Search results for: large language models (LLMS)

Authors: Davide Forcellini, James Marshal Kelly

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Seismic isolation using multi-layer elastomeric isolators has been used in the United States for more than 20 years. Although isolation bearings normally have a large factor of safety against buckling due to low shear stiffness, this phenomenon has been widely studied. In particular, the linearly elastic theory adopted to study this phenomenon is relatively accurate and adequate for most design purposes. Unfortunately it cannot consider the large deformation response of a bearing when buckling occurs and the unresolved behaviour of the stability of the post-buckled state. The study conducted in this paper may be viewed as a development of the linear theory of multi-layered elastomeric bearing, simply replacing the differential equations by algebraic equations, showing how it is possible to evaluate the post-buckling behaviour and the interactions at large deformations.

Keywords: multi-layer elastomeric isolators, large deformation, compressive load, tensile load, post-buckling behaviour

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Authors: Pinar Sali, Esim Gursoy, Ebru Atak Damar

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Teachers’ awareness of and involvement in educational research (ER) is regarded as an indispensable aspect of professional growth and development. It is also believed to be a catalyst for effective teaching and learning. This strong emphasis on the significance of teacher research engagement has sparked inquiry into how teachers construe ER and whether or not they practice it. However, there seems to exist a few researches on teachers’ perceptions of and experience with ER in the field of English Language Teaching (ELT). The present study thus attempts to fill this gap in the ELT literature and aims to unearth English language teachers’ perceptions of ER. Understanding these perceptions would undoubtedly aid in the development of strategies to promote teacher interest and involvement in research. The participants of the present study are 70 English language teachers in public and private schools in Turkey. A mixed-method approach has been used in the study. Both qualitative and quantitative data have been gathered by means of a questionnaire consisting of two parts. The first part of the questionnaire consists of 20 close-ended items of Teachers’ Attitude Scale Towards Educational Research (TASTER). The second part of the questionnaire has been developed by the researchers via an extensive literature review and consists of a mixture of close- and open-ended questions. In addition, 15 language teachers have been interviewed for an in-depth understanding of the results. Descriptive statistics and dual comparisons have been employed for the quantitative data, and the qualitative data have been analyzed by means of content analysis. The present study provides intriguing information as to the English language teachers’ perceptions of the usefulness and practicality of ER as well as the value they attain to it. The findings are discussed in relation to language teacher education. The research has implications for the teacher education process, teacher trainers and policy makers.

Keywords: attitudes toward educational research, educational research, language teachers, teacher research

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Authors: Arash Golzari Koloor

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Feedback seems to be an inseparable part of teaching a second/foreign language. One type of feedback is corrective feedback which is one type of error treatment in second language classrooms. This study is a report on the types of corrective feedback employed in an IELTS preparation course. The types of feedback, their frequencies, and their effectiveness are enlisted, enumerated, and interpreted. The results showed that explicit correction and recast were the most frequent types of feedback while repetition and elicitation were the least. The results also revealed that metalinguistic feedback, elicitation, and explicit correction were the most effective types of feedback and affected learners performance greatly.

Keywords: classroom interaction, corrective feedback, error treatment, oral performance

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Authors: Ali S. Gargoum

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Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

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Authors: Sharon Diaz Ruiz

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The population of Latinx adult English language learners (ELLs) in the United States will increase in the next few years and become even more racially and linguistically diverse. Our classrooms reflect these demographic changes; therefore, there will always be the need to identify language teaching practices that would allow educators to meet this linguistic diversity. This qualitative study explores Latinx adult English language learners' perceptions of culturally responsive teaching strategies. Participants in this study will be enrolled in an English developmental course for the Fall of 2022. The data collection process will consist of overt observation during five presentations/activities, including culturally inclusive readings and student reflections. The teaching materials selected will align with the course module's goals and objectives. The result of this investigation will shed light on the gap in the literature documenting the application of culturally responsive pedagogy to Latino adult language learners.

Keywords: emergent bilinguals, adult learners, Latinx learners, ELL

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Authors: Marta Bas-Szymaszek

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This research examines the intricate relationship between language practices and beliefs within international environmental non-governmental organizations (ENGOs), with a particular focus on the Climate Action Network Europe (CAN Europe). While acknowledging that ENGOs often employ multilingual staff, this study aims to analyze the dual role of English within this sector. While English facilitates practical communication among individuals from diverse backgrounds, it also perpetuates inequalities and marginalization within CAN Europe. Instances of linguistic dominance impede participation and representation, reinforcing language hierarchies. Furthermore, the symbolic power of English risks overshadowing the multilingual skills of NGO employees. Through fourteen in-depth interviews, focus group discussions, and observations, this research uncovers the lived experiences of individuals navigating Europe’s largest environmental NGO network. By analyzing CAN Europe’s implicit language policy and the hegemony of English, this study illuminates the challenges within multilingual settings. The organization advocates for the implementation of more inclusive language policies and practices, with the objective of recognizing and embracing linguistic diversity within international environmental NGOs.

Keywords: language policy, English, NGOs, linguistic inclusion, multilingualism

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Authors: Habib Khodaverdiloo, Fatemeh Afrasiabi, Farrokh Asadzadeh, Martinus Th. Van Genuchten

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The soil particle-size distribution (PSD) is known to affect a broad range of soil physical, mechanical and hydraulic properties. Complete descriptions of a PSD curve should provide more information about these properties as opposed to having only information about soil textural class or the soil sand, silt and clay (SSC) fractions. We compared the accuracy of 19 different models of the cumulative PSD in terms of fitting observed data from a large number of Iranian soils. Parameters of the six most promising models were correlated with measured values of the field saturated hydraulic conductivity (Kfs), the mean weight diameter of soil aggregates (MWD), bulk density (ρb), and porosity (∅). These same soil properties were correlated also with conventional PSD parameters (SSC fractions), selected geometric PSD parameters (notably the mean diameter dg and its standard deviation σg), and several other PSD parameters (D50 and D60). The objective was to find the best predictions of several soil physical quality indices and the soil hydraulic properties. Neither SSC nor dg, σg, D50 and D60 were found to have a significant correlation with both Kfs or logKfs, However, the parameters of several cumulative PSD models showed statistically significant correlation with Kfs and/or logKfs (|r| = 0.42 to 0.65; p ≤ 0.05). The correlation between MWD and the model parameters was generally also higher than either with SSC fraction and dg, or with D50 and D60. Porosity (∅) and the bulk density (ρb) also showed significant correlation with several PSD model parameters, with ρb additionally correlating significantly with various geometric (dg), mechanical (D50 and D60), and agronomic (clay and sand) representations of the PSD. The fitted parameters of selected PSD models furthermore showed statistically significant correlations with Kfs,, MWD and soil porosity, which may be viewed as soil quality indices. Results of this study are promising for developing more accurate pedotransfer functions.

Keywords: particle size distribution, soil texture, hydraulic conductivity, pedotransfer functions

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Authors: Saman Khairani

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Assessment is a pivotal component of the teaching and learning process, serving as a critical tool for evaluating student progress, diagnosing learning needs, and informing instructional decisions. In the context of English Language Teaching (ELT), effective assessment practices are essential to promote meaningful learning experiences and foster continuous improvement in language proficiency. This paper delves into various assessment strategies, explores associated challenges, and highlights best practices for assessing student learning in ELT. The paper begins by examining the diverse forms of assessment, including formative assessments that provide timely feedback during the learning process and summative assessments that evaluate overall achievement. Additionally, alternative methods such as portfolios, self-assessment, and peer assessment play a significant role in capturing various aspects of language learning. Aligning assessments with learning objectives is crucial. Educators must ensure that assessment tasks reflect the desired language skills, communicative competence, and cultural awareness. Validity, reliability, and fairness are essential considerations in assessment design. Challenges in assessing language skills—such as speaking, listening, reading, and writing—are discussed, along with practical solutions. Constructive feedback, tailored to individual learners, guides their language development. In conclusion, this paper synthesizes research findings and practical insights, equipping ELT practitioners with the knowledge and tools necessary to design, implement, and evaluate effective assessment practices. By fostering meaningful learning experiences, educators contribute significantly to learners’ language proficiency and overall success.

Keywords: ELT, formative, summative, fairness, validity, reliability

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Authors: Valdir Moura, FranciléIa De Oliveira E. Silva, Erivelto Mercante, Ranieli Dos Anjos De Souza, Jerry Adriani Johann

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Several colonization projects were implemented in the Brazilian Legal Amazon in the 1970s and 1980s. Among all of these colonization projects, the most prominent were those with the Fishbone and Topographic models. Within this scope, the projects of settlements known as Anari and Machadinho were created, which stood out because they are contiguous areas with different models and structure of occupation and colonization. The main objective of this work was to evaluate the dynamics of Land-Use and Land-Cover (LULC) in two different colonization models, implanted in the State of Rondonia in the 1980s. The Fishbone and Topographic models were implanted in the Anari and Machadinho settlements respectively. The understanding of these two forms of occupation will help in future colonization programs of the Brazilian Legal Amazon. These settlements are contiguous areas with different occupancy structures. A 32-year Landsat time series (1984-2016) was used to evaluate the rates and trends in the LULC process in the different colonization models. In the different occupation models analyzed, the results showed a rapid loss of primary and secondary forests (deforestation), mainly due to the dynamics of use, established by the Agriculture/Pasture (A/P) relation and, with heavy dependence due to road construction.

Keywords: land-cover, deforestation, rate fragments, remote sensing, secondary succession

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Authors: Aishatu Ibrahim Birma, Aminu Tukur, Abdulkarim Abbass Gora

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Machine translation plays a vital role in the Field of Natural Language Processing (NLP), breaking down language barriers and enabling communication across diverse communities. In the context of Hausa, a widely spoken language in West Africa, mainly in Nigeria, effective translation systems are essential for enabling seamless communication and promoting cultural exchange. However, due to the unique linguistic characteristics of Hausa, accurate translation remains a challenging task. The research proposes an approach to improving the machine learning translation of Hausa by integrating Named Entity Recognition (NER) techniques. Named entities, such as person names, locations, organizations, and dates, are critical components of a language's structure and meaning. Incorporating NER into the translation process can enhance the quality and accuracy of translations by preserving the integrity of named entities and also maintaining consistency in translating entities (e.g., proper names), and addressing the cultural references specific to Hausa. The NER will be incorporated into Neural Machine Translation (NMT) for the Hausa to English Translation.

Keywords: machine translation, natural language processing (NLP), named entity recognition (NER), neural machine translation (NMT)

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Authors: Ravi Ande, Mousumi Hazari

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One of the common geophysical techniques for mapping subsurface geo-electrical structures, extensive hydro-geological research, and engineering and environmental geophysics applications is the use of time domain electromagnetic (TDEM)/transient electromagnetic (TEM) soundings. A large transmitter loop for energising the ground and a small receiver loop or magnetometer for recording the transient voltage or magnetic field in the air or on the surface of the earth, with the receiver at the center of the loop or at any random point inside or outside the source loop, make up a large loop TEM system. In general, one can acquire data using one of the configurations with a large loop source, namely, with the receiver at the center point of the loop (central loop method), at an arbitrary in-loop point (in-loop method), coincident with the transmitter loop (coincidence-loop method), and at an arbitrary offset loop point (offset-loop method), respectively. Because of the mathematical simplicity associated with the expressions of EM fields, as compared to the in-loop and offset-loop systems, the central loop system (for ground surveys) and coincident loop system (for ground as well as airborne surveys) have been developed and used extensively for the exploration of mineral and geothermal resources, for mapping contaminated groundwater caused by hazardous waste and thickness of permafrost layer. Because a proper analytical expression for the TEM response over the layered earth model for the large loop TEM system does not exist, the forward problem used in this inversion scheme is first formulated in the frequency domain and then it is transformed in the time domain using Fourier cosine or sine transforms. Using the EMLCLLER algorithm, the forward computation is initially carried out in the frequency domain. As a result, the EMLCLLER modified the forward calculation scheme in NLSTCI to compute frequency domain answers before converting them to the time domain using Fourier Cosine and/or Sine transforms.

Keywords: time domain electromagnetic (TDEM), TEM system, geoelectrical sounding structure, Fourier cosine

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Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

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Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

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Authors: Raquel Zydeck, Karina Azzolin, Luis Kosteski, Alisson Milani

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This work presents numerical models in plane deformations (2D), using the Discrete Element Method formedbybars (LDEM) andtheFiniteElementMethod (FEM), in structuralmasonrywallswith horizontal chasesof 20%, 30%, and 50% deep, located in the central part and 1/3 oftheupperpartofthewall, withcenteredandeccentricloading. Differentcombinationsofboundaryconditionsandinteractionsbetweenthemethodswerestudied.

Keywords: chases in structural masonry walls, discrete element method formed by bars, finite element method, numerical models, boundary condition

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Authors: Nurudeen O. Lasisi, Sirajo Abdulrahman, Abdulkareem A. Ibrahim

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Newcastle disease is an infection of domestic poultry and other bird species with the virulent Newcastle disease virus (NDV). In this paper, we study the dynamics of the modeling of the Newcastle disease virus (NDV) using a novel quarantine-adjusted incidence. The comparison of Vaccination, linear incident rate and novel quarantine-adjusted incident rate in the models are discussed. The dynamics of the models yield disease-free and endemic equilibrium states.The effective reproduction numbers of the models are computed in order to measure the relative impact of an individual bird or combined intervention for effective disease control. We showed the local and global stability of endemic equilibrium states of the models and we found that the stability of endemic equilibrium states of models are globally asymptotically stable if the effective reproduction numbers of the models equations are greater than a unit.

Keywords: effective reproduction number, Endemic state, Mathematical model, Newcastle disease virus, novel quarantine-adjusted incidence, stability analysis

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Authors: Linda Torresin

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This paper is devoted to the Russian as a Foreign Language (RFL) textbook, which is understood as a fundamental element of the RFL system. The aim of the study is to explore the role of the RFL textbook in modern RFL teaching theories and practices. It is suggested that the RFL textbook is not a secondary factor but contributes to the advancement and rewriting of both RFL theories and practices. This study applies to the RFL textbook theory's recent pedagogical developments in education. Therefore, the RFL system is conceived as a complex adaptive system whose elements (teacher, textbook, students, etc.) interact in a dynamic network of interconnections. In particular, the author shows that the textbook plays a central role in the RFL system since it may change and even renew RFL teaching from both theoretical and practical perspectives. On the one hand, in fact, the use of an RFL textbook may impact teaching theories: that is, the textbook may either consolidate preexisting theories or launch new approaches. On the other hand, the RFL textbook may also influence teaching practices by reinforcing the preexisting ones or encouraging teachers to try new strategies instead. All this allows the RFL textbook, within the RFL complex adaptive system, to exert an influence on the specific teaching contexts in which Russian is taught, interacting with the other elements of the system itself. Through its findings, this paper contributes to the advancement of research on RFL textbook theory.

Keywords: adaptive system, foreign language textbook, teaching Russian as a foreign language, textbook of Russian as a foreign language

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Authors: Nazia Shehzad

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Language and art can supplement and correlate each other. Through the ages art has been a means of visual expression used to convey a wide series of incarnated ideas. Art can take the perceiver into different times and into different worlds. It can also be used to introduce different levels of vocabulary to the learners of a second language. Learning a second language for most students is a very difficult and strenuous experience. They are not only trying to accommodate to a new language but are also trying to adjust to themselves and a new environment. They are anxious about almost everything, but they are especially self-conscious about their performance in the classroom. By relocating the focus from the student to an object, everyone participates, thus waiving a certain degree of self-consciousness. The experience, a student has with art in the classroom has to be gratifying for both the student and the teacher. If the atmosphere in the classroom is too grave it will not serve any useful purpose. Art is an excellent way to teach English and encourage collaboration and interaction between students of all ages. As making art involves many different processes, it is wonderful for classification and following/giving instructions. It is also an effective way to achieve and implement language of characterization and comparison and vocabulary acquirement for the elements of design (shape, size, color, texture, tone etc.) is so much more entertaining if done in a practical and hands-on way. Expressing ideas and feelings through art is also of immeasurable value where students are at the beginning stages of English language acquisition and for many of my Saudi students it was a form of therapy. It is also a way to respect, search, examine and share the cultural traditions of different cultures, and of the students themselves. Art not only provides a field for ideas to keep aimless, meandering minds of students' busy but is also a productive tool to analyze English language in a new order. As an ESL teacher, using art is a highly compelling way to bridge the gap between student and teacher. It’s difficult to keep students concentrated, especially when they speak a different language. To get students to actually learn and explore something in your foreign language lesson, artwork is your best friend. Many teachers feel that through amalgamation of the arts into their academic lessons students are able to learn more profoundly because they use diverse ways of thinking and problem solving. Teachers observe that drawing often retains students who might otherwise be dispassionate and can help students move ahead simple recall when they are asked to make connections and come up with an exclusive interpretation through an artwork or drawing. Students use observation skills when they are drawing, and this can help to persuade students who might otherwise remain silent or need more time to process information.

Keywords: amalgamation of arts, expressing ideas and feelings through arts, effective way to achieve and implement language, language and art can supplement and correlate each other

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Iran Kalbasi, Foroozandeh Zardashti

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Dialectology is a branch of social linguistics that studies systematic language variations. Dialects are the branches of a unique language that have structural, morphological and phonetic differences with each other. In Iran, these dialects and language variations themselves have a lot of cultural loads, and studying them have linguistic and cultural importance. In this study, phonetic structure of two Iranian dialects, Bakhtiyari Lori of Masjedsoleyman and Shushtari in Khuzestan Province of Iran have been surveyed. Its statistical community includes twenty speakers of two dialects. The theoretic bases of this research is based on structuralism. Its data have been collected by interviewing the questionnaire that consist of 3000 words, 410 sentences and 110 complex and simple verbs. These datas are analysed and described synchronically. Then, the phonetic characteristics of these two dialects and standard Persian have been compared. Therefore, we can say that in phonetic level of these two dialects and standard Persian, there are clearly differences.

Keywords: standard language, dialectology, bakhtiyari lori dialect of Masjedsoleyman, Shushtari dialect, vowel, consonant

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Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa

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This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.

Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions

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Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: Mohd Asrul Affendi Bin Abdullah

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Sample size calculation is especially important for zero inflated models because a large sample size is required to detect a significant effect with this model. This paper verify how to present percentage of power approximation for categorical and then extended to zero inflated models. Wald test was chosen to determine power sample size of AIDS death rate because it is frequently used due to its approachability and its natural for several major recent contribution in sample size calculation for this test. Power calculation can be conducted when covariates are used in the modeling ‘excessing zero’ data and assist categorical covariate. Analysis of AIDS death rate study is used for this paper. Aims of this study to determine the power of sample size (N = 945) categorical death rate based on parameter estimate in the simulation of the study.

Keywords: power sample size, Wald test, standardize rate, ZINBDR

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Authors: Saad M. Algharib

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The major concern of planners when placing fire stations is finding their optimal locations such that the fire companies can reach fire locations within reasonable response time or distance. Planners are also concerned with the numbers of fire stations that are needed to cover all service areas and the fires, as demands, with standard response time or distance. One of the tools for such analysis is location-allocation models. Location-allocation models enable planners to determine the optimal locations of facilities in an area in order to serve regional demands in the most efficient way. The purpose of this study is to examine the geographic distribution of the existing fire stations in Kuwait City. This study utilized location-allocation models within the Geographic Information System (GIS) environment and a number of statistical functions to assess the current locations of fire stations in Kuwait City. Further, this study investigated how well all service areas are covered and how many and where additional fire stations are needed. Four different location-allocation models were compared to find which models cover more demands than the others, given the same number of fire stations. This study tests many ways to combine variables instead of using one variable at a time when applying these models in order to create a new measurement that influences the optimal locations for locating fire stations. This study also tests how location-allocation models are sensitive to different levels of spatial dependency. The results indicate that there are some districts in Kuwait City that are not covered by the existing fire stations. These uncovered districts are clustered together. This study also identifies where to locate the new fire stations. This study provides users of these models a new variable that can assist them to select the best locations for fire stations. The results include information about how the location-allocation models behave in response to different levels of spatial dependency of demands. The results show that these models perform better with clustered demands. From the additional analysis carried out in this study, it can be concluded that these models applied differently at different spatial patterns.

Keywords: geographic information science, GIS, location-allocation models, geography

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

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Authors: Parul Goel, Jyeshtharaj B. Joshi, Arun K. Nayak

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Nucleate boiling is characterized by the nucleation, growth and departure of the tiny individual vapor bubbles that originate in the cavities or imperfections present in the heating surface. It finds a wide range of applications, e.g. in heat exchangers or steam generators, core cooling in power reactors or rockets, cooling of electronic circuits, owing to its highly efficient transfer of large amount of heat flux over small temperature differences. Hence, it is important to be able to predict the rate of heat transfer and the safety limit heat flux (critical heat flux, heat flux higher than this can lead to damage of the heating surface) applicable for any given system. A large number of experimental and analytical works exist in the literature, and are based on the idea that the knowledge of the bubble dynamics on the microscopic scale can lead to the understanding of the full picture of the boiling heat transfer. However, the existing data in the literature are scattered over various sets of conditions and often in disagreement with each other. The correlations obtained from such data are also limited to the range of conditions they were established for and no single correlation is applicable over a wide range of parameters. More recently, a number of researchers have been trying to remove empiricism in the heat transfer models to arrive at more phenomenological models using extensive numerical simulations; these models require state-of-the-art experimental data for a wide range of conditions, first for input and later, for their validation. With this idea in mind, experiments with sub-cooled and saturated demineralized water have been carried out under atmospheric pressure to study the bubble dynamics- growth rate, departure size and frequencies for nucleate pool boiling. A number of heating elements have been used to study the dependence of vapor bubble dynamics on the heater surface finish and heater geometry along with the experimental conditions like the degree of sub-cooling, super heat and the heat flux. An attempt has been made to compare the data obtained with the existing data and the correlations in the literature to generate an exhaustive database for the pool boiling conditions.

Keywords: experiment, boiling, bubbles, bubble dynamics, pool boiling

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Authors: Bola M. Tunde-Awe

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The study investigated the influence of teacher’s non-verbal communication on secondary school students’ learning outcomes in English language. The study was a survey research. Participants were three hundred Senior Secondary School II students randomly selected from ten schools in Akoko South West Local Government Area of Ondo State, Nigeria. The instrument used for data collection was a questionnaire containing twenty items on a four-point Likert scale which measured teacher’s use of three types of non-verbal communication modes: body movement, eye contact and spatial distance. The data collected was analysed using simple percentage. Findings revealed that teacher’s use of these non-verbal communication modes enhanced learners’ learning outcomes in English language: a total of 271 (90.33%) participants affirmed that teacher’s body language influenced their learning of English; 224 (74.66%) maintained the same stand for eye contact; while 202 (67.33%) affirmed that teacher’s spatial distance had positive influence. Consequent upon these findings, it was recommended that teachers of English language should constantly utilize non-verbal communication in their instructional delivery. Also, non-verbal communication modes should be included in teacher education programme to equip prospective pre-service teachers with the art of non-verbal communication.

Keywords: non-verbal communication, body language, eye contact, spatial distance, learning outcomes

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Authors: Haneen Alrawashdeh, Naciye Kunt

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Intercultural communicative competence or (ICC), is an extension of communicative competence that takes into account the intercultural aspect of learning a foreign language. Accordingly, this study aimed at investigating the intercultural interaction impact on English as a foreign language learners' academic achievement of language as a scholastic subject and their motivation towards learning it. To achieve the aim of the study, a qualitative research approach was implemented by means of semi-structured interviews. Interview sessions were conducted with eight teachers of English as well as ten English language learners who work in the tourism industry in a variety of career paths, such as selling antiques and traditional costumes. An analysis of learners' grades of English subjects from 2014 to 2019 academic years was performed by using the Open Education Management Information System Database in Jordan to support the findings of the study. The results illustrated that due to the fact that they work in the tourism sector, students gain skills and knowledge that assist them in better academic achievement in the subject of English by practicing intercultural communication with different nationalities on a daily basis; intercultural communication enhances students speaking skills, lexicon, and fluency; however, despite that their grades showed increasing, from teachers perspectives, intercultural communicative competence reduces their linguistic accuracy and ability to perform English academic writing in academic contexts such as exams.

Keywords: intercultural communicative competence, Jordan, language learning motivation, language academic achievement

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

Procedia PDF Downloads 292

Authors: Martín Pratto Burgos

Abstract:

The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

Procedia PDF Downloads 94

Authors: Guofang Zeng, Anisa Cheung

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Teacher emotions are vitally important for the classroom environment and students’ language attainment; however, studies concerning foreign language teaching anxiety (FLTA) remain scarce. This study examined FLTA by administering questionnaires to 235 in-service teachers to investigate the impacts of educational stages and teaching experience on FLTA. The statistical results show that secondary school teachers exhibit significantly higher levels of FLTA than their primary counterparts, especially in “lack of student interest” and “fear of negative evaluation”. Novice teachers are significantly more anxious than experienced teachers in the dimension of ‘teaching inexperience’, while no other differences are shown in other aspects. No interaction effects are found between the two variables. Pedagogical implications for understanding FLTA in different educational and experiential stages and corresponding anxiety-reducing strategies are discussed.

Keywords: foreign language teaching anxiety, in-service teachers, novice and experienced teachers, primary and secondary school

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