Algorithm defined

The KTTS depends upon an absolute 2ero and one fixed point through which a straight line is projected. Because they are not ideally linear, practicable interpolation thermometers require additional fixed points to describe their individual characteristics. Thus a suitable number of fixed points, ie, temperatures at which pure substances in nature can exist in two- or three-phase equiUbrium, together with specification of an interpolation instmment and appropriate algorithms, define a temperature scale. The temperature values of the fixed points are assigned values based on adjustments of data obtained by thermodynamic measurements such as gas thermometry. 

We present a framework for algorithms which we call Subset-Cover. In this framework an algorithm defines a collection of subsets Si, S, Sj C J f. Each subset Sj is assigned (perhaps implicitly) a long-lived key Lj each member u of Sj should be able to deduce Lj from its secret information. Given a revoked set 1Z, the remaining users A/ 7 . are partitioned into disjoint subsets Si, ..., so that... 

The algorithm defined by Eqs. (27)—(29) can be effectively coded for both vector and parallel processor computers. 

Ant Colony fitness function. A parameter proposed for the ant colony optimization (AGO) algorithm, defined as [Shen, Jiang ct al., 2005]... 

Based on weighted walk degrees of different orders calculated by the algorithm defined above, the walk matrix Wjmi.Mj.Mj) is an unsymmetrical square Ax A matrix whose i-j entry is... 

One goal of population pharmacokinetic models is to relate subject-specific characteristics or covariates, e.g., age, weight, or race, to individual pharmacokinetic parameters, such as clearance. There are many different methods to determine whether such a relationship exists, some of which were discussed previously in the chapter, and they can be characterized as either manual or automated in nature. With manual methods, the user controls the model development process. In contrast, automated methods proceed based on an algorithm defined by the user a priori and a computer, not the user, controls the model development process. Consequently, the automated methods are generally considered somewhat less subjective than manual procedures. The advantage of the automated method is its supposed lack of bias and ability to rapidly test many different models. The advantage of the manual method is that the user... 

Again, in practical applications it is important to combine the raw branching algorithm defined above with importance sampling. Mathematically, this works in precisely the same way as in Section III in that one reformulates the same algorithm in terms of the similarity transform 6 with Mg = uT chosen to be an accurate, approximate dominant eigenstate [see Eq. 

Control system design consists of two steps control stmcture selection includes the choice of suitable manipulated and measured variables as well as their pairing design and parameterization of some control algorithm defines the computation of the required values of the manipulated variables from the measurements and given set-points. Let us first focus on the control structure selection problem. 

Let ModelCheck be the conventional CTL symbolic model checking algorithm defined in (McMillan 1993). This algorithm has been implemented in several tools and successfully used to verify hardware, software and protocols specifications. 

This algorithm defines the optimum distribution of flows from the sources which sets up the maximum possible flow in the network, in the presence of component failures. Theorem 2 is valid not only... 

The RG generation algorithm defined by Birchall et al. begins by fragmenting recursively a given molecule at all nonterminal, acydic single bonds with three exceptions acydic sp carbon to acyclic sp carbon bonds acyclic heteroatom to acyclic heteroatom bonds and acyclic heteroatom to acyclic sp bonds. 

The structure of ANNs is reminiscent of biological neural networks. Several simple nodes ( neurons ) are connected to form a network of nodes. Algorithms define the strengths between the neurons. Multilayer preceptron (MLP) is one of the most popular and traditional models of ANNs [15]. Its structure consists of an input layer, one or more hidden layers, and an output layer. All layers contain a variable number of neurons. The network maps the input data (e.g., UV-Vis data) to a set of outputs (e.g., concentrations). A training data set can be used to optimize the strength of the connections. The trained network is then able to make predictions for a validation data set. 

Definition 4-2 A logic algorithm defining a predicate r/n, denoted LA r), is a closed well-formed formula of the form ... 

In order to extract these MCS, we use the algorithms defined in Chaux et al. (2011) and Chaux et al. (2012). The first one transforms a BDMP model into a finite state automaton and the second one extract the MCS of a finite state automaton. Several MCS limited to the length 5 (selected arbitrary among the 84 existing) extracted... 

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