Search error

The output from the search function is either zero, one, or many indications that must be evaluated by the decision process. Logically, if no indications have been fonnd, the item or process must be classified as fit for use. Note that a false alarm is not possible nnless at least one indication reaches the decision stage thus, false alarms are directly diagnostic of decision error rather than search error. Given that decisions wUl be nontrivial only with an indication, the natnre of the decision or indication must be examined. 

As can be seen in Figure 5-17, some search fields (e.g., POW [= Power]) do not need any input in the search mask this means that all entries with any content of those Helds are retrieved. However, other fields always demand an input. In case the input is omitted (for example for the decadic logarithm of the partition coefficient), a corresponding error message results. Since the PCB are more soluble in the organic phase, the input of that Field is restricted to positive values. 

Side chain generation is often a source of error. It will be most reliable if certain rules of thumb are obeyed. Start with structurally conserved side chains and hold them fixed. Then look at the energy and entropy of rotamers for the remaining side chains. Conventional conformation search techniques are often used to place each side chain. 

The control chart is set up to answer the question of whether the data are in statistical control, that is, whether the data may be retarded as random samples from a single population of data. Because of this feature of testing for randomness, the control chart may be useful in searching out systematic sources of error in laboratory research data as well as in evaluating plant-production or control-analysis data. ... 

For a given drum pressure and feed composition, the bubble- and dew-point temperatures bracket the temperature range of the equilibrium flash. At the bubble-point temperature, the total vapor pressure exerted by the mixture becomes equal to the confining drum pressure, and it follows that X = 1.0 in the bubble formed. Since yj = KjXi and since the x/s stiU equal the feed concentrations (denoted bv Zi s), calculation of the bubble-point temperature involves a trial-and-error search for the temperature which, at the specified pressure, makes X KjZi = 1.0. If instead the temperature is specified, one can find the bubble-point pressure that satisfies this relationship. 

At the dew-point temperature y still equals Zj, and the relationshm X Xi = X i/K-i = 1.0 must be satisfied. As in the case of the bubble point, a trial-and-error search for the dew-point temperature at a specified pressure is involved. Or, if the temperature is specified, the dew-point pressure can be calculated. 

The authors test two methods coupled with the measurement test. In one, they sequentially eliminate measurements and rearrange the constraints to isolate the specific measurements that contain gross errors. In the other, streams are added back as the search continues. 

When performing human reliability assessment in CPQRA, a qualitative analysis to specify the various ways in which human error can occur in the situation of interest is necessary as the first stage of the procedure. A comprehensive and systematic method is essential for this. If, for example, an error with critical consequences for the system is not identified, then the analysis may produce a spurious impression that the level of risk is acceptably low. Errors with less serious consequences, but with greater likelihood of occurrence, may also not be considered if the modeling approach is inadequate. In the usual approach to human reliability assessment, there is little assistance for the analyst with regard to searching for potential errors. Often, only omissions of actions in proceduralized task steps are considered. 

Errors in instrumentation calibration have been reduced by 90 percent due to the elimination of multiple, outdated copies of calibration procedures/data sheets. An instrument mechanic can now get the current specification from a single, up-to-date source whenever a work order is received. The time wasted in searching multiple files has been eliminated. 

Successful recrystallization of an impure solid is usually a function of solvent selection. The ideal solvent, of course, dissolves a large amount of the compound at the boiling point but very little at a lower temperature. Such a solvent or solvent mixture must exist (one feels) for the compound at hand, but its identification may necessitate a laborious trial and error search. Solvent polarity and boiling point are probably the most important factors in selection. Benzhydrol, for example, is only slightly soluble in 30-60 petroleum ether at the boiling point but readily dissolves in 60-90° petroleum ether at the boiling point. 

Figure 22 Root-mean-squared error progression plot for Fletcher nonlinear optimization and back-propagation algorithms during training.-----Fletcher routine —A—Gradient search.

Consider the basic probkun of how information is distributed throughout a system, and the manner in which it is retrieved. We. know that in a conventional computer, for example, information is stored in random-access memory (RAM). This means that the memory address of where the information actually exists and the information itself are uncorrelated. In order to retrieve the information, one must know its address exactly, as even the slightest error renders that information effectively unretrievable. In particular, it is in general impossible to retrieve RAM data if armed only with a partial knowledge of its address. In contrast, associative memories (sometimes also called content-addressable memories), much like the form of memory believed to be used by human brains, are such that they can be completely retrieved even when searched for with partial information,... 

The theory of the separation of geometric isomers on stationary phases that have a number of sterogenic centers has not been developed to the point where a particular stationary phase together with an appropriate mobile phase can be deduced for the separation of a specific pair of isomers. A number of theories have been put forward to explain the resolution of geometric isomers (some of which have been quite "imaginative" and "colorful") yet a reliable theory to help in phase selection for a hitherto unresolved chiral pair is still lacking. Unfortunately, the analyst is left with only two alternatives. The first is to search the literature for a model separation similar to the problem in hand and start with that phase system or, alternatively, resort to the technique of the early days of LC, namely, find the best phase system by a trial-and-error routine. 

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