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{
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"label": "Defense Technical Information Center",
"creator": "Matt Burton",
"target": "^https?://oai\\.dtic\\.mil/oai/",
"minVersion": "3.0",
"maxVersion": "",
"priority": 100,
"inRepository": true,
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"browserSupport": "gcsibv",
"lastUpdated": "2013-01-09 15:36:32"
}
function detectWeb(doc, url) {
if (doc.title.indexOf("DTIC OAI Index for") != -1) {
return "multiple";
} else if (url.indexOf("verb=getRecord") != -1) {
return "report";
}
}
function doWeb(doc, url) {
var newURIs = new Array();
if (detectWeb(doc, url) == "multiple") {
var links = doc.evaluate("//a/@href", doc, null, XPathResult.Abstract, null);
var titles = doc.evaluate("//a/preceding::text()[1]", doc, null, XPathResult.Abstract, null);
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}
Zotero.selectItems(items, function (items) {
if (!items) {
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for (var url in items) {
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Zotero.Utilities.processDocuments(newURIs, scrape, function () {});
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} else {
newURIs = url.replace(/&metadataPrefix=html/, "&metadataPrefix=oai_dc");
scrape(doc, newURIs);
}
}
function scrape(doc, newURIs) {
var pdfurl = ZU.xpathText(doc, '//p/a[contains(@href, "doc=GetTRDoc.pdf")]/@href')
Zotero.Utilities.HTTP.doGet(newURIs, function (text) {
//cut down the XML to something RDF readable and add required xmlns to the header
text = text.replace(/\n/, "").replace(/.+<metadata>/, "").replace(/<\/metadata>.+/, "")
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translator.setString(text);
translator.setHandler("itemDone", function (obj, item) {
item.attachments = [{
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document: doc,
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if (pdfurl) {
item.attachments.push({
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item.reportType = "";
item.abstractNote = item.extra;
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item.itemID = "";
item.complete();
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translator.getTranslatorObject(function (trans) {
trans.defaultUnknownType = 'report';
trans.doImport();
});
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}/** BEGIN TEST CASES **/
var testCases = [
{
"type": "web",
"url": "http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA466425",
"items": [
{
"itemType": "report",
"creators": [
{
"firstName": "Dennis M.",
"lastName": "DeCoste",
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"notes": [],
"tags": [
"Cybernetics",
"*ARTIFICIAL INTELLIGENCE",
"*SYSTEMS ANALYSIS",
"*QUALITATIVE ANALYSIS",
"MONITORING",
"THESES",
"*QUALITATIVE REASONING",
"MEASUREMENT INTERPRETATION",
"EXPLANATION",
"*QUALITATIVE PHYSICS",
"SYSTEMS BEHAVIOR",
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"PINTERPS",
"QUALITATIVE STATES",
"ENVISIONMENTS",
"FAULTY DATA",
"INTERPRETATION CREDIBILITIES",
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"title": "Dynamic Across-Time Measurement Interpretation: Maintaining Qualitative Understandings of Physical System Behavior",
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"date": "1990-02",
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"abstractNote": "Incrementally maintaining a qualitative understanding of physical system behavior based on observations is crucial to real-time process monitoring, control, and diagnosis . This paper describes the DATMI theory for dynamically maintaining a pinterp-space, a concise representation of local and global interpretations consistent with the observations over time. Each interpretation signifies alternative paths of states in a qualitative envisionment . Representing a space of interpretations, instead of just a \"current best\" one, avoids the need for extensive backtracking to handle incomplete or faulty data. Domain-specific knowledge about state and transition probabilities can be used to maintain the best working interpretation as well. Domain-specific knowledge about durations of states and paths of states can also be used to further constrain the interpretation space. When all these constraints lead to inconsistencies, faulty-data hypotheses are generated and then tested by adjusting the pinterp-space. The time and space complexity of maintaining the pinterp-space is polynomial in the number of measurements and envisionment states.",
"libraryCatalog": "Defense Technical Information Center",
"shortTitle": "Dynamic Across-Time Measurement Interpretation"
}
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}
]
/** END TEST CASES **/
|
