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To quickly create a chart like the one in Figure 23.1, begin with a column chart like that in Figure 23.2. This column chart uses actual values for one series and target values for the second series. Figure 23.1 is nothing more than a column chart with an overlapping line chart. The target line is invisible, and the line s marker has been increased in size. To create target markers, follow these steps: 1. Right-click on a target column and choose Chart Type. In Excel 2007 choose Change Series Chart Type. 2. In the Chart Type dialog box, select the Line Type with Markers at each data value. Choose Ok. This produces a line chart of target values overlapping a column chart of actual values. 3. Right-click on the line and select Format Data Series. 4. From the Patterns tab, select a Line pattern of None. In Excel 2007 select Line Color, No Line. This makes the target line invisible. From the Marker pattern, select Custom and a wide line marker with a color visible over the column color. In Excel 2007 select Marker Options, Built In. Make the marker size greater than 10. Choose Ok.

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While the feedforward filter eliminates most of the pre-cursor ISI, the feedback filter mitigates the IS1 caused by the past data symbols, ie the post-cursor ISI Since the feedforward filter only eliminates the pre-cursor IS1 and not the post-cursor ISI, noise enhancementin the DFEis less significant, when compared to the linear MSE equalizer..

<xsd:complexType name="demo"> <xsd:sequence> <xsd:element name="one" type="xsd:string" /> <xsd:element name="two" type="xsd:string" /> </xsd:sequence> <xsd:choice> <xsd:element name="first" type="xsd:string" /> <xsd:element name="second" type="xsd:string" /> </xsd:choice> <xsd:all> <xsd:element name="harry" type="xsd:string" /> <xsd:element name="george" type="xsd:string" /> </xsd:all> </xsd:complexType> <xsd:element name="MyDemo" type="demo" />

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rst makes an independent decision as to whether or not a target is present and then the devices exchange their decisions to arrive at a fault tolerant consensus decision As in value-fusion, the fused data is obtained by averaging data received from all the sensors For the situation of faulty nodes, exact agreement is used to preserve precision The comparative results show that value-fusion is clearly preferable if the sensor network is highly reliable and fault-free However, when faulty nodes are present, the performance of value-fusion degrades faster than the performance of decision-fusion and decision-fusion becomes superior to value-fusion Achieving fault tolerance through consensus is a broad problem Generally, each node has the task of trying to obtain a con dent statement of the state or situation the environment is in This information constitutes the state information present at the node.

For this exercise, use the Car.obj file found in the Photoshop CD bonus content. To access this file, insert the CD containing the bonus content and navigate to Goodies 3D models Car.

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The state information needs to be refreshed periodically to account for changes in the topology due to movement of wireless sensors or due to nodes encountering crash failures The major challenge within the WSN context is to devise protocols that minimize the effort for refreshing and exchanging state information over the network The protocol described in [64] generates consensus under the assumption that the number of faulty nodes is less than the number of correct nodes The protocol is designed to enable self-correction in the network by isolating the faulty nodes and putting them in sleep mode, thereby increasing the concentration of nodes having correct information and improving their ability to generate consensus The consensus process relies on forming a quorum, ie subgroups of sensor nodes with a certain minimum size.

FIGURE 21-19

For instance, if there are k nodes having the same area of interest, the size of the quorum should be at least (k + 1)/2 A quorum is created after exchanging information among nodes as follows: (i) the node that needs to generate consensus starts the process by sending its information, (ii) other nodes answer with positive or negative acknowledgements, according to their information and (iii) the consensus is generated if the initial node receives more than (k + 1)/2 positive acknowledgements As we have mentioned before, under WSN constraints, protocols should reduce as much as possible the number of messages exchanged One way to achieve this is using aggregation [3] within the consensus process, either by concatenating values, summarizing them, or by the counting of a set Other operations as well as aggregation of data other than scalar numbers could also be possible.

$2.00 (cost per loaf) / 20 (number of slices) $0.10 (cost per slice of bread) A slice of bread costs $0.10. We use 2 slices of bread. We need to multiply the cost per slice by the number of slices we use to determine our portion cost per entree. $0.10 (cost per slice) 2 (portion size) $0.20 (cost for 2 slices of toast)

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