The best and most detailed structural information is obtained when the diffraction pattern of a single crystal a few tenths of a millimetre in each dimension is analyzed, but growing high-quality crystals of this size is often difficult, sometimes impossible. However, many crystallization experiments that do not yield single crystals do yield showers of randomly oriented microcrystals that can ...

Many important problems in Artificial Intelligence can be defined as Constraint Satisfaction Problems (CSP). These types of problems are defined by a limited set of variables, each having a limited domain and a number of Constraints on the values of those variables (these problems are also called Consistent Labeling Problems (CLP), in which “Labeling means assigning a value to a variable.) Solu...

The goal of theory of constraints (TOC) is to maximize output, which is achieved byidentifying and managing the critically constrained resources. To manage the constraints, Goldrattproposed five focusing steps (5FS). If we increase constrained output, the output of system will beincreased. In this paper, we focus on step four of the 5FS and use the remained capacity of nonconstraintto elevate t...

In general, Constraint Optimization Problems (COP) are NP-hard. Using variable elimination techniques [5, 13] COPs can be solved with computation that is exponential only in the induced-width of the constraint graph (given some order on the nodes), i.e. smaller than n. Orders on nodes allowing for some parallelism are offered by Depth First Search (DFS) trees of the constraint graph [3, 13]. An...

Abstract In this work a multi-point constraint unfitted finite element method for the solution of Poisson equation is presented. Key features approach are strong enforcement essential boundary, and interface conditions. This, along with stability method, achieved through use constraints that applied to so-called ghost nodes lie outside physical domain. Another key benefit lies in fact that, as ...