Search results for: Computational Linguistics

Authors: Lorraine Ramos

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The question of heritage language learners in foreign language classrooms has been widely debated in second language education, especially with Spanish in a U.S. Instructors of Spanish as a foreign language have brought pedagogical focus to Spanish heritage language students in order to retain, develop and maintain their first language. This paper proposes a thorough examination of the use of conceptual metaphors within autobiographical linguistic narratives as a key indicator of the writing development of advanced Spanish-language students. By pairing genre theory from Systemic Functional Linguistics with metaphor theory, this paper will examine the metaphors used by 3rd and 4th year university Spanish students within the narrative genre from a corpus of 16, 091 words. The investigation has found that heritage language students use a variety of bicultural metaphors, transferred from both languages to conceptualize their linguistic development, in addition to using metaphor in specific narrative stages as a literary strategy. Since it has been found that the metaphors used were transcultural, the use of conceptual metaphors in heritage language learners can be further examined to help these students achieve their linguistic and academic goals in the Spanish by transferring from their knowledge in English. In conclusion, by closely examining the function of student discourse through their multicultural metaphoric competence, this study provides important insights on how to enable instructors to best further their students’ writing development in the target language.

Keywords: academic writing development, heritage language learners, language attitudes and ideologies, metaphor

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Authors: McKenzie S. Braley, Lesley Jessiman

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If language reveals internal psychological processing, then it is also likely that language use in autobiographical memory transcripts may be used as a window into attachment style and related personality features. The current study, therefore, examined the possible associations between attachment style, negative affectivity, social inhibition, and linguistic features extracted from autobiographical memory transcripts. Young adult participants (n = 61) filled out attachment and personality questionnaires, and orally reported a relationship-related memory. Memories were audio-recorded and later transcribed verbatim. Using a computerized linguistic extraction tool, positive affect words, negative affect words, and cognition words were extracted. Spearman’s rank correlation coefficients revealed that attachment anxiety was negatively correlated with cognition words (r2 = -0.26, p = 0.047) and that negative affectivity was negatively correlated with positive affect words (r2 = -0.32, p = 0.012). The findings suggest that attachment style and personality are associated with speech styles indicative of both emotionality and depth of processing. Because attachment styles, negative affectivity, and social inhibition are associated with poor mental health outcomes, analyses of key linguistics features in autobiographical memory narratives may provide reliable screening tools for mental wellbeing.

Keywords: attachment style, autobiographical memory, language, negative affectivity, social inhibition

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Authors: Ravi Verma

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Cryosorption pump is the best solution to achieve clean, vibration free ultra-high vacuum. Furthermore, the operation of cryosorption pump is free from the influence of electric and magnetic fields. Due to these attributes, this pump is used in the space simulation chamber to create the ultra-high vacuum. The cryosorption pump comprises of three parts (a) panel which is cooled with the help of cryogen or cryocooler, (b) an adsorbent which is used to adsorb the gas molecules, (c) an epoxy which holds the adsorbent and the panel together thereby aiding in heat transfer from adsorbent to the panel. The performance of cryosorption pump depends on the temperature of the adsorbent and hence, on the thermal conductivity of the epoxy. Therefore we have made an attempt to increase the thermal conductivity of epoxy adhesive by mixing nano-sized graphene filler particles. The thermal conductivity of epoxy-graphene composite adhesive is measured with the help of indigenously developed experimental setup in the temperature range from 4.5 K to 7 K, which is generally the operating temperature range of cryosorption pump for efficiently pumping of hydrogen and helium gas. In this article, we have presented the experimental results of epoxy-graphene composite adhesive in the temperature range from 4.5 K to 7 K. We have also proposed an analytical heat conduction model to find the thermal conductivity of the composite. In this case, the filler particles, such as graphene, are randomly distributed in a base matrix of epoxy. The developed model considers the complete spatial random distribution of filler particles and this distribution is explained by Binomial distribution. The results obtained by the model have been compared with the experimental results as well as with the other established models. The developed model is able to predict the thermal conductivity in both isotropic regions as well as in anisotropic region over the required temperature range from 4.5 K to 7 K. Due to the non-empirical nature of the proposed model, it will be useful for the prediction of other properties of composite materials involving the filler in a base matrix. The present studies will aid in the understanding of low temperature heat transfer which in turn will be useful towards the development of high performance cryosorption pump.

Keywords: composite adhesive, computational modelling, cryosorption pump, thermal conductivity

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Authors: Amina Babou

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

Keywords: EFL students, gender identity, linguistic styles, foreign language

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Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

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Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

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Authors: Adrián D. García-Soto, Alejandro Hernández-Martínez, Jesús G. Valdés-Vázquez, Reyna A. Vizguerra-Alvarez

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Reinforced concrete bridges designed by code are intended to achieve target reliability levels adequate for the geographical environment where the code is applicable. Several methods can be used to estimate such reliability levels. Many of them require the establishment of an explicit limit state function (LSF). When such LSF is not available as a close-form expression, the simulation techniques are often employed. The simulation methods are computing intensive and time consuming. Note that if the reliability of real bridges designed by code is of interest, numerical schemes, the finite element method (FEM) or computational mechanics could be required. In these cases, it can be quite difficult (or impossible) to establish a close-form of the LSF, and the simulation techniques may be necessary to compute reliability levels. To overcome the need for a large number of simulations when no explicit LSF is available, the point estimate method (PEM) could be considered as an alternative. It has the advantage that only the probabilistic moments of the random variables are required. However, in the PEM, fitting of the resulting moments of the LSF to a probability density function (PDF) is needed. In the present study, a very simple alternative which allows the assessment of the reliability levels when no explicit LSF is available and without the need of extensive simulations is employed. The alternative includes the use of the PEM, and its applicability is shown by assessing reliability levels of reinforced concrete bridges in Mexico when a numerical scheme is required. Comparisons with results by using the Monte Carlo simulation (MCS) technique are included. To overcome the problem of approximating the probabilistic moments from the PEM to a PDF, a well-known distribution is employed. The approach mixes the PEM and other classic reliability method (first order reliability method, FORM). The results in the present study are in good agreement whit those computed with the MCS. Therefore, the alternative of mixing the reliability methods is a very valuable option to determine reliability levels when no close form of the LSF is available, or if numerical schemes, the FEM or computational mechanics are employed.

Keywords: structural reliability, reinforced concrete bridges, combined approach, point estimate method, monte carlo simulation

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Authors: Zixi You

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There are a number of verbal prefixes in Old Japanese. However, the selection or the compatibility of verbs and verbal prefixes is among the least investigated topics on Old Japanese language. Unlike other types of prefixes, verbal prefixes in dictionaries are more often than not listed with very brief information such as ‘unknown meaning’ or ‘rhythmic function only’. To fill in a part of this knowledge gap, this paper presents an exhaustive investigation based on the newly developed ‘Oxford Corpus of Old Japanese’ (OCOJ), which included nearly all existing resource of Old Japanese language, with detailed linguistics information in TEI-XML tags. In this paper, we propose the possibility that the following three prefixes, i-, sa-, ta- (with ta- being considered as a variation of sa-), are relevant to split intransitivity in Old Japanese, with evidence that unergative verbs favor i- and that unergative verbs favor sa-(ta-). This might be undermined by the fact that transitives are also found to follow i-. However, with several manifestations of split intransitivity in Old Japanese discussed, the behavior of transitives in verbal prefix selection is no longer as surprising as it may seem to be when one look at the selection of verbal prefix in isolation. It is possible that there are one or more features that played essential roles in determining the selection of i-, and the attested transitive verbs happen to have these features. The data suggest that this feature is a sense of ‘change’ of location or state involved in the event donated by the verb, which is a feature of typical unaccusatives. This is further discussed in the ‘affectedness’ hierarchy. The presentation of this paper, which includes a brief demonstration of the OCOJ, is expected to be of the interest of both specialists and general audiences.

Keywords: old Japanese, split intransitivity, unaccusatives, unergatives, verbal prefix selection

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Authors: Mohamed Ali Al Shaari, Khalid M. El Fitori

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In the field of Quran Studies known as Ghareeb A Quran (the study of the meanings of strange words and structures in Holy Quran), it is difficult to distinguish some pragmatic meanings from conceptual meanings. One who wants to study this subject may need to look for a common usage between any two words or more; to understand general meaning, and sometimes may need to look for common differences between them, even if there are synonyms (word sisters). Some of the distinguished scholars of Arabic linguistics believe that there are no synonym words, they believe in varieties of meaning and multi-context usage. Based on this viewpoint, our method was designed to look for synonyms of a word, then the differences that distinct the word and their synonyms. There are many available books that use such a method e.g. synonyms books, dictionaries, glossaries, and some books on the interpretations of strange vocabulary of the Holy Quran, but it is difficult to look up words in these written works. For that reason, we proposed a logical entity, which we called Differences Matrix (DM). DM groups the synonyms words to extract the relations between them and to know the general meaning, which defines the skeleton of all word synonyms; this meaning is expressed by a word of its sisters. In Differences Matrix, we used the sisters(words) as titles for rows and columns, and in the obtained cells we tried to define the row title (word) by using column title (her sister), so the relations between sisters appear, the expected result is well defined groups of sisters for each word. We represented the obtained results formally, and used the defined groups as a base for building the ontology of the Holy Quran synonyms.

Keywords: Quran, synonyms, differences matrix, ontology

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Authors: Jason D. Lin, Christine Sim

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This paper examines the nature of transnational media flows in East Asia, specifically expounding on the popularity of Korean dramas in China and Taiwan. Situated in interdisciplinary academic work from cultural studies, media studies, and linguistics, this project locates the significance of certain genres and regions in determining why some are subject to flow while others remain within domestic borders. Moreover, transnational flows can take one of two routes –official translations and adaptations by media corporations and subtitles written by fans in online communities. The work of 'fan-subbing' has allowed for a more democratized showcase of what bilingual fans consume and are invested in sharing, rather than what major media companies deem relevant and monetizable. This reflects a culture of relatability driven by audiences rather than by corporate direction. Of course, a variety of technological, political, and economic factors play imperative roles in how both professional and fan-made subtitles flowed across borders and between nations. While fan-subbed media may be subject to criticism because of a lack of formal regulation, these limitations can, in some cases, be overcome by the agency afforded to audiences in the digital landscape. Finally, this paper offers a critical lens for deliberating the lasting impact of fan involvement on both professional practices and the flows of mainstream media throughout East Asia.

Keywords: audience studies, bilingual, cultural proximity, fan-subbing, online communities, subtitles

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Authors: Fatma Hsain Ali Suliman

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Personality plays an important role in acquiring a second language. For second language learners to make maximum progress with their own learning styles, their individual differences must be recognized and attended to. Personality is considered to be a pattern of unique characteristics that give a person’s behavior a kind of consistency and individuality. Therefore, the enclosed study, which is entitled “The Role of Personality in Second language Acquisition: Extroversion and Introversion”, tends to shed light on the relationship between learners’ personalities and second language acquisition process. In other words, it aims at drawing attention to how individual differences of students as being extroverts or introverts could affect the language acquisition process. As a literature review, this paper discusses the results of some studies concerning this issue as well as the point views of researchers and scholars who have focused on the effect of extrovert and introvert personality on acquiring a second language. To accomplish the goals of this study, which is divided into 5 chapters including introduction, review of related literature, research method and design, results and discussions and conclusions and recommendations, 20 students of English Department, Faculty of Arts, Misurata University, Libya were handed out a questionnaire to figure out the effect of their personalities on the learning process. Finally, to be more sure about the role of personality in a second language acquisition process, the same students who were given the questionnaire were observed in their ESL classes.

Keywords: second language acquisition, personality, extroversion, introversion, individual differences, language learning strategy, personality factors, psycho linguistics

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Authors: Eliziane Navarro, Aparecida Citta

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Child of the dark is the work of the Brazilian author Carolina Maria de Jesus published at the first time by Ática & Francisco Alves in 1960. It is, mostly, a story of lack of rights. It lacks to men who live in the slums what is essential in order to take advantage of the privilege of rationality to develop themselves as civilized humans. It is, therefore, in the withholding of the basic rights that inequality finds space to build itself to be the main misery on Earth. Antonio Candido, a Brazilian sociologist, claims that it is the right to literature has the ability to humanize men, once the aptitude to create fiction and fable is essential to the social balance. Hence, for the forming role that literature holds, it must be thought as the number of rights that assure human dignity, such as housing, education, health, freedom, etc. When talking about her routine, Carolina puts in evidence something that has great influence over the formation of human beings, contributing to the way they live: the slum. Even though it happens in a distinct way and using her linguistics variation, Carolina writes about something that will only be discussed later on Brazil’s Cities Statute and Ermia Maricato: the right to the city, and how the slums are, although inserted in the city, an attachment, an illegal city, a dismissing room. It interests ourselves, for that matter, in this work, to analyse how the deprivation of the rights to the city and literature, detailed in Carolina’s journal, conditions human beings to a life where the instincts overcome the social values.

Keywords: Child of the dark, slum, Brazil, architecture and literature

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Authors: Lai Yi-Hsiu

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The present study addressed the nature of bilingual semantic processing in Mandarin Chinese and Southern Min and examined category effects and age effects. Nineteen bilingual adults of Mandarin Chinese and Southern Min, nine monolingual seniors of Mandarin Chinese, and ten monolingual seniors of Southern Min in Taiwan individually completed two semantic tasks: Picture naming and category fluency tasks. The instruments for the naming task were sixty black-and-white pictures, including thirty-five object pictures and twenty-five action pictures. The category fluency task also consisted of two semantic categories – objects (or nouns) and actions (or verbs). The reaction time for each picture/question was additionally calculated and analyzed. Oral productions in Mandarin Chinese and in Southern Min were compared and discussed to examine the category effects and age effects. The results of the category fluency task indicated that the content of information of these seniors was comparatively deteriorated, and thus they produced a smaller number of semantic-lexical items. Significant group differences were also found in the reaction time results. Category effects were significant for both adults and seniors in the semantic fluency task. The findings of the present study will help characterize the nature of the bilingual semantic processing of adults and seniors, and contribute to the fields of contrastive and corpus linguistics.

Keywords: bilingual semantic processing, aging, Mandarin Chinese, Southern Min

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Authors: Gabriela Rivadeneyra-Romero, Claudia del C. Gutierrez Torres, Sergio A. Martinez-Delgadillo, Victor X. Mendoza-Escamilla, Alejandro Alonzo-Garcia

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Ultrasonic degradation is currently being used in sonochemical reactors to degrade pollutant compounds from aqueous media, as emerging contaminants (e.g. pharmaceuticals, drugs and personal care products.) because they can produce possible ecological impacts on the environment. For this reason, it is important to develop appropriate water and wastewater treatments able to reduce pollution and increase reuse. Pollutants such as textile dyes, aromatic and phenolic compounds, cholorobenzene, bisphenol-A and carboxylic acid and other organic pollutants, can be removed from wastewaters by sonochemical oxidation. The effect on the removal of pollutants depends on the type of the ultrasonic frequency used; however, not much studies have been done related to the behavior of the fluid into the sonoreactors operated at different ultrasonic frequencies. Based on the above, it is necessary to study the hydrodynamic behavior of the liquid generated by the ultrasonic irradiation to design efficient sonoreactors to reduce treatment times and costs. In this work, it was studied the hydrodynamic behavior of the fluid in sonochemical reactors at different frequencies (250 kHz, 500 kHz and 1000 kHz). The performances of the sonoreactors at those frequencies were simulated using computational fluid dynamics (CFD). Due to there is great sound speed gradient between piezoelectric and fluid, k-e models were used. Piezoelectric was defined as a vibration surface, to evaluate the different frequencies effect on the fluid into sonochemical reactor. Structured hexahedral cells were used to mesh the computational liquid domain, and fine triangular cells were used to mesh the piezoelectric transducers. Unsteady state conditions were used in the solver. Estimation of the dissipation rate, flow field velocities, Reynolds stress and turbulent quantities were evaluated by CFD and 2D-PIV measurements. Test results show that there is no necessary correlation between an increase of the ultrasonic frequency and the pollutant degradation, moreover, the reactor geometry and power density are important factors that should be considered in the sonochemical reactor design.

Keywords: CFD, reactor, ultrasound, wastewater

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Authors: Moharram Sharifi

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Despite a growing interest in the study of the introduction section of Research Articles (RA), there have been few studies to investigate how academic writers engage with other voices and alternative positions in this academic genre. Therefore, the purpose of this study was to show how Native Speaker (NS) and (Non-Native Speaker (NNS) writers take positions and stances in research article introductions. For this purpose, Engagement resources based on the appraisal framework were investigated in sixty articles written by English NS and Iranian NNS published in applied linguistics journals. It was found that the mean occurrences of heteroglossic items in both corpora were larger than those of monoglossic items, but comparing the means of monoglossic engagements between the two corpora, it was revealed that NS writers’ corpus had larger mean occurrences of monoglossic engagements than NNS writers’ corpus implying the native’s stronger authorial stance in the texts. The results also revealed that there was no significant difference in the use of contractive and expansive engagements by NS writers (t (29) = -0.995, p>0.05), indicating a balanced use between the two options. However, the higher mean occurrences of expansive options compared with contractive options in the NNS corpus may suggest that NN writers open up more dialogic room for alternative positions in the RA introductions. The findings of this study may help writers to better perceive the creation of a strong authorial position using appropriate engagement resources in RA introductions.

Keywords: engagement, heteroglossic, monoglossic, introduction

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Erica Lima

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In Brazil, considering the (little) age of translation studies, it can be argued that the University of Campinas is traditionally an important place for graduate studies in translation. The story is told from the accreditation for the Masters, in 1987, and the Doctoral program, in 1993, within the Graduate Program in Applied Linguistics. Since the beginning, the program boasted cutting-edge research, with theoretical reflections on various aspects, and with different methodological trends. However, on the one hand, the graduate studies development was continuously growing, but on the other, it is not what was observed in the undergraduate degree program. Currently, there are only a few disciplines of Translation Theory and Practice, which does not seem to respond to student aspirations. The objective of this paper is to present the characteristics of the university’s graduate program as something profitable, considering the concern in relating the research to the historical moment in which we are living, with research conducted in a socially compromised environment and committed to the impact that it will cause ethically and socially, as well as to question the undergraduate program paths. The objective is also to discuss and propose changes, considering the limited scope currently achieved. In light of the information age, in which we have an avalanche of information, we believe that the training of translators in the undergraduate degree should be reviewed, with the goal of retracing current paths and following others that are consistent with our historical period, marked by virtual and real, by the shuffling of borders and languages, the need for new language policies, greater inclusion, and more acceptance of others. We conclude that we need new proposals for the development of the translator in an undergraduate program, and also present suggestions to be implemented in the graduate program.

Keywords: graduate Brazilian program, undergraduate Brazilian program, translator’s education, Unicamp

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Authors: Mostafa Zandi, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and  equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.

Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function

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Authors: Faith Fang Xi Ooi, Kam-Fong Lee

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Headlines are generally the summary of the content of news articles. With the added influence of hectic lifestyles, readers may rely solely on the headlines for information. In the media, what is reported concerning health issues are government responses and community involvement. There is a need for a call to action to curb health issues and not just reporting on what the government is doing about these health-related issues. In other words, linguistic elements of persuasive communicative function should be realized when reporting on health issues. Hence, this paper aims at identifying and analyzing the transitivity, Mood and Modality systems in two hundred news headlines from two Malaysian online news portals, namely The Star Online and New Straits Times. This study employs the purposive sampling method to obtain the news headlines on healthy eating using the search keyword ‘healthy eating’ and is based on Halliday’s Systemic Functional Linguistics (SFL) framework. The results show that the Material process dominates the process types along with its participants of Scope and Goal. The mood type that constitutes most of the headlines in the two newspapers is the declarative mood. Moreover, for Modality, the median Probability constitutes the highest in the headlines on healthy eating. This study contributes to the implications of being a source of reference for news writers and producers in constructing news headlines and for health campaign strategists to realize the persuasive appeals to influence behaviors and attitudes of the public towards healthy eating.

Keywords: healthy eating, modality, mood, news headlines, SFL

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Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

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The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

Procedia PDF Downloads 314

Authors: M. O. Olayiwola

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Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems.

Keywords: burger-fisher, modified variational iteration method, lagrange multiplier, Taylor’s series, partial differential equation

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Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

Procedia PDF Downloads 198

Authors: G. St-Pierre-Lemieux, E. Askari Mahvelati, D. Groleau, P. Proulx

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Mathematical modeling has become an important tool for the study of foam behavior. Computational Fluid Dynamic (CFD) can be used to investigate the behavior of foam around foam breakers to better understand the mechanisms leading to the ‘destruction’ of foam. The focus of this investigation was the simple cone foam breaker, whose performance has been identified in numerous studies. While the optimal pumping angle is known from the literature, the contribution of pressure drop, shearing, and centrifugal forces to the foam syneresis are subject to speculation. This work provides a screening of those factors against changes in the cone angle and foam rheology. The CFD simulation was made with the open source OpenFOAM toolkits on a full three-dimensional model discretized using hexahedral cells. The geometry was generated using a python script then meshed with blockMesh. The OpenFOAM Volume Of Fluid (VOF) method was used (interFOAM) to obtain a detailed description of the interfacial forces, and the model k-omega SST was used to calculate the turbulence fields. The cone configuration allows the use of a rotating wall boundary condition. In each case, a pair of immiscible fluids, foam/air or water/air was used. The foam was modeled as a shear thinning (Herschel-Buckley) fluid. The results were compared to our measurements and to results found in the literature, first by computing the pumping rate of the cone, and second by the liquid break-up at the exit of the cone. A 3D printed version of the cones submerged in foam (shaving cream or soap solution) and water, at speeds varying between 400 RPM and 1500 RPM, was also used to validate the modeling results by calculating the torque exerted on the shaft. While most of the literature is focusing on cone behavior using Newtonian fluids, this works explore its behavior in shear thinning fluid which better reflects foam apparent rheology. Those simulations bring new light on the cone behavior within the foam and allow the computation of shearing, pressure, and velocity of the fluid, enabling to better evaluate the efficiency of the cones as foam breakers. This study contributes to clarify the mechanisms behind foam breaker performances, at least in part, using modern CFD techniques.

Keywords: bioreactor, CFD, foam breaker, foam mitigation, OpenFOAM

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Authors: Nicolas M. Beleski, Gustavo A. G. Lugo

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Robotic agents are taking more and increasingly important roles in society. In order to make these robots and agents more autonomous and efficient, their systems have grown to be considerably complex and convoluted. This growth in complexity has led recent researchers to investigate forms to explain the AI behavior behind these systems in search for more trustworthy interactions. A current problem in explainable AI is the inner workings with the logic inference process and how to conduct a sensibility analysis of the process of valuation and alteration of beliefs. In a social HRI (human-robot interaction) setup, theory of mind is crucial to ease the intentionality gap and to achieve that we should be able to infer over observed human behaviors, such as cases of cognitive dissonance. One specific case inspired in human cognition is the role emotions play on our belief system and the effects caused when observed behavior does not match the expected outcome. In such scenarios emotions can make a person wrongly assume the antecedent P for an observed consequent Q, and as a result, incorrectly assert that P is true. This form of cognitive dissonance where an unproven cause is taken as truth induces changes in the belief base which can directly affect future decisions and actions. If we aim to be inspired by human thoughts in order to apply levels of theory of mind to these artificial agents, we must find the conditions to replicate these observable cognitive mechanisms. To achieve this, a computational architecture is proposed to model the modulation effect emotions have on the belief system and how it affects logic inference process and consequently the decision making of an agent. To validate the model, an experiment based on the prisoner's dilemma is currently under development. The hypothesis to be tested involves two main points: how emotions, modeled as internal argument strength modulators, can alter inference outcomes, and how can explainable outcomes be produced under specific forms of cognitive dissonance.

Keywords: cognitive architecture, cognitive dissonance, explainable ai, sensitivity analysis, theory of mind

Procedia PDF Downloads 126

Authors: M. Y. Waziri, M. A. Aliyu

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The paper proposes an approach to improve the performance of Broyden’s method for solving systems of nonlinear equations. In this work, we consider the information from two preceding iterates rather than a single preceding iterate to update the Broyden’s matrix that will produce a better approximation of the Jacobian matrix in each iteration. The numerical results verify that the proposed method has clearly enhanced the numerical performance of Broyden’s Method.

Keywords: mulit-step Broyden, nonlinear systems of equations, computational efficiency, iterate

Procedia PDF Downloads 633

Authors: Said Algarni

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The purpose of this study was to investigate selected numerical methods that demonstrate good performance in solving PDEs. We adapted alternative method that involve rational polynomials. Padé time stepping (PTS) method, which is highly stable for the purposes of the present application and is associated with lower computational costs, was applied. Furthermore, PTS was modified for our study which focused on diffusion equations. Numerical runs were conducted to obtain the optimal local error control threshold.

Keywords: Padé time stepping, finite difference, reaction diffusion equation, PDEs

Procedia PDF Downloads 291

Authors: Masato Saeki

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Presented herein is a novel algorithms for calculating the damping performance of particle dampers. The particle damper is a passive vibration control technique and has many practical applications due to simple design. It consists of granular materials constrained to move between two ends in the cavity of a primary vibrating system. The damping effect results from the exchange of momentum during the impact of granular materials against the wall of the cavity. This damping has the advantage of being independent of the environment. Therefore, particle damping can be applied in extreme temperature environments, where most conventional dampers would fail. It was shown experimentally in many papers that the efficiency of the particle dampers is high in the case of resonant vibration. In order to use the particle dampers effectively, it is necessary to solve the equations of motion for each particle, considering the granularity. The discrete element method (DEM) has been found to be effective for revealing the dynamics of particle damping. In this method, individual particles are assumed as rigid body and interparticle collisions are modeled by mechanical elements as springs and dashpots. However, the computational cost is significant since the equation of motion for each particle must be solved at each time step. In order to improve the computational efficiency of the DEM, the new algorithms are needed. In this study, new algorithms are proposed for implementing the high performance DEM. On the assumption that behaviors of the granular particles in the each divided area of the damper container are the same, the contact force of the primary system with all particles can be considered to be equal to the product of the divided number of the damper area and the contact force of the primary system with granular materials per divided area. This convenience makes it possible to considerably reduce the calculation time. The validity of this calculation method was investigated and the calculated results were compared with the experimental ones. This paper also presents the results of experimental studies of the performance of particle dampers. It is shown that the particle radius affect the noise level. It is also shown that the particle size and the particle material influence the damper performance.

Keywords: particle damping, discrete element method (DEM), granular materials, numerical analysis, equivalent noise level

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Authors: Muhammed-Badar Salihu Jibrin, Chibabi Makedono Darlington

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This paper studied Ideational Grammatical Metaphor (IGM) of Narrative History in Chinua Achebe’s There Was a Country. It started with a narrative historical style as a recent genre out of the conventional historical writings. In order to explore the linguistic phenomenon using a particular lexico-grammatical tool of IGM, the theoretical background was examined based on Hallidayan Systemic Functional Linguistics. Furthermore, the study considered the possibility of applying IGM to the Part 4 of Achebe’s historical text with recourse to the concept of congruence in IGM and research questions before formulating a working methodology. The analysis of Achebe’s memoir was, thus, presented in tabular forms to account for the quantitative content analysis with qualitative research technique, as well as the metaphorical and congruent wording through nominalization and process types with samples. The frequencies and percentage were given appropriately with respect to each subheadings of the text. To this end, the findings showed that material and relational types indicated dominance. The discussion and implications were that the findings confirmed earlier study by MAK Halliday and C.I.M.I.M. Matthiessen’s suggestion that IGM should show dominance of material type process. The implication is that IGM can be an effective tool for the analysis of a narrative historical text. In conclusion, it was observed that IGM does not only carry grammatical function but also an ideological role in shaping the historical discourse within the narrative mode between writers and readers.

Keywords: ideational grammatical metaphor, nominalization, narrative history, memoire, dominance

Procedia PDF Downloads 211

Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

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Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 125

Authors: Sophie Whittle

Abstract:

Prior to present day, English syntax historically exhibited an inconsistent verb-second (V2) rule, which saw the verb move to the second position in the sentence following the fronting of a type of phrase. There was a high amount of variation throughout the history of English with regard to the ordering of subject and verb, and many explanations attempting to account for this variation have been documented in previous literature. However, these attempts have been contradictory, with many accounts positing the effect of previous syntactic changes as the main motivations behind the decline of V2. For instance, morphosyntactic changes, such as the loss of clitics and the loss of empty expletives, have been loosely connected to changes in frequency for the loss of V2. The questions surrounding the development of non-V2 in English have, therefore, yet to be answered. The current paper aims to bring together a number of explanations from different linguistic fields to determine the factors driving the changes in English V2. Using historical corpus-based methods, the study analyses both quantitatively and qualitatively the changes in frequency for the history of V2 in the Old, Middle, and Modern English periods to account for the variation in a range of sentential environments. These methods delve into the study of information structure, prosody and language contact to explain variation within different contexts. The analysis concludes that these factors, in addition to changes within the syntax, are responsible for the position of verb movement. The loss of V2 serves as an exemplar study within the field of historical linguistics, which combines a number of factors in explaining language change in general.

Keywords: corpora, English, language change, mixed-methods, syntax, verb-second

Procedia PDF Downloads 127