Search results for: text labeling

Authors: Manssour Habbash, Srinivasa Rao Idapalapati

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Although writing is a multifaceted task, teaching writing is a demanding task basically for two reasons: Grammar and Syntax. This article provides a method of teaching writing that was found to be effective in improving students’ academic writing composition skill. The article explains the concepts of ‘guided-discovery’ and ‘guided-construction’ upon which a method of teaching writing is grounded and developed. Providing a brief commentary on what the core could mean primarily, the article presents an exposition of understanding and identifying the core and building upon the core that can demonstrate the way a teacher can make use of the concepts in teaching for improving the writing skills of their students. The method is an adaptation of grammar translation method that has been improvised to suit to a student-centered classroom environment. An intervention of teaching writing through this method was tried out with positive outcomes in formal classroom research setup, and in view of the content’s quality that relates more to the classroom practices and also in consideration of its usefulness to the practicing teachers the process and the findings are presented in a narrative form along with the results in tabular form.

Keywords: core of a text, guided construction, guided discovery, theme of a text

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Authors: Olga Bernikova, Oleg Redkin

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Islamic Studies and the Arabic language are indivisible from each other starting from the appearance of Islam and formation of the Classical language. The present paper demonstrates correlation among linguistics and religion in historical perspective with regard to peculiarities of the Arabic language which distinguish it from the other prophetic languages. Islamic Studies and Linguistics are indivisible from each other starting from the invent of Islam and formation of the Classical language. In historical perspective, the Arabic language has been and remains a tool for the expression of Islamic rhetoric being a prophetic language. No other language in the world has preserved its stability for more than 14 centuries. Islam is considered to be one of the most important factors which secure this stability. The analysis and study of the text of Qurʾān are of special importance for those who study Islamic civilization, its role in the destinies of the mankind, its values and virtues. Without understanding of the polyphony of this sacred text, indivisible unity of its form and content it is impossible to understand social developments both in the present and the past. Since the first years of Islam Qurʾān had been in the center of attention of Muslim scholars, and in the center of attention of theologians, historians, philologists, jurists, mathematicians. Only quite recently it has become an object of analysis of the specialists of computer technologies. In Arabic and Islamic studies mediaeval texts i.e. textual documents are considered the main source of information. Hence the analysis of the multiplicity of various texts and finding of interconnections between them help to set scattered fragments of the riddle into a common and eloquent picture of the past, which reflects the state of the society on certain stages of its development. The text of the Qurʾān like any other phenomenon is a multifaceted object that should be studied from different points of view. As a result, this complex study will allow obtaining a three-dimensional image rather than a flat picture alone.

Keywords: Arabic, Islamic studies, linguistics, religion

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Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

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Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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Authors: Ankita Sharma

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The study proposes to review the perception of women in the Classical Age (500-336 BC) when Greek Philosophy was in bloom. It was observed that women had very few rights and were still under the control of men. One of the possible reasons for this exclusion was woman’s biology that had a huge influence on her being seen as inferior to men. The text ‘Hippocratic Corpus’ focuses on the biological construct of the female body in classical Greek science that perpetuated the idea of women as second-class citizens and were considered inherently weaker than men. The research highlights the significance of the text that was used to encourage women of that time to get married and produce children and how till today the perception remains the same. The Greek belief of need for confinement and control of 'wandering uterus' has led to superior understanding of men. The pivotal emphasis of this research is to women and their bodies that are depicted in a misogynistic way which paved the way for Hippocratic writers to influence the society’s attitude towards women in their writings. It is intended to draw attention to the prevailing cultural assumptions and preconceived notions about female anatomy that had a pervasive influence in the following centuries with its roots being in ancient science.

Keywords: classical Greek theory, women, wandering womb, modern ideology

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Authors: L. Hamsaveni, Navya Prakash, Suresha

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Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

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Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway

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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.

Keywords: steganography, stego, LSB, crop

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Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: Sharifa Alshahrani

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Comics is a multimodal text wherein meaning is created by taking in all modes of expression at once. It uses two different semiotic modes, the verbal and the visual modes, together to make meaning and these different semiotic modes can be socially and culturally shaped to give meaning. Therefore, comics translation cannot treat comics as a monomodal text by translating only the verbal mode inside or outside the speech balloons as the cultural differences are encoded in the visual mode as well. Due to the development of the internet and editing software, comics translation is not anymore confined to the publishing houses and official translation as scanlation, or the fan translation took the initiative in translating comics for being emotionally attracted to the culture and genre. Scanlation is carried out by volunteering fans who translate out of passion. However, quality is one of the debatable issues relating to scanlation and fan translation. This study will investigate how the dynamic multimodal relationship in comics is exploited and interpreted in the translation by exploring the translation strategies and procedures adopted by the publishing houses and scanlation in interpreting comics into Arabic using three analytical frameworks; cultural references model, multimodal relation model and translation strategies and procedures models.

Keywords: comics, multimodality, translation, scanlation

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Authors: Mariam Matiashvili

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Argumentation is an integral part of our daily communications - formal or informal. Argumentative reasoning, techniques, and language tools are used both in personal conversations and in the business environment. Verbalization of the opinions requires the use of extraordinary syntactic-pragmatic structural quantities - arguments that add credibility to the statement. The study of argumentative structures allows us to identify the linguistic features that make the text argumentative. Knowing what elements make up an argumentative text in a particular language helps the users of that language improve their skills. Also, natural language processing (NLP) has become especially relevant recently. In this context, one of the main emphases is on the computational processing of argumentative texts, which will enable the automatic recognition and analysis of large volumes of textual data. The research deals with the linguistic analysis of the argumentative structures of Georgian political speeches - particularly the linguistic structure, characteristics, and functions of the parts of the argumentative text - claims, support, and attack statements. The research aims to describe the linguistic cues that give the sentence a judgmental/controversial character and helps to identify reasoning parts of the argumentative text. The empirical data comes from the Georgian Political Corpus, particularly TV debates. Consequently, the texts are of a dialogical nature, representing a discussion between two or more people (most often between a journalist and a politician). The research uses the following approaches to identify and analyze the argumentative structures Lexical Classification & Analysis - Identify lexical items that are relevant in argumentative texts creating process - Creating the lexicon of argumentation (presents groups of words gathered from a semantic point of view); Grammatical Analysis and Classification - means grammatical analysis of the words and phrases identified based on the arguing lexicon. Argumentation Schemas - Describe and identify the Argumentation Schemes that are most likely used in Georgian Political Speeches. As a final step, we analyzed the relations between the above mentioned components. For example, If an identified argument scheme is “Argument from Analogy”, identified lexical items semantically express analogy too, and they are most likely adverbs in Georgian. As a result, we created the lexicon with the words that play a significant role in creating Georgian argumentative structures. Linguistic analysis has shown that verbs play a crucial role in creating argumentative structures.

Keywords: georgian, argumentation schemas, argumentation structures, argumentation lexicon

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Authors: Slwa Al-Hammad

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Adaptation studies have been closely aligned to translation studies as both deal with the process of rendering the meaning from one culture to another. These two disciplines are related to each other, but the theories are still being developed. This research aims to fill this gap and provide a contribution to the growing discipline of adaptation studies through a theoretical perspective while investigating how different cultural interpretations of adaptation influence the final literary product. This research focuses on the theoretical concepts of Barthes’s death of the author and Benjamin’s afterlife of the text in translation, which is believed to lead to the birth of the adapter in a literary work. That is, in adaptation, the ‘death’ of the author allows for the ‘birth’ of the adapter, offering them all the creative possibilities of authorship. It also explores the differences between the meanings of adaptation in the West and the Arab world through the analysis of adapted texts in Arabic initially deriving from the European and American literature of the 19th and 20th centuries. The methodology of this thesis is based upon qualitative literary analysis, in which original and adapted works are compared and contrasted, with the additional insights of literary and adaptation theories and prior scholarship. The main works discussed are the Arabic adaptations of William Faulkner’s novels. The analysis is guided by theories of adaptation studies to help in explaining the concepts of relocating, recreating, and rewriting in the process of adaptation. It draws on scholarship on adaptations to inquire into the status of the adapted texts in relation to the original texts. Also, these theories prove that adaptation is the process that is used to transfer text from source to adapted text, not some other analytical practice. Through the textual analysis, concepts of the death of the author and the birth of the adapter will be illustrated, as will the roles of the adapter and the task of rendering works for a different culture, and the understanding of adaptation and Arabization in Arabic literature.

Keywords: adaptation, Arabization, authorship, recreating, relocating

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Authors: Mark Herman Sumagang Potoy

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State of the City Address (SOCA) is a speech, modelled after the State of the Nation Address, given not as mandated by law but usually a matter of practice or tradition delivered before the chief executive’s constituents. Through this, the general public is made to know the performance of the local government unit and its agenda for the coming year. Therefore, it is imperative for SOCAs to clearly convey its message and carry out the myriad function of enlightening its readers which could be achieved through the proper use of reference. Anaphora and cataphora are the two major types of reference; the former refer back to something that has already been mentioned while the latter points forward to something which is yet to be said. This paper seeks to identify the types of reference employed on the SOCAs from 2014 to 2016 of Hon. Rosalina Garcia Jalosjos, Mayor of Dapitan City and look into how the references contribute to the clarity of the message of the text. The qualitative method of research is used in this study through an in-depth analysis of the corpus. As soon as the copies of the SOCAs are secured from the Office of the City Mayor, they are then analyzed using documentary technique categorizing the types of reference as to anaphora and cataphora, counting each of these types and describing the implications of the dominant types used in the addresses. After a thorough analysis, it is found out that the two reference types namely, anaphora and cataphora are both employed on the three SOCAs, the former being used more frequently than the latter accounting to 80% and 20% of actual usage, respectively. Moreover, the use of anaphors and cataphora on the three addresses helps in conveying the message clearly because they primarily become aids to avoid the repetition of the same element in the text especially when there wasn’t a need to emphasize a point. Finally, it is recommended that writers of State of the City Addresses should have a vast knowledge on how reference should be used and the functions they take in the text since this is a vital tool to clearly transmit a message. Moreover, English teachers should explicitly teach the proper usage of anaphora and cataphora, as instruments to develop cohesion in written discourse, to enable students to write not only with sense but also with fluidity in tying utterances together.

Keywords: anaphora, cataphora, reference, State of the City Address

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Francis Alterado, Jennifer Enriquez

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Semantic Based Analysis in Complaint Management System with Analytics is an enhanced tool of providing complaints by the clients as well as a mechanism for Palawan Polytechnic College to gather, process, and monitor status of these complaints. The study has a mobile application that serves as a remote facility of communication between the students and the school management on the issues encountered by the student and the solution of every complaint received. In processing the complaints, text mining and clustering algorithms were utilized. Every module of the systems was tested and based on the results; these are 100% free from error before integration was done. A system testing was also done by checking the expected functionality of the system which was 100% functional. The system was tested by 10 students by forwarding complaints to 10 departments. Based on results, the students were able to submit complaints, the system was able to process accordingly by identifying to which department the complaints are intended, and the concerned department was able to give feedback on the complaint received to the student. With this, the system gained 4.7 rating which means Excellent.

Keywords: technology adoption, emerging technology, issues challenges, algorithm, text mining, mobile technology

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Authors: C. Brierley, H. El-Farahaty, A. Farhan

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The Leeds Parallel Corpus of Arabic-English Constitutions is a parallel corpus for the Arabic legal domain. Analysis of legal language via Corpus Linguistics techniques is an important development. In legal proceedings, a corpus-based approach to disambiguating meaning is set to replace the dictionary as an interpretative tool, and legal scholarship in the States is now attuned to the potential for Text Analytics over vast quantities of text-based legal material, following the business and medical industries. This trend is reflected in Europe: the interdisciplinary research group in Computer Assisted Legal Linguistics mines big data collections of legal and non-legal texts to analyse: legal interpretations; legal discourse; the comprehensibility of legal texts; conflict resolution; and linguistic human rights. This paper focuses on ‘dignity’ as an important aspect of the overarching concept of human rights in current constitutions across the Arab world. We have compiled a parallel, Arabic-English raw text corpus (169,861 Arabic words and 205,893 English words) from reputable websites such as the World Intellectual Property Organisation and CONSTITUTE, and uploaded and queried our corpus in Sketch Engine. Our most challenging task was sentence-level alignment of Arabic-English data. This entailed manual intervention to ensure correspondence on a one-to-many basis since Arabic sentences differ from English in length and punctuation. We have searched for morphological variants of ‘dignity’ (رامة ك, karāma) in the Arabic data and inspected their English translation equivalents. The term occurs most frequently in the Sudanese constitution (10 instances), and not at all in the constitution of Palestine. Its most frequent collocate, determined via the logDice statistic in Sketch Engine, is ‘human’ as in ‘human dignity’.

Keywords: Arabic constitution, corpus-based legal linguistics, human rights, parallel Arabic-English legal corpora

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Authors: Ameen Alahdal

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This paper investigates copular constructions in Raimi Yemeni Arabic (RYA). The aim of the paper is actually twofold. First it explores the types of copular constructions in Raimi Yemeni Arabic, a variety of Arabic that has not attracted a lot of attention. In this connection, the paper shows that RYA manifests ‘bare’, verbal and pronominal/PRON copular constructions, just like other varieties of Arabic and indeed other Semitic languages like Hebrew. The sentences below from RYA represent the three constructions, respectively. (1) a. nada Hilwah Nada pretty.3sf ‘Nada is pretty’ b. kan al-banat hina was the-girls here ‘The girls were here c. ali hu-l mudiir Ali he-the manager ‘Ali is the manager’ Interestingly, in addition to these common types of copular constructions, RYA seems to exhibit dual copula sentences, a construction that features both a pronominal copula and a verbal copula. Such a construction is attested neither in Standard Arabic nor in other modern varieties of Arabic such as Lebanese, Moroccan, Egyptian, Jordanian. Remarkably, dual copular sentences do not appear even in other dialects of Yemeni Arabic such as Sanaani, Adeni and Tehami. (2) is an example. (2) maha kan-ih mudarrisah maha was-she teacher.3sf ‘Maha was a teacehr’ Second, the paper considers the cartography of subject positions in copular constructions proposed by Shlonsky and Rizzi (2018). Different copular constructions seem to involve different subject positions (which might eventually correlate with different interpretations – not our concern in this paper). Here, it is argued that in a bare copular sentence, as in (1a), RYA might exploit two criterial subject positions (in Rizzi’s sense), in addition to the canonical Spec,TP position. Under mainstream minimalist assumption, a copular sentence is analyzed as a PredP. Thus, in addition to the PredP-related thematic subject position, a criterial subject position is posited outside of PredP. (3) below represents the cartography of subject positions in a bare copular construction. (3) [……..DP subj PredP DP Pred DP/AP/PP ] In PRON sentences, as exemplified in (1c), another two subject positions are postulated high in the clause, particularly above PolP. (4) illustrates the hierarchy of the subject positions in a PRON copular construction. The subject resides in Spec,SUBJ2P. (4) …DP SUBJ2 …DP SUBJ1 … Pol … DP subj PredP Another related phenomenon in RYA which sets it apart from other languages like Hebrew is that of negative bare copular construction. This construction involves a PRON, which is not found in its affirmative counterpart. PRON, however, is hosted neither by SUBJ20 nor by SUBJ10. Rather, PRON occurs below Neg0 (Pol0 in the hierarchy). This situation raises interesting issues for the hierarchy of subjects in copular constructions as well as to the syntax of the left periphery in general. With regard to what causes the subject to move, there are different potential triggers. For instance, movement of the subject at the base, i.e., out of PredP is triggered by a labeling failure. Other movements of the subject can be driven by a formal feature like EPP, or a criterial feature like [subj].

Keywords: Yemeni Arabic, copular constructions, cartography of subjects, labeling, criterial positions

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Authors: Shatha Khuzaee

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The study develops multimodal stylistic approach to analyse a number of BBC online news articles reporting some key events from the so called ‘Arab Uprisings’. Critical stylistics (CS) and visual grammar (VG) provide insightful arguments to the ways ideology is projected through different verbal and visual modes, yet they are mode specific because they examine how each mode projects its meaning separately and do not attempt to clarify what happens intersemiotically when the two modes co-occur. Therefore, it is the task undertaken in this research to propose multimodal stylistic approach that addresses the issue of ideology construction when the two modes co-occur. Informed by functional grammar and social semiotics, the analysis attempts to integrate three linguistic models developed in critical stylistics, namely, transitivity choices, prioritizing and hypothesizing along with their visual equivalents adopted from visual grammar to investigate the way ideology is constructed, in multimodal text, when text/image participate and interrelate in the process of meaning making on the textual level of analysis. The analysis provides comprehensive theoretical and analytical elaborations on the different points of integration between CS linguistic models and VG equivalents which operate on the textual level of analysis to better account for ideology construction in news as non-literary multimodal texts. It is argued that the analysis well thought out a plan that would remark the first step towards the integration between the well-established linguistic models of critical stylistics and that of visual analysis to analyse multimodal texts on the textual level. Both approaches are compatible to produce multimodal stylistic approach because they intend to analyse text and image depending on whatever textual evidence is available. This supports the analysis maintain the rigor and replicability needed for a stylistic analysis like the one undertaken in this study.

Keywords: multimodality, stylistics, visual grammar, social semiotics, functional grammar

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Authors: Makhim Artikova, Shavkat Duschanov

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So far, there have been a plethora of attempts to improve learners’ academic writing skills. However, this issue remains to be a real concern among the majority of students, especially those who are standing on their academic life threshold. The purpose of this research is improving students’ academic writing skills through 'Questions and Answer Reading' activities. Using well-prepared and well-chosen reading materials (from textbooks, scientific journals, or magazines) and applying questions and answer activities in the classroom facilitate learners to become great critical readers. Furthermore, it boosts their writing skills, which are the most crucial part of students’ personal and academic developments. In this activity, the class is divided into small groups of four. Then, the instructor will give students whether one section of the text or full text asking them to read and to find unfamiliar words within the group. After discovering the meaning of unknown words, each group has to share their findings with the class. In the next stage of the activity, students should be asked to create questions in a group based on the given reading material. Follow by each group should ask the other groups their questions which are an excellent opportunity to challenge leads to improve critical thinking skills. In the last part, the students are asked to write the text or article summary, which is the activity core that pilots to the writing skills perfection. This engaging activity highlights the effectiveness of incorporating reading materials into the classroom when it comes to improving students’ composition writings. Structural writing after every reading activity resulted in improving students’ coherence and cohesion in writing well-organized essays. Having experimented with high school 9th and 11th-grade students, implementing reading activities into the classroom is proved to be a productive tool to enhance one’s academic writing skills. In the future, this method planning to be implemented among university students.

Keywords: academic writing, coherence and cohesion, questions and answer activities, scientific reading

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Authors: Lutendo Nendauni

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Colonialism breaks things, colonisers exploded native cultural solidarity, producing the spiritual confusion, psychic wounding, and economic exploitation of a new and dominated ‘other’. Colonialism as the cultural and economic exploitation began when the West defended in their seizure of foreign territories for the exploitation of its natural resources; this resulted in brutal socio-economic imbalances. The Western profited at the detriment of the weak Africa. However, colonialism has since passed, but the effects are still evident culturally, socially, and economically. This paper explored how postcolonial writers and critics attempt to reverse the socio-economic imbalances resulting from the fragmentation of colonialism, with a focus on the play 'I will Marry When I Want' by Ngugi wa Thiong’o and Ngugi wa Mirii, as a primary text. Using qualitative discourse-textual analysis as the research methodology, the researcher purposively extracts discourse segments from the text for analysis and interpretation. The findings reveal that Postcolonial critics and writers attempt to reverse the socio-economic effects of colonialism through various counter discourses; their literature is concerned with the destruction of colonised identity, the search for this identity, and its assertion. It is manifest in the text that writers offer corrective views about Africans; they stress that they write their literary texts to conscientise their fellow Africans. Postcolonial writers and critics argue that language is a carrier of culture and that the only way to break free from colonial influence is by not adopting a foreign language. They further through their poems, novels, plays, and music strategically shine the spotlight on the previously nameless and destitute people so that they can develop the human spirit’s desire to overcome defeat, socio-political deprivation, and isolation.

Keywords: colonialism, postcoloniality, critics, socio-economic imbalances

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Authors: Slava Kalyuga, Sujanya Sombatteera

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In multimedia learning, written text is often transformed into spoken (narrated) text. This transient information may overwhelm limited processing capacity of working memory and inhibit learning instead of improving it. The paper reviews recent empirical studies in modality and verbal redundancy effects within a cognitive load framework and outlines conditions under which negative effects of transiency may occur. According to the modality effect, textual information accompanying pictures should be presented in an auditory rather than visual form in order to engage two available channels of working memory – auditory and visual - instead of only one of them. However, some studies failed to replicate the modality effect and found differences opposite to those expected. Also, according to the multimedia redundancy effect, the same information should not be presented simultaneously in different modalities to avoid unnecessary cognitive load imposed by the integration of redundant sources of information. However, a few studies failed to replicate the multimedia redundancy effect too. Transiency of information is used to explain these controversial results.

Keywords: cognitive load, transient information, modality effect, verbal redundancy effect

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Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

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Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

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Authors: Minh Huynh, Aaron Heuser, Luke Patterson, Chris Zhang, Mason Miller, Daniel Wang, Sandeep Shetty, Mike Trinh, Abigail Miller, Adaeze Enekwechi, Tenille Daniels, Lu Huynh

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Machine learning and text analytics have been used to analyze child abuse, cyberbullying, domestic abuse and domestic violence, and hate speech. However, to the authors’ knowledge, no research to date has used these methods to study elder abuse in nursing homes or skilled nursing facilities from field inspection reports. We used machine learning and text analytics methods to analyze 356,000 inspection reports, which have been extracted from CMS Form-2567 field inspections of US nursing homes and skilled nursing facilities between 2016 and 2021. Our algorithm detected occurrences of the various types of abuse, including physical abuse, psychological abuse, verbal abuse, sexual abuse, and passive and active neglect. For example, to detect physical abuse, our algorithms search for combinations or phrases and words suggesting willful infliction of damage (hitting, pinching or burning, tethering, tying), or consciously ignoring an emergency. To detect occurrences of elder neglect, our algorithm looks for combinations or phrases and words suggesting both passive neglect (neglecting vital needs, allowing malnutrition and dehydration, allowing decubiti, deprivation of information, limitation of freedom, negligence toward safety precautions) and active neglect (intimidation and name-calling, tying the victim up to prevent falls without consent, consciously ignoring an emergency, not calling a physician in spite of indication, stopping important treatments, failure to provide essential care, deprivation of nourishment, leaving a person alone for an inappropriate amount of time, excessive demands in a situation of care). We further compare the prevalence of abuse before and after Covid-19 related restrictions on nursing home visits. We also identified the facilities with the most number of cases of abuse with no abuse facilities within a 25-mile radius as most likely candidates for additional inspections. We also built an interactive display to visualize the location of these facilities.

Keywords: machine learning, text analytics, elder abuse, elder neglect, nursing home abuse

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Authors: Khan Farhan Rafat, M. Junaid Hussain

Abstract:

Seamless modification of an entity for the purpose of hiding a message of significance inside its substance in a manner that the embedding remains oblivious to an observer is known as steganography. Together with today's pervasive registering frameworks, steganography has developed into a science that offers an assortment of strategies for stealth correspondence over the globe that must, however, need a critical appraisal from security breach standpoint. Microsoft Word is amongst the preferably used word processing software, which comes as a part of the Microsoft Office suite. With a user-friendly graphical interface, the richness of text editing, and formatting topographies, the documents produced through this software are also most suitable for stealth communication. This research aimed not only to epitomize the fundamental concepts of steganography but also to expound on the utilization of Microsoft Word document as a carrier for furtive message exchange. The exertion is to examine contemporary message hiding schemes from security aspect so as to present the explorative discoveries and suggest enhancements which may serve a wellspring of information to encourage such futuristic research endeavors.

Keywords: hiding information in plain sight, stealth communication, oblivious information exchange, conceal, steganography

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Authors: Da Tao, Mingfu Qin, Wenkai Li, Tieyan Wang

Abstract:

While the use of electronic personal health portals has gained increasing popularity in the healthcare industry, users usually experience difficulty in comprehending and correctly responding to personal health information, partly due to inappropriate or poor presentation of the information. The way personal health information is visualized may affect how users perceive and assess their personal health information. This study was conducted to examine the effects of information visualization format and visualization mode on the comprehension and perceptions of personal health information among personal health information users with eye tracking techniques. A two-factor within-subjects experimental design was employed, where participants were instructed to complete a series of personal health information comprehension tasks under varied types of visualization mode (i.e., whether the information visualization is static or dynamic) and three visualization formats (i.e., bar graph, instrument-like graph, and text-only format). Data on a set of measures, including comprehension performance, perceptions, and eye movement indicators, were collected during the task completion in the experiment. Repeated measure analysis of variance analyses (RM-ANOVAs) was used for data analysis. The results showed that while the visualization format yielded no effects on comprehension performance, it significantly affected users’ perceptions (such as perceived ease of use and satisfaction). The two graphic visualizations yielded significantly higher favorable scores on subjective evaluations than that of the text format. While visualization mode showed no effects on users’ perception measures, it significantly affected users' comprehension performance in that dynamic visualization significantly reduced users' information search time. Both visualization format and visualization mode had significant main effects on eye movement behaviors, and their interaction effects were also significant. While the bar graph format and text format had similar time to first fixation across dynamic and static visualizations, instrument-like graph format had a larger time to first fixation for dynamic visualization than for static visualization. The two graphic visualization formats yielded shorter total fixation duration compared with the text-only format, indicating their ability to improve information comprehension efficiency. The results suggest that dynamic visualization can improve efficiency in comprehending important health information, and graphic visualization formats were favored more by users. The findings are helpful in the underlying comprehension mechanism of visualized personal health information and provide important implications for optimal design and visualization of personal health information.

Keywords: eye tracking, information comprehension, personal health information, visualization

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Authors: Laidson P. Gomes, Cristina T. Andrade, Eduardo M. Del Aguila, Cameron Alexander, Vânia M. F. Paschoalin

Abstract:

Chitosan is a natural polysaccharide prepared by the N-deacetylation of chitin. In this study, the physicochemical and antibacterial properties of chitosan nanoparticles, produced by ultrasound irradiation, were evaluated. The physicochemical properties of the nanoparticles were determined by dynamic light scattering and zeta potential analysis. Chitosan nanoparticles inhibited the growth of E. coli. The minimum inhibitory concentration (MIC) values were lower than 0.5 mg/mL, and the minimum bactericidal concentration (MBC) values were similar or higher than MIC values. Confocal laser scanning micrographs (CLSM) were used to observe the interaction between E. coli suspensions mixed with FITC-labeled chitosan polymers and nanoparticles.

Keywords: chitosan nanoparticles, dynamic light scattering, zeta potential, confocal microscopy, antibacterial activity

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Authors: Sara Sharifi Yazdi

Abstract:

The main purpose of this study is to find out about the reasons and the ways of middle-class married women betrayal via their living world. This is qualitative research, so deep semi-structured, episodic interview techniques and observation techniques were used to collect data; meanwhile, the basic theory method was used to analyze the data. The sample in this research includes 34 women with emotional and sexual relationships out of marriage. The results indicate that some set of conditions created the first spark of change in their opinions. These changes are empowered through both experiences of tolerance and exclusion, so strategies such as distance, compulsive tolerance, counteract, etc. have been used for reacting by the people in this study; besides some of the other consequences of betrayal which can be named are lack of comfort, feeling of deprivation, violence, labeling, guilty feelings of grief, and so on.

Keywords: living world, rejection, admission, betrayal, sexual relationship, marriage

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

Abstract:

Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

Abstract:

Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Mingshu Liu, Laura Santamaria, Xavier Carmaniu Mainadé

Abstract:

As one of the sectors most affected by the COVID-19 pandemic, tourism is facing challenges in revitalizing the industry. But at the same time, it would be a good opportunity to take advantage of digital communication as an effective tool for tourism promotion. Our proposal aims to verify the linguistic operations on online platforms in China. The research is carried out based on the theory of Eco-traductology put forward by Gengshen Hu, whose contribution focuses on the translator's adaptation to the ecosystem environment and the three elaborated parameters (linguistic, cultural and communicative). We also relate it to Even-Zohar's and Toury's theoretical postulates on the Polysystem to elaborate on interdisciplinary methodology. Such a methodology allows us to analyze personal treatments and phraseology in the target text. As for the corpus, we adopt the official Spanish-language website of Turismo de España as the source text and the postings on the two major social networks in China, Weibo and Wechat, in 2019. Through qualitative analysis, we conclude that, in the tourism advertising campaign on Chinese social networks, chengyu (Chinese phraseology) and honorific titles are used very frequently.

Keywords: digital communication, eco-traductology, polysystem theory, tourism advertising

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