117,422 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
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
Square Dancing with the Stars to Enhance Dynamic Hirschman Linkages?
In this Presidential Address, the author takes the reader on a reconnaissance of his life and time as a regional scientist. He points out scenery he found scintillating along the way, hoping that some may pick up the banner and chew on a few of the ideas for a while. He suggests a revisit to Albert O. Hirschman’s notion of key sectors and more empirical analysis related to Marcus Berliant’s and Masahisa Fujita’s notion of knowledge creation and transfer.Presidential Address, San Antonio, Texas, March 29, 2014 (53rd Meetings of the Southern Regional Science Association
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Corresponding author:
We describe a novel approach to modeling idiosyncratic prosodic behavior for automatic speaker recognition. The approach computes various duration, pitch, and energy features for each estimated syllable in speech recognition output, quantizes the features, forms N-grams of the quantized values, and models normalized counts for each feature N-gram using support vector machines (SVMs). We refer to these features as “SNERF-grams ” (N-grams of Syllable-based Nonuniform Extraction Region Features). Evaluation of SNERF-gram performance is conducted on two-party spontaneous English conversational telephone data from the Fisher corpus, using one conversation side in both training and testing. Results show that SNERF-grams provide significant performance gains when combined with a state-of-the-art baseline system, as well as with two highly successful long-range feature systems that capture word usage and lexically constrained duration patterns. Further experiments examine the relative contributions of features by quantization resolution, N-gram length, and feature type. Results show that the optimal number of bins depends on both feature type and N-gram length, but is roughly in the range of 5 to 10 bins. We find that longer N-grams are better than shorter ones, and that pitch features are most useful, followed by duration and energy features. The most important pitch features are those capturing pitch level, whereas the most important energy features reflect patterns of rising and falling. For duration features, nucleus duration i
Extensions to the Speech Disorders Classification System (SDCS)
This report describes three extensions to a classification system for pediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). Part I describes a classification extension to the SDCS to differentiate motor speech disorders from speech delay and to differentiate among three subtypes of motor speech disorders. Part II describes the Madison Speech Assessment Protocol (MSAP), an approximately two-hour battery of 25 measures that includes 15 speech tests and tasks. Part III describes the Competence, Precision, and Stability Analytics (CPSA) framework, a current set of approximately 90 perceptual- and acoustic-based indices of speech, prosody, and voice used to quantify and classify subtypes of Speech Sound Disorders (SSD). A companion paper,
Shriberg, Fourakis, et al. (2010)
provides reliability estimates for the perceptual and acoustic data reduction methods used in the SDCS. The agreement estimates in the companion paper support the reliability of SDCS methods and illustrate the complementary roles of perceptual and acoustic methods in diagnostic analyses of SSD of unknown origin. Examples of research using the extensions to the SDCS described in the present report include diagnostic findings for a sample of youth with motor speech disorders associated with galactosemia (
Shriberg, Potter, & Strand, 2010
) and a test of the hypothesis of apraxia of speech in a group of children with autism spectrum disorders (
Shriberg, Paul, Black, & van Santen, 2010
). All SDCS methods and reference databases running in the PEPPER (Programs to Examine Phonetic and Phonologic Evaluation Records; [
Shriberg, Allen, McSweeny, & Wilson, 2001
]) environment will be disseminated without cost when complete
Letter from unknown writer to Jesse L. Boyce
Letter to Jesse L. Boyce from unknown author (possibly Jack) about the investigation into the powder magazine located in the Grand Canyon. Some personal news is included in the letter such as the writer's marriage to the daughter of C.A. Taylor, former Supervisor of Cochise County
Dispelling the Myths Behind First-author Citation Counts
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
Sarah L. Blum Author Visit - Warrior Nurse: PTSD and Healing
Hear Sarah L. Blum, author of Women Under Fire: Abuse in the Military, discuss her newest book, Warrior Nurse: PTSD and Healing followed by a Q&A and book signing.
Sarah L. Blum is a decorated Vietnam veteran who served as an operating room nurse during the intense fighting of 1967. In recognition of her service, she was awarded the Army Commendation Medal.
Sponsored by CWU Veterans Center and CWU Libraries.https://digitalcommons.cwu.edu/libraryevents/1252/thumbnail.jp
Lillian L. Lambert, Author, Speaker, and Entrepreneur
Lillian L. Lambert, Author, Speaker, and Entrepreneu
Letter to Alfred L. Shoemaker, February 10, 1948
A handwritten letter from an unknown author addressed to Alfred L. Shoemaker, dated February 10, 1948. Within, the author discusses the Pennsylvania Dutch word for Ash Wednesday, along with traditions associated with this day.https://digitalcommons.ursinus.edu/shoemaker_documents/1118/thumbnail.jp
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