Search results for: Language disorders

Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm.

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Authors: Kanakasabha Ramana

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The Post colonial society in India has witnessed the turmoil to come out from the widespread control and influence of colonialism. The socio-cultural life of a society with all its dynamics is reflected in realistic forms of literature. The social events and human experience are drawn into a new creative form and are given to the reader as a new understanding and perspective of life. It enables the reader to understand the essence of life and motivates him to prepare for a positive change. After India becoming free from the colonial rule in 1947, systematic efforts were made by central and state governments and institutions to limit the role of English and simultaneously enlarge the function of Indian languages by planning in a strategic manner. The eighteen languages recognized as national languages are having very rich literatures. Telugu language is one among the Dravidian language family and is widely spoken by a majority of people. The post colonial socio-cultural factors were very well reflected in Telugu literature. The anti-colonial, reform oriented, progressive, post modernistic trends in Telugu literature are nothing but creative reflections of the post colonial society. This paper examines the major socio-cultural reflections in Telugu literature of the post colonial period.

Keywords: postcolonialism, culture, progressive movement, Telugu Literature.

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Authors: Moorthi S., Meganathan D., Janarthanan D., Praveen Kumar P., J. Raja paul perinbam

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An efficient architecture for low jitter All Digital Phase Locked Loop (ADPLL) suitable for high speed SoC applications is presented in this paper. The ADPLL is designed using standard cells and described by Hardware Description Language (HDL). The ADPLL implemented in a 90 nm CMOS process can operate from 10 to 200 MHz and achieve worst case frequency acquisition in 14 reference clock cycles. The simulation result shows that PLL has cycle to cycle jitter of 164 ps and period jitter of 100 ps at 100MHz. Since the digitally controlled oscillator (DCO) can achieve both high resolution and wide frequency range, it can meet the demands of system-level integration. The proposed ADPLL can easily be ported to different processes in a short time. Thus, it can reduce the design time and design complexity of the ADPLL, making it very suitable for System-on-Chip (SoC) applications.

Keywords: All Digital Phase Locked Loop (ADPLL), Systemon-Chip (SoC), Phase Locked Loop (PLL), Very High speedIntegrated Circuit (VHSIC) Hardware Description Language(VHDL), Digitally Controlled Oscillator (DCO), Phase frequencydetector (PFD) and Voltage Controlled Oscillator (VCO).

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Authors: Anjin Park, Sungju Yun, Jungwhan Kim, Seungk Min, Keechul Jung

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Finger spelling is an art of communicating by signs made with fingers, and has been introduced into sign language to serve as a bridge between the sign language and the verbal language. Previous approaches to finger spelling recognition are classified into two categories: glove-based and vision-based approaches. The glove-based approach is simpler and more accurate recognizing work of hand posture than vision-based, yet the interfaces require the user to wear a cumbersome and carry a load of cables that connected the device to a computer. In contrast, the vision-based approaches provide an attractive alternative to the cumbersome interface, and promise more natural and unobtrusive human-computer interaction. The vision-based approaches generally consist of two steps: hand extraction and recognition, and two steps are processed independently. This paper proposes real-time vision-based Korean finger spelling recognition system by integrating hand extraction into recognition. First, we tentatively detect a hand region using CAMShift algorithm. Then fill factor and aspect ratio estimated by width and height estimated by CAMShift are used to choose candidate from database, which can reduce the number of matching in recognition step. To recognize the finger spelling, we use DTW(dynamic time warping) based on modified chain codes, to be robust to scale and orientation variations. In this procedure, since accurate hand regions, without holes and noises, should be extracted to improve the precision, we use graph cuts algorithm that globally minimize the energy function elegantly expressed by Markov random fields (MRFs). In the experiments, the computational times are less than 130ms, and the times are not related to the number of templates of finger spellings in database, as candidate templates are selected in extraction step.

Keywords: CAMShift, DTW, Graph Cuts, MRF.

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Authors: Haibo Hu, Dan Yang, Chunxiao Ye, Chunlei Fu, Ren Li

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High quality requirements analysis is one of the most crucial activities to ensure the success of a software project, so that requirements verification for software system becomes more and more important in Requirements Engineering (RE) and it is one of the most helpful strategies for improving the quality of software system. Related works show that requirement elicitation and analysis can be facilitated by ontological approaches and semantic web technologies. In this paper, we proposed a hybrid method which aims to verify requirements with structural and formal semantics to detect interactions. The proposed method is twofold: one is for modeling requirements with the semantic web language OWL, to construct a semantic context; the other is a set of interaction detection rules which are derived from scenario-based analysis and represented with semantic web rule language (SWRL). SWRL based rules are working with rule engines like Jess to reason in semantic context for requirements thus to detect interactions. The benefits of the proposed method lie in three aspects: the method (i) provides systematic steps for modeling requirements with an ontological approach, (ii) offers synergy of requirements elicitation and domain engineering for knowledge sharing, and (3)the proposed rules can systematically assist in requirements interaction detection.

Keywords: Requirements Engineering, Semantic Web, OWL, Requirements Interaction Detection, SWRL.

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Authors: Sunee Pongpinigpinyo, Wanchai Rivepiboon

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Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely  /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.

Keywords: Distributional semantics, Latent Semantic Indexing, natural language processing, Polysemous words, unsupervisedlearning, Word Sense Disambiguation.

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Authors: Vishal Raj, Noorhan Abbas

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Ambiguity in NLP (Natural Language Processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a method to create an affinity matrix to calculate the affinity between any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an algorithm to create the sense clusters of tokens using affinity matrix under hierarchy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contextual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and challenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: Word Sense Disambiguation, WSD, Contextual SenSe Model, Most Frequent Sense, part of speech, POS, Natural Language Processing, NLP, OOV, out of vocabulary, ELMo, Embeddings from Language Model, BERT, Bidirectional Encoder Representations from Transformers, Word2Vec, lemma_POS, Algorithm.

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Authors: Leo Laine, Morgan Johansson

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To meet the civilizations future needs for safe living and low environmental footprint, the engineers designing the complex systems of tomorrow will need efficient ways to model and optimize these systems for their intended purpose. For example, a civil defence shelter and its subsystem components needs to withstand, e.g. airblast and ground shock from decided design level explosion which detonates with a certain distance from the structure. In addition, the complex civil defence shelter needs to have functioning air filter systems to protect from toxic gases and provide clean air, clean water, heat, and electricity needs to also be available through shock and vibration safe fixtures and connections. Similar complex building systems can be found in any concentrated living or office area. In this paper, the authors use a multidomain modelling language called Modelica to model a concrete wall as a single degree of freedom (SDOF) system with elastoplastic properties with the implemented option of plastic hardening. The elastoplastic model was developed and implemented in the open source tool OpenModelica. The simulation model was tested on the case with a transient equivalent reflected pressure time history representing an airblast from 100 kg TNT detonating 15 meters from the wall. The concrete wall is approximately regarded as a concrete strip of 1.0 m width. This load represents a realistic threat on any building in a city like area. The OpenModelica model results were compared with an Excel implementation of a SDOF model with an elastic-plastic spring using simple fixed timestep central difference solver. The structural displacement results agreed very well with each other when it comes to plastic displacement magnitude, elastic oscillation displacement, and response times.

Keywords: Airblast from explosives, elastoplastic spring model, Modelica modelling language, SDOF, structural response of concrete structure.

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Authors: Subramaniam Chandran

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This paper explains how mobile learning assures sustainable e-education for multicultural group of students. This paper reports the impact of mobile learning on distance education in multicultural environment. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective purposes. Their sustainability is conditioned by the structure of learners as well as the teaching community. The experimental study was conducted among the distant learners of Vinayaka Missions University located at Salem in India. Students were drawn from multicultural environment based on different languages, religions, class and communities. During the mobile learning sessions, the students, who are divided on language, religion, class and community, were dominated by play impulse rather than study anxiety or cultural inhibitions. This study confirmed that mobile learning improved the performance of the students despite their division based on region, language or culture. In other words, technology was able to transcend the relative deprivation in the multicultural groups. It also confirms sustainable e-education through mobile learning and cost-effective system of instruction. Mobile learning appropriates the self-motivation and play impulse of the young learners in providing sustainable e-education to multicultural social groups of students.

Keywords: E-Education, mobile learning, multiculturalism.

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Authors: Nazar Zaki, Safaai Deris, Hany Alashwal

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Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.

Keywords: Protein-Protein Interaction, support vector machine, feature extraction, pairwise alignment, Smith-Waterman score.

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Authors: Ashly Joseph, Jithu Paulose

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The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.

Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.

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Authors: Kanika Sood, Sijie Shang

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A fundamental goal of education includes preparing students to become a part of the global workforce by making beneficial contributions to society. In this paper, we analyze student performance for multiple courses that involve different teaching pedagogies: a cooperative learning technique and an inquiry-based learning strategy. Student performance includes student engagement, grades, and attendance records. We perform this study in the Computer Science department for online and in-person courses for 450 students. We will perform correlation analysis to study the relationship between student scores and other parameters such as gender, mode of learning. We use natural language processing and machine learning to analyze student feedback data and performance data. We assess the learning outcomes of two teaching pedagogies for undergraduate and graduate courses to showcase the impact of pedagogical adoption and learning outcome as determinants of academic achievement. Early findings suggest that when using the specified pedagogies, students become experts on their topics and illustrate enhanced engagement with peers.

Keywords: Bag-of-words, cooperative learning, education, inquiry-based learning, in-person learning, Natural Language Processing, online learning, sentiment analysis, teaching pedagogy.

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Authors: N. Khiati

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The present paper attempts to report on some findings that emerged out of a larger scale doctorate research into English language needs of a renowned Algerian company of Hydrocarbon industry. From a multifaceted English for specific purposes (ESP) research perspective, the paper considers the English needs of the finance/legal department staff in the midst of the conflicting needs perspectives involving both objective needs indicators (i.e., the pressure of globalised business) and the general negative attitudes among the administrative -mainly jurists- staff towards English (favouring a non-adaptation strategy). The researcher’s unearthing of the latter’s needs is an endeavour to concretise the concepts of unmet, or unconscious needs, among others. This is why, these initially uncovered hidden needs will be detailed questioning educational background, namely previous language of instruction; training experiences and expectations; as well as the actual communicative practices derived from the retrospective interviews and preliminary quantitative data of the questionnaire. Based on these rough clues suggesting real needs, the researcher will tentatively propose some implications for both pre-service and in-service training organisers as well as for educational policy makers in favour of an English course in legal English for the jurists mainly from pre-graduate phases to in-service training.

Keywords: English for specific purposes, ESP, legal and finance staff, needs analysis, unmet/unconscious needs, training implications.

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Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

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Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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Authors: Azizeh Chalak, Firouzeh Baktash

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Reticence is a prominent and complex phenomenon which occurs in foreign language classrooms and influences students’ oral passivity. The present study investigated the extent in which students experience reticence in the EFL classrooms and explored the underlying factors triggering reticence. The participants were 104 Iranian freshmen undergraduate male and female EFL students, who enrolled in listening and speaking courses, all majoring in English studying at Islamic Azad University Isfahan (Khorasgan) Branch and University of Isfahan, Isfahan, Iran. To collect the data, the Reticence Scale-12 (RS-12) questionnaire which measures the level of reticence consisting of six dimensions (anxiety, knowledge, timing, organization, skills, and memory) was administered to the participants. The statistical analyses showed that the reticent level was high among the Iranian EFL undergraduate students, and their major problems were feelings of anxiety and delivery skills. Moreover, the results revealed that factors such as low English proficiency, the teaching method, and lack of confidence contributed to the students’ reticence in Iranian EFL classrooms. It can be implied that language teachers’ awareness of learners’ reticence can help them choose more appropriate activities and provide a friendly environment enhancing hopefully more effective participation of EFL learners. The findings can have implications for EFL teachers, learners and policy makers.

Keywords: Reticence, reticence scale, anxiety, Iranian EFL learners.

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Authors: F. Habibi Tirtash, M. Keshavarzi, F. Fazeli

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The genus Fumaria L. (Papaveraceae) in Iran comprises 8 species with a vast medicinal use in Asian folk medicine. These herbs are considered to be useful in the treatment of gastrointestinal disease and skin disorders. Antioxidant activities of alkaloids and phenolic extracts of these species had been studied previously. These species are: F. officinalis, F. parviflora, F. asepala, F. densiflora, F. schleicheri, F. vaillantii and F. indica. More than 50 populations of Fumaria species were sampled from nature. In this study different fatty acids are extracted. Their picks were recorded by GC technique. This species contain some kind of fatty acids with antioxidant effects. A part of these lipids are phospholipids. As these are unsaturated fatty acids they may have industrial use as natural additive to cosmetics, dermal and oral medicines. The presences of different materials are discussed. Our studies for antioxidant effects of these substances are continued.

Keywords: Fumaria, Papaveraceae, fatty acid, antioxidant, Iran

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Authors: Sankalp Devanand, Prateek Agasimani, V. S. Shamith, Rohith Neeraje

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Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English to Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity etc.

Keywords: Machine translation, English to Sanskrit, natural language processing, word meaning retrieval, FastText embeddings.

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Authors: A. Knezović

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21st century has transformed the labor market landscape in a way of posing new and different demands on university graduates as well as university lecturers, which means that the knowledge and academic skills students acquire in the course of their studies should be applicable and transferable from the higher education context to their future professional careers. Given the context of the Languages for Specific Purposes (LSP) classroom, the teachers’ objective is not only to teach the language itself, but also to prepare students to use that language as a medium to develop generic skills and competences. These include media and information literacy, critical and creative thinking, problem-solving and analytical skills, effective written and oral communication, as well as collaborative work and social skills, all of which are necessary to make university graduates more competitive in everyday professional environments. On the other hand, due to limitations of time and large numbers of students in classes, the frequently topic-centered syllabus of LSP courses places considerable focus on acquiring the subject matter and specialist vocabulary instead of sufficient development of skills and competences required by students’ prospective employers. This paper intends to explore some of those issues as viewed both by LSP lecturers and by business professionals in their respective surveys. The surveys were conducted among more than 50 LSP lecturers at higher education institutions in Croatia, more than 40 HR professionals and more than 60 university graduates with degrees in economics and/or business working in management positions in mainly large and medium-sized companies in Croatia. Various elements of LSP course content have been taken into consideration in this research, including reading and listening comprehension of specialist texts, acquisition of specialist vocabulary and grammatical structures, as well as presentation and negotiation skills. The ability to hold meetings, conduct business correspondence, write reports, academic texts, case studies and take part in debates were also taken into consideration, as well as informal business communication, business etiquette and core courses delivered in a foreign language. The results of the surveys conducted among LSP lecturers will be analyzed with reference to what extent those elements are included in their courses and how consistently and thoroughly they are evaluated according to their course requirements. Their opinions will be compared to the results of the surveys conducted among professionals from a range of industries in Croatia so as to examine how useful and important they perceive the same elements of the LSP course content in their working environments. Such comparative analysis will thus show to what extent the syllabi of LSP courses meet the demands of the employment market when it comes to the students’ language skills and competences, as well as transferable skills. Finally, the findings will also be compared to the observations based on practical teaching experience and the relevant sources that have been used in this research. In conclusion, the ideas and observations in this paper are merely open-ended questions that do not have conclusive answers, but might prompt LSP lecturers to re-evaluate the content and objectives of their course syllabi.

Keywords: Languages for specific purposes (LSP), language skills, topic-centered syllabus, transferable skills.

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Authors: O. F. Elkommos

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“Humour studies” is an interdisciplinary research area that is relatively recent. It interests researchers from the disciplines of psychology, sociology, medicine, nursing, in the work place, gender studies, among others, and certainly teaching, language learning, linguistics, and literature. Linguistic theories of humour research are numerous; some of which are of interest to the present study. In spite of the fact that humour courses are now taught in universities around the world in the Egyptian context it is not included. The purpose of the present study is two-fold: to review the state of arts and to show how linguistic theories of humour can be possibly used as an art and craft of teaching and of learning in EFL literature classes. In the present study linguistic theories of humour were applied to selected literary texts to interpret humour as an intrinsic artistic communicative competence challenge. Humour in the area of linguistics was seen as a fifth component of communicative competence of the second language leaner. In literature it was studied as satire, irony, wit, or comedy. Linguistic theories of humour now describe its linguistic structure, mechanism, function, and linguistic deviance. Semantic Script Theory of Verbal Humor (SSTH), General Theory of Verbal Humor (GTVH), Audience Based Theory of Humor (ABTH), and their extensions and subcategories as well as the pragmatic perspective were employed in the analyses. This research analysed the linguistic semantic structure of humour, its mechanism, and how the audience reader (teacher or learner) becomes an interactive interpreter of the humour. This promotes humour competence together with the linguistic, social, cultural, and discourse communicative competence. Studying humour as part of the literary texts and the perception of its function in the work also brings its positive association in class for educational purposes. Humour is by default a provoking/laughter-generated device. Incongruity recognition, perception and resolving it, is a cognitive mastery. This cognitive process involves a humour experience that lightens up the classroom and the mind. It establishes connections necessary for the learning process. In this context the study examined selected narratives to exemplify the application of the theories. It is, therefore, recommended that the theories would be taught and applied to literary texts for a better understanding of the language. Students will then develop their language competence. Teachers in EFL/ESL classes will teach the theories, assist students apply them and interpret text and in the process will also use humour. This is thus easing students' acquisition of the second language, making the classroom an enjoyable, cheerful, self-assuring, and self-illuminating experience for both themselves and their students. It is further recommended that courses of humour research studies should become an integral part of higher education curricula in Egypt.

Keywords: ABTH, deviance, disjuncture, episodic, GTVH, humour competence, humour comprehension, humour in the classroom, humour in the literary texts, humour research linguistic theories, incongruity- resolution, isotopy-disjunction, jab line, longer text joke, narrative story line (macro-micro), punch line, six knowledge resource, SSTH, stacks, strands, teaching linguistics, teaching literature, TEFL, TESL.

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Authors: Aghamusa Azizov

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This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: Solar Activity Correlation, Media Sentiment Analysis, Natural Language Processing, NLP, Historical Event Patterns.

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Authors: Safwa Yargui

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This research is about the quest for a post-war American epic poem in the age of late capitalism. This paper explores the possibility of an epic poem in the context of post-war late capitalist America, despite the prevailing scholarly scepticism regarding the existence of epic poetry after Milton’s Paradise Lost. The aim of this paper is to demonstrate the possibility of a post-war American epic through the argument of epic consciousness by distinguishing the scholarly views on the impossibility of an epic poem and the counterargument of epic consciousness which contends that American epic poetry is possible. Epic consciousness provides a significant nuance to the reading of the post-war American epic by focusing on the epic’s responsiveness to late capitalism, via various language forms; cultural manifestations; and conscious distortions of late capitalist media-related language; in addition to the epic’ conscious inclusion of the process of writing a post-war epic that requires a direct engagement with American-based materials. By focusing on interdisciplinary theoretical approaches, this paper includes both socio-cultural literary theories as well as literary and epic approaches developed by scholars that respectively contextualise the late capitalist situation and the question of post-war American epic poetry. In examining the role of consciousness, this paper aims to suggest a re-thinking of the post-war American epic that is capable of self-commitment, for the purpose of achieving a new sense of epic poetry in post-war late capitalist America.

Keywords: American epic, epic consciousness, late capitalism, post-war poetry.

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Authors: Marcia T. Mitchell

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This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Keywords: Natural language understanding, computational linguistics, knowledge representation, linguistic theories.

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Authors: A. Chirita, L. Alexandru, D. Marcoci, C. Ene-Draghici

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Minor law breaking seems more and more to be a part of adolescence behavior. An important risk factor which seems to influence delinquency appears to be the socio-economic one. According to Romanian statistics, during the first six months of 2012, 1,378 minors have committed various crimes, the most common being theft, sexual offenses and violent assaults. Drug-related offenses did not reach the gravity of those from high income countries of the European Union, but have a continuous upward during the last years. The aim of our research was to examine whether delinquency in adolescence is correlated to mental disorders or socio-economic and familial factors. Forensic psychiatric expertise was performed to 79 adolescents who committed offenses between 01 January 2012 and 31 December 2012. Teenagers, with ages between 12 and 17, were examined by day hospitalization in the University Clinic of Psychiatry Craiova.

Keywords: Adolescents, criminal behavior, mental illness.

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Authors: Adnan Z. Mkhelif

Abstract:

The production of number forms in English tends to be problematic for Iraqi learners of English as a foreign language (EFL), even at the undergraduate level. To help better understand and consequently address this problem, it is important to identify its sources. This study aims at: (1) statistically analysing Iraqi EFL undergraduates' performance in the production of number forms in English; (2) classifying learners' errors in terms of their possible major causes; and (3) outlining some pedagogical recommendations relevant to the teaching of number forms in English. It is hypothesized in this study that (1) Iraqi EFL undergraduates still face problems in the production of number forms in English and (2) errors pertaining to the context of learning are more numerous than those attributable to the other possible causes. After reviewing the literature available on the topic, a written test comprising 50 items has been constructed and administered to a randomly chosen sample of 50 second-year college students from the Department of English, College of Education, Wasit University. The findings of the study showed that Iraqi EFL undergraduates still face problems in the production of number forms in English and that the possible major sources of learners’ errors can be arranged hierarchically in terms of the percentages of errors to which they can be ascribed as follows: (1) context of learning (50%), (2) intralingual transfer (37%), and (3) interlingual transfer (13%). It is hoped that the implications of the study findings will be beneficial to researchers, syllabus designers, as well as teachers of English as a foreign/second language.

Keywords: L2 morphology, L2 number forms, L2 vocabulary learning, productive knowledge.

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Authors: Mona Soliman Habib

Abstract:

This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features. The performance results of a set of experiments conducted using binary and multi-class SVM with increasing training data sizes are examined. The NER domain chosen for these experiments is the biomedical publications domain, especially selected due to its importance and inherent challenges. A simple machine learning approach is used that eliminates prior language knowledge such as part-of-speech or noun phrase tagging thereby allowing for its applicability across languages. No domain-specific knowledge is included. The accuracy measures achieved are comparable to those obtained using more complex approaches, which constitutes a motivation to investigate ways to improve the scalability of multiclass SVM in order to make the solution more practical and useable. Improving training time of multi-class SVM would make support vector machines a more viable and practical machine learning solution for real-world problems with large datasets. An initial prototype results in great improvement of the training time at the expense of memory requirements.

Keywords: Named entity recognition, support vector machines, language independence, bioinformatics.

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Authors: Ahmet Kurnaz, Eyup Yurt, Ümit Çiftci

Abstract:

In this study, too, an attempt was made to reveal the place and effects of information technologies on the lives and education of gifted children based on the views of gifted. To this end, the effects of information technologies on gifted are general skills, technology use, academic and social skills, and cooperative and personal skills were investigated. These skills were explored depending on whether or not gifted had their own computers, had internet connection at home, or how often they use the internet, average time period they spent at the computer, how often they played computer games and their use of social media. The study was conducted using the screening model with a quantitative approach. The sample of the study consisted of 129 gifted attending 5-12th classes in 12 provinces in different regions of Turkey. 64 of the participants were female while 65 were male. The research data were collected using the using computer of gifted and information technologies (UCIT) questionnaire which was developed by the researchers and given its final form after receiving expert view. As a result of the study, it was found that UCIT use improved foreign language speaking skills of gifted, enabled them to get to know and understand different cultures, and made use of computer and information technologies while they study. At the end of the study these result were obtained: Gifted have positive idea using computer and communication technology. There are differences whether using the internet about the ideas UCIT. But there are not differences whether having computer, inhabited city, grade level, having internet at home, daily and weekly internet usage durations, playing the computer and internet game, having Facebook and Twitter account about the UCIT. UCIT contribute to the development of gifted vocabulary, allows knowing and understand different cultures, developing foreign language speaking skills, gifted do not give up computer when they do their homework, improve their reading, listening, understanding and writing skills in a foreign language. Gifted children want to have transition to the use of tablets in education. They think UCIT facilitates doing their homework, contributes learning more information in a shorter time. They'd like to use computer-assisted instruction programs at courses. They think they will be more successful in the future if their computer skills are good. But gifted students prefer teacher instead of teaching with computers and they said that learning can be run from home without going to school.

Keywords: Gifted, using computer, communication technology.

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Authors: Regius Asiimwe, Amir Anvar

Abstract:

This paper describes the process used in the automation of the Maritime UAV commands using the Kinect sensor. The AR Drone is a Quadrocopter manufactured by Parrot [1] to be controlled using the Apple operating systems such as iPhones and Ipads. However, this project uses the Microsoft Kinect SDK and Microsoft Visual Studio C# (C sharp) software, which are compatible with Windows Operating System for the automation of the navigation and control of the AR drone. The navigation and control software for the Quadrocopter runs on a windows 7 computer. The project is divided into two sections; the Quadrocopter control system and the Kinect sensor control system. The Kinect sensor is connected to the computer using a USB cable from which commands can be sent to and from the Kinect sensors. The AR drone has Wi-Fi capabilities from which it can be connected to the computer to enable transfer of commands to and from the Quadrocopter. The project was implemented in C#, a programming language that is commonly used in the automation systems. The language was chosen because there are more libraries already established in C# for both the AR drone and the Kinect sensor. The study will contribute toward research in automation of systems using the Quadrocopter and the Kinect sensor for navigation involving a human operator in the loop. The prototype created has numerous applications among which include the inspection of vessels such as ship, airplanes and areas that are not accessible by human operators.

Keywords: UAV, AR drone, Kinect Sensors, Automation, Real time, C sharp, Microsoft Kinect SDK.

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Authors: Saeedeh Shafiee Nahrkhalaji

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Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.

Keywords: Metacognotive Knowledge, Pedagogical Performance, Language Teacher Characteristics Questionnaire, Metacognitive Awareness Inventory.

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Authors: Nebi Gedik

Abstract:

One of the important parts of the brain-computer interface (BCI) studies is the classification of motor imagery (MI) obtained by electroencephalography (EEG). The major goal is to provide non-muscular communication and control via assistive technologies to people with severe motor disorders so that they can communicate with the outside world. In this study, an EEG signal classification approach based on multiscale and multi-resolution transform method is presented. The proposed approach is used to decompose the EEG signal containing motor image information (right- and left-hand movement imagery). The decomposition process is performed using curvelet transform which is a multiscale and multiresolution analysis method, and the transform output was evaluated as feature data. The obtained feature set is subjected to feature selection process to obtain the most effective ones using t-test methods. SVM and k-NN algorithms are assigned for classification.

Keywords: motor imagery, EEG, curvelet transform, SVM, k-NN

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Authors: Min-Chuan Huang, I-Ping Chen, Shu-Ying Chung

Abstract:

Taking the medical staff in an emergency ward of a medical center in Central Taiwan as the research object, the questionnaire data were collected by anonymous and voluntary reporting methods with structured questionnaires to explore organ donation’s actual situation, willingness, and attitude. Only 80 valid questionnaires were gathered. Of the 8 questions, the correct mean rate was 5.9 and the correct rate was 73.13%. According to the statistics of organ donation survey, only 8.7% have signed the consent for organ donation, 21.3% are willing but have not yet signed the consent for organ donation, 62.5% have not yet decided, and 7.5% are unwilling. The average total score (standard deviation) of attitude towards organ donation was 36.2. There is no significant difference between the demographic variables and the awareness and willingness of organ donation, but there is a significant correlation between marital status and the attitude toward organ donation.

Keywords: clinical psychology, organ donation, factors affecting psychological disorders, commitment

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