Search results for: language problem

Authors: Ali Kirkbas

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R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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Authors: Orlyn Joyce D. Esquivel

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This study analyzed 50 selected research papers from professional language and linguistic academic journals to portray the differences between Kachru’s (1994) outer circle and expanding circle Englishes. The selected outer circle Englishes include those of Bangladesh, Malaysia, the Philippines, India, and Singapore; and the selected expanding circle Englishes are those of China, Indonesia, Japan, Korea, and Thailand. The researcher built ten corpora (five research papers for each corpus) to represent each variety of Englishes. The corpora were examined under grammatical and lexical features using Modified English TreeTagger in Sketch Engine. Results revealed the distinct grammatical and lexical features through the table and textual analyses, illustrated from the most to least dominant linguistic elements. In addition, comparative analyses were done to distinguish the features of each of the selected Englishes. The Language Change Theory was used as a basis in the discussion. Hence, the findings suggest that the ‘outer circle’ Englishes and ‘expanding circle’ Englishes will continue to drift from International English.

Keywords: applied linguistics, English as a global language, expanding circle Englishes, global Englishes, outer circle Englishes

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Authors: Nina Leila Mussa

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Background: The devastating effects of the war on Syria’s educational infrastructure has been widely reported, with millions of children denied access. However, among those who resettled in Lebanon, the impact of receiving educational assistance on their abilities to pass the English entrance exam is not well described. The aim of this study was to identify predictors of success among Syrian refugees receiving English language courses in a Lebanese university. Methods: The database of Syrian refugee girls matriculated in English courses at the American University of Beirut (AUB) was reviewed. The study period was 7/2018-09/2020. Variables compared included: family size and income, welfare status, parents’ education, English proficiency, access to the internet, and need for external help with homework. Results: For the study period, there were 28 girls enrolled. The average family size was 6 (range 4-9), with eight having completed primary, 14 secondary education, and 6 graduated high school. Eighteen were single-income families. After 12 weeks of English courses, 16 passed the Test of English as Foreign Language (TOEFL) from the first attempt, and 12 failed. Out of the 12, 8 received external help, and 6 passed on the second attempt, which brings the total number of successful passing to 22. Conclusion: Despite the tragedy of war, girls receiving assistance in learning English in Lebanon are able to pass the basic language test. Investment in enhancing those educational experiences will be determinantal in achieving widespread progress among those at-risk children.

Keywords: refugee girls, TOEFL, education, success

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Authors: Yun-Ching Tu, Yu-Chun Chih

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People with aphasia (PWA) may have communicative difficulties in their daily lives, but research on functional communication in aphasia is still limited in Taiwan. The aim of the study was to investigate the impact of aphasia-related factors on functional communication assessment. This study adopted a convenience sampling method. Thirty aphasic participants participated in the study. During the test, the examiner would ask questions that are encountered in daily life and record the participant‘s responses. Some questions would provide pictures to simulate situations in daily life. The results showed that the non-fluent aphasia group performed significantly worse than the fluent aphasia group. In addition, patients with severe aphasia performed significantly lower scores than patients with moderate aphasia and mild aphasia. However, group differences in the chronic stage and acute stage were not significant. In sum, since communication in daily life is diverse and language is still needed in the communication process, patients with aphasia who have better language ability may have relatively better functional communication. In contrast, the more severely impaired the language ability of a patient with aphasia is, the more functional communication will be affected, resulting in poor communication performance in daily life.

Keywords: adult, aphasia, assessment, functional communication

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Authors: Muhammad Mukhtar Aliyu

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This study investigated tutors’ experiences and perceptions of a problem-based learning approach (PBL) in a writing classroom. The study involved two Nigerian lecturers who facilitated an intact class of second-year students in an English composition course for the period of 12 weeks. Semi-structured interviews were employed to collect data of the study. The lecturers were interviewed before and after the implementation of the PBL process. The overall findings of the study show that the lecturers had positive perceptions of the use of PBL in a writing classroom. Specifically, the findings reveal the lecturers’ positive experiences and perception of the group activities. Finally, the paper gives some pedagogical implications which would give insight for better implementation of the PBL approach.

Keywords: experiences and perception, Nigeria, problem-based learning approach, writing classroom

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Authors: Tomas Kos

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An increasing body of research has explored patterns of interaction and peer support among young learners. Although some studies suggest that young learners can collaborate and support each other, other studies indicate that young learners may lack the ability to work together and support one another when interacting on classroom tasks. Moreover, despite the claims that peer collaboration is conducive to learning, studies have not paid enough attention to the “how” to enhance peer collaboration on classroom tasks. To fill this gap, this “how-to” article proposes that teaching young learners how to work together is a powerful pedagogical tool that can greatly improve collaborative behavior and a sense of mutuality among young learners. This article will pay particular attention to primary schools and the context of English as a foreign language. It will first review literature related to patterns of interaction and peer support conducted in the cognitive and sociocultural framework. It will then address what it actually means to collaborate. At the heart of the article, it will discuss some practical pedagogical ideas for language teachers, which entail teaching collaborative principles and strategies that will help their students to support each other and engage in communication with each other.

Keywords: young learners, peer collaboration, peer interaction, peer support, patterns of interaction

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Authors: Muhammed Kök & Adem Kantar

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Learning a foreign language can be affected by various factors such as age, aptitude, motivation, L2 disposition, etc. Among these factors, masculine gender roles stress (MGRS) that male learners possess is the least touched area that has been examined so far.MGRS can be defined as the traditional male role stress when the male learners feel the masculinity threat against their traditionally adopted masculinity norms. Traditional masculine norms include toughness, accuracy, completeness, and faultlessness. From this perspective, these norms are diametrically opposed to the language learning process since learning a language, by its nature, involves stages such as making mistakes and errors, not recalling words, pronouncing sounds incorrectly, creating wrong sentences, etc. Considering the potential impact of MGRS on the language learning process, the main purpose of this study is to investigate the mediating role of MGRS on the relationship between the EFL learners’ self-disclosure and English class anxiety. Data were collected from Turkish EFL learners (N=282) who study different majors in various state universities across Turkey. Data were analyzed by means of the Bootstraping method using the SPSS Process Macro plugin. The findings show that the indirect effect of self-disclosure level on the English Class Anxiety via MGRS was significant. We conclude that one of the reasons why Turkish EFL learners have English class anxiety might be the pressure that they feel because of their traditional gender role stress.

Keywords: masculine, gender role stress, english class anxiety, self-disclosure, masculinity norms

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Authors: Diane Ghanem, Oscar Covarrubias, Michael Raad, Dawn LaPorte, Babar Shafiq

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Introduction: Standardized exams have long been considered a cornerstone in measuring cognitive competency and academic achievement. Their fixed nature and predetermined scoring methods offer a consistent yardstick for gauging intellectual acumen across diverse demographics. Consequently, the performance of artificial intelligence (AI) in this context presents a rich, yet unexplored terrain for quantifying AI's understanding of complex cognitive tasks and simulating human-like problem-solving skills. Publicly available AI language models such as ChatGPT have demonstrated utility in text generation and even problem-solving when provided with clear instructions. Amidst this transformative shift, the aim of this study is to assess ChatGPT’s performance on the orthopaedic surgery in-training examination (OITE). Methods: All 213 OITE 2021 web-based questions were retrieved from the AAOS-ResStudy website. Two independent reviewers copied and pasted the questions and response options into ChatGPT Plus (version 4.0) and recorded the generated answers. All media-containing questions were flagged and carefully examined. Twelve OITE media-containing questions that relied purely on images (clinical pictures, radiographs, MRIs, CT scans) and could not be rationalized from the clinical presentation were excluded. Cohen’s Kappa coefficient was used to examine the agreement of ChatGPT-generated responses between reviewers. Descriptive statistics were used to summarize the performance (% correct) of ChatGPT Plus. The 2021 norm table was used to compare ChatGPT Plus’ performance on the OITE to national orthopaedic surgery residents in that same year. Results: A total of 201 were evaluated by ChatGPT Plus. Excellent agreement was observed between raters for the 201 ChatGPT-generated responses, with a Cohen’s Kappa coefficient of 0.947. 45.8% (92/201) were media-containing questions. ChatGPT had an average overall score of 61.2% (123/201). Its score was 64.2% (70/109) on non-media questions. When compared to the performance of all national orthopaedic surgery residents in 2021, ChatGPT Plus performed at the level of an average PGY3. Discussion: ChatGPT Plus is able to pass the OITE with a satisfactory overall score of 61.2%, ranking at the level of third-year orthopaedic surgery residents. More importantly, it provided logical reasoning and justifications that may help residents grasp evidence-based information and improve their understanding of OITE cases and general orthopaedic principles. With further improvements, AI language models, such as ChatGPT, may become valuable interactive learning tools in resident education, although further studies are still needed to examine their efficacy and impact on long-term learning and OITE/ABOS performance.

Keywords: artificial intelligence, ChatGPT, orthopaedic in-training examination, OITE, orthopedic surgery, standardized testing

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Authors: Hanadi Khadawardi

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The current study contributes to research on foreign/second language (L2) academic reading by presenting a significant case study, which seeks to investigate specific groups of international (Arab) postgraduate students’ L2 academic reading practices in the UK educational context. In particular, the study scrutinises postgraduate students’ L2 paper-based and digital-based academic reading strategies, and their use of digital aids while engaged in L2 academic reading. To this end, the study investigates Arab readers’ attitudes toward digital L2 academic reading. The study aims to compare between paper and digital L2 academic reading strategies that the students employ and which reading formats they prefer. This study tracks Masters-level students and examines the way in which their reading strategies and attitudes change throughout their Masters programme in the UK educational context. The academic reading strategies and attitudes of five students from four different disciplines (Health Science, Psychology, Management, and Education) are investigated at two points during their one-year Masters programmes. In addition, the study investigates the same phenomenon with 15 Saudi PhD students drawn from seven different disciplines (Computer Science, Engineering, Psychology, Management, Marketing, Health Science, and Applied Linguistics) at one period of their study in the same context. The study uses think-aloud protocol, field notes, stimulated recall, and semi-structured interviews to collect data. The data is analysed qualitatively. The results of the study will explain the process of learning in terms of reading L2 paper and digital academic texts in the L2 context.

Keywords: EFL: English as a foreign language, ESL: English as a second language, L: Language

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Anteneh Getachew Gebrie, Rabian Wangkeeree

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The purpose of this paper is to introduce iterative algorithm solving split system of minimization problem given as a task of finding a common minimizer point of finite family of proper, lower semicontinuous convex functions and whose image under a bounded linear operator is also common minimizer point of another finite family of proper, lower semicontinuous convex functions. We obtain strong convergence of the sequence generated by our algorithm under some suitable conditions on the parameters. The iterative schemes are developed with a way of selecting the step sizes such that the information of operator norm is not necessary. Some applications and numerical experiment is given to analyse the efficiency of our algorithm.

Keywords: Hilbert Space, minimization problems, Moreau-Yosida approximate, split feasibility problem

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Authors: Anita De Melo

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Today we live in a crucial time of ecological crisis, of environmental catastrophes worldwide, and this scenario is, arrogantly, overlooked by powerful economic forces and their politics. Thus, a critical pedagogy that leads to action and that fosters ecoliteracy, environment education, is now inevitable, and it must become an integral part of the school curriculum across the disciplines, including the social sciences and the humanities. One of the most important contemporary and emerging movement of today is ecopedagogy, a movement that blends theory and ethics towards a curriculum that focus on an environmental education that will promote ecological justice, respect, and care by educating students to become planetary citizens. This paper aims, first, to emphasize the need for discussions and investigations regarding ecoliteracy within our field of teaching foreign languages, which will consider, among others, the of role language in stimulating sustainability, and the role of second language proficiency in fostering positive transnational dialogues conducive to fighting our current planetary crisis. Second, this paper suggests and discusses some critical ecopedagogical practices -- in the form of project-based learning, service-learning and environmental-oriented study abroad programs – apropos to ecoliteracy. These interdisciplinary projects can and should bring students in contact with communities speaking the target language, and such encounter would facilitate cultural exchanges and promote positive language proficiency whilst it would also give students the opportunity to work with finding ideas/projects to fight our current ecological catastrophe.

Keywords: critical pedagogy, ecoliteracy, ecopedagogy, planetary crisis

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Taoues Hadour

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Twitter has become a popular means of communication used in a variety of fields, such as politics, journalism, and academia. This widely used online platform has an impact on the way people express themselves and is changing language usage worldwide at an unprecedented pace. The language used online reflects the linguistic battle that has been going on for several decades in French society. This study enables a deeper understanding of users' linguistic behavior online. The implications are important and allow for a rise in awareness of intercultural and cross-language exchanges. This project investigates the mixing of French-English language usage among French users of Twitter using a topic analysis approach. This analysis draws on Gumperz's theory of conversational switching. In order to collect tweets at a large scale, the data was collected in R using the rtweet package to access and retrieve French tweets data through Twitter’s REST and stream APIs (Application Program Interface) using the software RStudio, the integrated development environment for R. The dataset was filtered manually and certain repetitions of themes were observed. A total of nine topic categories were identified and analyzed in this study: entertainment, internet/social media, events/community, politics/news, sports, sex/pornography, innovation/technology, fashion/make up, and business. The study reveals that entertainment is the most frequent topic discussed on Twitter. Entertainment includes movies, music, games, and books. Anglicisms such as trailer, spoil, and live are identified in the data. Change in language usage is inevitable and is a natural result of linguistic interactions. The use of different languages online is just an example of what the real world would look like without linguistic regulations. Social media reveals a multicultural and multilinguistic richness which can deepen and expand our understanding of contemporary human attitudes.

Keywords: code-switching, French, sociolinguistics, Twitter

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Authors: Rolando Barradas, Salviano Soares, António Valente, José Alberto Lencastre, Paulo Oliveira

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This article reviews the Ant Colony Optimization, a nature-inspired algorithm, and its implementation in the Scratch/m-Block programming environment. The Ant Colony Optimization is a part of Swarm Intelligence-based algorithms and is a subset of biological-inspired algorithms. Starting with a problem in which one has a maze and needs to find its path to the center and return to the starting position. This is similar to an ant looking for a path to a food source and returning to its nest. Starting with the implementation of a simple wall follower simulator, the proposed solution uses a dynamic graphical interface that allows young students to observe the ants’ movement while the algorithm optimizes the routes to the maze’s center. Things like interface usability, Data structures, and the conversion of algorithmic language to Scratch syntax were some of the details addressed during this implementation. This gives young students an easier way to understand the computational concepts of sequences, loops, parallelism, data, events, and conditionals, as they are used through all the implemented algorithms. Future work includes the simulation results with real contest mazes and two different pheromone update methods and the comparison with the optimized results of the winners of each one of the editions of the contest. It will also include the creation of a Digital Twin relating the virtual simulator with a real micromouse in a full-size maze. The first test results show that the algorithm found the same optimized solutions that were found by the winners of each one of the editions of the Micromouse contest making this a good solution for maze pathfinding.

Keywords: nature inspired algorithms, scratch, micromouse, problem-solving, computational thinking

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Authors: Mafunda Esther

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The paper seeks to find out and document the impact of culture and religion on disability, specifically language impairment and health care seeking practices of the Shona people. Its main objectives are to explore the cultural and religious beliefs that affect the utilization of rehabilitation services in a rural community in Zimbabwe. The other objective of the paper is to describe how language impairment is presented and understood by people living in a Zimbabwean rural area. The research is qualitative interpretive phenomenological research, and it utilizes the case study approach using semi structured interviews and focus group discussions. Results from the research established that religious and cultural beliefs determine how the Shona people view disability, and this guides their health care seeking practices. The research is important since communication disorders occur in populations worldwide though they are not always recognized as such. The lack of recognition of and the attitudes toward speech and languages disorders, as well as the beliefs about the causes of such disorders, affect people's attitudes toward the treatment of the disorders.

Keywords: culture, religion, disability, language impairment

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Authors: Vinay Suhalka

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In India, the official nomenclature used by the State for persons with disability is divyang (literally, the one with a divine limb), a word coming from the Sanskrit language. Disability thus gets portrayed as divine, at least in the welfare sector from where it flows down even to the popular imagination where it gets equated to divinity. This paper looks at reference to persons with disabilities as divyangs and goes on to discusses what such usage for an already marginalized group achieves and misses out. The issue of nomenclature and language has always been a contested one when it comes to disability. At the same time, there is also an issue of who determines these labels for the persons with disability. Nomenclature and language used for disability can have real consequences for the population of persons with disability as it may empower or disempower them. Thus, this paper looks at the issue of what it means for persons with disabilities as ‘exceptionally gifted’ and hence divyang. Language can be a powerful tool to communicate meanings and messages associated with a term. When the persons with disabilities as a group are described as ‘exceptionally gifted, talented and the source of inspiration’, it essentially stereotypes and marginalizes them by putting a burden of performance that all of them ought to be achievers, and it is only then that they would be assimilated in the larger society. This paper also argues that such a situation creates a ‘double bind’ where the person is always trying to match up to the labels (the disabled as ‘achiever, overcomer, inspirational’) created by somebody else and looks at self through the eyes of others. This conceptual paper also presents an overview of disability labels while simultaneously looking at projecting disability as divinity which has the potential to wrongly portray the lives of persons with disability in India due to the official usage of the term. It also explores the question of visibility of disability since the idea of divyang implicitly assumes that all disabilities are visible. In reality, however, it may not be the case simply because all forms of disabilities are not visible, people may choose not to visibilize their disabilities if they can and pass as able-bodied, fearing the stigma that surrounds disability. Finally, it argues for an increased focus on understanding the everyday lived realities of those with disability in order to regard it as an important form of difference which could be a potential resource for the society.

Keywords: persons with disability, labels, language use, divinity

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Authors: Suzi M. S. Cavalari, Tim Lewis

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Teletandem is a bilingual model of virtual exchange in which two partners from different countries( and speak different languages) meet synchronously and regularly over a period of 8 weeks to learn each other’s mother tongue (or the language of proficiency). At São Paulo State University (UNESP), participants should answer a questionnaire before starting the exchanges in which one of the questions refers to setting a goal to be accomplished with the help of the teletandem partner. In this context, the present presentation aims to examine the goal-setting activity of 79 Brazilians who participated in Portuguese-English teletandem exchanges over a period of four years (2012-2015). The theoretical background is based on goal setting and self-regulated learning theories that propose that appropriate efficient goals are focused on the learning process (not on the product) and are specific, proximal (short-term) and moderately difficult. The data set used was 79 initial questionnaires retrieved from the MulTeC (Multimodal Teletandem Corpus). Results show that only approximately 10% of goals can be considered appropriate. Features of these goals are described in relation to specificities of the teletandem context. Based on the results, three mechanisms that can help learners to set attainable goals are discussed.

Keywords: foreign language learning, goal setting, teletandem, virtual exchange

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Authors: Feiying Wu

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Chatbots are computer programs that attempt to engage a human in a dialogue, which originated in the 1960s with MIT's Eliza. However, they have become widespread more recently as advances in language technology have produced chatbots with increasing linguistic quality and sophistication, leading to their potential to serve as a tool for Computer-Assisted Language Learning(CALL). The aim of this article is to assess the feasibility of using two chatbots, Mitsuku and CleverBot, as pedagogical tools for learning English as a second language by stimulating L2 learners with distinct English proficiencies. Speaking of the input of stimulated learners, they are measured by AntWordProfiler to match the user's expected vocabulary proficiency. Totally, there are four chat sessions as each chatbot will converse with both beginners and advanced learners. For evaluation, it focuses on chatbots' responses from a linguistic standpoint, encompassing vocabulary and sentence levels. The vocabulary level is determined by the vocabulary range and the reaction to misspelled words. Grammatical accuracy and responsiveness to poorly formed sentences are assessed for the sentence level. In addition, the assessment of this essay sets 25% lexical and grammatical incorrect input to determine chatbots' corrective ability towards different linguistic forms. Based on statistical evidence and illustration of examples, despite the small sample size, neither Mitsuku nor CleverBot is ideal as educational tools based on their performance through word range, grammatical accuracy, topic range, and corrective feedback for incorrect words and sentences, but rather as a conversational tool for beginners of L2 English.

Keywords: chatbots, CALL, L2, corrective feedback

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Authors: Anna-Maria Ramezanzadeh

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Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

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The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

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Authors: Chibuzo Okoye Daniels, Gillian Glegg, Lynda Rodwell

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The continuously growing quantity of very slow degrading litter deliberately discarded into the coastal waters around Lagos as marine debris is obvious. What is not known is how to tackle this problem to reduce its prevalence and impact on the environment, economy and community. To identify ways of tackling the marine debris problem two case study areas (Ikoyi and Victoria Islands of Lagos State) were used to assess the root causes, the threat posed by marine debris in the coastal waters around Lagos and the efficacy of current instruments, programmes and initiatives that address marine debris in the study areas. The following methods were used: (1) Self-completed questionnaires for households and businesses within the study areas; (2) Semi-structured interviews with key stakeholders; (3) Observational studies of waste management from collection to disposal and waste management facilities for waste originating from land and maritime sources; (4) Beach surveys and marine debris surveys on shorelines and ports; and (5) Fishing for marine debris. Results of this study identified the following root causes: (1) Indiscriminate human activities and behaviors, and lack of awareness on the part of the main stakeholders and the public of the potential consequences of their actions; (2) Poor solid waste management practices; (3) Lack of strict legal frameworks addressing waste and marine debris problem; and (4) Disposal of non-degradable wastes into domestic sewer system and open streets drains. To effectively tackle marine debris problem in the study areas, adequate, appropriate and cost effective solutions to the above mentioned root causes needs to be identified and effectively transferred for implementation in the study areas.

Keywords: marine debris problem, Lagos state, litter, coastal waters

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Authors: Nashwah Alnajjar

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This research paper provides an overview of Replika, an AI chatbot application that uses natural language processing technology to engage in conversations with users. The app was developed to provide users with a virtual AI friend who can converse with them on various topics, including mental health. This study explores the experiences of Replika users using quantitative research methodology. A survey was conducted with 12 participants to collect data on their demographics, usage patterns, and experiences with the Replika app. The results showed that Replika has the potential to play a role in mental health support and well-being.

Keywords: Replika, chatbot, mental health, artificial intelligence, natural language processing

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Authors: Ajay R, Rammohan B, Sridhar K S S, Gurusharan N

Abstract:

The objective of the work is to develop a numerical method to solve the inverse mode shape problem by determining the cross-sectional area of a structure for the desired mode shape via the vibration response study of the humerus bone, which is in the form of a cantilever beam with anisotropic material properties. The humerus bone is the long bone in the arm that connects the shoulder to the elbow. The mode shape is assumed to be a higher-order polynomial satisfying a prescribed set of boundary conditions to converge the numerical algorithm. The natural frequency and the mode shapes are calculated for different boundary conditions to find the cross-sectional area of humerus bone from Eigenmode shape with the aid of the inverse mode shape algorithm. The cross-sectional area of humerus bone validates the mode shapes of specific boundary conditions. The numerical method to solve the inverse mode shape problem is validated in the biomedical application by finding the cross-sectional area of a humerus bone in the human arm.

Keywords: Cross-sectional area, Humerus bone, Inverse mode shape problem, Mode shape

Procedia PDF Downloads 120

Authors: Abdul Basit Kiani

Abstract:

Web technologies are growing rapidly in the current era with the increasing development of the web, various novel web technologies emerged to web applications, compared to HTML. JavaScript is the language that provided a dynamic web site which actively interacts with users. The JavaScript language supports the Model View Controller (MVC) architecture that maintains a readable code and clearly separates parts of the program code. Our research is focused on the comparison of the popular JavaScript frameworks; Angular JS, Django, Node JS, Laravel. These frameworks are rely on MVC. In this paper, we will discuss the merits and demerits of each framework, the influence on the application speed, testing methods, for example, JS applications, and methods to advance code security.

Keywords: java script, react, nodejs, htmlcsss

Procedia PDF Downloads 109

Authors: Didem Can

Abstract:

Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

Procedia PDF Downloads 231

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

Abstract:

People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 144

Authors: S. Zenhari, M. R. Hematiyan, A. Khosravifard, M. R. Feizi

Abstract:

The boundary element method (BEM) and the method of fundamental solutions (MFS) are well-known fundamental solution-based methods for solving a variety of problems. Both methods are boundary-type techniques and can provide accurate results. In comparison to the finite element method (FEM), which is a domain-type method, the BEM and the MFS need less manual effort to solve a problem. The aim of this study is to compare the accuracy and reliability of the BEM and the MFS. This comparison is made for 2D potential and elasticity problems with different boundary and loading conditions. In the comparisons, both convex and concave domains are considered. Both linear and quadratic elements are employed for boundary element analysis of the examples. The discretization of the problem domain in the BEM, i.e., converting the boundary of the problem into boundary elements, is relatively simple; however, in the MFS, obtaining appropriate locations of collocation and source points needs more attention to obtain reliable solutions. The results obtained from the presented examples show that both methods lead to accurate solutions for convex domains, whereas the BEM is more suitable than the MFS for concave domains.

Keywords: boundary element method, method of fundamental solutions, elasticity, potential problem, convex domain, concave domain

Procedia PDF Downloads 88