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Zeitschriftenartikel zum Thema „Text“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 9. Juni 2025

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1

LOW, G. D. "FROM TEXT TO TEST." World Englishes 4, no. 1 (March 1985): 180–83. http://dx.doi.org/10.1111/j.1467-971x.1985.tb00400.x.

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2

Reddy, Mr B. Ravinder, J. Nandini, and P. Sowmya Y. Sathwik. "Handwritten Text Recognition and Digital Text Conversion." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1826–27. http://dx.doi.org/10.31142/ijtsrd23508.

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3

Theunissen, T. J. J. M. "Text banking and test design." Language Testing 4, no. 1 (June 1987): 1–8. http://dx.doi.org/10.1177/026553228700400101.

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4

Kumar HM, Prashanth, and Subramanya Bhat B. "Implementation of Converting Unicode Text to Original Text." International Journal of Scientific Engineering and Research 12, no. 1 (January 27, 2024): 12–16. https://doi.org/10.70729/se231222125142.

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5

Soboleva, Ya S., S. Šandalová, A. V. Sobolev, and I. A. Presnyakov. "Probe Mössbauer Study of Magnetically Ordered Manganite $${\text{ScMn}}_{{{\text{0}}{\text{.996}}}}^{{{\text{57}}}}{\text{F}}{{{\text{e}}}_{{{\text{0}}{\text{.004}}}}}{{{\text{O}}}_{{\text{3}}}}$$." Inorganic Materials 60, no. 10 (October 2024): 1226–30. https://doi.org/10.1134/s0020168524701619.

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6

Cope, Bill, and Mary Kalantzis. "Text-Made Text." E-Learning and Digital Media 1, no. 2 (June 2004): 198–282. http://dx.doi.org/10.2304/elea.2004.1.2.4.

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7

Vössing, J., C. Stamov-Roßnagel, and K. Heinitz. "Text difficulty affects metacomprehension accuracy and knowledge test performance in text learning." Journal of Computer Assisted Learning 33, no. 3 (March 19, 2017): 282–91. http://dx.doi.org/10.1111/jcal.12179.

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8

Sundberg, Norman D. "A Text for Future Test Users." Contemporary Psychology: A Journal of Reviews 30, no. 3 (March 1985): 203–4. http://dx.doi.org/10.1037/023632.

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9

Mohammed Ali, Kawthar, and Diaa Abdul Razzaq Alani. "THE CHARACTER BETWEEN READING TEXT AND VISUAL TEXT(2000-2017)." Journal of The University of Duhok 22, no. 1 (November 25, 2019): 358–68. http://dx.doi.org/10.26682/hjuod.2019.22.1.19.

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10

Sarangi, Srikant. "Editorial: Text & Talk." Text - Interdisciplinary Journal for the Study of Discourse 25, no. 1 (January 1, 2005): 1–5. http://dx.doi.org/10.1515/text.2005.25.1.1.

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11

Kim, Tatyana S. "Opposition Text Structure." International Journal of Psychosocial Rehabilitation 24, no. 4 (February 28, 2020): 3689–99. http://dx.doi.org/10.37200/ijpr/v24i4/pr201482.

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12

James Gifford. "Dramatic Text, Music Text:." Interdisciplinary Literary Studies 14, no. 1 (2012): 21. http://dx.doi.org/10.5325/intelitestud.14.1.0021.

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13

Lotman, Yu M. "Text within a Text." Soviet Psychology 26, no. 3 (April 1988): 32–51. http://dx.doi.org/10.2753/rpo1061-0405260332.

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14

Hevia, J. L. "Image/Text::Text/Image." positions: asia critique 23, no. 1 (January 1, 2015): 115–19. http://dx.doi.org/10.1215/10679847-2870510.

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15

Dowden, Ken. "Homer's sense of text: Homeric ‘Text’, Cyclic ‘Text’." Journal of Hellenic Studies 116 (November 1996): 47–61. http://dx.doi.org/10.2307/631955.

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In this article I am concerned to form a view of the interaction of Homer's Iliad with other texts prior to his. This is an issue whose legitimacy, particularly in English-language scholarship, has been rather obscured by scholarly discourse in terms of oral poetics, an issue I shall discuss presently. Yet, unless they are completely new fictions, the Cyclic epics do show us some of the material with which Homer was bound to be interacting, and it has been the achievement of the Neoanalysts to detail that interaction. In the following I do not claim to add greatly to the repertoire of neoanalytic data, but I do hope to build on it some sense of Homer's achievement in this area and to make clear our entitlement to respond to Homer's intertextuality.

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16

Yingguang, Shi. "The exact order of $$\sum\nolimits_{k = 1}^{\text{n}} {|{\text{x - x}}_{\text{k}} } |^8 |{\text{l}}_{\text{k}} ({\text{x)|}}^{\text{t}} $$." Approximation Theory and its Applications 8, no. 3 (September 1992): 1–10. http://dx.doi.org/10.1007/bf02836333.

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17

Yoon, Junyeon, Youngsook Huh, Insung Lee, Seulgi Moon, Hyonjeong Noh, and Jianhua Qin. "Weathering Processes in the Min Jiang: Major Elements, $$ {}^{87}{\text{Sr/}}{}^{86}{\text{Sr}},\;\delta {}^{34}{\text{S}}_{{\text{SO}}_{\text{4}} } ,\;{\text{and}}\;\delta {}^{18}{\text{O}}_{{\text{SO}}_{\text{4}} } $$." Aquatic Geochemistry 14, no. 2 (April 3, 2008): 147–70. http://dx.doi.org/10.1007/s10498-008-9030-7.

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18

J Ilumin, Reynaldo. "Explicit Instruction of Pure Text Structure: Arming Maturing Readers for Expository Science Texts." International Journal of Science and Research (IJSR) 10, no. 1 (January 27, 2021): 275–79. https://doi.org/10.21275/sr21101213911.

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19

Kant, Ravi, Kulvir Singh, and O. P. Pandey. "Structural, thermal and transport properties of $$ {\text{B}}{{\text{i}}_4}{{\text{V}}_{2 - {\text{x}}}}{\text{G}}{{\text{a}}_{\text{x}}}{{\text{O}}_{11 - \delta }} $$ (0 ≤ x ≤ 0.4)." Ionics 16, no. 3 (November 4, 2009): 277–82. http://dx.doi.org/10.1007/s11581-009-0392-7.

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20

Gordon, Cynthia. "Reshaping prior text, reshaping identities." Text & Talk - An Interdisciplinary Journal of Language, Discourse Communication Studies 26, no. 4-5 (January 1, 2006): 545–71. http://dx.doi.org/10.1515/text.2006.022.

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21

Prasad KM, Shiva, and Dr T. Hanumantha Reddy. "Text Mining: Classification of Text Documents using Granular Hybrid Classification Technique." International Journal of Research in Advent Technology 7, no. 6 (July 10, 2019): 1–8. http://dx.doi.org/10.32622/ijrat.76201910.

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22

Pathak, Rajesh, and Ravi Kumar Tewari. "Distinction between Machine Printed Text and Handwritten Text in a Document." International Journal of Scientific Engineering and Research 3, no. 7 (July 27, 2015): 13–17. https://doi.org/10.70729/ijser15298.

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23

Neha K, Shah. "Introduction of Text mining and an Analysis of Text mining Techniques." Paripex - Indian Journal Of Research 2, no. 2 (January 15, 2012): 56–57. http://dx.doi.org/10.15373/22501991/feb2013/18.

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24

Jingyan, Ma. "Poster as polycode small-format text." Bulletin of the Donetsk National University. Series D: Philology and Psychology 3 (April 29, 2025): 81–91. https://doi.org/10.5281/zenodo.15301482.

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The work considers the poster as a polycode small-format text with a modular structure. The poster is a complex dynamic system that includes hierarchies of codes of the addresser, the addressee, the national language and individual speech features. The results emphasize that the poster is characterized by the combination of different linguistic codes and non-linguistic visual elements such as iconic signs, images, graphic forms and color solutions. These components enhance the impact of the verbal code and increase the expressiveness of the poster. A special attention is paid to modularity as the key parameter of poster polycode phenomenon. The modular structure is expressed through composition, the use of backgrounds and frames, and the interaction of visual and verbal elements. Frame borders play an important role in the modular non-verbal and verbal components, ensuring the structural integrity and functionality of the poster.

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25

Brodić, Darko, Dragan R. Milivojević, and Zoran Milivojević. "Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction." Sensors 10, no. 5 (May 25, 2010): 5263–79. http://dx.doi.org/10.3390/s100505263.

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26

Supeno and Suseno Imam. "Anxiety contribution on students' text comprehension in various test types." Journal of Education and Learning (EduLearn) 14, no. 2 (May 1, 2020): 248–54. https://doi.org/10.11591/edulearn.v14i2.14258.

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This study aims to understand how anxiety as a variable contributes to affect the ability in comprehending English texts evaluated on students’ performance on various test types, namely 1) multiple-choice tests (MC), 2) fill-in-the-blank tests (FTB), and 3) true/false tests (TF). This research used ex post facto method, with responses collected from eleventh grade high school students in Jakarta. Respondents worked on tests with similar material, although at different times. Students’ anxiety was measured based on behavioral and cognitive characteristics listed on the questionnaire given to respondents along with the English test. The results pointed out that there was indeed a difference of students’ anxiety levels in working on the various English text comprehension tests given. The results of the English text comprehension tests were generally influenced by the anxiety variable, although the effect was found to be small. Teachers are recommended to apply multiple variations of ability evaluation in measuring the students’ English text comprehension by using multiple test modes.

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27

Sodiqova, Yulduz Furqatovna. "LITERARY TEXT AS AN OBJECT OF LINGUISTIC RESEARCH AND THE PROBLEM OF ITS INTERPRETATION." International journal of word art 5, no. 3 (June 14, 2022): 134–37. https://doi.org/10.5281/zenodo.6642870.

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This article is devoted to the concept of the text, its main functions and main features, as well as the problem of its interpretation. The text is a multidimensional linguistic unit, the definition of which is not unanimous among linguists, which is a serious problem in any modern linguistic research, and the analysis of the text, especially the literary text. This article discusses several approaches to the problem presented of particular interest in linguistic analysis, is the fact that the literary text has a number of distinctive features that distinguish it from the real text. Thanks to modern methods of text linguistics, it will also be possible to combine research methods in combining different branches of linguistics, including stylistics, the theory of speech acts, as well as related disciplines such as philosophy and psychology, the development of a complex system, the main purpose of which is an in-depth and detailed analysis of a complex language unit such as text.

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Bracisiewicz, Klaudia. "Text usability test of French braid instructions." Oblicza Komunikacji 11 (April 7, 2021): 223–34. http://dx.doi.org/10.19195/2083-5345.11.14.

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Usable texts should be extremely clear and functional. The present article focuses on instructions as a genre. Using French braid instructions as an example, the author presents how the form and layout of a text influence its usability. To this end an experiment was conducted on a sample of 32 individuals. The subjects received four versions of the same instructions — in the form of continuous text, in the form of continuous text with fragments in bold type, bullet point instructions and bullet point instructions with illustrations. The objective was to compare various forms of instructions (a form of text often used in everyday life, the clarity of which should consequently be as high as possible) in order to test their usability.

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Kang, YannaShen, and Mehmet Kayaalp. "Extracting laboratory test information from biomedical text." Journal of Pathology Informatics 4, no. 1 (2013): 23. http://dx.doi.org/10.4103/2153-3539.117450.

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30

Syrdal, Ann K., and Beki A. Sciacca. "A diagnostic text‐to‐speech intelligibility test." Journal of the Acoustical Society of America 94, no. 3 (September 1993): 1842–43. http://dx.doi.org/10.1121/1.407715.

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31

Collins, W. Matthew, and Betty Ann Levy. "Text repetition and text integration." Memory & Cognition 35, no. 7 (October 2007): 1557–66. http://dx.doi.org/10.3758/bf03193490.

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32

Lotman, Yury M., Jerry Leo, and Amy Mandelker. "The Text within the Text." PMLA 109, no. 3 (May 1994): 377. http://dx.doi.org/10.2307/463074.

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33

Fabião, Eleonora. "Call Me Text, Just Text*." Studies in Gender and Sexuality 19, no. 1 (January 2, 2018): 55–68. http://dx.doi.org/10.1080/15240657.2018.1421304.

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34

Anhalt, Istvan. "Music: context, text, counter-text." Contemporary Music Review 5, no. 1 (January 1989): 101–35. http://dx.doi.org/10.1080/07494468900640571.

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35

Cardwell, Richard A. "Byron: Text and counter‐text." Renaissance and Modern Studies 32, no. 1 (January 1988): 6–23. http://dx.doi.org/10.1080/14735788809366514.

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36

Lokendra, Singh Banafar, and Lalita Gupta Dr. "Text Detection from Natural Images using MSER Algorithm." International Journal of Trend in Scientific Research and Development 2, no. 3 (April 2, 2018): 73–81. https://doi.org/10.31142/ijtsrd10806.

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In present daily life text plays an important role in daily life because of its rich information that is why automatic text detection in natural images has many applications. But detecting the text from natural image is always a challenging problem. Due to the presence of variation in the background and as the size of the text also not fixed in case of natural images it is very difficult to identify the text accurately. Through tremendous efforts have recently been devoted in this research but still reading texts in unconstrained environment is still challenging and remain a problem. Today text detection finds many applications in various fields, including visual impairment assistance, tourist assistance, content based image retrieval and unmanned ground vehicle navigation. Today most of the images are taken from the camera and other handhold devices which are not fixed and sometimes due to the movement of the object the problem of blurring is observed which makes it even more difficult to detect the text from natural images. Here in this thesis an idea is proposed to detect and recognize the text contains in the image as the main problem in Computer vision is to separate the text from the background components. There are many methods which are still used to detect the text from the natural scene such as text detection using edge analysis, robust text detection, Real time text tracking, but none of them is promising. In this paper text detection is carried by using canny edge detection algorithm and MSER based method along with the image enhancement which results in the improved performance in terms of text detection. In addition, we improve current MSERs by developing a contrast Enhancement mechanism that enhances region stability of text patterns.to remove the blurring caused during the capture of image Lucy Richardson de blurring Algorithm is used. Lokendra Singh Banafar | Dr. Lalita Gupta "Text Detection from Natural Images using MSER Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: https://www.ijtsrd.com/papers/ijtsrd10806.pdf

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37

Heo, Jongkook, Sae Rin Lim, Sihu Ahn, Jinhyeok Park, Young Jae Lee, Yongwon Jo, Chunghyup Mok, Junho Cho, and Seoung Bum Kim. "Text-to-Text Multi-Task Learning to Generate Battlefield Situation Awareness Report." Journal of the Korean Institute of Industrial Engineers 48, no. 6 (December 15, 2022): 603–14. http://dx.doi.org/10.7232/jkiie.2022.48.6.603.

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38

Jiang, Lipeng, Xiyan Zhang, Chengli Wang, He Tang, Shiqi Zhu, Qingxi Li, Xiaoyun Mi, and Liping Lu. "Luminescence and energy transfer of Sm3+-codoped $${{\text{Y}}_{2.9}}{\text{A}}{{\text{l}}_{4.25}}{\text{G}}{{\text{a}}_{0.75}}{{\text{O}}_{12}}:{\text{Ce}}_{{0.1}}^{{3+}}$$ phosphor." Journal of Materials Science: Materials in Electronics 28, no. 24 (September 9, 2017): 18898–902. http://dx.doi.org/10.1007/s10854-017-7843-0.

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39

С., П. Галаур. "ТАКСОНОМІЯ КАТЕГОРІЙ ХУДОЖНЬОГО ТЕКСТУ-ДИСКУРСУ". Лінгвістичні дослідження: Зб. наук. праць ХНПУ ім. Г.С. Сковороди, № 46 (14 листопада 2017): 146–53. https://doi.org/10.5281/zenodo.1048781.

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<em>The re-interpretation</em> <em>of communication phenomenon, claiming “to other” focus to be the prerogative, causes consecutive refusal of text’s traditional consideration. The latter is being expounded as empirical substance and real material manifestation of speakers communication intentions as well as their mental universes’ interaction. This way of approach opens further perspective to define artistic text categories’ taxonomy more precisely; the text likewise remains hyponymically-hyperonically connected to the artistic discourse, being its constitutive substratum. The artistic text represents totality of categories of the certain type of correlation, synchronized within three dimensions; their parameters depend upon anthropocentric inclusiveness degree. The fact is the text category integrates certain set of the most important text characteristic features and gets evaluation due to its field structure, two-dimensions’ construction, and functional direction. Each one of the text categories, social-semiotic and situation interactions’ result receives interpretation in accordance with the structure, semantics, also pragmatics. Therefore, syntagmatic and paradigmatic intercategorical interconnections of the text-discourse make the opportunity to accentuate on its completeness and synergy.</em>

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40

Jing, Chen, and Zhang Baolin. "Alternating band Crank-Nicolson method for $$\frac{{\partial {\text{u}}}}{{\partial {\text{t}}}} = \frac{{\partial ^2 {\text{u}}}}{{\partial {\text{x}}^{\text{2}} }} + \frac{{\partial ^2 {\text{u}}}}{{\partial {\text{y}}^{\text{2}} }}$$." Applied Mathematics-A Journal of Chinese Universities 8, no. 2 (December 1993): 150–62. http://dx.doi.org/10.1007/bf02661999.

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41

Semeniuk, Tetiana, and Yulia Gordienko. "FROM TEXT TO POLYCODE TEXT: SEMIOTIC CHANGES IN TEXT PRODUCTION." RESEARCH TRENDS IN MODERN LINGUISTICS AND LITERATURE 1 (November 22, 2018): 122–34. http://dx.doi.org/10.29038/2617-6696.2018.1.122.134.

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The article is devoted to the investigation of the linguistic notions of “text” and “polycode text”. The notion of a text has recently undergone a lot of changes in its interpretation. Nowadays, while defining of texts it has been offered to take into account different approaches to their study including not only grammatical, cognitive-semantic, communicative-pragmatic, but also semiotic and semiotic-cultural. The development of IT, the globalization, and changes in the ways of coding of information have increased the role of the semiotic approach in the interpretation of texts. Within the semiotic approach, today’s text is regarded as a set of monocode or polycode communicative resources which correlate with each other, form a complex integrative meaning and are addressed to recipients with a certain pragmatic purpose. It has been proposed to distinguish between monocode and polycode texts and to use the term “polycode” to accentuate the coexistence of two or more codes in one text space. A polycode text is regarded in the article as a coherent unit consisting of several semiotic codes: verbal, non-verbal (photographs, pictures, pictograms, ideograms, smiles, cartoons, tables), paraverbal (color, font, punctuation, layout, diacritical marks). Changes in the encoding of the information in texts and the emergence of new communicative resources have led to the necessity of the reviewing of text’s textuality. Polycoding and multimodality have been regarded in the research as standarts of textuality as well as cohesion, coherence, intentionality, acceptability, informativity, situationality and intertextuality.

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42

Oh, Takkeun, Jianlin Li, Heesung Yoon, and Eric D. Wachsman. "Stability of $$ {\text{SrCe}}_{{0.9}} {\text{Eu}}_{{0.1}} {\text{O}}_{{3 - \delta }} $$ and $$ {\text{SrZr}}_{{0.2}} {\text{Ce}}_{{0.7}} {\text{Eu}}_{{0.1}} {\text{O}}_{{3 - \delta }} $$ under H2 atmospheres." Ionics 15, no. 5 (May 22, 2009): 525–30. http://dx.doi.org/10.1007/s11581-009-0349-x.

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43

Silvia, Golubițchi. "Methodological Aspects of Multimodal Text Study in Primary School." Journal of Educational Theory and Practice DIDACTICA PRO... 23, no. 2-3 (138-139) (May 26, 2023): 57–60. https://doi.org/10.5281/zenodo.7974409.

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Multimedia means tend to have a strong impact on students. Multimodal texts are a way of using information technology in primary school, which combine two or more semiotic systems (linguistic, visual, audio, gestural, or spatial) and include several ways of representing reality, which can reach the receiver much easier and more effectively. The multimodal text highlights changes at content, didactic strategy, and goal level. Reading a multimodal text involves understanding, reception, interpretation, reflection, and evaluation, while composing one follows three stages: pre-editing, editing, and post-editing.  

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Jones, Rodney H. "The role of text in televideo cybersex." Text & Talk - An Interdisciplinary Journal of Language, Discourse Communication Studies 28, no. 4 (January 2008): 453–73. http://dx.doi.org/10.1515/text.2008.022.

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45

Ying, Yi, T. N. Mursitama, Shidarta, and Lohansen. "Effectiveness of the News Text Classification Test Using the Naïve Bayes’ Classification Text Mining Method." Journal of Physics: Conference Series 1764, no. 1 (February 1, 2021): 012105. http://dx.doi.org/10.1088/1742-6596/1764/1/012105.

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46

Pubby, Kunal, Puneet Sharma, and Sukhleen Bindra Narang. "Structural, magnetic, dielectric, microwave absorption, and optical characterization of $${\text{Ni}}_{0.1} {\text{Co}}_{0.9} \left({\text{MnZr}} \right)_{x} {\text{Fe}}_{2 - 2x} {\text{O}}_{4}/{\text{Ba}}_{y} {\text{Sr}}_{1 - y} {\text{Fe}}_{12} {\text{O}}_{19}$$ nanocomposites." Journal of Materials Science: Materials in Electronics 31, no. 1 (November 23, 2019): 599–609. http://dx.doi.org/10.1007/s10854-019-02564-7.

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47

Hasan, Ismael, Javier Parapar, and Álvaro Barreiro. "Improving the Extraction of Text in PDFs by Simulating the Human Reading Order." JUCS - Journal of Universal Computer Science 18, no. (5) (March 1, 2012): 623–49. https://doi.org/10.3217/jucs-018-05-0623.

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Text preprocessing and segmentation are critical tasks in search and text mining applications. Due to the huge amount of documents that are exclusively presented in PDF format, most of the Data Mining (DM) and Information Retrieval (IR) systems must extract content from the PDF files. In some occasions this is a difficult task: the result of the extraction process from a PDF file is plain text, and it should be returned in the same order as a human would read the original PDF file. However, current tools for PDF text extraction fail in this objective when working with complex documents with multiple columns. For instance, this is the case of official government bulletins with legal information. In this task, it is mandatory to get correct and ordered text as a result of the application of the PDF extractor. It is very usual that a legal article in a document refers to a previous article and they should be offered in the right sequential order. To overcome these difficulties we have designed a new method for extraction of text in PDFs that simulates the human reading order. We evaluated our method and compared it against other PDF extraction tools and algorithms. Evaluation of our approach shows that it significantly outperforms the results of the existing tools and algorithms.

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48

Zeitlin, Aaron. "Text." Anglican Theological Review 103, no. 4 (November 2021): 492. http://dx.doi.org/10.1177/00033286211056826.

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49

Adithan, C. "“TEXT”." Annals of SBV 5, no. 1 (2016): 4. http://dx.doi.org/10.5005/jp-journals-10085-5101.

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Temple, Wm. "Text." Irish Historical Studies 34, no. 136 (November 2005): 456–61. http://dx.doi.org/10.1017/s002112140000643x.

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Annotation:

After the Conquest of Ireland by Henry the 2nd most of the Lands in Leinster & Munster were Distributed among those English who Served in that or the Succeeding Expeditions of our Kings into Ireland. From those English were Derived most of the Great Families in Ireland: Few of the Old native Irish remaining in those provinces besides those of Bryan or Maccarty of any Great Notte or Titles.Some of the Great English Families were Generally Imployed in the Cheif Government of this Province ‘till the tyme of Henry the 7th but Cheifly those of Ormond or Kildare.

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