Search results for: sign language recognition

Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Magdalena Madany-Saá

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This paper compares the language management of two language policies in plurinational Ecuador: (1) mandatory English language teaching that uses Western standards of quality, and (2) indigenous educación intercultural bilingüe, which promotes ancestral knowledge and the indigenous languages of Ecuador. The data are from a comparative institutional ethnography conducted between 2018 and 2022 in English and Kichwa teacher preparation programs in an Ecuadorian teachers’ college. Specifically, the paper explores frameworks of knowledge promoted by different educational actors in both teacher education programs and the ways in which the Ecuadorian transformation towards a knowledge-based economy is intertwined with the country’s linguistic policies. Focusing on the specific role of language advocates and their discursive role in knowledge production, the paper elaborates on the notion of agency in Language Policy and Planning (LPP), referred to as epistemic agency. Specifically, the epistemic agency is conceptualized through the analysis of English language epistemic advocates who participate in empowering English language policies and endorse knowledge production in that language. By proposing an epistemic agency, this paper argues that in the context of knowledge-based societies, advocates are key in transferring the policies from the political to the epistemic realm – where decisions about what counts as legitimate knowledge are made. The study uses the decolonial option as its analytical framework for critiquing the hegemonic perpetuation of modernity and its knowledge-based models in Latin America derived from the colonial matrix of power. Through this theoretical approach, it is argued that if indigenous stakeholders are only viewed as political actors and not as knowledge producers, the hegemony of Global English will reinforce a knowledge-based society constructed upon Global North modernity. In the absence of strong epistemic advocates for indigenous language policies, powerful Global English advocates occupy such vacancies at the language management level, thus dominating the ecology of knowledge in a plurinational and plurilingual Ecuador.

Keywords: educación intercultural bilingüe, English language teaching, epistemic agency, language advocates, plutinationality

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Authors: Lidia N. Hernández-Piña, Carlos R. Jaimez-González

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Interoperability in distributed systems is an important feature that refers to the communication of two applications written in different programming languages. This paper presents a serializer and a de-serializer of PHP objects to and from XML, which is an independent library written in the PHP programming language. The XML generated by this serializer is independent of the programming language, and can be used by other existing Web Objects in XML (WOX) serializers and de-serializers, which allow interoperability with other object-oriented programming languages.

Keywords: interoperability, PHP object serialization, PHP to XML, web objects in XML, WOX

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Authors: Fakieh Alrabai

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This study investigated the effects on learner anxiety of anxiety-reducing strategies utilized by English as foreign language teachers in Saudi Arabia. The study was conducted in two stages. In the first stage, sources of foreign language anxiety for Saudi learners of English (N = 596) were identified using The Foreign Language Classroom Anxiety Scale (FLCAS). In the second stage, 465 learners who were divided almost equally into two groups (experimental vs. control) and 12 teachers were recruited. Anxiety-reducing strategies were implemented exclusively in the treatment group for approximately eight weeks. FLCAS was used to assess learners’ FL anxiety levels before and after treatment. Statistical analyses (e.g. ANOVA and ANCOVA) were used to evaluate the study findings. These findings revealed that the intervention led to significantly decreased levels of FL anxiety for learners in the experimental group compared with increased levels of anxiety for those in the control group.

Keywords: communication apprehension, EFL teaching/learning, fear of negative evaluation, foreign language anxiety

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Authors: Paul Lam, Kevin Wong, Chi Him Chan

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

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

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Lucia Silveira Alda

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This research aims to analyze critically a set of studies published in the Proceedings of the International Conference on Mobile Learning of IADIS, from 2008 until 2012, which addresses the issue of foreign language learning mediated by mobile phones. The theoretical review of this study is based on the Vygotskian assumptions about tools and mediated learning and the concepts of mobile learning, CALL and MALL. In addition, the diffusion rates of the mobile phone and especially its potential are considered. Through systematic review and meta-analysis, this research intended to identify similarities and differences between the identified characteristics in the studies on the subject of language learning and mobile phone. From the analysis of the results, this study verifies that the mobile phone stands out for its mobility and portability. Furthermore, this device presented positive aspects towards student motivation in language learning. The studies were favorable to mobile phone use for learning. It was also found that the challenges in using this tool are not technical, but didactic and methodological, including the need to reflect on practical proposals. The findings of this study may direct further research in the area of language learning mediated by mobile phones.

Keywords: language learning, mobile learning, mobile phones, technology

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Jamshid Qodirov, Sirojiddin Komolov, Ravilov Mirahmad, Olimjon Mirzayev

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Nowadays, natural language processing tools play a crucial role in our daily lives, including various techniques with text processing. There are very advanced models in modern languages, such as English, Russian etc. But, in some languages, such as Uzbek, the NLP models have been developed recently. Thus, there are only a few NLP models in Uzbek language. Moreover, there is no such work that could show which Uzbek NLP model behaves in different situations and when to use them. This work tries to close this gap and compares the Uzbek NLP models existing as of the time this article was written. The authors try to compare the NLP models in two different scenarios: sentiment analysis and sentence similarity, which are the implementations of the two most common problems in the industry: classification and similarity. Another outcome from this work is two datasets for classification and sentence similarity in Uzbek language that we generated ourselves and can be useful in both industry and academia as well.

Keywords: NLP, benchmak, bert, vectorization

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Authors: Naomi Mutea, Jossete Jones

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The project aimed at exploring the views and perceptions of nurse leaders and educators regarding use of International Classification for Nursing Practice (ICNP) in an informal approach which involved face to face discussions, after which a decision would be made on whether to proceed and propose introduction of ICNP project in Kenya as a pilot project which would mean all nurses would use a standard approach to reporting and documenting nursing care. In addition the project was to determine the best approaches/methods that can be used to introduce ICNP in the Kenyan nursing education and practice environment using the findings of the pilot project. Further four cardex reports were reviewed to establish if nurses on the bedside used a standardized language in documenting and reporting care processes. The cardex reports showed that nurses do not use ICNP or any other standardized language. The results of the discussions revealed that this would be a challenge due to several challenges experienced in conducting nursing research in resource-limited environments. The following questions were asked during the informal discussions with the educators/leaders: •What is currently being taught in terms of standardized nursing language? •Are you familiar with ICNP? •Do you view it advantageous to have a standardized language? •What is the greatest need at the moment in terms of curriculum development for BSN regarding use of standardized nursing language? •If you had a wish to change something in your curriculum, what would that be?

Keywords: nursing, standardized language, ICNP, resource-limited care environments

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Authors: Agnieszka Kałdonek-Crnjaković

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Research on Attention-Deficit/Hyperactivity Disorder (ADHD) is abundant but not in the field of applied linguistics and foreign or second language education. To fill this research gap, the present study aimed to investigate the effect of ADHD on skills and systems development in a second and foreign language from the teacher's perspective. The participants were 51 English as a foreign language (EFL) teachers in Poland working in state pre-, primary, and high schools. Research questions were as follows: Do ADHD-type behaviors affect EFL learning of the individual with the condition and their classmates to the same extent considering different educational settings and specific skills and systems? And To what extent do ADHD-type behaviors affect ESL/EFL skills and systems considering different ADHD presentations? Data were collected by means of a questionnaire distributed via a Google form. It contained 14 statements on a six-point Likert scale related to the effect of ADHD on specific language skills and systems in the context of an individual with the condition and their classmates and situations related to inattention and hyperactivity/impulsivity presentations of the condition, where the participants needed to identify skills and systems affected by the given ADHD manifestation. The results show that ADHD affects all language skills and systems development in both the individual with the condition and their classmates, but this effect is more significant in the latter. However, ADHD affected skills and systems to a different degree; writing skills were reported as the most affected by this disorder. Also, the effect of ADHD differed depending on the educational setting, being the highest in high school and lowest in the first three grades of primary school. These findings will be discussed in the context of foreign/second language teaching in the school context, considering different phases of education as well as future research on ADHD and language learning and teaching.

Keywords: ADHD, EFL teachers, foreign/second language learning, language skills and systems development

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Authors: Yenie Norambuena

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Analogical reasoning is a cognitive process that consists of structured comparisons of mental representations and scheme construction. Because of its heuristic function, it is ubiquitous in cognition and could play an important role in language development. The use of analogies is expressed early in children and this behavior is also reflected in language, suggesting a possible way to understand the complex links between thought and language. The current research examines factors of verbal and non-verbal reasoning that should be taken into consideration in the study of language development for their relations and predictive value. The study was conducted with 48 Chilean preschoolers (Spanish speakers) from 4 to 6-year-old. We assessed children’s verbal analogical reasoning, non-verbal analogical reasoning and linguistics skills (Listening Comprehension, Phonemic awareness, Alphabetic principle, Syllabification, Lexical repetition and Lexical decision). The results evidenced significant correlations between analogical reasoning factors and linguistic skills and they can predict linguistic performance mainly on oral comprehension, lexical decision and phonological skills. These findings suggest a fundamental interrelationship between analogical reasoning and linguistic performance on children’s and points to the need to consider this cognitive process in comprehensive theories of children's language development.

Keywords: verbal analogical reasoning, non-verbal analogical reasoning, linguistic skills, language development

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Authors: Amina Babou

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Gender and language is a moot and miscellaneous arena in the sphere of sociolinguistics, which has been proliferated so widely and rapidly in recent years. The dawn of research on gender and foreign language education was against the feminist researchers who allowed space for the bustling concourse of voices and perspectives in the arena of gender and language differences, in the early to the mid-1970. The objective of this scrutiny is to explore to what extent teaching gender and language in the English as a Foreign Language (EFL) classroom plays a pivotal role in learning language information and skills. And the gist of this paper is to investigate how EFL students in Algeria conflate their gender identities with the linguistic practices and scholastic expertise. To grapple with the full range of issues about the EFL students’ awareness about the negotiation of meanings in the classroom, we opt for observing, interviewing, and questioning later to check using ‘how-do-you do’ procedure. The analysis of the EFL classroom discourse, from five Algerian universities, reveals that speaking strategies such as the manners students make an abrupt topic shifts, respond spontaneously to the teacher, ask more questions, interrupt others to seize control of conversations and monopolize the speaking floor through denying what others have said, do not sit very lightly on 80.4% of female students’ shoulders. The data indicate that female students display the assertive style as a strategy of learning to subvert the norms of femininity, especially in the speaking module.

Keywords: gender identities, EFL students, classroom discourse, linguistics

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Lana Whiskeyjack, Kyle Napier

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The Spirit of the language embodies the motivation for indigenous people to connect with the indigenous language of their lineage. While the concept of the spirit of the language is often woven into the discussion by indigenous language revitalizationists, particularly those who are indigenous, there are few tangible terms in academic research conceptually actualizing the term. Through collaborative work with indigenous language speakers, elders, and learners, this research sets out to identify the spirit of the language, the catalysts of disconnection from the spirit of the language, and the sources of reconnection to the spirit of the language. This work fundamentally addresses the terms of engagement around collaboration with indigenous communities, itself inviting a decolonial approach to community outreach and individual relationships. As indigenous researchers, this means beginning, maintain, and closing this work in the ceremony while being transparent with community members in this work and related publishing throughout the project’s duration. Decolonizing this approach also requires maintaining explicit ongoing consent by the elders, knowledge keepers, and community members when handling their ancestral and indigenous knowledge. The handling of this knowledge is regarded in this work as stewardship, both in the handling of digital materials and the handling of ancestral Indigenous knowledge. This work observes recorded conversations in both nêhiyawêwin and English, resulting from 10 semi-structured interviews with fluent nêhiyawêwin speakers as well as three structured dialogue circles with fluent and emerging speakers. The words were transcribed by a speaker fluent in both nêhiyawêwin and English. The results of those interviews were categorized thematically to conceptually actualize the spirit of the language, catalysts of disconnection to thespirit of the language, and community voices methods of reconnection to the spirit of the language. Results of these interviews vastly determine that the spirit of the language is drawn from the land. Although nêhiyawêwin is the focus of this work, Indigenous languages are by nature inherently related to the land. This is further reaffirmed by the Indigenous language learners and speakers who expressed having ancestries and lineages from multiple Indigenous communities. Several other key differences embody this spirit of the language, which include ceremony and spirituality, as well as the semantic worldviews tied to polysynthetic verb-oriented morphophonemics most often found in indigenous languages — and of focus, nêhiyawêwin. The catalysts of disconnection to the spirit of the language are those whose histories have severed connections between Indigenous Peoples and the spirit of their languages or those that have affected relationships with the land, ceremony, and ways of thinking. Results of this research and its literature review have determined the three most ubiquitously damaging interdependent factors, which are catalysts of disconnection from the spirit of the language as colonization, capitalism, and Christianity. As voiced by the Indigenous language learners, this work necessitates addressing means to reconnect to the spirit of the language. Interviewees mentioned that the process of reconnection involves a whole relationship with the land, the practice of reciprocal-relational methodologies for language learning, and indigenous-protected and -governed learning. This work concludes in support of those reconnection methodologies.

Keywords: indigenous language acquisition, indigenous language reclamation, indigenous language revitalization, nêhiyawêwin, spirit of the language

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Junwon Seo, Bipin Adhikari, Euiseok Jeong

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This paper is intended to evaluate the structural performance of welded electronic road signs under various damage scenarios (DSs) using a finite element (FE) model calibrated with full-scale ultimate load testing results. The tested electronic road sign specimen was built with a back skin made of 5052 aluminum and two channels and a frame made of 6061 aluminum, where the back skin was connected to the frame by welding. The size of the tested specimen was 1.52 m long, 1.43 m wide, and 0.28 m deep. An actuator applied vertical loads at the center of the back skin of the specimen, resulting in a displacement of 158.7 mm and an ultimate load of 153.46 kN. Using these testing data, generation and calibration of a FE model of the tested specimen were executed in ABAQUS, indicating that the difference in the ultimate load between the calibrated model simulation and full-scale testing was only 3.32%. Then, six different DSs were simulated where the areas of the welded connection in the calibrated model were diminished for the DSs. It was found that the corners at the back skin-frame joint were prone to connection failure for all the DSs, and failure of the back skin-frame connection occurred remarkably from the distant edges.

Keywords: computational analysis, damage scenarios, electronic road signs, finite element, welded connections

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Authors: Shatha Alkhalaf

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This study aimed to investigate the effectiveness of the English Speaking Practice App in improving the speaking skills of English as a Foreign Language (EFL) learners. The participants were 44 diploma students at Qassim University in Saudi Arabia. They used the app for 30 minutes per week over a 12-week period. A survey questionnaire was used to measure their perceptions of the app's effectiveness, usability, and impact on motivation. The questionnaire showed high internal consistency (Cronbach's alpha = 0.89). The findings suggest that the app was perceived positively by the participants in terms of its effectiveness in improving speaking skills, usability, and motivation. This research contributes to the field of language teaching by highlighting the potential of technology-enhanced language learning.

Keywords: second language, English, speaking, technology

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Authors: Pelumi Olowofoyeku

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English as a language has great reach and influence; it is taught all over the world. For instance, in Nigeria, English language is been taught and learned as a second language; therefore second learners of English in Nigeria have certain problems they contend with. Because of the dissimilarities in word formation patterns of English and Yoruba languages, Yoruba learners of English mostly found in the south west of Nigeria, and some parts of Kwara, Kogi, and Edo states of Nigeria have problems with word formation patterns in English. The objectives of this paper therefore, are: to identify the levels of word formation dissimilarities in English and Yoruba languages and to examine the effects of these dissimilarities on the Yoruba learners of English. The data for this paper were graded words purposely selected and presented to selected students of Adeniran Ogunsanya College of Education, Oto-Ijanikin, Lagos, who are Yoruba learners of English. These respondents were randomly selected to form words which are purposively selected to test the effects of word formation dissimilarities between Yoruba (the respondent’s first language) and English language on the respondents. The dissimilarities are examined using contrastive analysis tools. This paper reveals that there are differences in the word formation patterns of Yoruba and English languages. The writer believes that there is need for language teachers to undertake comparative studies of the two languages involved for methodological reasons. The author then suggests that teachers should identify the problem areas and systematically teach their students. The paper concludes that although English and Yoruba word formation patterns differ very significantly in many respects, there exist language universals in all languages which language educators should take advantage of in teaching.

Keywords: word formation patterns, graded words, ESL, Yoruba learners

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Authors: Elizabeth Mahenge

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Unemployment is a problem that face many graduates all over the world. Every year universities in many parts of the world produce graduates who are looking for an employment. Swahili, a Bantu language originated in East African coast, can be used as an avenue for youth’s employment in South Africa. This paper helps youth to know about job opportunities available through teaching Swahili language. The objective of this paper is capacity building to youths to be teachers of Swahili and be ready to compete in the marketplace. The methodology was through two weeks online training on how to teach Swahili as a foreign language. The communicative approach and task-based approach were used.  Participants to this training were collected through a WhatsApp group advertisement about “short training for Swahili teachers for foreigners”. A total number of 30 participants registered but only 11 attended the training. Training was online via zoom. The contribution of this paper is that by being fluent in Swahili one would benefit with teaching job opportunities anywhere in the world. Hence the problem of unemployment among the youths would be reduced as they can employ themselves or being employed in academic institutions anywhere in the world. The paper calls for youths in South Africa to opt for Swahili language courses to be trained and become experts in the teaching Swahili as a foreign language.

Keywords: foreign language, linguistic market, Swahili, employment

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Authors: Clifford Irikefe Gbeyonron

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The Nigerian educational system, which has English language as a major medium of instruction, has been designed in such a way that the cognitive, psychomotor and affective endowments of the Nigerian learner could be explored. However, the human resources that would impart the desired knowledge, skills and values in the learners seem to be in short supply. This paucity is more manifest in the area of teachers of English. As a result, this research was conducted on the demand and supply of teachers of English at the junior secondary schools in Gashua, Yobe State. The results indicate that there was dearth of teachers of English the domain under review. This thus presents a challenge that should propel English language teacher education industries to produce more teachers of English. As a result, this paper recommends that the teacher production process should make use of qualified and enthusiastic teacher trainers that would be able to inculcate in-depth linguistic and communicative competence of English language and English language teaching skills in the potential teachers of English. In addition, English language education service providers should attract and retain the trained teachers of English in the business of English language teaching in such a way that all the states of Nigeria could experience educational development.

Keywords: demand, supply, teachers of English, Yobe State

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Authors: Fatma Al-Maadheed

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Following an ethnographic approach this study explored bilingual programmes offered by two types of primary schools in Qatar: international and Independent schools. Qatar with its unique linguistic and socio-economic situation launched a new initiative for educatiobnal development in 2001 but with hardly any research linked to theses changes. The study reveals that the Qatari bilingual schools context was one of heteroglossia, with three codes in operation: Modern Standard Arabic, Colloquial Arabic dialects and English. The two schools adopted different models of bilingualism. The international school adopted a strict separation policy between the two languages following a monoglossic belief. The independent school was found to apply a flexible language policy. The study also highlighted the daily challnges produced from the diglossia situation in Qatar, the difference between students and teacher dialect as well as acquiring literacy in the formal language. In addition to an abscence of a clear language policy in Schools, the study brought attention to the instructional methods utilised in language teaching which are mostly associated with successful bilingual education.

Keywords: diglossia, instructional methods, language policy, qatari primary schools

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Authors: A. Robbin

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Language selection can be an efficient negotiation strategy employed by both service or product providers and their customers to achieve transactional success. The transactional scenario in Gbagi Market, Ibadan, Nigeria provides an appropriate setting for the exploration of the Nigerian multilingual situation with its own interesting linguistic peculiarities which questions the functionality of the ‘Lingua Franca’ in trade situations. This study examined English Language proficiency among Yoruba Traders in Gbagi Market, Ibadan and its use as determinants of transactional success during service encounters. Randomly selected Yoruba-English bilingual traders and customers were administered questionnaires and the data subjected to statistical and descriptive analysis using Giles Communication Accommodation Theory. Findings reveal that only fifty percent of the traders used for the study were proficient in speaking English language. Traders with minimal proficiency in Standard English, however, resulted in the use of the Nigerian Pidgin English. Both traders and customers select the Mother Tongue, which is the Yoruba Language during service encounters but are quick to converge to the other’s preferred language as the transactional exchange demands. The English language selection is not so much for the prestige or lingua franca status of the language as it is for its functions, which include ease of communication, negotiation, and increased sales. The use of English during service encounters is mostly determined by customer’s linguistic preference which the trader accommodates to for better negotiation and never as a first choice. This convergence is found to be beneficial as it ensures sales and return patronage. Although the English language is not a preferred code choice in Gbagi Market, it serves a functional trade strategy for transactional success during service encounters in the market.

Keywords: communication accommodation theory, language selection, proficiency, service encounter, transaction

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

Abstract:

A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

Abstract:

Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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Authors: Randa Alahmadi

Abstract:

Because the world has become a global village, English is not only used by native speakers, but also by non-native speakers from culturally diverse backgrounds. Even though learning a second/foreign language requires development of the four skills: reading, writing, listening, and speaking, there is also an intertwined relationship between language and culture, making it difficult to teach language without knowing the cultural context in which it is to be used. In the past decade, the number of international students enrolled in universities around the world has increased significantly. Having the urge to communicate effectively would serve as a motivation for both international and domestic students. The teaching of culture is important because linguistic competence is not enough for successful communication with speakers of other languages. Therefore, whether teaching natives or non-natives, students need to improve their cross-cultural communication skills and become culturally prepared to communicate successfully with people from other cultures. Teachers can equip their students for this environment by giving them appropriate knowledge and skills for effective intercultural communication. This paper will focus on the importance of intercultural communicative competence and its role in developing students’ understanding of diverse cultures as part of learning foreign/second languages. It will also explain how teachers can decide which culture should be taught: the target culture, the learners’ culture, or both. Moreover, practical and effective techniques that can be used in cultural-based language teaching will be shared.

Keywords: cultural-based language teaching, English as a lingua franca, English language learners, intercultural communicative competence

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

Abstract:

In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Reza Shakoori

Abstract:

This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.

Keywords: Arabic, chain code normalization, OCR systems, image processing

Procedia PDF Downloads 384