Search results for: text processing

Authors: Zeineb Ben Azzouz, Wahiba Ben Abdessalem Karaa

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The automated extraction of UML class diagram from natural language requirements is a highly challenging task. Many approaches, frameworks and tools have been presented in this field. Nonetheless, the experiments of these tools have shown that there is no approach that can work best all the time. In this context, we propose a new accurate approach to facilitate the automatic mapping from textual requirements to UML class diagram. Our new approach integrates the best properties of statistical Natural Language Processing (NLP) techniques to reduce ambiguity when analysing natural language requirements text. In addition, our approach follows the best practices defined by conceptual modelling experts to determine some patterns indispensable for the extraction of basic elements and concepts of the class diagram. Once the relevant information of class diagram is captured, a XMI document is generated and imported with a CASE tool to build the corresponding UML class diagram.

Keywords: class diagram, user’s requirements, XMI, software engineering

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Sumaira Mukhtar

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The present research aims at the discussion of the subversion of the hegemony of the feminine self in the text Moth Smoke by a Pakistani novelist Mohsin Hamid. It presents the notion of the subversion of the grand narratives of the ‘positioning’ of feminine identity in Pakistani patriarchal society by presenting a de-stereotyped personality of Mumtaz, the protagonist in Moth Smoke. The dominant masculine traits in Mumtaz’s personality have been negotiated since she is an untraditional female character in the novel. In this regard, the researcher has taken a feministic stance in this study by presenting the proposition that subaltern can also speak. Mumtaz’s character reminds one of Hedda from Henrik Ibsen’s play Hedda Gabler. So, the masculine traits in Mumtaz’s personality have also been compared with Hedda’s. Besides, the research study will also bring into notice that how that in the postmodern scenario, marginalization of the women have been responded back by women and hereby Mumtaz by uplifting her social status and class. Her de-stereotyped feminine self has been reinforced by the dialogues and incidents in the text. This research is qualitative in design and is based on the textual analysis. An interpretive research method has also been utilized since the researcher has tried to decode the text in supporting the notion of de-stereotyping of feminine self. This research would add to the body of Pakistani literature and Feministic theory.

Keywords: de-stereotyped, feminine identity, marginalization, masculine traits

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: Albert Oluwole Uzodimma Authority

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Nigeria is a diverse nation with a rich cultural heritage that has produced numerous art musicians and a vast range of art songs. The compositional styles, tonal rhythm, text rhythm, word painting, and text-tone relationship vary extensively from one dialect to another, indicating the need for standardized tools for the structural and analytical deconstruction of Nigerian indigenous art music. The purpose of this research is to examine the structures of Nigerian indigenous art music and outline some crucibles for analyzing it, by investigating how dialectical inflection influences the choice of text tone, scale mode, tonal rhythm, and the general ambiance of Nigerian art music. The research used a structured questionnaire to collect data from 50 musicologists, out of which 41 responded. The study's focus was on the works of two prominent twentieth-century composers, Stephen Olusoji, and Nwamara Alvan-Ikoku, titled "Oyigiyigi" and "O Chineke, Inozikwa omee," respectively. The data collected was presented in percentages using pie charts and tables. The study shows that in Nigerian Indigenous music, several aspects are to be considered for proper analysis, such as linguistic sensitivity, dialectical inflection influences text-tone relationship, text rhythm and tonal rhythm, which help to convey the proper meanings of messages in songs. It also highlights the lack of standardized rubrics for analysis, which necessitated the proposal of robust criteria for analyzing African music, known as Neo-Eclectic-Crucibles. Hinging on eclectic approach, this research makes significant contributions to music scholarship by addressing the need for standardized tools and crucibles for the structural and analytical deconstruction of Nigerian indigenous art music. It provides a template for further studies leading to standardized rubrics for analyzing African music. This research collected data through a structured questionnaire and analyzed it using pie charts and tables to present the findings accurately. The analysis focused on the respondents' perspectives on the research objectives and structural analysis of two indigenous music compositions by Olusoji and Nwamara. This research answers the questions on the structures and analytical crucibles used in Nigerian indigenous art music, how dialectical inflection influences text-tone relationship, scale mode, tonal rhythm, and the general ambiance of Nigerian art music. This paper demonstrates the need for standardized tools and crucibles for the structural and analytical deconstruction of Nigerian indigenous art music. It highlights several aspects that are crucial to analyzing Nigerian indigenous music and proposes the Neo-Eclectic-Crucibles criteria for analyzing African music. The contribution of this research to music scholarship is significant, providing a template for further studies and research in the field.

Keywords: art-music, crucibles, dialectical inflections, indigenous, text-tone, tonal rhythm, word-painting

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Authors: M. C. Padma, R. J. Prathibha

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Parts of speech tagging is the process of assigning appropriate parts of speech tags to the words in a given text. The critical or crucial information needed for tagging a word come from its internal structure rather from its neighboring words. The internal structure of a word comprises of its morphological features and grammatical information. This paper presents a morpheme based parts of speech tagger for Kannada language. This proposed work uses hierarchical tag set for assigning tags. The system is tested on some Kannada words taken from EMILLE corpus. Experimental result shows that the performance of the proposed system is above 90%.

Keywords: hierarchical tag set, morphological analyzer, natural language processing, paradigms, parts of speech

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Authors: Muhammad Hamza

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This research is based on the effect of self-questioning strategy on reading comprehension of second language learners at medium level. This research is conducted to find out the effects of self-questioning strategy and how self-questioning strategy helps English learners to improve their reading comprehension. In this research study the researcher has analyzed that how much self-questioning is effective in the field of learning second language and how much it helps second language learners to improve their reading comprehension. For this purpose, the researcher has studied different reading strategies, analyzed, collected data from certificate level class at NUML, Peshawar campus and then found out the effects of self-questioning strategy on reading comprehension of ESL learners. The researcher has randomly selected the participants from certificate class. The data was analyzed through pre-test and post-test and then in the final stage the results of both tests were compared. After the pre-test and post-test, the result of both pre-test and post-test indicated that if the learners start to use self-questioning strategy before reading a text, while reading a text and after reading a particular text there’ll be improvement in comprehension level of ESL learners. The present research has addressed the benefits of self-questioning strategy by taking two tests (pre and post-test).After the result of post-test it is revealed that the use of the self-questioning strategy has a significant effect on the readers’ comprehension thus, they can improve their reading comprehension by using self-questioning strategy.

Keywords: strategy, self-questioning, comprehension, intermediate level ESL learner

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Fateme Montazeri

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Literary approaches towards the text of the Quran predate the modern period. Suyuti (d.1505)’s encyclopedia of Quranic sciences, Al-Itqan, provides a notable example. In the modern era, the study of the Quranic rhetorics received particular attention in the second half of the twentieth century by Egyptian scholars. Amin Al-Khouli (d. 1966), who might be considered the first to argue for the necessity of applying a literary-rhetorical lens toward the tafseer, Islamic exegesis, and his students championed the literary analysis as the most effective approach to the comprehension of the holy text. Western scholars continued the literary criticism of the Islamic scripture by applying to the Quran similar methodologies used in biblical studies. In the history of the literary examination of the Quran, the scope of the critical methods applied to the Quranic text has been limited. For, the rhetorical approaches to the Quran, in the premodern as well as the modern period, concerned almost exclusively with the lexical layer of the text, leaving the narratological dimensions insufficiently examined. Recent contributions, by Leyla Ozgur Alhassen, for instance, attempt to fill this lacunae. This paper aims at advancing the studies of the Quranic narratives by investigating the application of a literary device whose role in the Quranic stories remains unstudied, that is, “foreshadowing.” This paper shall focus on Chapter 12, “Surah al-Yusuf,” as its case study. Chapter 12, the single chapter that includes the story of Joseph in one piece, contains several instances in which the events of the story are foreshadowed. As shall be discussed, foreshadowing occurs either through a monolog or dialogue whereby one or more of the characters allude to the future happenings or through the manner in which the setting is described. Through a close reading of the text, it will be demonstrated that the usage of the rhetorical tool of foreshadowing meets a dual purpose: on the one hand, foreshadowing prepares the reader/audience for the upcoming events in the plot, and on the other hand, it highlights the psychological dimensions of the characters, their thoughts, intentions, and disposition. In analyzing the story, this study shall draw on psychoanalytical criticism to explore the layers of meanings embedded in the Quranic narrative that are unfolded through foreshadowing.

Keywords: foreshadowing, quranic narrative, literary criticism, surah yusuf

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Authors: Lynnette Lyzwinski, Liam Caffery, Matthew Bambling, Sisira Edirippulige

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Introduction: A novel method of delivering mindfulness interventions for populations at risk of weight gain and stress-related eating, in particular, college students, is through mHealth. While there have been qualitative studies on mHealth for weight loss, there has not been a study on mHealth for weight loss using mindfulness that has explored student perspectives on a student centred mindfulness app and mindfulness-based text messages for eating and stress. Student perspective data will provide valuable information for creating a specific purpose weight management app and mindfulness-based text messages (for the Mindfulness App study). Methods: A qualitative focus group study was undertaken at St Lucia campus at the University of Queensland in March 2017. Students over the age of 18 were eligible to participate. Interviews were audiotaped and transcribed. One week following the focus group, students were sent sample mindfulness-based text messages based on their responses. Students provided written feedback via email. Data were analysed using N Vivo software. Results: The key themes in a future mindfulness-based app are a simple design interface, a focus on education/practical tips, and real-life practical exercises. Social media should be avoided. Key themes surrounding barriers include the perceived difficulty of mindfulness and a lack of proper guidance or knowledge. The mindfulness-based text messages were received positively. Key themes were creating messages with practical tips about how to be mindful and how to integrate mindful reflection of both one’s body and environment while on campus. Other themes including creating positive, inspirational messages. There was lack of agreement on the ideal timing for messages. Discussion: This is the first study that explored student perspectives on a mindfulness-app and mindfulness-based text messages for stress and weight management as a pre-trial study for the Mindfulness App trial for stress, lifestyle, and weight in students. It is important to consider maximizing the potential facilitators of use and minimize potential identified barriers when developing and designing a future mHealth mindfulness-based intervention tailored to the student consumer. Conclusion: Future mHealth studies may consider integrating mindfulness-based text messages in their interventions for weight and stress as this is a novel feature that appears to be acceptable for participants. The results of this focus group provide the basis to develop content for a specific purpose student app for weight management.

Keywords: mindfulness, college students, mHealth, weight loss

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: Mona Masood, Norshazlina Shaik Othman

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The purpose of this study was to investigate graduate students’ visual attention and perceptions of a Prezi presentation. Ten post-graduate master students were presented with a Prezi presentation at the Centre for Instructional Technology and Multimedia, Universiti Sains Malaysia (USM). The eye movement indicators such as dwell time, average fixation on the areas of interests, heat maps and focus maps were abstracted to indicate the students’ visual attention. Descriptive statistics was employed to analyze the students’ perception of the Prezi presentation in terms of text, slide design, images, layout and overall presentation. The result revealed that the students paid more attention to the text followed by the images and sub heading presented through the Prezi presentation.

Keywords: eye tracking, Prezi, visual attention, visual perception

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Authors: Ogbonna Olelewe

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This quality improvement project seeks to address the background and significance of promoting antidepressant (AD) medication adherence to reduce depression symptoms in patients diagnosed with major depression. This project aims to substantiate using daily encrypted short message service (SMS) text reminders to take prescribed antidepressant medications with the goal of increasing medication adherence to reduce depression scores in patients diagnosed with major depression, thereby preventing relapses and increasing remission rates. Depression symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) scale. The PHQ-9 provides a total score of depression symptoms from mild to severe, ranging from 0 to 27. A -pretest/post-test design was used, with a convenience sample size of 35 adult patients aged 18 years old to 45 years old, diagnosed with MDD, and prescribed at least one antidepressant for one year or more. Pre- and post-test PHQ-9 scores were conducted to compare depression scores before and after the four-week intervention period. The results indicated improved post-intervention PHQ-9 scores, improved AD medication adherence, and a significant reduction in depression symptoms.

Keywords: major depressive disorder, antidepressants, short message services, text reminders, Medication adherence/non-adherence, Patient Health Questionnaire 9

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Authors: Mohsen Maraoui

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In the face of the growth in the quantity of data produced, several methods and techniques appear to remedy the problems of processing and analyzing large amounts of information mainly in the field of teaching. In this paper, we propose an intelligent cloud-based teaching system for E-learning content services. This system makes easy the manipulation of various educational content forms, including text, images, videos, 3 dimensions objects and scenes of virtual reality and augmented reality. We discuss the integration of institutional and external services to provide personalized assistance to university members in their daily activities. The proposed system provides an intelligent solution for media services that can be accessed from smart devices cloud-based intelligent service environment with a fully integrated system.

Keywords: cloud computing, e-learning, indexation, IoT, learning in Arabic language, smart tools

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Authors: Xueying Li

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Different from English, it is common to observe Chinese clauses logically related in an implicit way without any conjunctions. This typological difference has posed a great challenge for Chinese-English translators, as 1) translators may interpret logical meaning in different ways when there are no conjunctions in Chinese Source Text (ST); 2) translators may have questions whether to make Chinese implicit logical meaning explicit or to remain implicit in Target Text (TT), and whether other dimensions of logical meaning (e.g., type of logical meaning) should be shifted or not. Against this background, this study examines a comprehensive arrange of Chinese-English translation choices of logical meaning to deal with this challenge in a systematic way. It compiles several ST-TT passages from a set of translation textbooks in a corpus, namely Ying Yu Bi Yi Shi Wu (Er Ji)) [Translation Practice between Chinese and English: Intermediate Level] and its supportive training book, analyzes how logical meaning in ST are translated in TT in texts across different text types with Systemic Functional Linguistics (SFL) as the theoretical framework, and finally draws a system network of translation choices of logical meaning from Chinese into English. Since translators may probably think about semantic meaning rather than lexico-grammatical resources in translation, this study goes away from traditional lexico-grammatical choices, but rather describing translation choices from the semantic level. The findings in this study can provide some help and support for translation practitioners so that they can understand that besides explicitation, there are a variety of possible linguistic choices available for making informed decisions when translating Chinese logical meaning into English.

Keywords: Chinese-English translation, logical meaning, systemic functional linguistics, translation choices

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: document analysis, sentimental analysis, emotion detection, WEKA tool, NRC lexicon

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Authors: M. Kustyawati, F. Pratama, D. Saputra, A. Wijaya

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Tempe composes of not only molds but also bacteria and yeasts. The structure of microorganisms needs to be in balance number in order the tempe to be an acceptable quality for an extended time. Sub supercritical carbon dioxide can be a promising preservation method for tempe as it induces microbial inactivation avoiding alterations of its quality attributes. Fresh tempe were processed using supercritical and sub supercritical CO2 for a defined holding times, then the growth ability of molds and bacteria were analyzed. The results showed that the supercritical CO2 processing for 5 minutes reduced the number of bacteria and molds to 0.30 log cycle and 1.17 log cycles, respectively. In addition, sub supercritical CO2 processing for 20 minutes had fungicidal effect against mold tempe; whereas, the sub supercritical CO2 for 10 minutes had reducing effect against bacteria tempe, and had fungistatic affect against mold tempe. It suggested that sub-supercritical CO2 processing for 10 min could be useful alternative technique for preservation of tempe.

Keywords: tempe, sub supercritical CO2, fungistatic effect, preservation

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Arkadiusz Adam Gardaś

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In his theory of gaps, Wolfgang Iser states that literary texts often lack direct messages. Instead of using straightforward descriptions, authors leave the gaps or blanks, i.e., the spaces within the text that come into existence only when readers fill them with their understanding and experiences. This paper’s aim is to present Iser’s literary theory in an intersectional way by comparing it to the idea of intersemiotic translation. To be more precise, the author uses the example of Netflix’s adaption of Lucy Maud Montgomery’s Anne of Green Gables as a form of rendering a book into a film in such a way that certain textual gaps are filled with film images. Intersemiotic translation is a rendition in which signs of one kind of media are translated into the signs of the other media. Film adaptions are the most common, but not the only, type of intersemiotic translation. In this case, the role of the translator is taken by a screenwriter. A screenwriter’s role can reach beyond the direct meaning presented by the author, and instead, it can delve into the source material (here – a novel) in a deeper way. When it happens, a screenwriter is able to spot the gaps in the text and fill them with images that can later be presented to the viewers. Anne with an E, the Netflix adaption of Montgomery’s novel, may be used as a highly meaningful example of such a rendition. It is due to the fact that the 2017 series was broadcasted more than a hundred years after the first edition of the novel was published. This means that what the author might not have been able to show in her text can now be presented in a more open way. The screenwriter decided to use this opportunity to represent certain groups in the film, i.e., racial and sexual minorities, and women. Nonetheless, the series does not alter the novel; in fact, it adds to it by filling the blanks with more direct images. In the paper, fragments of the first season of Anne with an E are analysed in comparison to its source, the novel by Montgomery. The main purpose of that is to show how intersemiotic translation connected with the Iser’s literary theory can enrich the understanding of works of art, culture, media, and literature.

Keywords: intersemiotic translation, film, literary gaps, representation

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Authors: Jodie Bradnam, Mark Edwards, Bruce Watt

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Mobile technologies have emerged as tools to create and sustain social and romantic relationships. The integration of technologies in close relationships has been of particular research interest with findings supporting the positive role of mobile phones in nurturing feelings of closeness and connection. More recently, the use of text messaging to manage conflict has become a focus of research attention. Four hundred and eleven adults in committed romantic relationships completed a series of questionnaires measuring attachment orientation, relationship quality, texting frequencies, attitudes, and response expectations. Attachment orientation, relationship length, texting for connection and disconnection were significant predictors of relationship quality, specifically relationship intimacy. Text frequency varied as a function of attachment orientation, with high attachment anxiety associated with high texting frequencies and with low relationship quality. Sending text messages of love and support was related to higher intimacy and relationship satisfaction scores, while sending critical or impersonal texts was associated with significantly lower intimacy and relationship satisfaction scores. The use of texting to manage relational conflict was a stronger negative predictor of relationship satisfaction than was the use of texting to express love and affection. Consistent with research on face-to-face communication in couples, the expression of negative sentiments via text were related to lower relationship quality, and these negative sentiments had a stronger and more enduring impact on relationship quality than did the expression of positive sentiments. Attachment orientation, relationship length and relationship status emerged as variables of interest in understanding the use of mobile technologies in romantic relationships.

Keywords: attachment, destructive conflict, intimacy, mobile communication, relationship quality, relationship satisfaction, texting

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Amal Sellami, Ahlem Ammar

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Writing is acknowledged to be a cognitively demanding and complex task. Indeed, the writing process is composed of three iterative sub-processes, namely planning, translating (writing), and reviewing. Not only do second or foreign language learners need to write according to this process, but they also need to respect the norms and rules of language and writing in the text to-be-produced. Accordingly, researchers have suggested to approach writing as a collaborative task in order to al leviate its complexity. Consequently, collaboration has been implemented during the whole writing process or only during planning orreviewing. Researchers report that implementing collaboration during the whole process might be demanding in terms of time in comparison to individual writing tasks. Consequently, because of time constraints, teachers may avoid it. For this reason, it might be pedagogically more realistic to limit collaboration to one of the writing sub-processes(i.e., planning or reviewing). However, previous research implementing collaboration in planning or reviewing is limited and fails to explore the effects of the seconditionson the written text. Consequently, the present study examines the effects of collaboration in planning and collaboration in reviewing on the written text. To reach this objective, quantitative as well as qualitative methods are deployed to examine the written texts holistically and in terms of fluency, complexity, and accuracy. Participants of the study include 4 pairs in each group (n=8). They participated in two experimental conditions, which are: (1) collaborative planning followed by individual writing and individual reviewing and (2) individual planning followed by individual writing and collaborative reviewing. The comparative research findings indicate that while collaborative planning resulted in better overall text quality (precisely better content and organization ratings), better fluency, better complexity, and fewer lexical errors, collaborative reviewing produces better accuracy and less syntactical and mechanical errors. The discussion of the findings suggests the need to conduct more comparative research in order to further explore the effects of collaboration in planning or in reviewing. Pedagogical implications of the current study include advising teachers to choose between implementing collaboration in planning or in reviewing depending on their students’ need and what they need to improve.

Keywords: collaboration, writing, collaborative planning, collaborative reviewing

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Authors: Aji Budi Rinekso

Abstract:

There are some common problems that are often faced by students in writing. The problems are related to macro and micro skills of writing, such as incorrect spellings, inappropriate diction, grammatical errors, random ideas, and irrelevant supporting sentences. Therefore, it is needed a teaching technique that can solve those problems. Dictogloss technique is a teaching technique that involves listening practices. So, it is a suitable teaching technique for students with auditory learning style. Dictogloss technique comprises of four basic steps; (1) warm up, (2) dictation, (3) reconstruction and (4) analysis and correction. Warm up is when students find out about topics and do some preparatory vocabulary works. Then, dictation is when the students listen to texts read at normal speed by a teacher. The text is read by the teacher twice where at the first reading the students only listen to the teacher and at the second reading the students listen to the teacher again and take notes. Next, reconstruction is when the students discuss the information from the text read by the teacher and start to write a text. Lastly, analysis and correction are when the students check their writings and revise them. Dictogloss offers some advantages in relation to the efforts of improving writing skills. Through the use of dictogloss technique, students can solve their problems both on macro skills and micro skills. Easier to generate ideas and better writing mechanics are the benefits of dictogloss.

Keywords: auditory learners, writing skills, dictogloss technique, second language learning

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

Abstract:

Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: Shilpagauri Prasad Ganpule

Abstract:

The teaching of drama is considered as the most significant and noteworthy area in an ESL classroom. Diverse innovative techniques can be used to make the teaching of drama worthwhile and interesting. The paper presents the different innovative techniques that can be used while teaching Henrik Ibsen’s A Doll’s House [2007]. The innovative techniques facilitate students’ understanding and comprehension of the text. The use of the innovative techniques makes them explore the dramatic text and uncover a multihued arena of meanings hidden in it. They arouse the students’ interest and assist them overcome the difficulties created by the second language. The diverse innovative techniques appeal to the imagination of the students and increase their participation in the classroom. They help the students in the appreciation of the dramatic text and make the teaching learning situation a fruitful experience for both the teacher and students. The students successfully overcome the problem of L2 comprehension and grasp the theme, story line and plot-structure of the play effectively. The innovative techniques encourage a strong sense of participation on the part of the students and persuade them to learn through active participation. In brief, the innovative techniques promote the students to perform various tasks and expedite their learning process. Thus the present paper makes an attempt to present varied innovative techniques that can be used while teaching drama. It strives to demonstrate how the use of innovative techniques improve and enhance the students’ understanding and appreciation of Ibsen’s A Doll’s House [2007].

Keywords: ESL classroom, innovative techniques, students’ participation, teaching of drama

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

Abstract:

Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

Procedia PDF Downloads 96