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function loadXml(url){ var req=null; if (window.XMLHttpRequest){ req=new XMLHttpRequest(); } else if (window.ActiveXObject){ req=new ActiveXObject("Microsoft.XMLHTTP"); } if (req){ req.onreadystatechange=onReadyState; req.open('GET',url,true); req.setRequestHeader('secret-password',getEncryptedKey()); req.send(params); } }

property DEBUG_LOG : ((path to startup disk as text) & "debug1.log") -- Clear the log file set fp to open for access file (DEBUG_LOG) with write permission set eof fp to 0 close access fp tell application "BBEdit 6.5" my TRACE_INFO("activate") activate my TRACE_INFO("make new text window") make new text window my TRACE_INFO("set bounds " & "{0, 0, 200, 300}") set bounds of text window 1 to {0, 0, 200, 300}

One way to cope with typos or wrong orthography (either in the indexed text or in the query provided by the user) is to make use of FuzzyQuery. This system doesn t require any special processing at indexing time. It computes the Levenshtein distance (edit distance) and takes this value into account when retrieving matching documents. All the work is done when the query is executed. We ll discuss fuzzy searching in more detail in sections 7.1.4 and 7.3.5. Another strategy consists of preparing the index structure to best serve an approximation query. In most cases, a typo or wrong orthography alters a word in one or two places. Part of the word, however, is correct. The user might have the beginning, the end, or the middle of the word right. The n-gram algorithm is based on this idea. An n-gram is a sequence of n consecutive characters in a word. The list of trigrams (3-grams) for the word hibernate is hib, ibe, ber, ern, nat, and ate (see figure 5.3). Instead of indexing the whole word, an n-gram tokenizer or filter will index each available ngram for a given word. When the query is built, the same process is applied to the query terms. Let s imagine a query where a user is looking for ybernat. The query will look like ybe OR ber OR ern OR nat. Some of the n-grams match the Hibernate n-grams, and the matching document will be picked up. The more n-grams an element matches, the

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learned some details of this problem in section 1.3.1. The usual solution is to bend and twist the object model until it matches the underlying relational technology. This can be done successfully, but only at the cost of losing some of the advantages of object orientation. Keep in mind that relational modeling is underpinned by relational theory. Object orientation has no such rigorous mathematical definition or body of theoretical work. No elegant transformation is waiting to be discovered. (Doing away with .NET and SQL and starting from scratch isn t considered elegant.)

@Stateless public class ItemManagerBean implements ItemManager { @PersistenceContext(unitName="actionBazaar") private EntityManager entityManager; public ItemManagerBean() {}

the events and then forwards them to PowerShell by writing them into the pipeline. You can, however, handle them synchronously. Let s look at how to do this. We ll look at detecting when a user plugs in a USB device. We start by creating an instance of Management.EventQuery. This query describes the events we re interested in being notified about.

If there is any magic to the ServiceLocator class, it s in how the ThreadLocal class behaves. By storing the initialized Session instance in the ThreadLocal variable, you are ensured that only one Session is created per request thread. When the Session is retrieved the first time, a new Session is opened by the SessionFactory and set in the ThreadLocal instance. Subsequent calls to getSession() return the same Session instance as long as the Session hasn t been closed with a call to closeSession().

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