $Z_i^*$ either an or matrix, each $Y_{ij}$ observed independently with probability $p$. analyze iterative polar decomposition algorithm for $Z^*$ show it ha...

Let Q(A) be number of comparisons done on input array A: (A) For 1 ≤ i < j < n let R ij be the event that rank i element is compared with rank j element. (B) X ij is the indicator random variable for R ij. That is, X ij = 1 if rank i is compared with rank j element, otherwise 0. Q(A) = ∑ 1≤i<j≤n X ij and hence by linearity of expectation,

Let Q(A) be number of comparisons done on input array A: (A) For 1 ≤ i < j < n let R ij be the event that rank i element is compared with rank j element. (B) X ij is the indicator random variable for R ij. That is, X ij = 1 if rank i is compared with rank j element, otherwise 0. Q(A) = ∑ 1≤i<j≤n X ij and hence by linearity of expectation,