305,147 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    USING PROGRAM ERHAM TO ANALYZE HIGH-RESOLUTION INFRARED SPECTRA OF MOLECULES WITH INTERNAL ROTORS

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    Author Institution: Department of Chemistry, University of Missouri-Kansas City, Kansas City, MO 64110-2499; Physical Chemistry, ETH Zurich, CH-8093 Zurich, SwitzerlandThe effective rotational Hamiltonian for molecules with one or two periodic large-amplitude motions 107, 4483 (1997).} implemented in program ERHAM has been adapted to enable prediction and least-squares fits of rotationally resolved lines in vibration-rotation spectra in the infrared region. The modified program is currently applied to assign the band of methyl formate at 925 cm1^{-1} that has been measured at ETH in Zurich on the IFS125 Bruker prototype ZP 2001 FTIR spectrometer 8, 1271 (2007)} at a resolution of 0.001 cm1^{-1}. An external glass cell with an optical path length of 3 m contained the sample, and 150 interferograms were co-added. Right now it looks as if the splitting into AA and EE components were a little too small to be resolved sufficiently for positive identification

    Author, publisher and bookseller : a tripartite synergy in Nigerian book industry

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    This work is about the roles of Author, Publisher and Bookseller in Book development in Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after which it proceeded by defining who an author, a publisher, and a bookseller is and expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in the emerging Information Society. Furthermore, the various constraints to book development were identified while the paper advised on how the Book Industry can be further promoted in Nigeria. However, the paper concluded and made recommendations on how the Book sector can help in enhancing scholarship in the country

    LOW-TEMPERATURE HIGH-RESOLUTION INFRARED SPECTRUM OF ETHANE-1D, C2H5D: ROTATIONAL ANALYSIS OF THE _17 BAND NEAR 805 cm_1using ERHAM.

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    The high-resolution infrared spectrum of gaseous ethane-d1_{1} at 130 K shows transitions that are split into A and E components due to the interaction of overall rotation with the internal rotation of the chem{CH_3} group. An analysis of the spectrum from 680 to 900 wn with an expanded version of the program ERHAM footnote{P. Groner, textit{J. Chem. Phys.} textbf{107} 4483 (1997)},^{,}footnote{P. Groner, textit{J. Mol. Spectrosc.} textbf{278} 52 (2012)} is in progress to assign the bands at E(nub{17}) = 805 wn and E(nub{11}) = 715 wn. A discussion of the interactions among the fundamental levels of nub{17} and nub{11} with overtone levels of nub{18} and the(chem{CH_3} torsion) will be given. ERHAM has been and continues to be very successful in the analysis of pure the rotational spectra of molecules containing internal rotation and the vibrational spectrum of chem{C_2H_5D} serves as an excellent system to test the extension of the program.Made available in DSpace on 2016-01-05T20:05:48Z (GMT). No. of bitstreams: 3 933.pdf: 23177 bytes, checksum: edec0d2e3440f5e2c03c6b58d655c303 (MD5) 342411.pptx: 340368 bytes, checksum: 353b27c41b3664f8b941140a90a6f33b (MD5) license.txt: 4813 bytes, checksum: 715c4321821a960fa1a1e91d2ac7ebce (MD5) Previous issue date: 2

    [Report to Chief J. E. Curry, by an unknown author #2]

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    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    [Report to Chief J. E. Curry, by an unknown author #1]

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    Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney

    Mining e-mail content for author identification forensics

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    We describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation
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