Ambassador of Kazakhstan to UNESCO, O.O. Suleimenov, Uldanai M. Bakhtikireeva et al. · RUDN Journal of Language Education and Translingual Practices · 2018
This discussion took place on December 3-6, 2017 in Karlovy Vary. Its initiator was the foundation “Culture”, headed by O.O. Suleimenov, a well-known poet and authoritative thinker of our modernity. Participants of the Polylogue were scientists from the Peoples’ Friendship University of Russia (Doctor in Philology, Professor Bakhtikireyeva U.M., Doctor in Philology, Professor Valentinova O.I., Director of the Institute of Hospitality and Tourism Dikhtyar S.V., PhD in Philology Valikova O.A.), Uzbek State University of World Languages (Doctor in Philology, Professor Dzhusupov M., Ph.D., Senior Researcher Ismailov G.M.), Eastern Institute of St. Petersburg State University (PhD in Turkology Dubrovina M.E.). The central theme of the discussion was the concept of O.O. Suleimenov about a new approach to etymology as a science. On the example of several time slices, the author reconstructs the routes of movement, phonetic modifications (in some cases - transformations) and word resemantization, citing illustrations and arguments from his own researches and observations.
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Anna Ursyn · 2025
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Martin H. Weik · 2000
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Heather O. Browning, Patrice M. Palmer · 2023
This chapter equips the reader with an understanding of how the interconnectedness and influence of race and racism, individual characteristics, and sociocultural factors shape interactions, decision-making, and the lens through which job culture, and fit, are constructed. It provides clarity and validation to professionals of color who may find themselves challenged with similar struggles of showing up authentically in their respective work environments. The chapter provides general insight for those looking to understand the workplace challenges many student affairs professionals of color experience in order to create critical conversations and thoughts around the concepts of job fit and professionalism. Institutional environments contribute to excluding professionals of color, and limit their abilities to be authentic, in the workplace at predominantly White institutions. The chapter examines the multilayered environments that influence a person’s experience at work, including the individual and contextual factors that play a role in creating and shaping job fit.
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George Edward Stanley, Guy Francis · Medical Entomology and Zoology · 2004
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Collins, Jodie · Bulletin of Miscellaneous Information (Royal Gardens Kew) · 1984
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Daniel Pargman · 2015
ABSTRACT: This paper examines imaginary worlds – complex but logical-and-controllable systems. The paper analyzes the overlap between structural characteristics of different sorts of imaginary worlds, as they are constituted in (fantasy) literature, role-playing games and computer code.
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Zhu, Lin · Figshare · 2024
This code for calculating CBGI
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Zhou, Shengshi, Xu, Lei, Liu, Xia et al. · Figshare · 2025
The code for calculating word frequency in the paper of a dataset on time value propositions.
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Zhu, Lin · Figshare · 2024
This code for calculating CBGI
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Cheng, Qian, Tian, Jinfang, Xue, Rui et al. · Figshare · 2023
This code for calculating word frequency
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Tian, Jinfang, Cheng, Qian, Xue, Rui et al. · Figshare · 2023
This code for calculating word frequency
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Chemical & Engineering News · 1970
RETURN TO ISSUEPREVNewsNEXTPHARMACOLOGY: Code Word of MemoryCite this: Chem. Eng. News 1970, 48, 6, 11Publication Date (Print):February 9, 1970Publication History Published online7 November 2010Published inissue 9 February 1970https://doi.org/10.1021/cen-v048n006.p011Copyright © 1970 AMERICAN CHEMICAL SOCIETYArticle Views3Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (353 KB) SUBJECTS:Circuits Get e-Alerts
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Jiang Zong · 2000
In verbal communication code switching has great influence upon language system.It gradually enriches the Chinese vocabulary system,which is mainly shown from the absorbing of alien words and dialectal words.And with no excptions,alien words and dialcctal words are both the result of code switching.Therefore Chinese normalization(referring to normalization of alien words and dialectal words)should start from the angle of occurence,which is determined by code switching associated with socialization background and individual psychology.
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Timothy M. Thomas · University of Calgary Press eBooks · 2024
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Tian, Jinfang, Cheng, Qian, Xue, Rui et al. · Figshare · 2023
This code for calculating word frequency
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Zhou, Shengshi, Xu, Lei, Liu, Xia et al. · Figshare · 2025
The code for calculating word frequency in the paper of a dataset on time value propositions.
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Tony Attanasio · 2013
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Jichang Zhao · Figshare · 2017
<pre>1. Introduction --------------- <br></pre><pre><br></pre><pre>Class PrepareInput can convert the original documents into word co-occurrence network and re-weight it, then save it as pseudo documents. The output of PrepareInput can be used directly as the input of jGibbsLDA. Class InferenceTopicsForOrgDocs is used to inference topics of original documents, after the execution of jGibbsLDA. * Note that jGibbsLDA is a free software written by Xuan-Hieu Phan. More details can be found in http://jgibblda.sourceforge.net. <br></pre><pre><br></pre><pre>2. Installation --------------- Straightforward Java compilation can be done with the following commands: > tar -xzcf wntm.tar.gz > cd wntm > javac *.java <br></pre><pre><br></pre><pre>3. Usage -------- > java PrepareInput Example usage: > java PrepareInput sample.txt ./ sample 10 * Note that constructing word network might require lots of memory, especially when the original input file is large. For example, original file size of 250MB needs 7GB memory in our experiment. In this case, one might use following command to configure the maximum memory can be used by Java. > java -Xmx10g PrepareInput sample.txt ./ sample 10 <br></pre><pre><br></pre><pre>4. Output --------- When PrepareInput completes, it will output two files. The file named with suffix ".word" stores all the nodes in the word network. The file named with suffix ".adjacent" stores pseudo documents ready to be used in jGibbsLDA. <br></pre><pre><br></pre><pre>5. Inference ------------ Since WNTM models topics for a word's adjacent node list. Therefore, we need to inference the topic distribution of original documents, when jGibbsLDA finished training pseudo documents. One can use following command to do inference: > java InferenceTopicsForOrgDocs to get topics of original documents, aka the .theta file for original corpus. <br></pre><pre><br></pre><pre>6. Contact ---------- If you have any problem, please feel free to contact Jichang Zhao(jichang@buaa.edu.cn) </pre>
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Greg Guarnaccia · Lighting Design + Application · 2010
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