Institution
General Electric
Company•Boston, Massachusetts, United States•
About: General Electric is a company organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Turbine & Rotor (electric). The organization has 76365 authors who have published 110557 publications receiving 1885108 citations. The organization is also known as: General Electric Company & GE.
Topics: Turbine, Rotor (electric), Signal, Combustor, Coating
Papers published on a yearly basis
Papers
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TL;DR: This work describes a system for extracting PGSM interactions from unstructured text using a lexical analyzer and context free grammar, and demonstrates that efficient parsers can be constructed for extracting these relationships from natural language with high rates of recall and precision.
Abstract: Motivation: As research into disease pathology and cellular function continues to generate vast amounts of data pertaining to protein, gene and small molecule (PGSM) interactions, there exists a critical need to capture these results in structured formats allowing for computational analysis. Although many efforts have been made to create databases that store this information in computer readable form, populating these sources largely requires a manual process of interpreting and extracting interaction relationships from the biological research literature. Being able to efficiently and accurately automate the extraction of interactions from unstructured text, would greatly improve the content of these databases and provide a method for managing the continued growth of new literature being published. Results: In this paper, we describe a system for extracting PGSM interactions from unstructured text. By utilizing a lexical analyzer and context free grammar (CFG), we demonstrate that efficient parsers can be constructed for extracting these relationships from natural language with high rates of recall and precision. Our results show that this technique achieved a recall rate of 83.5% and a precision rate of 93.1% for recognizing PGSM names and a recall rate of 63.9% and a precision rate of 70.2% for extracting interactions between these entities. In contrast to other published techniques, the use of a CFG significantly reduces the complexities of natural language processing by focusing on domain specific structure as opposed to analyzing the semantics of a given language. Additionally, our approach provides a level of abstraction for adding new rules for extracting other types of biological relationships beyond PGSM relationships. Availability: The program and corpus are available by request from the authors. Contact: gilder@research.ge.com; jtemkin1@comcast.net
199 citations
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TL;DR: In this paper, the concentration of resines epoxydes (oxyde de butadiene, dioxyde de limonene, phenyl glycidyl ether) is influenced by leur concentration sur la cinetique du durcissement de resines.
Abstract: Preparation et caracterisation (RMN, UV, point fusion, SIMS, toxicologie, solubilite) d'hexafluoroantimoniate et -phosphates d'alcoxy-4 diphenyl iodonium. Influence de leur concentration sur la cinetique du durcissement de resines epoxydes (oxyde de butadiene, dioxyde de limonene, phenyl glycidyl ether)
198 citations
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198 citations
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198 citations
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TL;DR: In this paper, a Nusselt number correlation is proposed to determine the flow transition from the initial annular regime to the final stratified regime, which exhibits errors of similar magnitude to established methods for annular and stratified flow condensation.
198 citations
Authors
Showing all 76370 results
Name | H-index | Papers | Citations |
---|---|---|---|
Cornelia M. van Duijn | 183 | 1030 | 146009 |
Krzysztof Matyjaszewski | 169 | 1431 | 128585 |
Gary H. Glover | 129 | 486 | 77009 |
Mark E. Thompson | 128 | 527 | 77399 |
Ron Kikinis | 126 | 684 | 63398 |
James E. Rothman | 125 | 358 | 60655 |
Bo Wang | 119 | 2905 | 84863 |
Wei Lu | 111 | 1973 | 61911 |
Harold J. Vinegar | 108 | 379 | 30430 |
Peng Wang | 108 | 1672 | 54529 |
Hans-Joachim Freund | 106 | 962 | 46693 |
Carl R. Woese | 105 | 272 | 56448 |
William J. Koros | 104 | 550 | 38676 |
Thomas A. Lipo | 103 | 682 | 43110 |
Gene H. Golub | 100 | 342 | 57361 |