In this paper, two additional matrices which can be directly added to the original stiffness matrix are derived by additional functions. Based on the experiment of the 2.5-inch 8-layer typical flexible riser, and combined with the finite element method, the value of penalty parameter in penalty...
Furthermore, evaluating each decoherence functional element \({\cal{D}}({\boldsymbol{\alpha }},{\boldsymbol{\alpha }}\prime )\) requires the equivalent of a Hamiltonian simulation of the system, i.e., the multiplication of 2n × 2n matrices. This means modern clusters would take ...
This choice is already difficult in relatively easy settings, like flat clustering on data matrices, but on tensors it could be even more frustrating. To face this issue, we propose a new tensor co-clustering algorithm that does not require the number of desired co-clusters as input, as it...
In this study, the key streams were first produced from three improved 1D chaotic systems using the secret keys and the plain image and the key streams; in addition, the plain image were transformed randomly into the DNA matrices by the DNA encoding rules, respectively. Secondly, the DNA ...
CONCOR can use multiple adjacency matrices to partition nodes based on all relations simultaneously. The package includesigraphdata files for the Krackhardt (1987) high-tech managers study, which gives networks for advice, friendship, and reporting among 21 managers at a firm. (These networks were ...
changing the model to partition extra input signals for each parameter is cumbersome. Instead, add a mask parameter to a for-each subsystem. For more information, seeCreate a Simple Mask. To select the mask parameter for partitioning, use theParameter Partitiontab of theFor Eachblock dialog box...
input to the algorithm The content of the input affects the running time typically, the input size (number of items in the input) is the main consideration E.g. sorting problem the number of items to be sorted E.g. multiply two matrices together the total number of elements in...
gamultiobjcan be used to solve multiobjective optimization problem in several variables. Here we want to minimize two objectives, each having one decision variable. min F(x) = [objective1(x); objective2(x)] x where, objective1(x) = (x+2)^2 - 10, and ...
As our second contribution, we add a real-valued parameterβto our pruning algorithm that extends the flexibility of our approach and allows to control the quality of pruning. Specifically, when deciding whether a route shall be pruned, we compare the route distance between two locations to the...
The present study develops a two-dimensional (2D) weight-based MM algorithm by considering the road width that strives to localize the vehicle at lane-level. In doing so, it incorporates dynamic weight coefficients to address different operational environments. Therefore, the algorithm is termed as...