Telephone Verification in .NET

Integrate qr codes in .NET Telephone Verification

For a given convolutional code Cconv (n, k, K ), the input vector is a sequence of k L information bits and the code sequence contains N = n L + n K = n(L + K ) bits. The n K additional bits are related to the memory of the FSSM or encoder. The amount n A = n(K + 1) (20)
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Part III Understanding Visual Basic for Applications
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The fully qualified reference for the preceding example also includes the Application object, as follows:
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In this approach, a transaction s writes are divided into two phases the pre-write phase and the commit phase. When transaction Ti wants to write data item X, it calls the algorithm shown in Figure 5.16a, passing parameter Ti to it as the transaction ID and X as the data item name and value. Once Ti is ready to commit the new value for X, it calls the algorithm in Figure 5.16b to commit the new value for X to the database. If transaction Ti needs to read a data item such as X, then it needs to call the algorithm shown in Figure 5.16c, passing it Ti as the transaction ID and X as the data item name. If the algorithm actually performs the read, we can use X as an output value or return the new value as a return value the mechanism is not important to the algorithm, and therefore not shown here. In the algorithms shown in Figure 5.16, ts(Ti) represents the timestamp for transaction Ti. The TO algorithms also need to maintain two other timestamps these timestamps are maintained for each data item stored in the database. We use rts(X) to represent the read timestamp of data item X rts(X) holds the timestamp of the youngest transaction that has ever read data item X. Similarly, we use wts(X) to represent the write timestamp of data item X wts(X) holds the timestamp of the last (most recent) transaction that wrote to data item X. The notation /* . . . */ indicates a comment to help understand the algorithm. During the pre-write phase, the changes for the transaction are kept in memory not stored in the database. During the commit, the changes are transferred from memory to the database. When changes from more than one transaction are buffered, the order of committing these transactions is dictated by the ages of the transactions as well. If two con icting transactions are ready to commit, the system allows the younger one to commit only after the older one has been committed or restarted. Each transaction s reads are always processed from the information stored on the disk. Based on this, if transaction T1 reads X, writes X, and then reads X again, the value it reads for the second time is the same value that it read the rst time. If the intention of T1 is to use the new value it generated for X, then T1 should not issue a new read and should continue using what is stored in memory for X. The implementation of the TO concurrency control algorithm shown in Figure 5.16 suffers from many unnecessary restarts. Assume there are 15 transactions currently running in the system. Let s consider the case where the system receives a write request from transaction T14 for item X. Also, assume that X has not been requested by any other transaction so far. In this case, the system is going to allow T14 to pre-write and then commit a new value to the database. This commitment of T14 invalidates any read or write request from transactions T1 through T13. This results in many restarts for transactions that are older than T14. That is why this algorithm is also known as the aggressive TO algorithm.
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Source: Ref. 17, Table 1. (Reprinted with permission of the IEEE.)
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n+ n+ C C
Trials and Evaluation for Acceptance
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