Search results for: machine language

Authors: Christopher Celozzi, Sarah Kochav

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Our research investigates the numerous challenges faced by Chinese ESL university students enrolled in the medical and related healthcare professional fields. The over-arching research question is how gender influences classroom participation and learning. The second research question addressed is 'what instructional strategies may be utilized to promote student participation and language acquisition?'. Participants’ language ability has been assessed and evaluated in order to facilitate the establishment of a statistical baseline for the subsequent intervention. This research delves deeper into each individual’s personal and academic circumstances, in an effort to reveal any held intrinsic gender beliefs and social identities that may influence learning. Also considered is the impact on learning for a homogenized student population within a uniform, highly structured learning environment. Specially, what is the influence of China’s ‘one-child policy’ on individual learning habits? The impact of their millennial identity and reliance on social media is also examined. A qualitative methodology with a case study approach is employed, with interviews conducted among the participants. Student response to the intervention and selected remediation strategies are documented, analyzed and discussed. The findings of the study may serve to inform educator instructional practice, while advancing the student learner in their pursuit of English competency in highly competitive professions.

Keywords: Chinese students, gender, English, language acquisition

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Authors: Marian Lissett Olaya

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This article examined the factors associated with incorporating peer assessment into English language classes in a public university in Colombia. This is done in the context of writing English class for 4th-semester students. The research instruments consisted of peer assessment questionnaires, student diaries, and interviews. Findings showed that among the factors, motivation, frustration, anxiety, and lack of confidence appeared. Data revealed that peer assessment enables students to write competencies through training, teachers' guidance, and the provision of a collaborative environment.

Keywords: writing skills, peer assessment, formative assessment, language acquisition

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Authors: Huang Yajing

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Multimodal discourse refers to the phenomenon of using various senses such as hearing, vision, and touch to communicate through various means and symbolic resources such as language, images, sounds, and movements. With the development of modern technology and multimedia, language and technology have become inseparable, and foreign language teaching is becoming more and more modal. Teacher-student communication resorts to multiple senses and uses multiple symbol systems to construct and interpret meaning. The classroom is a semiotic space where multimodal discourses are intertwined. College English multi-modal teaching is to rationally utilize traditional teaching methods while mobilizing and coordinating various modern teaching methods to form a joint force to promote teaching and learning. Multimodal teaching makes full and reasonable use of various meaning resources and can maximize the advantages of multimedia and network environments. Based upon the above theories about multimodal discourse and multimedia technology, the present paper will propose a multi-modal teaching model for college English in China.

Keywords: multimodal discourse, multimedia technology, English education, applied linguistics

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Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

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The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

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Authors: Meruyert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova, Madina Ermaganbetova

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This research paper explores the process of creating a proctoring system by evaluating the implementation of practical face recognition algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As an outcome, a proctoring system will be created, enabling the conduction of tests and ensuring academic integrity checks within the system. Due to the correct operation of the system, test works are carried out. The result of the creation of the proctoring system will be the basis for the automation of the informational, educational portal developed by machine learning.

Keywords: artificial intelligence, education portal, face recognition, machine learning, proctoring

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Mahdi Bazarganigilani

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Computer-aided diagnosis (CAD) systems can play crucial roles in diagnosing crucial diseases such as breast cancer at the earliest. In this paper, a CAD system for the diagnosis of breast cancer was introduced and evaluated. This CAD system was developed by using spatio-temporal analysis of data on a set of consecutive thermographic images by employing wavelet transformation. By using this analysis, a very accurate machine learning model using random forest was obtained. The final results showed a promising accuracy of 91% in terms of the F1 measure indicator among 200 patients' sample data. The CAD system was further extended to obtain a detailed analysis of the effect of smaller sub-areas of each breast on the occurrence of cancer.

Keywords: computer-aided diagnosis systems, thermographic analysis, spatio-temporal analysis, image processing, machine learning

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Authors: Natasha Perez

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This autobiographical narrative inquiry explores the relationship between religious practice, identity, language and literacy in the author’s life experience as a second-generation Cuban-American growing up in the bilingual spaces of South Florida. The author describes how the social practices around language, including the flexibility to communicate in English and Spanish simultaneously, known as translanguaging, were instrumental to developing a biliterate cosmopolitan identity, along with a greater sense of Latinidad through interactions with diverse Latinx church members. This narrative study involved cycles of writing, reading, and reflection within a three-dimensional narrative inquiry space in order to discover the ways in which language and literacy development in the relationship between the personal and the social, across time and space, as historically situated phenomena. The findings show that Catholic faith practices have always been a source and expression of Cuban-ness, a means of sustaining Cuban identity, as well as a medium for bilingual language and literacy practice in the author’s life. Despite lacking formal literacy education in Spanish, she benefitted from the Catholic Church’s response to the surge of Spanish-speaking immigrants in South Florida in the 1980s and the subsequent flexibility of language practice in church-sponsored youth groups. The faith-sharing practices of the youth group created a space to use Spanish in more sophisticated ways that served to build confidence as a bilingual speaker and expand bilingual competence. These experiences also helped the author develop a more salient identity as Cuban-American and a deeper connection to her Cuban-ness in relation to the Nicaraguan, Venezuelan, and first-generation Cuban identities of my peers. The youth group also fostered cosmopolitan identity building through interactions with pan-ethnic Spanish speakers, with Catholicism as a common language and culture that served as a uniting force. Interaction with these peers also fostered cosmopolitan understandings that deepened the author’s knowledge of the geographical boundaries, political realities, and socio-historical differences between these groups of immigrants. This narrative study opens a window onto the micro-processes and socio-cultural dynamics of language and identity development in the second generation, with the potential to deepen our understanding of the impact of religious practice on these.

Keywords: literacy, religion, identity, comopolitanism, culture, language, translanguaging

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Authors: Mohammad Akram

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The aim of this study is to improve classroom management while teaching especially ESL/EFL. At the same time, it has been discussed about the standard of the students through some surveys held in Jazan University in the month of February and March, 2013. The present research is a classroom action-oriented study. The subject of the study is mainly the students whose first language is not English at all. The study is prepared in one cycle that has planning, action, and reaction as well. Teachers of English as a second language/foreign language generally face numerous of unexpected problems while dealing with their students. To make the classes practical, meaningful, and easy like fun for the students is really a cumbersome task. It's a very practical move towards classroom ESL/EFL teaching if we want to apply anything new, I mean new policies, tactics, recent/smart teaching methodologies, we must peep into the hole of past because it will give us the best solution for the present strategies. We need to academically study the past of our students to make their present fruitful. Here, author wants to present a few important problematic issues like classroom management in the area of ESL/EFL while teaching ESL students. Impact these are suggestions to combat drawbacks of 'Classroom Teaching'. “Classroom management is to put into practice and a process through teaching and learning process”.

Keywords: global, teachers, perceptions, classroom, management, integrated, segregated, comprehension, productive

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Authors: Prasenjit Panda

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Jean Rhys’s Wide Sargasso Sea, a prequel to Bronte’s Jane Eyre, explores the history of the other and gives voices to the people who were silenced and kept under the darkness of negation and denial for a long time. Jean Wide Sargasso Sea provides an alternative understanding of Charlotte Brontë’s mad Creole woman, i.e., Bertha Mason of Jane Eyre in the postcolonial context. Rhys transforms Charlotte Bronte’s Victorian romance into a realistic narrative. In doing so, she re-reads Bertha as Antoinette, the unspeakable figure of otherness, into an unnameable self, and creates a new stage for the inner self. She in the novel is no longer a lunatic heiress in Rochester’s attic rather in this novel she finds her fantasy, dream and most importantly, voice. Rhys peeps through the character of Antoinette through her fragmented memories, dreams, and identity. Antoinette’s identity is mutilated constantly in the conflicts between colonizers and colonized, male and female, black and white. We shall use postcolonial theories like Bhaba’s hybridity and third space as a methodology to reveal the dialectics of struggle of a doubly colonized woman.We shall see that Bertha Mason was neglected by Bronte because of her madness and was locked in the Rochester’s Attic, but here Rhys beautifully converts her madness as a language of Antoinette, a language for her protest, a language for her liberation, a language for her dreams. In this present paper, we shall try to show how Antoinette tries to free her soul and body from the clutches of her multiple existences, identity, and narratives.

Keywords: colonizer, dislocation, fragmented memories, identity, narratives

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Authors: Sylvester Akpah, Selasi Vondee

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Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: Mark McGuire, Eric Shannon, John Parmigiani

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Timber harvesting increasingly involves mechanized equipment. This has increased the efficiency of harvesting, but has also introduced worker-safety concerns. One such concern arises from the use of harvesters. During operation, harvesters subject saw chain to large dynamic mechanical stresses. These stresses can, under certain conditions, cause the saw chain to fracture. The high speed of harvester saw chain can cause the resulting open chain loop to fracture a second time due to the dynamic loads placed upon it as it travels through space. If a second fracture occurs, it can result in a projectile consisting of one-to-several chain links. This projectile is referred to as a chain shot. It has speeds similar to a bullet but typically has greater mass and is a significant safety concern. Numerous examples exist of chain shots penetrating bullet-proof barriers and causing severe injury and death. Improved harvester-cab barriers can help prevent injury however a comprehensive scientific understanding of chain shot is required to consistently reduce or prevent it. Obtaining this understanding requires a test machine with the capability to cause chain shot to occur under carefully controlled conditions and accurately measure the response. Worldwide few such test machine exist. Those that do focus on validating the ability of barriers to withstand a chain shot impact rather than obtaining a scientific understanding of the chain shot event itself. The purpose of this paper is to describe the design, fabrication, and use of a test machine capable of a comprehensive scientific investigation of chain shot. The capabilities of this machine are to test all commercially-available saw chains and bars at chain tensions and speeds meeting and exceeding those typically encountered in harvester use and accurately measure the corresponding key technical parameters. The test machine was constructed inside of a standard shipping container. This provides space for both an operator station and a test chamber. In order to contain the chain shot under any possible test conditions, the test chamber was lined with a base layer of AR500 steel followed by an overlay of HDPE. To accommodate varying bar orientations and fracture-initiation sites, the entire saw chain drive unit and bar mounting system is modular and capable of being located anywhere in the test chamber. The drive unit consists of a high-speed electric motor with a flywheel. Standard Ponsse harvester head components are used to bar mounting and chain tensioning. Chain lubrication is provided by a separate peristaltic pump. Chain fracture is initiated through ISO standard 11837. Measure parameters include shaft speed, motor vibration, bearing temperatures, motor temperature, motor current draw, hydraulic fluid pressure, chain force at fracture, and high-speed camera images. Results show that the machine is capable of consistently causing chain shot. Measurement output shows fracture location and the force associated with fracture as a function of saw chain speed and tension. Use of this machine will result in a scientific understanding of chain shot and consequently improved products and greater harvester operator safety.

Keywords: chain shot, safety, testing, timber harvesters

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Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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Authors: Victor Ademulegun Arijeniwa

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This is a sociolinguistic study of Olu Obafemi’s Naira Has No Gender as a microcosm of life experiences. The paper assesses how Olu Obafemi’s use of language in the dramatic world serves as both social relationships and symbolic order of communicative roadmap that are capable of yielding well expressed and richly articulated sociolinguistic implications. Being the interface between language and social institutions, sociolinguistics and its application is highly utilitarian in linguistics analysis, especially where the language of a text appears to be deeply tensed, such as found in dramatic texts. The aim of this paper has been (i) to assess the symbolic orderly presentation of form in Olu Obafemi’Naira Has No Gender; (ii) to find out the linguistic elements and textual organization that represent social relationships in Olu Obafemi’s Naira Has No Gender. Using qualitative research design in data generation with insights from John Gumperz Interactional Sociolinguistics Theory with particular reference to contextualization cues and miscommunication, the paper identifies the implication of the dramatic discourse on society.

Keywords: sociolinguistics, Microcosm, contextualisation, miscommunication variable, identity, symbolic order

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Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

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Authors: Helen Zhang

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Accurate segmentation of the airways from CT scans is crucial for early diagnosis of lung cancer. However, the existing airway segmentation algorithms often rely on thin-slice CT scans, which can be inconvenient and costly. This paper presents a set of machine learning-based 3D super-resolution algorithms along heterogeneous dimensions to improve the resolution of thicker CT scans to reduce the reliance on thin-slice scans. To evaluate the efficacy of the super-resolution algorithms, quantitative assessments using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural SIMilarity index) were performed. The impact of super-resolution on airway segmentation accuracy is also studied. The proposed approach has the potential to make airway segmentation more accessible and affordable, thereby facilitating early diagnosis and treatment of lung cancer.

Keywords: 3D super-resolution, airway segmentation, thin-slice CT scans, machine learning

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Authors: Carla Lopes

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It is clear nowadays that the proper performance of different speech acts is one of the most difficult obstacles that a foreign language learner has to overcome to be considered communicatively competent. This communication presents the results of an investigation on the pragmatic performance of Portuguese Language students at the University of Macau. The research discussed herein is based on a survey consisting of fourteen speaking situations to which the participants must respond in writing, and that includes different types of speech acts: apology, response to a compliment, refusal, complaint, disagreement and the understanding of the illocutionary force of indirect speech acts. The responses were classified in a five levels Likert scale (quantified from 1 to 5) according to their suitability for the particular situation. In general terms, we can summarize that about 45% of the respondents' answers were pragmatically competent, 10 % were acceptable and 45 % showed weaknesses at socio-pragmatic competence level. Given that the linguistic deviations were not taken into account, we can conclude that the faults are of cultural origin. It is natural that in the presence of orthogonal cultures, such as Chinese and Portuguese, there are failures of this type, barely solved in the four years of the undergraduate program. The target population, native speakers of Cantonese or Mandarin, make their first contact with the English language before joining the Bachelor of Portuguese Language. An analysis of the socio - pragmatic failures in the respondents’ answers suggests the conclusion that many of them are due to the lack of cultural knowledge. They try to compensate for this either using their native culture or resorting to a Western culture that they consider close to the Portuguese, that is the English or US culture, previously studied, and also widely present in the media and on the internet. This phenomenon, known as 'pragmatic transfer', can result in a linguistic behavior that may be considered inauthentic or pragmatically awkward. The resulting speech act is grammatically correct but is not pragmatically feasible, since it is not suitable to the culture of the target language, either because it does not exist or because the conditions of its use are in fact different. Analysis of the responses also supports the conclusion that these students present large deviations from the expected and stereotyped behavior of Chinese students. We can speculate while this linguistic behavior is the consequence of the Macao globalization that culturally casts the students, makes them more open, and distinguishes them from the typical Chinese students.

Keywords: Portuguese foreign language, pragmatic failures, pragmatic transfer, pragmatic competence

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Authors: Nguyen The Hoang Anh, Tran Huy Hoang, Vu Tat Thang, T. T. Quyen Bui

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Mental state classification is an important step for realizing a control system based on electroencephalography (EEG) signals which could benefit a lot of paralyzed people including the locked-in or Amyotrophic Lateral Sclerosis. Considering that EEG signals are nonstationary and often contaminated by various types of artifacts, classifying thoughts into correct mental states is not a trivial problem. In this work, our contribution is that we present and realize a novel model which integrates different techniques: Independent component analysis (ICA), relative wavelet energy, and support vector machine (SVM) for the same task. We applied our model to classify thoughts in two types of experiment whether with two or three mental states. The experimental results show that the presented model outperforms other models using Artificial Neural Network, K-Nearest Neighbors, etc.

Keywords: EEG, ICA, SVM, wavelet

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Authors: Liu Si, Wang Chunmei, Liu Huangmei

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A prominent component of the semantic versus pragmatic debate, scalar implicature (SI) has been gaining great attention ever since it was proposed by Horn. The constant debate is between the structural and pragmatic approach. The former claims that generation of SI is costless, automatic, and dependent mostly on the structural properties of sentences, whereas the latter advocates both that such generation is largely dependent upon context, and that the process is costly. Many experiments, among which Katsos’s text comprehension experiments are influential, have been designed and conducted in order to verify their views, but the results are not conclusive. Besides, most of the experiments were conducted in English language materials. Katsos conducted one off-line and three on-line text comprehension experiments, in which the previous shortcomings were addressed on a certain extent and the conclusion was in favor of the pragmatic approach. We intend to test the results of Katsos’s experiment in Chinese scalar implicature. Four experiments in both off-line and on-line conditions to examine the generation and response time of SI in Chinese "yixie" (some) and "quanbu (dou)" (all) will be conducted in order to find out whether the structural or the pragmatic approach could be sustained. The study mainly aims to answer the following questions: (1) Can SI be generated in the upper- and lower-bound contexts as Katsos confirmed when Chinese language materials are used in the experiment? (2) Can SI be first generated, then cancelled as default view claimed or can it not be generated in a neutral context when Chinese language materials are used in the experiment? (3) Is SI generation costless or costly in terms of processing resources? (4) In line with the SI generation process, what conclusion can be made about the cognitive processing model of language meaning? Is it a parallel model or a linear model? Or is it a dynamic and hierarchical model? According to previous theoretical debates and experimental conflicts, presumptions could be made that SI, in Chinese language, might be generated in the upper-bound contexts. Besides, the response time might be faster in upper-bound than that found in lower-bound context. SI generation in neutral context might be the slowest. At last, a conclusion would be made that the processing model of SI could not be verified by either absolute structural or pragmatic approaches. It is, rather, a dynamic and complex processing mechanism, in which the interaction of language forms, ad hoc context, mental context, background knowledge, speakers’ interaction, etc. are involved.

Keywords: cognitive linguistics, pragmatics, scalar implicture, experimental study, Chinese language

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: I. Wardana Ketut, I. Suparwa Nyoman

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This study investigated the form and characteristic of speech sound produced by three Balinese subjects who have recovered from aphasia as well as intervened their language impairment on side of linguistic and neuronal aspects of views. The failure of judging the speech sound was caused by impairment of motor cortex that indicated there were lesions in left hemispheric language zone. Sound articulation phenomena were in the forms of phonemes deletion, replacement or assimilation in individual words and meaning building for anomic aphasia. Therefore, the Balinese sound patterns were stimulated by showing pictures to the subjects and recorded to recognize what individual consonants or vowels they unclearly produced and to find out how the sound disorder occurred. The physiology of sound production by subject’s speech organs could not only show the accuracy of articulation but also any level of severity the lesion they suffered from. The subjects’ speech sounds were investigated, classified and analyzed to know how poor the lingual units were and observed to clarify weaknesses of sound characters occurred either for place or manner of articulation. Many fricative and stopped consonants were replaced by glottal or palatal sounds because the cranial nerve, such as facial, trigeminal, and hypoglossal underwent impairment after the stroke. The phonological intervention was applied through a technique called phonemic articulation drill and the examination was conducted to know any change has been obtained. The finding informed that some weak articulation turned into clearer sound and simple meaning of language has been conveyed. The hierarchy of functional parts of brain played important role of language formulation and processing. From this finding, it can be clearly emphasized that this study supports the role of right hemisphere in recovery from aphasia is associated with functional brain reorganization.

Keywords: aphasia, intervention, phonology, stroke

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Authors: Shashwat Mookherjee, Shruti Dutta

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This study explores linguistic distinctions among American, Indian, and Irish English dialects and assesses various Language Models (LLMs) in their ability to generate British English translations from these dialects. Using cosine similarity analysis, the study measures the linguistic proximity between original British English translations and those produced by LLMs for each dialect. The findings reveal that Indian and Irish English translations maintain notably high similarity scores, suggesting strong linguistic alignment with British English. In contrast, American English exhibits slightly lower similarity, reflecting its distinct linguistic traits. Additionally, the choice of LLM significantly impacts translation quality, with Llama-2-70b consistently demonstrating superior performance. The study underscores the importance of selecting the right model for dialect translation, emphasizing the role of linguistic expertise and contextual understanding in achieving accurate translations.

Keywords: cross-dialect translation, language models, linguistic similarity, multilingual NLP

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Authors: Ahmad Tijani Surajudeen, Muhammad Zahiri Awang Mat, Aliy Abdulwahid Adebisi

Abstract:

With arrival of Islam in the South-Western Nigeria in the late fifteenth and early sixteenth centuries, various masājid established in different parts of the area played vital roles towards the betterment and unity of the Muslims. However, despite the fact that the masājid in the South-Western part of Nigeria contributed immensely to the spiritual and educational enhancement of the Muslims, it has not fully captured the holistic educational roles as a unique model used by the Prophet (S.A.W). Therefore, the primary objective of this paper is to investigate and broaden the roles of masjid towards its compartmentalized and holistic contributions among the Muslims in the south-western Nigeria. The findings from the paper have identified five holistic roles of masjid, namely, spiritual, intellectual, physical, social and emotional contributions which have been exemplified in the prophetic model of masjid. The paper has argued that the five factors must be unreservedly unified towards the betterment of the Muslims and enhancement of Islamic education and Arabic Language in the South-Western Nigeria. However, the challenges of masjid management in the South-Western Nigeria are the main hindrance in achieving the holistic roles of masjid. It is thereby suggested that, the management of masjid should take the identified prophetic model of masjid into account in order to positively improve the affairs of Muslims as well as promoting the teaching and learning of Islamic education and Arabic language among the Muslims in the South-Western Nigeria.

Keywords: worship, Islamic education, Arabic language, prophetic holistic model

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Authors: Sarra Hasni, Sami Faiz

Abstract:

In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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Authors: Nguyen Thu Ha, Vu Viet Phuong, Do Thi Tieu Yen, Nguyen Thi Thanh Ha

Abstract:

This semi-experimental research investigated the correlation between 42 English as a foreign language (EFL) sophomores' self-regulated learning strategies (SRL) use and their reading comprehension in the Vietnamese context. The analysis from TOEIC reading tests with SPSS 25.0 indicated that there are substantial differences between the post-test reading scores between the experimental group and the control group; therefore, SRL impacts the reading comprehension of EFL participants. Contrary to the alternative hypothesis, teaching learners SRL approaches had a statistically significant influence on reading comprehension. The findings may aid educators in teaching reading comprehension as an essential skill and in using SRL to improve reading comprehension and achievement and enhance reading comprehension aids for language students and instructors. They should equip educators with a variety of instructional strategies which assist academics in preparing learners for lifetime language study and independence. Moreover, the results might encourage educators, administrators, and policymakers to capitalize on the effects of teaching SRL strategies by providing EFL teachers with preparation programs and experiences that help them improve their teaching methods and strategies, especially when teaching reading comprehension.

Keywords: correlation, reading proficiency, self-regulated learning strategies, SRL, TOEIC reading comprehension

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Authors: Michael Amankwaa Adu

Abstract:

This study investigates the speech acts employed by a Career Technology teacher during classroom interactions in a junior high school. While much research exists on speech acts in language teaching, little attention has been given to technical subjects. This has created a gap in understanding how teachers of non-language subjects utilize speech acts in classroom communication. This study aims to analyze the types and frequencies of speech acts used by a Career Technology teacher during three key classroom encounters: lesson introduction, content delivery, and classroom management. Using a mixed-methods approach, the study examines 113 utterances from the teacher's lesson, categorizing them into four primary speech act types: directives, assertives, expressives, and commissives. Directives emerged as the most dominant form, accounting for 59.3% of the utterances, followed by assertives (20.4%), expressives (14.2%), and commissives (6.2%). No declarations were observed. The study demonstrates how the teacher uses directives to manage student behavior and assertives to reinforce information. Expressives are used sparingly but play a role in motivating or disciplining students, while commissives help establish classroom rules and set expectations. The findings contribute to understanding classroom interaction strategies in non-language subjects, offering insights that could inform teacher training and curriculum development. The study underscores the importance of effective communication in technical subjects and suggests ways in which language teaching techniques might be integrated into other subject areas.

Keywords: classroom management, directives, speech acts, technical subjects., assertives

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Authors: Abir Hmida, Nihel Chekir, Ammar Ben Brahim

Abstract:

In the present paper, we investigate the feasibility of a thermal solar driven cold room in Gabes, southern region of Tunisia. The cold room of 109 m³ is refrigerated using an ammonia absorption machine. It is destined to preserve dates during the hot months of the year. A detailed study of the cold room leads previously to the estimation of the cooling load of the proposed storage room in the operating conditions of the region. The next step consists of the estimation of the required heat in the generator of the absorption machine to ensure the desired cold temperature. A thermodynamic analysis was accomplished and complete description of the system is determined. We propose, here, to provide the needed heat thermally from the sun by using vacuum tube collectors. We found that at least 21m² of solar collectors are necessary to accomplish the work of the solar cold room.

Keywords: absorption, ammonia, cold room, solar collector, vacuum tube

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Authors: Jingsong Ma

Abstract:

In political translation, ideology plays an important role in conveying implications accurately. Ideological collisions can occur in political translation when there existdifferences of political environments embedded in the translingual political texts in both source and target languages. To reach an accurate translationrequires the translatorto understand the ideologies implied in (and often transcending) the texts. This paper explores the conditions, procedure, and purpose of processingideological collision and resolution of such issues in political translation. These points will be elucidated by case studies of translating English and Chinese political texts. First, there are specific political terminologies in certain political environments. These terminological peculiarities in one language are often determined by ideological elements rather than by syntactical and semantical understanding. The translation of these ideological-loaded terminologiesis a process and operation consisting of understanding the ideological context, including cultural, historical, and political situations. This will be explained with characteristic Chinese political terminologies and their renderings in English. Second, when the ideology in the source language fails to match with the ideology in the target language, the decisions to highlight or disregard these conflicts are shaped by power relations, political engagement, social context, etc. It thus is necessary to go beyond linguisticanalysis of the context by deciphering ideology in political documents to provide a faithful or equivalent rendering of certain messages. Finally, one of the practical issues is about equivalence in political translation by redefining the notion of faithfulness and retainment of ideological messages in the source language in translations of political texts. To avoid distortion, the translator should be liberated from grip the literal meaning, instead diving into functional meanings of the text.

Keywords: translation, ideology, politics, society

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