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In this section, a particular application of a soft sensor that is based on eTS , called eSensor, will be presented for monitoring the quality of oil products online. Soft sensors and eSensors in particular can contribute to increasing the level of automation and to bringing down life-cycle costs of the exploitation of these sensors in the O&G industry. Due to the extremely high throughput of the oil re nery process, any improvement in product quality has signi cant impact on the cost and the nal pro t. The process is complex; a large number of internal variables and many process products (outputs) are involved. Operational environment may also affect the process. Due to the complexity and high setting requirement, the data is usually collected on a daily basis. Considering the high throughput, interrupts of the process are very costly. The continuous running of such a process is very important. As described in the previous sections, the crude oil distillation tower is the rst and most important part of the oil re nery. Crude oil is separated into several major cuts (contents) in the distillation tower according to their density and temperature after being heated. These contents are extracted from the distillation tower with lateral pipes and in the consequent processes are re ned and blended into gasoline, gas oil, and other commercial products. The speci cation for distillation usually is very strict (Macias et al., 2003). The quality of this initial separation of crude oil has a fundamental impact on the ef ciency of the later re ning process. The 95% ASTM distillation curve (Macias et al., 2003) speci es the relation between the distillated products and the temperature of the corresponding side vapor stream from the tower (see Figure 17.3). Normally, the



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Conceptual Analysis Feltz and Chase (1998) recommend an a priori conceptual analysis, with the active input of at least one content expert, to determine the skills needed to perform in the domain of interest These skills should be reflected in both the efficacy measure and the external measure of interest That is, the efficacy measure and the external measure should be reasonably concordant, an issue that is explored in a subsequent section Here, however, the focus is on the construction of indicators of collective efficacy, not relevant external variables As can be seen in Table 361, the occurrence of an a priori conceptual analysis to guide the construction of indicators of collective efficacy has become more frequent across time The most rigorous example of such an analysis is provided by Paskevich et al (1999) These scholars put forth an eight-dimensional factor model that was defined by 56 items.





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sleeves, so to speak; they are spoken of in the theory as actively ambivalent, a more varied lot than earlier DSM portrayals of the so-called passive-aggressive. There are four negativistic subtypes, the circuitous, with dependent traits prevalent, as seen in their inefficiency, forgetfulness, and procrastination. Also common is the discontented variant, seen frequently with depressive traits, and noted by their grumbling, petty, complaining, and embittered feelings. Other subtypes include the abrasive and vacillating variants.

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Other studies that have employed a conceptual analysis have typically specified a unidimensional factor model defined by fewer items (range = 4 to 27) We recommend that the domain of interest, the external variable(s) one wishes to relate collective efficacy to, and the amount of time participants are expected to have to respond to items should determine the scope of the conceptual analysis An often-cited study on collective efficacy in sport was provided by Watson, Chemers, and Preiser (2001) Although this study advanced the literature in many ways, it suffers from questionable measurement of collective efficacy First, there is no evidence that a conceptual analysis of the skill necessary to perform in the domain of interest, high school basketball, in this case, was performed Second, the items that were used were adapted from a scale by Riggs and Knight (1994) that was developed for use in organizational psychology.

kMDItemCity City City of the item kMDItemCodecs Codecs Codecs used to encode and decode the media kMDItemColorSpace Color space Color space model of this image kMDItemComment Comment Comments about this item kMDItemComposer Composer Composer of the song in the audio file kMDItemFSCreationDate Created Date the file was created kMDItemFSExists File exists (null) kMDItemFSInvisible File invisible Whether the file is visible kMDItemFSIsExtensionHidden File extension hidden File extension is hidden kMDItemFSIsReadable File readable File can be opened but not changed kMDItemFSIsWriteable File writable Whether the file can be changed

stant amount of extra storage in which a constant amount of information regarding some data concerning the route that a message has traveled is recorded 2 At each node of the network, a processor has some geographical local information concerning only the location of its neighbors 3 Based only on the local information stored at the nodes of the network, the locations of s and t, and the information stored in the extra memory the message itself carries, a decision is taken regarding on where to send the message next It is not straightforward to develop a routing algorithm that satisfies the above restriction and yet guarantees that a message arrives at its destination In fact, some earlier papers on the subject [5] seemed to assume that their algorithms guaranteed message delivery! Our objective in this section is to develop such an algorithm 181.

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