Search results for: large language models

Authors: Richard Fairchild, Abdullah Al-Ghazali, Yilmaz Guney

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This study analyses the relationship between managerial overconfidence, dividends, and firm value by developing theoretical models that examine the condition under which managerial overconfident, dividends, and firm value may be positive or negative. Furthermore, the models incorporate moral hazard, in terms of managerial effort shirking, and the potential for the manager to choose negative NPV projects, due to private benefits. Our models demonstrate that overconfidence can lead to higher dividends (when the manager is overconfident about his current ability) or lower dividends (when the manager is overconfident about his future ability). The models also demonstrate that higher overconfidence may result in an increase or a decrease in firm value. Numerical examples are illustrated for both models which interestingly support the models’ propositions.

Keywords: behavioural corporate finance, dividend policy, overconfidence, moral hazard

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Authors: Azadeh Jafari, Robert G. Owens

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In this study, a geometrical multiscale approach which means coupling together the 2-D Navier-Stokes equations, constitutive equations and 0-D lumped parameter models is investigated. A multiscale approach, suggest a natural way of coupling detailed local models (in the flow domain) with coarser models able to describe the dynamics over a large part or even the whole cardiovascular system at acceptable computational cost. In this study we introduce a new velocity correction scheme to decouple the velocity computation from the pressure one. To evaluate the capability of our new scheme, a comparison between the results obtained with Neumann outflow boundary conditions on the velocity and Dirichlet outflow boundary conditions on the pressure and those obtained using coupling with the lumped parameter model has been performed. Comprehensive studies have been done based on the sensitivity of numerical scheme to the initial conditions, elasticity and number of spectral modes. Improvement of the computational algorithm with stable convergence has been demonstrated for at least moderate Weissenberg number. We comment on mathematical properties of the reduced model, its limitations in yielding realistic and accurate numerical simulations, and its contribution to a better understanding of microvascular blood flow. We discuss the sophistication and reliability of multiscale models for computing correct boundary conditions at the outflow boundaries of a section of the cardiovascular system of interest. In this respect the geometrical multiscale approach can be regarded as a new method for solving a class of biofluids problems, whose application goes significantly beyond the one addressed in this work.

Keywords: geometrical multiscale models, haemorheology model, coupled 2-D navier-stokes 0-D lumped parameter modeling, computational fluid dynamics

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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: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

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Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: cross-language analysis, machine learning, machine translation, sentiment analysis

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Authors: M. A. N. Masrom, M. H. I. A. Rahim, G. K. Chen, S. Mohamed

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Large infrastructure project is one of significant category in the development of Malaysian construction industry. This type of project has been recognized as a high complexity project with numerous construction risks, large cost involvement, highly technical requirements and divers of resources. Besides, the development of large infrastructure such as highway, railway, Mass Rapid Transit (MRT) and airport are also needed a large investment of public and private sector. To accomplish the development successfully, several challenges has to be determined prior the project commencement. To date, a comprehensive assessment of key success criteria particularly for large infrastructure in developing country such as Malaysia, is still not systematically defined and therefore, it needs further investigation. This paper aims to explore the potential success criteria that would be useful in gauging overall performance of large infrastructure implementation particularly in developing country. Previous successful criteria studies were used to develop a conceptual framework that possibly suitable for measuring large infrastructure performance. The findings show that successful criteria of infrastructure projects implementation could be grouped according to several key elements as it seems significant to the participants in prioritizing project challenges more systematically.

Keywords: successful criteria, performance, large infrastructure, Malaysia

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Authors: Md. Abud Darda

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Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability.

Keywords: diffusion models, energy forecast, natural gas, nonlinear production

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Authors: Mikel Alonso López

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In order to begin the process of studying the task of making consumer decisions, the main decision models must be analyzed. The objective of this task is to see if there is a presence of emotions in those models, and analyze how authors that have created them consider their impact in consumer choices. In this paper, the most important models of consumer behavior are analysed. This review is useful to consider an unproblematic background knowledge in the literature. The order that has been established for this study is chronological.

Keywords: consumer behaviour, emotions, decision making, consumer psychology

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Authors: Elżbieta Turska

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Introduction: One of the most difficult times in a person’s life is adolescence. The experiences in this period may shape the future life of this person to a large extent. This is the reason why many young people experience sadness, dejection, hopelessness, sense of worthlessness, as well as losing interest in various activities and social relationships, all of which are often classified as mood disorders. As many as 15-40% adolescents experience depressed moods and for most of them they resolve and are not carried into adulthood. However, (5-6%) of those affected by mood disorders develop the depressive syndrome and as many as (1-3%) develop full-blown clinical depression. Materials: A large questionnaire was given to 2508 students, aged 13–16 years old, and one of its parts was the Burns checklist, i.e. the standard test for identifying depressed mood. The questionnaire asked about many aspects of the student’s life, it included a total of 53 questions, most of which had subquestions. It is important to note that the data suffered from many problems, the most important of which were missing data and collinearity. Aim: In order to identify the correlates of mood disorders we built predictive models which were then trained and validated. Our aim was not to be able to predict which students suffer from mood disorders but rather to explore the factors influencing mood disorders. Methods: The problems with data described above practically excluded using all classical statistical methods. For this reason, we attempted to use the following Artificial Intelligence (AI) methods: classification trees with surrogate variables, random forests and xgboost. All analyses were carried out with the use of the mlr package for the R programming language. Resuts: The predictive model built by classification trees algorithm outperformed the other algorithms by a large margin. As a result, we were able to rank the variables (questions and subquestions from the questionnaire) from the most to least influential as far as protection against mood disorder is concerned. Thirteen out of twenty most important variables reflect the relationships with parents. This seems to be a really significant result both from the cognitive point of view and also from the practical point of view, i.e. as far as interventions to correct mood disorders are concerned.

Keywords: mood disorders, adolescents, family, artificial intelligence

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Authors: Silvia Hvozdíková, Eva Stranovská

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The purpose of the article is to discuss the results of the research conducted during the period of two semesters paying attention to selected factors of foreign language reading comprehension through the means of Linguistic Intervention Program. The Linguistic Intervention Program was designed for the purpose of the current research. It refers to such method of foreign language teaching which emphasized active social learning, creative drama strategies, self-directed learning. The research sample consisted of 360 respondents, foreign language learners ranging from 13 – 17 years of age. Specifically designed questionnaire and a standardized foreign language reading comprehension tests were applied to serve the purpose. The outcomes of the research recorded significant results towards significant relationship between selected elements of the Linguistic Intervention Program and the academic achievements in the factors of reading comprehension.

Keywords: foreign language learning, linguistic intervention program, reading comprehension, social learning

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Authors: Sugandhi, Parteek Kumar, Sanmeet Kaur

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Sign Language (SL) is used by deaf and other people who cannot speak but can hear or have a problem with spoken languages due to some disability. It is a visual gesture language that makes use of either one hand or both hands, arms, face, body to convey meanings and thoughts. SL automation system is an effective way which provides an interface to communicate with normal people using a computer. In this paper, an avatar based dictionary has been proposed for text to Indian Sign Language (ISL) generation system. This research work will also depict a literature review on SL corpus available for various SL s over the years. For ISL generation system, a written form of SL is required and there are certain techniques available for writing the SL. The system uses Hamburg sign language Notation System (HamNoSys) and Signing Gesture Mark-up Language (SiGML) for ISL generation. It is developed in PHP using Web Graphics Library (WebGL) technology for 3D avatar animation. A multilingual ISL dictionary is developed using HamNoSys for both English and Hindi Language. This dictionary will be used as a database to associate signs with words or phrases of a spoken language. It provides an interface for admin panel to manage the dictionary, i.e., modification, addition, or deletion of a word. Through this interface, HamNoSys can be developed and stored in a database and these notations can be converted into its corresponding SiGML file manually. The system takes natural language input sentence in English and Hindi language and generate 3D sign animation using an avatar. SL generation systems have potential applications in many domains such as healthcare sector, media, educational institutes, commercial sectors, transportation services etc. This research work will help the researchers to understand various techniques used for writing SL and generation of Sign Language systems.

Keywords: avatar, dictionary, HamNoSys, hearing impaired, Indian sign language (ISL), sign language

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Authors: Jiao Li

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Language teachers have been expected to play diversified new roles in times of educational changes. Considering the critical role that materials play in teaching and learning, language teachers have been increasingly involved in developing materials. Using identity as an analytic lens, this study aims to explore language teachers’ experiences as materials developers in China, focusing on the challenges they face and responses to them. It will adopt a multimethod approach. At the first stage, about 12 language teachers who have developed or are developing materials will be interviewed to have a broad view of their experiences. At the second stage, three language teachers who are developing materials will be studied by collecting interview data, policy documents, and data obtained from online observation of their group meetings so as to gain a deeper understanding of their experiences in materials development. It is expected that this study would have implications for teacher development, materials development, and curriculum development as well.

Keywords: educational changes, teacher development, teacher identity, teacher learning, materials development

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Authors: S. Tarighat, F. Shateri

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This study explored the relationship between L2 Willingness to Communicate (WTC) of bilinguals and monolinguals in a foreign language using a snowball sampling method to collect questionnaire data from 200 bilinguals and monolinguals studying a foreign language (FL). The results indicated a higher willingness to communicate in a foreign language (WTC-FL) performed by bilinguals compared to that of the monolinguals with a weak significance. Yet a stronger significance was found in the relationship between the age of onset of bilingualism and WTC-FL. The researcher proposed that L2 WTC is indirectly influenced by knowledge of other languages, which can boost L2 confidence and reduce L2 anxiety and consequently lead to higher L2 WTC when learning a different L2. The study also found the age of onset of bilingualism to be a predictor of L2 WTC when learning a FL. The results emphasize the importance of bilingualism and early bilingualism in particular.

Keywords: bilingualism, foreign language learning, l2 acquisition, willingness to communicate

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Authors: Sajjad Hussain

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Technology has revolutionized the way of communication around the globe. Its use and users are multiplying with every passing minute. The current study reveals the effect of SMS on the formal writing of the students. Students are the regular users of this service and have become addict to short language. This short language is understandable to a particular community and not to the whole as it does not adhere to the Standard English writing practices. Data has been collected from quiz, assignments text and through questionaries’ which supports this postulate that students are frequently practicing it in their formal writing. Certain corrosive measures needs to be taken to address the issue. Second language learners have been found it practicing to greater extent.

Keywords: information technology, SMS, messaging, communication, social media, internet, language

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Authors: Vishal D. Pandya

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A great deal of perceptible change has been taking place in the way our institutions of higher learning are being managed in India today. It is believed that managers, whose intuition proves to be accurate, often tend to be the most successful, and this is what makes them almost like entrepreneurs. A certain entrepreneurial spirit is what is expected and requires a degree of insight of the manager to be successful depending upon the situational and more importantly, the heterogeneity as well as the socio-cultural aspect. Teachers in Higher Education have to play multiple roles to make sure that the Learning-Teaching process becomes effective in the real sense of the term. This paper makes an effort to take a close look at that, especially in the context of the management of English language teaching in Higher Education and, therefore, focuses on the management of English language teaching in higher education by understanding target situation analyses at the socio-cultural level.

Keywords: management, language teaching, English language teaching, higher education

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Authors: Masood Varshosaz, Kamyar Hasanpour

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In recent years, we have seen growing interest in recognizing humans in drone images for post-disaster search and rescue operations. Deep learning algorithms have shown great promise in this area, but they often require large amounts of labeled data to train the models. To keep the data acquisition cost low, augmentation techniques can be used to create additional data from existing images. There are many techniques of such that can help generate variations of an original image to improve the performance of deep learning algorithms. While data augmentation is potentially assumed to improve the accuracy and robustness of the models, it is important to ensure that the performance gains are not outweighed by the additional computational cost or complexity of implementing the techniques. To this end, it is important to evaluate the impact of data augmentation on the performance of the deep learning models. In this paper, we evaluated the most currently available 2D data augmentation techniques on a standard convolutional network which was trained for recognizing humans in drone images. The techniques include rotation, scaling, random cropping, flipping, shifting, and their combination. The results showed that the augmented models perform 1-3% better compared to a base network. However, as the augmented images only contain the human parts already visible in the original images, a new data augmentation approach is needed to include the invisible parts of the human body. Thus, we suggest a new method that employs simulated 3D human models to generate new data for training the network.

Keywords: human recognition, deep learning, drones, disaster mitigation

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Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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Authors: Raluca-Ioana Antonescu

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The field research of the paper stands at the intersection between Linguistics and Sociology, while the problem of the research is the importance of language in the modernization process and in a globalized society. The research objective is to prove that language is a stimulant for modernity, while it defines the tradition and the culture of a specific society. In order to examine the linguistic change of the Korean language due to the modernity and globalization, the paper tries to answer one main question, What are the changes the Korean language underwent from a traditional version of Korean, towards one influenced by modernity?, and two secondary questions, How are explored in specialized literature the relations between globalization (and modernity) and culture (focusing on language)? and What influences the Korean language? For the purpose of answering the research questions, the paper has the main premise that due to modernity and globalization, the Korean language changed its discourse construction, and two secondary hypothesis, first is that in literature there are not much explored the relations between culture and modernity focusing on the language discourse construction, but more about identity issue and commodification problems, and the second hypothesis is that the Korean language is influenced by traditional values (like Confucianism) while receiving influence also of globalization process (especially from English language). In terms of methodology, the paper will analyze the two main influences upon the Korean language, referring to traditionalism (being defined as the influence of Confucianism) and modernism (as the influence of other countries’ language and culture), and how the Korean language it was constructed and modified due to these two elements. The paper will analyze at what level (grammatical, lexical, etc.) the traditionalism help at the construction of the Korean language, and what are the changes at each level that modernism brought along. As for the results of this research, the influence of modernism changed both lexically and grammatically the Korean language. In 60 years the increase of English influence is astonishing, and this paper shows the main changes the Korean language underwent, like the loanwords (Konglish), but also the reduction of the speech levels and the ease of the register variation use. Therefore the grammatical influence of modernity and globalization could be seen at the reduction of the speech level and register variation, while the lexical change comes with the influence of English language especially, where about 10% of the Korean vocabulary is considered to be loanwords. Also the paper presents the interrelation between traditionalism and modernity, with the example of Konglish, but not only (we can consider also the Korean greetings which are translated by Koreans when they speak in other languages, bringing their cultural characteristics in English discourse construction), which makes the Koreans global, since they speak in an international language, but still local since they cannot get rid completely of their culture.

Keywords: Confucianism, globalization, language and linguistic change, modernism, traditionalism

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Authors: Dennis Kreutzer, Sarah Müller-Abdelrazeq, Ingrid Isenhardt

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Resource scarcity, energy transition and the planned climate neutrality pose enormous challenges for manufacturing companies. In order to achieve these goals and a holistic sustainable development, the European Union has listed the circular economy as part of the Circular Economy Action Plan. In addition to a reduction in resource consumption, reduced emissions of greenhouse gases and a reduced volume of waste, the principles of the circular economy also offer enormous economic potential for companies, such as the generation of new circular business models. However, many manufacturing companies, especially small and medium-sized enterprises, do not have the necessary capacity to plan their transformation. They need support and strategies on the path to circular transformation, because this change affects not only production but also the entire company. Maturity models offer an approach, as they enable companies to determine the current status of their transformation processes. In addition, companies can use the models to identify transformation strategies and thus promote the transformation process. While maturity models are established in other areas, e.g. IT or project management, only a few circular economy maturity models can be found in the scientific literature. The aim of this paper is to analyse the identified maturity models of the circular economy through a systematic literature review (SLR) and, besides other aspects, to check their completeness as well as their quality. Since the terms "maturity model" and "readiness model" are often used to assess the transformation process, this paper considers both types of models to provide a more comprehensive result. For this purpose, circular economy maturity models at the company (micro) level were identified from the literature, compared, and analysed with regard to their theoretical and methodological structure. A specific focus was placed, on the one hand, on the analysis of the business units considered in the respective models and, on the other hand, on the underlying metrics and indicators in order to determine the individual maturity level of the entire company. The results of the literature review show, for instance, a significant difference in the holism of their assessment framework. Only a few models include the entire company with supporting areas outside the value-creating core process, e.g. strategy and vision. Additionally, there are large differences in the number and type of indicators as well as their metrics. For example, most models often use subjective indicators and very few objective indicators in their surveys. It was also found that there are rarely well-founded thresholds between the levels. Based on the generated results, concrete ideas and proposals for a research agenda in the field of circular economy maturity models are made.

Keywords: maturity model, circular economy, transformation, metric, assessment

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Maaly Jarrah

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In a study abroad context, students have the advantage of immersing themselves in the environment of the target language and being exposed to it. However, in and a stay home context, where English is not the mother tongue, students’ exposure to the second language is often times restricted to the classroom. Although language teachers are keen to develop inside class room activities and practices that increase the suitability of students to acquire a second language (Cook & Singleton, 2014), many would agree that class time is too limited to enhance students’ oral fluency skills. Consequently, creating opportunities outside the classroom for students to speak English is an effective strategy in compensating for students’ limited use of the L2. In an argument by Ortega (2012) external classroom activities have equal significance in enabling students learn English as a second language. The author further asserts that the activities provide a non-educational environment from which a student may feel free and comfortable to acquire new language skills. This study investigates the significance of outside classroom activities in promoting students’ oral proficiency. In addition, it reports on students’ perceptions of such activities. 15 participants from the American University of Kuwait took part in this study. Open-ended interviews were done to find out what the participants thought of these activities, and what they gained from them. Interview results show that students found outside classroom activities very effective in improving not only their oral fluency skills, but their confidence and critical thinking skills as well. The implications of this research study are for language practitioners and language programs in the EFL context to be aware of the benefits of incorporating outside classroom activities in language teaching.

Keywords: language teaching, oral fluency, outside classroom activities

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Authors: S. Yordchim, G. Anugkakul, T. Gibbs

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The English competence of Thai people was examined in the context of knowledge of English in everyday life for SME entrepreneurs, and also integrated with SLA students’ classroom. Second language acquisition was applied to the results of the questionnaires and interview forms. Levels of the need on English used for SME entrepreneurs in Thailand, satisfaction on joining the street classroom project were shown to be significantly high for some certain language functions and satisfaction. Finding suggests that the language functions on etiquette for professional use is essential and useful because lesson learned can be used in the real situation for their career. Implications for the climate of the street classroom are discussed.

Keywords: English classroom, SME entrepreneurs, second language acquisition, Thai students

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Authors: Slim Namouchi, Bruno Vallet, Imed Riadh Farah

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3D urban models provide powerful tools for decision making, urban planning, and smart city services. The accuracy of this 3D based systems is directly related to the quality of these models. Since manual large-scale modeling, such as cities or countries is highly time intensive and very expensive process, a fully automatic 3D building generation is needed. However, 3D modeling process result depends on the input data, the proprieties of the captured objects, and the required characteristics of the reconstructed 3D model. Nowadays, producing 3D real-world model is no longer a problem. Remotely sensed data had experienced a remarkable increase in the recent years, especially data acquired using unmanned aerial vehicles (UAV). While the scanning techniques are developing, the captured data amount and the resolution are getting bigger and more precise. This paper presents a literature review, which aims to identify different methods of automatic 3D buildings extractions either from LiDAR or the combination of LiDAR and satellite or aerial images. Then, we present open source technologies, and data models (e.g., CityGML, PostGIS, Cesiumjs) used to integrate these models in geospatial base layers for smart city services.

Keywords: CityGML, LiDAR, remote sensing, SIG, Smart City, 3D urban modeling

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Authors: Samuel Ahamefula Mba

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Fluid turbulence is a complex and nonlinear phenomenon that occurs in various natural and industrial processes. Understanding turbulence remains a challenging task due to its intricate nature. One approach to gain insights into turbulence is through the study of entropy, which quantifies the disorder or randomness of a system. This research presents a numerical investigation of entropy signatures in fluid turbulence. The work is to develop a numerical framework to describe and analyse fluid turbulence in terms of entropy. This decomposes the turbulent flow field into different scales, ranging from large energy-containing eddies to small dissipative structures, thus establishing a correlation between entropy and other turbulence statistics. This entropy-based framework provides a powerful tool for understanding the underlying mechanisms driving turbulence and its impact on various phenomena. This work necessitates the derivation of the Poisson equation for pressure transformation of Navier-Stokes equation and using Chebyshev-Finite Difference techniques to effectively resolve it. To carry out the mathematical analysis, consider bounded domains with smooth solutions and non-periodic boundary conditions. To address this, a hybrid computational approach combining direct numerical simulation (DNS) and Large Eddy Simulation with Wall Models (LES-WM) is utilized to perform extensive simulations of turbulent flows. The potential impact ranges from industrial process optimization and improved prediction of weather patterns.

Keywords: turbulence, Navier-Stokes equation, Poisson pressure equation, numerical investigation, Chebyshev-finite difference, hybrid computational approach, large Eddy simulation with wall models, direct numerical simulation

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Authors: Ekin Ozer

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Assessment of structural reliability is essential for efficient use of civil infrastructure which is subjected hazardous events. Dynamic analysis of finite element models is a commonly used tool to simulate structural behavior and estimate its performance accordingly. However, theoretical models purely based on preliminary assumptions and design drawings may deviate from the actual behavior of the structure. This study proposes up-to-date reliability estimation procedures which engages actual bridge vibration data modifying finite element models for finite element model updating and performing reliability estimation, accordingly. The proposed method utilizes vibration response measurements of bridge structures to identify modal parameters, then uses these parameters to calibrate finite element models which are originally based on design drawings. The proposed method does not only show that reliability estimation based on updated models differs from the original models, but also infer that non-updated models may overestimate the structural capacity.

Keywords: earthquake engineering, engineering vibrations, reliability estimation, structural health monitoring

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Authors: Haira Rizka, Imas Istiani

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The way women and men use language is an interesting topic to discuss. Nowadays, Instagram shows many videos which illustrate the difference of women’s and men’s language. Furthermore, the videos show how different genders behave in daily communication. This research aims to (1) investigate conversational characteristics of women represented in Indonesian Instagram videos, and (2) investigate how different genders behave in daily communication. To analyze the two research problems, this research employs Tannen’s theory of language and gender (1996). This is a descriptive qualitative research which describes phenomena of language and gender shown in Indonesian Instagram videos. The data were collected through observation. The collected data were then analyzed by employing ethnography and textual analysis. The research results show that in Indonesian Instagram videos, women dominate the conversation than men. Women’s are portrayed as a figure who are talkative, never wrong, and sensitive. Women’s dominating men proves that women always want to be understood, produce more words than men, and are more creative in producing verbal communication. Meanwhile, men are portrayed as calm, gentle, and patient creature who listen to women’s talk. Furthermore, men are portrayed to prefer being silent for avoiding conflict.

Keywords: gender, Instagram videos, language variety, women's language

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Authors: Alfia Sari

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The implementation of the Content Language Integrated Learning (CLIL) approach in Indonesia has shown positive impacts in several educational institutions. Several studies have proven the benefits of implementing the CLIL approach, including the development of students’ language and content subject knowledge. Interestingly, one primary school in Surabaya, Indonesia, has been successfully implementing the CLIL approach. The students achieved high content and language subject scores, and the school was accredited A. A study on how the CLIL approach was practiced is important to investigate how teachers implemented it and how students benefited from it. Therefore, this present study attempted to investigate the implementation of the CLIL approach in this school to characterize good practices that can be implemented in other schools. A case study was conducted to observe its implementation in the third-grade classes (English, Science, and Math) by using the Protocol for Language Arts Teaching Observation (PLATO). The findings indicated that the CLIL teaching in this school accommodated the content and language well (scores 3-4). The content and language were clearly integrated, and the teachers successfully carried out the subjects in English. Teachers offered students opportunities to listen, speak, read, and write using the target language. This study described some characteristics of CLIL teaching in primary school that can be used as examples for future CLIL teachers to integrate the content and language in their teaching practices.

Keywords: CLIL, ELT, young learners, case study

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Authors: Farina Yasmin

Abstract:

Motivation is an important issue in an EFL setting where very little exposure to English in everyday life is clearly evident. In Bangladesh, English is taught as a foreign language. Language teachers cannot effectively teach a language if they do not understand the relationship between motivation and its effect on foreign language learning. The main purpose of this research is to explore the fact why HSC students are less motivated towards English language learning, what factors are affecting motivation, how to motivate them and the role of motivation in their success. The research questions were (a) what are the reasons of lack of motivation? and (b) what are the impacts of motivation on English language learning? The study was both qualitative and quantitative in nature. The data was collected via pretest - posttest, interviews, and a questionnaire on the five point Likert scale. Triangulation of the data was made for the validity of the research. The population of this research consisted of 50 HSC level students from Jatir Janak Bangabandhu Sheikh Mujibur Rahman Government College, Dhaka, Bangladesh. The data was analyzed with means, comparison and t-test. The results showed that there is a strong relation between motivation and success in foreign language learning. Finally, some pedagogical implications and suggestions were presented to arouse the students’ motivation to learn English.

Keywords: EFL, HSC, motivation, success

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

Abstract:

Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Vinai K. Singh

Abstract:

In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Divya Pande

Abstract:

The dynamics of culture expresses itself in language. Even after India got independence in 1947 English subtly crept in the language of the masses with a silent and powerful flow towards the vernacular. The culture contact resulted in learning and emergence of a new language across the Hindi speaking belt of Northern and Central India. The hybrid words thus formed displaced the original word and got contextualized and absorbed in the language of the common masses. The research paper explores the interesting new vocabulary used extensively in the urban and rural districts of the state of Uttar- Pradesh which is the most populous state of India. The paper adopts a two way classification- formal and contextual for the analysis of the hybrid vocabulary of the linguistic items where one element is necessarily from the English language and the other from the Hindi. The new vocabulary represents languages of the wider world cutting across the geographical and the cultural barriers. The paper also broadly points out to the Hinglish commonly used in the state.

Keywords: assimilation, culture contact, Hinglish, hybrid words

Procedia PDF Downloads 385