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Further application examples of SPNs can be found in a number of books on SPNs, e.g., by Ajmone Marsan et al. [l, 21 and by Bause and Kritzinger [15]. Also the book on Sharpe by Sahner et al. [249] p rovides application examples. Regarding SPN-based polling models, we refer to papers from Ajmone Marsan et al. [5, 7, 61, Ibe et al. [141, 142, 1401, Choi and Trivedi [50] and Haverkort et al. [124]. The model in Section 16.3 is elaborated in [121]. Sanders and Malhis also present SPN dependability models [252]. C iar d o et al. also present interesting SPN-based performance and dependability models in [54]. Finally, more application examples of SPNs can, among others, be found in the proceedings of the IEEE workshop series on Petri Nets and Performance Models. SPN-based dependability models can be found in the proceedings of the annual IEEE Fault-Tolerant Computer Systems Symposium and in the proceedings of the IEEE International Performance and Dependability Symposium.

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2.2.4.1 Grouping Grouping is an approach that starts by creating as many vertical fragments as possible and then incrementally reducing the number of fragments by merging the fragments together. Initially, we create one fragment per nonkey column, placing the nonkey column and the primary key of the table into each vertical fragment. This rst step creates as many vertical fragments as the number of nonkey columns in the table. Most of the time, this degree of fragmentation is too ne and impractical. The grouping approach uses joins across the primary key, to group some of these fragments together, and we continue this process until the desired design is achieved. Aside from needing to ful ll the requirements for one or more application, there are very few restrictions placed upon the groups (fragments) we create in this approach. For example, the same nonkey column can participate in more than one group that is, groups can have overlapping (nonkey) columns. If this overlap does occur, obviously, it will add to the overhead of replication control in a distributed DBMS system. As a result, grouping is not usually considered a valid approach for vertical fragmentation design. For more details on grouping see [Hammer79] and [Sacca85]. Hammer and Niamir introduced grouping for centralized DBMSs and Sacca and Wiederhold discussed grouping for distributed DBMSs. 2.2.4.2 Splitting Splitting is essentially the opposite of grouping. In this approach, a table is fragmented by placing each nonkey column in one (and only one) fragment, focusing on identifying a set of required columns for each vertical fragment. As such, there is no overlap of nonprimary key columns in the vertical fragments that are created using splitting. Hoffer and Severance [Hoffer75] rst introduced splitting for centralized systems, while Navathe and colleagues [Navathe84] introduced splitting for

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27 Apr 2018 ... UPCMain . java is a command line program that takes in a 12 digit number and checks to see if it is a valid UPC-A barcode. It does this by ...

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Validate is used with Combo Box and Text field types to ensure acceptable responses from user-supplied values.

The importance of psychological processes in the experience of health and illness is being increasingly recognized. More and more evidence is accumulating for the role of behavior in current trends of morbidity and mortality: Certain health behaviors reduce morbidity and mortality (Breslow & Enstrom, 1980; Broome & Llewellyn, 1995; Marks, Murray, Evans, & Willig, 2000; Matarazzo, Weiss, Herd, Miller, & Weiss, 1984; Taylor, 1986). Maes and von Veldhoven (1989), reviewing all the English language handbooks on health psychology

26

SUMMARY De nition. The Kolmogorov complexity K(x) of a string x is K(x) = K(x|l(x)) =

two levels suffice, but the above examples suggest how a programmer might proceed. For example, it is not surprising that $data{$i} [$j] [$k] accesses a value of a hash of arrays of arrays. There is more to know about references, but the material above suffices for the tasks in this book. Now we apply the tools discussed in this section to text. In the next section, we learn how to compare the words in two texts by using an array of hashes.

You create an associative array when you need placeholders to accept data that will be displayed later. Each element in an associative array is linked to a variable in the movie. For example, if your client wants you to create a customer survey form, you can create an associative array to accept the data the customer enters. After the customer answers a question, the result is transferred to an element in the associative array. After the customer answers all the questions, they can be reviewed by transferring the element from the array to a variable, which is displayed in a dynamic text box. When you create an associative array, you create blank placeholders for data to be transferred to. To create an associative array: 1. Create a variable and assign its value to the newArray method of the Array object as outlined previously. After you create the new array, your cursor blinks between the parentheses in the Value field.

and the result is proved. Here (a) follows from Lemma 9.6.1, (b) is the inequality in Lemma 9.6.4, and (c) is Lemma 9.6.5 in which causality is used.

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UPC-A Java Barcode Generator/Class Library - TarCode.com
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