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Online collected CD-imprint data containing 1534 samples that were labeled by four different operators with different experiences (so, we obtained four different classi ers with different accuracies): The task was to distinguish between real faults on CD imprints such as weak colors, wrong palettes, and so on, and pseudoerrors such as shifts of discs in the tray 2 Online collected egg data containing 4238 samples labeled by just one operator: The task was to discriminate between real faults on eggs, such as scratches or yolks, and nonfaulty appearances on the eggs, such as different kinds of dirt.

Overall, their (potential) scope for development was comparable to the expert group Hence, these were persons with the capability to reach an expert level who had not got there yet The main aspect for the present study was that the novices mastered the technical execution of the front loop far less reliably and regularly than the experts Experts stated that mastery depends highly on experience in windsurfing and repeated practice under various conditions The minimum condition for acceptance in the novice group was to have performed the front loop at least twice (according to their own reports) The results of this study are illustrated in Figures 158 through 1510 For this illustration, is constantly set at 5%; this equals a dcrit value of 351 Figure 15.

8 displays the group structure of the experts based on cluster analysis in the form of a dendrogram and reports the factor matrix arranged according to clusters There were three clusters The structures of mental movement representation in the expert group showed a remarkable affinity to the biomechanical functional structure of the movement As Figure 158 shows, the functional structure of the movement could be divided into several phases Takeof f could be classified as a second-order supportive phase, preparation of rotation as a first-order supportive phase, and rotation as the main phase The superordinate concepts acquired on the basis of clusters (takeoff, preparation of rotation, rotation) are spatially distinct and organized in a temporal sequence We assume that they serve as a means to solve specific subproblems (energizing, introduction of impulse, rotation) Figure 159 illustrates the cluster solution for the novice group.

These cluster solutions reveal a weak structural link between elements The BACs were located slightly above the critical distance (dcrit = 351) Therefore, no structure could be proven for the whole group..

S1 = R1(X), W1(X), W2(X), W3(X) S2 = R1(X), W2(X), W1(X), W3(X)

Figure 4-8

In both cases, the online collected data were stored onto hard-disc in the same order as they were recorded; so a valid simulation of the online mode is the case when sending sample per sample into the evolution of the fuzzy models and taking the label entries as a simulation of online operator feedback Both data sets were split into a training data set (two-thirds of the data) and a test data set (one-third of the data) The training data was split into two halves, one taken for initial of ine training, the other for further evolution of the classi ers The test data set is for the purpose of evaluating the evolved classi ers on new unseen data Table 53 shows the performance of evolving classi ers obtained by FLEXFIS-Class MM (see Algorithm 2) vs.

All the values, given in meters, are typical one sigma values. PPS, Precise Positioning Service; SPS, Standard Positioning Service.

1.4. Regulation of the Hepatocyte Microenvironment Toward the Development of Engineered Liver Tissue The importance of extracellular signals in hepatocyte culture in vitro correlates with the signi cant role of the microenvironment in the liver in vivo. It is well established that the proper function of liver cells in vivo is maintained by a complex combination of extracellular cues, including tightly controlled cell-cell interactions and distribution of extracellular matrix [Gebhardt and Mecke, 1983; Michalopoulos and DeFrances, 1997; Olson et al., 1990; Reid et al., 1992]. Furthermore, alterations in the liver microenvironment are important aspects of liver pathologies [Giannelli et al., 2003] such as brosis and have additionally been implicated in repair processes [Kim et al., 1997; Michalopoulos and DeFrances, 1997; Rudolph et al., 1999]. Therefore, an understanding of the microenvironmental mechanisms regulating hepatocyte function represents a crucial issue for not only the improvement of in vitro culture models and extracorporeal liver devices, but also the manufacture of implantable hepatocyte constructs. Notably, in addition to tissue engineering applications, functional in vitro hepatic models would

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