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For all predictors the assessment of cooperative ability demonstrated discriminant validity Additionally, partial correlations were computed It is immediately obvious that the different variables predict similar variance to a large extent This leads to the question of whether a combination of predictors is able to raise the validity of the prediction, ie incremental validity This was tested by a hierarchical regression analysis In the rst step, based on the highest bivariate correlation, intelligence was included, yielding an R of 039 By also including system speci c knowledge about the tailorshop as a second predictor, R was raised to 046 This equals an incremental percentage of explained variance of 7% Another increment in prediction was achieved by including the third predictor, control performance on the tailorshop , but was signi cant only at the 10% level After inclusion of all predictors a multiple correlation of R 0:50 was obtained Considering a predictor above and beyond intelligence thus provides a substantive contribution to predictive power On purely statistical terms control performance and knowledge proved to be similarly adequate in achieving signi cant prediction increments The variable that was added to intelligence on the second step led to a statistically signi cant increase of the multiple R The variable that was included on the third step did not The sequence in which the predictors were included in the hierarchical regression shown here was based on the theoretical assumption that the systematic variance in control performance on problem solving scenarios can essentially be attributed to intelligence and knowledge Accordingly, based on these theoretical assumptions, intelligence and knowledge were given priority in the hierarchical regression analysis Problem solving scenarios are diagnostically interesting, because it is not only intelligence but also knowledge that is required for managing these scenarios Inclusion of knowledge in job performance may yield an increment in overall validity For practical purposes it may be worthwhile to use both intelligence and knowledge assessment Problem solving scenarios will be helpful in this regard, because managing complex problem solving scenarios demands acquiring knowledge, which could subsequently be tested Signi cant progress in the domain of problem solving assessment cannot be expected until both the operationalization of problem solving quality and the psychometric quality of assessment instruments are improved Above all, it is essential to classify the ability tapped by the performance measures within an existing nomological network Studies are required in which suf ciently reliable measures are implemented by means of different computer-based scenarios, and differentiated measures of intelligence are administered in suf ciently large samples At the same time, tests of additional theoretically relevant constructs such as knowledge also need to be administered In investigations of this kind (see Wittmann & Su , 1999) it was shown that the systematic variance captured by problem solving scenarios can mainly be attributed to intelligence and prior knowledge There is no empirical evidence for the existence of something like a problem solving ability as an independent construct.



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(both increase and decrease) the estimated distances in nearly all these techniques The computation schemes on the other hand can be in uenced indirectly by corrupting the ranging schemes, and hence we do not consider them explicitly here

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As seen from the previous section, location is an important aspect for several scenarios involving ad hoc or sensor networks Given that these infrastructureless wireless networks may be deployed in hostile environments, they would be susceptible to a variety of attacks such as wormhole or Sybil in addition to the traditional attacks such as replay and jamming that could signi cantly impact the accuracy of the localization process Hence, it is necessary to devise localization techniques that are robust even in the face of such attacks In this section we investigate how to secure the localization process We are not concerned with attacks against any other network protocol Secure localization is focused on enabling nodes in a sensor or ad hoc network to determine their location securely The secure localization problem has been solved using one of the following two approaches:

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