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Examples : tesseract - ocr -eng (English), tesseract - ocr -ara (Arabic), ... Installer for Windows for Tesseract 3.05 and Tesseract 4 are available from Tesseract at UB ... This example has two generalized superclasses, Book and Person Each of these describes generic objects Presumably, each would contain attributes common to all Books and all Persons, such as a name Note that a Book is composed of Pages The composition relationship shown indicates that a Book will have from one to any number of pages Any methods a Book requires to manipulate Pages would be implemented in the Book class, and would be available for subclasses of Book A LibraryBook is derived from Book, and is a specialized kind of Book It might have additional attributes such as an acquisition date, borrowing status, and an identification number A Reader is a special case of a Person who uses the Library A Reader object would contain specialized attributes such as a list of checked out books The Borrowing class in this example is used to implement the same borrowing association between a Reader and a Library book as we used in Figure 2-1 Now, however, a Borrowing is also a part of a library - a list of all ooks borrowed We could use the same simple direct association as we used before, but then the library would still need some other object to track books that have been borrowed In addition, the Borrowing class can now have added responsibilities of tracking just when a Reader borrows a LibraryBook, for example, and or could track overdue books The dashed line from Borrowing is the UML notation to show this relationship In our earlier example, the borrowing association could be implemented as a simple double link between a LibraryBook and a Reader Using a class to implement this association means the links between the LibraryBook and the Reader will be managed by the Borrowing class Note the 04 multiplicity for a Reader borrowing LibraryBooks This would indicate that a reader could have from 0 to 4 books borrowed Figure 2-6 shows an aggregation relationship between a Library and. mac batch ocr: FreeOCR Alternatives for Mac - AlternativeTo.net free ocr software windows 10 FreeOCR - Free download and software reviews - CNET Download ...
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Tips ... length is 3k (Figure 52(c)) For any C a k with k > 1, k > C can be chosen so that sl(S) = 3k > 3C = C sl(Sopt ) In particular, list scheduling with start time minimization does not even guarantee a schedule length shorter than the sequential time of a task graph Still, numerous experiments have demonstrated that list scheduling produces good schedules for task graphs with low to medium communication (eg, Khan et al [103], Kwok and Ahmad [111], Sinnen and Sousa [177]) 512 With Dynamic Priorities The simple list scheduling outlined in Algorithm 9 establishes the schedule order of the nodes before the actual scheduling process During the node scheduling in the second part, this order remains unaltered, so the node priorities are static To achieve better schedules, it might be bene cial to consider the state of the partial schedule in the schedule order of the nodes Changing the order of the nodes is equivalent to changing their priorities, hence the node priorities are dynamic It remains that the node order must be compatible with the precedence constraints of the task graph, which is obeyed if only free nodes are scheduled A list scheduling algorithm for dynamic node priorities is given in Algorithm 11 Algorithm 11 List Scheduling Dynamic Priorities (G (V, E, w, c), P) 1: Put source nodes {ni V : pred(ni ) = } into set S 2: while S = do S only contains free nodes 3: Calculate priorities for nodes ni S 4: Choose a node n from S; S S n 5: Choose a processor P for n 6: Schedule n on P 7: S S {ni succ(n) : pred(ni ) Scur } 8: end while Instead of iterating over the node list, Algorithm 11 calculates in each step the priority of all free nodes and only then selects a node and a processor for scheduling After the scheduling of node n, the set S of free nodes is updated with the nodes that became free by the scheduling of n (line 7) Obviously, this approach has higher complexity in general than the simple list scheduling presented in Algorithm 9, because the priority of every node is determined several times Algorithm 11 is a generalization of the simple list scheduling, which becomes apparent by considering line 3 If this line is moved to the beginning of the algorithm and the priorities are calculated for all nodes, not only for the free nodes, the simple list scheduling is obtained This becomes even more distinct in Section 513, where the construction of node lists is explained Choosing Node Processor Pair Some algorithms dynamically compute the priorities of the free nodes by evaluating the start time (see Eq (51)) for every free. those following VB.NET barcode generation program to . 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