Severity: Warning
Message: file_get_contents(https://...@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f08&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The proposition that writing profiles are unique is considered a key premise underlying forensic handwriting comparisons. An empirical study cannot validate this proposition because of the impossibility of observing sample documents written by every individual. The goal of this paper is to illustrate what can be stated about the individuality of writing profiles using a database of handwriting samples and an automated comparison procedure. In this paper, we provide a strategy for bounding the probability of observing two writers with indistinguishable writing profiles (regardless of the comparison methodology used) with a random match probability that can be estimated statistically. We illustrate computation of this bound using a convenience sample of documents and an automated comparison procedure based on Pearson's chi-squared statistic applied to frequency distributions of letter shapes extracted from handwriting samples. We also show how this bound can be used when designing an empirical study of individuality.
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Source |
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http://dx.doi.org/10.1111/j.1556-4029.2011.01713.x | DOI Listing |
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