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Nevertheless, by observation of past trends, a future trend can usually be built into the forecast figures. However, some variables are unpredictable (e.g., events that occur for no particular or observable reason, or sudden and drastic decreases in demand caused by severe and unusual weather conditions), and such random variables are difficult or even impossible to include in forecasts. Moving averages attempt to remove the random variations that can occur from period to period in the operation of the typical hospitality business. Note that the larger the number of periods used, the less likely it is that any random causes will affect the moving average. To take care of those random variations for a monthly forecast, we can calculate a 12-month moving average. The 12 monthly figures for the past year are added together and then divided by 12. For example, suppose for the past year a restaurant s monthly guest counts were as follows: Month 1 2 3 4 5 6 7 8 9 10 11 12 Total Rounded, the moving average is 30,003 12 2,500 Guest Count 2,406 2,502 1,986 1,829 2,312 2,587 2,804 3,009 3,102 2,748 2,406 2,312 30,003

destination dual-stack IP host. Host to Host: Dual-stack IP hosts can tunnel IPv6 packets between themselves over an IPv6 infrastructure (without the use of a router). These two types provide for tunneling all the way to a final destination. In these cases, the tunnel endpoint is the node to which the IPv6 packet is addressed. This is automatic tunneling and it simply allows for IPv6 packets that are to be sent to IPv6 destinations using the IPv4-compatible address and located remotely (off-link) to be encapsulated in IPv4 headers and sent through the IPv4 infrastructure.

effect model, (b) the nicotine regulation model, and (c) the multiple regulation model. Leventhal and Cleary (1980) provide a review of the literature and description of each of the three models. Velicer, Redding, et al. (1992) identi ed each of the three models with one of three broad classes of time series models: (a) a positive dependency model, (b) a white noise model (no dependency), and (c) a negative dependency model. The nicotine xed effect model assumes that smoking is reinforced because nicotine stimulates speci c reward inducing centers of the nervous system. These have been identi ed as either autonomic arousal or a feeling of mental alertness and relaxation or both. Following this model, an increase on one occasion should be followed by an increase on the next occasion or a decrease on one occasion should

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Scenario 1: Tb is active at Site K The concurrency control at Site K will enforce the wound rule In this case, Tb is given the wound period of time to nish If Tb does not nish within the speci ed period of time, Site K will roll back Tb locally and broadcast the wound-rollback message to all the sites that Tb has already visited Each of these sites will roll back Tb locally, once they receive this message from Site K Scenario 2: Tb has left Site K, so it is not active there, but Tb is active at Site L In this case, the concurrency control at Site K broadcasts the fact that Tb has been wounded to all sites When Site L receives the wound message, that site carries out the wound rule.

Again, if Tb does not nish within the time period speci ed by the wound process, then Site L kills Tb locally and broadcasts the wound-rollback message to all sites where Tb had previously done work If Tb does nish within the wound period, then Site L broadcasts the committed message to all sites where Tb had previously done work Scenario 3: Tb has left Site K but Tb is waiting (blocked) at Site N This scenario is the same as Scenario 2 with one minor difference Since Tb is blocked at Site N, Site N will carry out the wound rule rather than Site L, and there is very little chance of Tb committing during the wound period In general, when a wound message is broadcast for a given transaction, the site at which Tb is active or is blocked has the responsibility of carrying out the wound process.

404 A P P L I C A T I O N S O F E V O L V I N G I N T E L L I G E N T S Y S T E M S T O O I L A N D G A S I N D U S T R Y

According to our processing model, Tb cannot be both active at one site and blocked at another site Thus, there is only one site that carries out the wound process and there is no need for further synchronization Note also that there is a case when Tb might not be active at any site: this transaction is not blocked (not waiting for a locked resource), and this transaction is not active This transaction is in transit from one site to another As soon as the transaction arrives at its destination, it becomes active there This can be handled simply by caching the message that was broadcast from Site K and applying it when the transaction arrives at the site with the newly activated transaction..