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This paper studies the simulation problem of meshes with separable buses by meshes with multiple partitioned buses . The and the are the mesh connected computers enhanced by the addition of broadcasting buses along every row and column. The broadcasting buses of the , called separable buses, can be dynamically sectioned into smaller bus segments by program control, while those of the , called partitioned buses, are statically partitioned in advance. In the model, each row/column has only one separable bus, while in the model, each row/column has L partitioned buses (L≥2). We consider the simulation and the scaling-simulation of the by the , and show that the of size n×n can be simulated in O(n^1/(2L)) steps by the of size n×n, and that the of size n×n can be simulated in steps by the of size m×m(m<n). The latter result implies that the of size n×n can be simulated time-optimally by the of size m×m when n≥m^1+∊ holds where .

As Dempster–Shafer theory spreads in different application fields, and as mass functions are involved in more and more complex systems, the need for algorithms randomly generating mass functions arises. Such algorithms can be used, for instance, to evaluate some statistical properties or to simulate the uncertainty in some systems (e.g., data base content, training sets). As such random generation is often perceived as secondary, most of the proposed algorithms use straightforward procedures whose sample statistical properties can be difficult to characterize. Thus, although such algorithms produce randomly generated mass functions, they do not always produce what could be expected from them (for example, uniform sampling in the set of all possible mass functions). In this paper, we briefly review some well-known algorithms, explaining why their statistical properties are hard to characterize. We then provide relatively simple algorithms and procedures to perform efficient random generation of mass functions whose sampling properties are controlled.

In this paper, we use the variational iteration method (VIM) to construct approximate solutions for the general $n$th-order integro-differential equations. We show that his method can be effectively and easily used to solve some classes of linear and nonlinear Volterra integro-differential equations. Finally, some numerical examples with exact solutions are given.

DEVS is a sound Modeling and Simulation (M&S) framework that describes a model in a modular and hierarchical way. It comes along with an abstract simulation algorithm which defines its operational semantics. Many variants of such an algorithm have been proposed by DEVS researchers. Yet, the proper interpretation and analysis of the computational complexity of such approaches have not been systematically addressed and defined. As systems become larger and more complex, the efficiency of the DEVS simulation algorithms in terms of time complexity measure becomes a major issue. Therefore, it is necessary to devise a method for computing this complexity. This paper proposes a generic method to address such an issue, taking advantage of the recursion embedded in the triggered-by-message principle of the DEVS simulation protocol. The applicability of the method is shown through the complexity analysis of various DEVS simulation algorithms.

A three-dimensional phase-field model with two kinds of needle-like phase of ceramic composite materials is set up in this paper. The three-dimensional simulation algorithm is modified and a new efficient algorithm is established. The grain growth process of the ceramic tool materials containing two kinds of nano-particles with various particle radius is successfully simulated in 200x200x200 unit size.