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In this chapter, I described a relatively complex user-oriented application that creates a worksheet based on user-specified options. This chapter concludes Part VI. s in the next part cover a variety of topics that you may find helpful, including compatibility issues, manipulating text files with VBA, modifying VBA components, and class modules.
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TinyDB queries are generally speci ed on a PC and then distributed throughout the sensor network by a query executor. The query is disseminated and results are returned in an energy-ef cient manner using a variety of in-network processing techniques and cross-layer optimizations. For example, in the preceding sample query, the query executor is responsible for determining which predicate to evaluate rst in the sensor network: the temp predicate or light predicate. Queries in TinyDB are disseminated through the entire network and collected via a routing tree. The root node of the routing tree is end point of the query, which is generally where the user that issued the query is located. Nodes within the routing tree maintain a parent child relationship in order to properly propagate results to the root. Research into query processing techniques include the design of an acquisitional query processor for data collection in wireless sensor networks. Information such as where, when, and how often data are physically collected and delivered, can be leveraged to signi cantly reduce the overall power consumption in the sensor network [61]. Directed diffusion [7,8] employs a different approach to query processing. Rather than utilizing a speci c query language, an application speci es a named interest, which is used to query the sensor network. Interests contain the query particulars, expressed through a sequence of attribute/value pairs. For example, an interest expressed as:
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You ll need to perform your menu changes with VBA code when the workbook is opened, and restore the menu to normal when the workbook is closed.
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