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unsupervised clustering algorithm. Clustering is a key issue in evolving fuzzy systems because they must dynamically nd an appropriate structure in a stream of data. Unsupervised dynamic clustering provides an ef cient mechanism to implement a form of self-organization in system modeling. Similarly to eTS, parameters of rule consequents are computed using the least-squares algorithm. Computational experiments with a classic benchmark problem and a real-world application concerning hourly electrical load forecasting show that ePL is a promising approach in the adaptive fuzzy systems modeling area.

a more functional and pragmatic approach to incorporating various treatment strategies to fit the needs of the individual patient (O Brien & Houston, 2000).

Summary

effective caching scheme include (1) what to cache (and when and for how long), (2) when and how to invalidate the cached items and at what granularity level, (3) data consistency provided to the user and at what cost Most of these concerns, especially the consistency management of cached data, are exacerbated in mobile computing environments Mobile computing environments are characterized by slow wireless links (low bandwidth radio links) that are susceptible to frequent disconnections from the base station (server) and low battery power at the mobile clients (hosts), which necessitates the clients to minimize up-link queries as well as to voluntarily disconnect from the network to conserve battery power This unique feature of frequent disconnection adds a new dimension to the task of maintaining consistent cache at the mobile client, since the underlying cache maintenance protocol should make optimal use of the limited bandwidth.

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PURPOSE INHERITED VALUES Specifies the maximum width of an element. No Specify a length or a percentage of the containing block, or none.

In addition to being tolerant of disconnections, these protocols should be energy-efficient and adaptive to varying quality-of-service provided by the wireless network Various models have been suggested in the literature to estimate the usefulness of caching in mobile environments under different cost models [1 5] with encouraging results Our purpose in this chapter is to consider the problem of management of cache consistency in a mobile wireless environment, once the question of what to cache has been answered Frequent voluntary and involuntary disconnection of clients from servers makes this a very challenging problem [6] Efficient caching schemes for mobile environments should ideally take into account the following factors: data access pattern and update rates, communication/access costs, mobility pattern of the client, connectivity characteristics (disconnection pattern, available bandwidth, etc), and location dependence of the data.

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A FOUR-STAGE GENERAL PROCESS OF MODELING The process of modeling could be thought of as a four-stage process: model speci cation, model estimation, model evaluation, and model modi cation. In this section each of these stages will be discussed and illustrated with an example based on data collected as part of an ongoing Drug Abuse Resistance Education (D.A.R.E.) evaluation (see Dukes, Ullman, & Stein 1995, for a full description of the study). This example uses data from students responses immediately following completion of the D.A.R.E. program (see Dukes, Ullman, & Stein, 1995). Model Speci cation/Hypotheses The rst step in the process of estimating an SEM model is model speci cation. This stage consists of (a) stating the hypotheses to be tested in both diagram and equation form, (b) statistically identifying the model, and (c) evaluating the statistical assumptions that underlie the model. This section contains discussion of each of these components using the

Validation checks that are normally used in an wired environment are not at all suitable for mobile environments since they waste precious wireless bandwidth Almost all the cache coherency schemes proposed for mobile environment are based on a call-back (invalidation report) mechanism A client may miss invalidation reports from the server if it is disconnected during the broadcast In an attempt to solve this problem, Barbara and Imielinski [7] have developed a periodic broadcast invalidation report scheme In this chapter, we describe a caching scheme, called AS [21], for wireless networks that uses asynchronous invalidation reports (call-backs) to maintain cache consistency, ie, reports are broadcast by the server only when some data changes, and not periodically Each mobile client (host) (MH) maintains its own home location cache (HLC) to deal with the problem of disconnections.

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