Count variables

Ordinal tab Establishes counting variable for the variable selected. 

Kwauk, M. (1956) AIChE Jl 2, 240. A system for counting variables in separation processes. 

Counting variables is of obvious importance in setting up problems, but it is relatively simple. Ensuring that the variables of interest are independent may be difficult for complicated processes, and determining the allowable limits of these variables can be extremely difficult. 

Three different variables are used for calculating molecular descriptors indicator variable, count variable, and graph-theoretical indices, as described below. Molecular... 

An attractive alternative to counting variables and equations is to use the Description Rule of Hanson, Duifin, and Somerville. ... 

To obtain the generating function monomer, both a monomer counting variable t and dummy position variables x, y, z are introduced. We substitute... 

The circle around the node of the force is a convention for an external force apphed ( powered ). The drawing convention for the distance node means that this variable is neither a state variable nor a gate variable but a counted variable (or merely a count). 

This indefinite growth is a proof that this variable is not a state variable, because with a constant velocity (and mass), the inductive (kinetic) and total energy of the moving body remains constant. The general name given to this category of variable is counted variable. ... 

Gate variable Count variable Localized variable... 

Variable similar to an entity number resulting from a counting (discrete case) of circulating entities or from integration (continuous case) of the energy-per-entity. Examples of counted variables are the charge passed in an electric circuit and the distance covered by a moving object. 

Two approaches were used to determine the half-life of lutetium-176. These were analysis of lutetium-bearing minerals with known ages and direct counting. Variable results range from 2 to 7 X 10 ° years and a calculation from the slope of a Lu/Hf isochron formed by ten achondrites (eucrites) with an age of 4.55 x 10 years gave a value of (3.53 0.14) x 10 years. This value accords with a recent estimate of 3.8 x 10 years. 

The literature offers a wide variety of count data models to regress a count variable on a set of independent variables (see for example Cameron and Trivedi, 1998). A well-known example is the Poisson model. The applicability of this model however is limited due to the fact that it imposes equi-dispersion, which means that the conditional mean and variance are equal. This is a rather strong assumption. A more flexible count data model is obtained when unobserved heterogeneity is introduced in the Poisson intensity parameter A. The most commonly used extension to the Poisson model is the negative binomial model (negbin). 

For each Petri-Net that has an output for which a reduction in performance is noted, a voltage drop count variable is used to store the total amount of degradation in performance due to the failure relationships. Therefore for each output place in a degradation module Petri-Net, a voltage drop figure is added to the overall voltage drop count. 

The degradation rate was programmed to take affect per SSC, through the transition T1 in Figure 9. Therefore, for each time there is an instance of SSC, a degradation rate of 5.333 x 10 V is applied to a voltage drop count variable. 

An advantage of the latter two EMG feature variables is that they do not require calibration, whereas the EMG Count variable requires visual inspection so that meaningful threshold values can be chosen. 

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