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Hindi OCR software Professional Edition scans and converts Hindi Documents to soft-copy to enable the visually challenged to then read it with the JAWS ...

By default, when you save information to a local shared object, it is associated with the SWF that created it. The SWF is identi ed by the location it was loaded from, so that each SWF gets its own whole namespace of possible SharedObject names. This means you don t have to worry if another SWF on the internet wants to use the name storage for its SharedObject. To understand this better, let s lift back the hood of Flash Player and nd how SharedObjects are stored on your local drive. Somewhere in your drive, under your username, is a folder that stores all



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1 finds a set of starting points and ending points for r m chains, each of length t Consequently, at most rmt different keys could be recovered in the attack phase although, due to the inevitable cycling and merging, the actual number will be significantly less than rmt, as discussed below If the desired key K is within one or more of the chains, then it will be found following the algorithm in Table 42 The definition of the function findKey in Table 42 is given in Table 43 Note that findKey corresponds to the steps illustrated in Figure 48, while.





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Assume that you start with the instance of a database in Table 23.4. This table links three different entities: suppliers, projects and parts. We assume that initially, we ignore these entities and would like to discover these entities automatically. We can notice that an entity is defined as a subset of attributes. In this example, we have the following attributes: {S#, SNAME, STATUS, SCITY, P#, PNAME, COLOR, WEIGHT, PCITY, J#, JNAME, JCITY, QTY }.

those SharedObjects. Let s call this directory #SharedObjects. When you create an LSO named storage in a le hosted at http://example.com/examples/sharedobjects.swf, information stored in that shared object ends up in a le named

This literal mapping between the name of the SharedObject and a le on the lesystem explains why you are prevented from using speci c characters when naming an LSO.

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// Given C , search for an endpoint E P findEP(C) for i = 0 to r - 1 Y = F,(C) for j = 1t o t for t =0 to m- 1 i f Y == EPie t h e n found = findKey(i,l,j) i f not found t h e n false alarm e l s e / / found = K r e t u r n ( found) end i f end i f next t Y = Fz(E(P,Y ) ) next j next i r e t u r n ( k e y not found) end findEP

I m using the #SharedObjects alias for the shared object directory because the full path differs by operating system and contains a random string. If you poke around your lesystem, you can nd this actual directory. For me it happens to be

the algorithm in Table 4.2 corresponds to the steps illustrated in Figure 4.7. Recall that r is the number of tables, m is the number of chains per table and t is the length of each chain. Also note that searching for a matching endpoint EPij in Table 4.2 can bc made considerably more efficient if the pairs (SPij,EPij) within each table are sorted by endpoints. That is, we sort the pairs (SPij,EPij) by EPij, where j = 0 , 1 , . . . , m - 1.

The Wikipedia article http://en.wikipedia.org/wiki/Local Shared Object#File locations can help you nd your own shared object directory.

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This scheme of storing shared object les also allows you to share shared objects between SWFs hosted in different locations on the same domain. You can, for example, store a central set of preferences that are implemented across several modules seamlessly. To be able to share local shared objects, you must ensure that the shared object le is stored in a place that is accessible to SWFs in both locations. If you placed the shared object le at

In Trudy s ideal world, all of the rmt chain elements would be distinct,. If this werc the case, then the chance of finding a randomly selected key would he r m t / 2 k (assuming rmt 5 2 k ; otherwise the probability would be one). Due to the merging and cycling discussed above, the real world is not so kind tjo Trudy (which is fortunate for Alice and Bob). While random functions help: they can only reduce the severity of the problem. Below we consider the probability of success in more detail.

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