. As organizations in both the private and the public sectors routinely exchange such information, individ.uals have no way of knowing if the information is inaccurate, obsolete, or otherwise inappropriate. The foundation is being laid for a dossier society, in which computers could be used to infer individuals

The present paper considers the effects of introducing inaccuracies in a learner’s environ-ment in Gold’s learning model of identification in the limit. Three kinds of inaccuracies are considered: presence of spurious data is modeled as learning from a noisy environment, miss-ing data is modeled

. One consequence of this is that a simple inspection of the port numbers used by flows may lead to the inaccurate classification of network traffic. In this work, we look at these inaccuracies in detail. Using a full payload packet trace collected from an Internet site we attempt to identify the types

in favor of a more realistic learning model in which data emanates from multiple sources, some or all of which may be inaccurate. Three kinds of inaccuracies are considered: spurious data (modeled as noisy texts), missing data (modeled as incomplete texts), and a mixture of spurious and missing data

physical and recorded inventory levels. Expected benefits of new technology, such as radio frequency identification (RFID) include improvements in the accuracy of supply chain data, including possibilities of real-time alignment of the data. This research looks at the factors of theft, order error, lead

, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. METHODS

(simplified method and disk method), in the identification of 100 CNS strains. Compared to the reference method, the simplified method and disk method correctly identified 100 and 99% of the CNS species, respectively, while this rate was 84 % for the API Staph system. Inaccurate identification by the API

extracted from BGP routing tables is not sufficient for determining the ASlevel forwarding paths [1]. By comparing BGP and traceroute AS paths from multiple vantage points, [1] proposed heuristics that identify the root causes of the mismatches and fix the inaccurate IP-to-AS mappings. These heuristics

increasingly inaccurate. An alternate, more accurate technique is to use specific application-level features in the protocol exchange to guide the identification. Unfortunately deriving the signatures manually is very time consuming and difficult. In this paper, we explore automatically extracting application

of glottal pulses, 2) inaccurate estimation of formants and band-widths, 3) phase angles. of formants at the instants of excitation, and 4) zeros in the vocal tract system. A method for the unambiguous identification of epochs from LP residual is then presented. The ac-curacy of the method is tested