Search results for: computational linguistics

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: 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: 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: 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: 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: 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

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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: 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)

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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: 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

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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

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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

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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: 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: 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

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Authors: Mehdi Nakisa, Adi Maimun, Yasser M. Ahmed, Fatemeh Behrouzi

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Squat is the reduction in under-keel clearance between a vessel at-rest and underway due to the increased flow of water past the moving body. The forward motion of the ship induces a relative velocity between the ship and the surrounding water that causes a water level depression in which the ship sinks. The problem of ship squat is one among the crucial factors affecting the navigation of ships in restricted waters. This article investigates the LNG ship squat, its effects on flow streamlines around the ship hull and ship behavior and motion using computational fluid dynamics which is applied by Ansys-Fluent.

Keywords: ship squat, CFD, confined, mechanic

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Authors: Erdogan Kaygan, Alvin Gatto

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An investigation of adaptable winglets for enhancing morphing aircraft performance is described in this paper. The concepts investigated consist of various winglet configurations fundamentally centered on a baseline swept wing. The impetus for the work was to identify and optimize winglets to enhance the aerodynamic efficiency of a morphing aircraft. All computations were performed with Athena Vortex Lattice modelling with varying degrees of twist and cant angle considered. The results from this work indicate that if adaptable winglets were employed on aircraft’s improvements in aircraft performance could be achieved.

Keywords: aircraft, drag, twist, winglet

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Authors: Zina Ghiloufi, Tahar Khir

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A transient three-dimensional computational fluid dynamics (CFD) model is developed to determine the velocity and temperature distribution in different positions cold room during pre-cooling of dates. The turbulence model used is the k-ω Shear Stress Transport (SST) with the standard wall function, the air. The numerical results obtained show that cooling rate is not uniform inside the room; the product at the medium of room has a slower cooling rate. This cooling heterogeneity has a large effect on the energy consumption during cold storage.

Keywords: CFD, cold room, cooling rate, dDates, numerical simulation, k-ω (SST)

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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

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Authors: Rudolf Hrach, Stanislav Novak, Vera Hrachova

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Composite and nanocomposite films represent the class of promising materials and are often objects of the study due to their mechanical, electrical and other properties. The most interesting ones are probably the composite metal/dielectric structures consisting of a metal component embedded in an oxide or polymer matrix. Behaviour of composite films varies with the amount of the metal component inside what is called filling factor. The structures contain individual metal particles or nanoparticles completely insulated by the dielectric matrix for small filling factors and the films have more or less dielectric properties. The conductivity of the films increases with increasing filling factor and finally a transition into metallic state occurs. The behaviour of composite films near a percolation threshold, where the change of charge transport mechanism from a thermally-activated tunnelling between individual metal objects to an ohmic conductivity is observed, is especially important. Physical properties of composite films are given not only by the concentration of metal component but also by the spatial and size distributions of metal objects which are influenced by a technology used. In our contribution, a study of composite structures with the help of methods of computational physics was performed. The study consists of two parts: -Generation of simulated composite and nanocomposite films. The techniques based on hard-sphere or soft-sphere models as well as on atomic modelling are used here. Characterizations of prepared composite structures by image analysis of their sections or projections follow then. However, the analysis of various morphological methods must be performed as the standard algorithms based on the theory of mathematical morphology lose their sensitivity when applied to composite films. -The charge transport in the composites was studied by the kinetic Monte Carlo method as there is a close connection between structural and electric properties of composite and nanocomposite films. It was found that near the percolation threshold the paths of tunnel current forms so-called fuzzy clusters. The main aim of the present study was to establish the correlation between morphological properties of composites/nanocomposites and structures of conducting paths in them in the dependence on the technology of composite films.

Keywords: composite films, computer modelling, image analysis, nanocomposite films

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Authors: Sophie Whittle

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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

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Authors: Temitope Ogungbemi

Abstract:

Jama'atu Ahlis Sunna Lidda'awati wal-Jihad (also called Boko Haram) in the North-East of Nigeria has facilitated ideological binarity in discourses on the crisis. Since its proliferation, media representation of the crisis has facilitated identity contamination and ideological struggle through which other critical issues, such as religious intolerance, ethnic diversity and other forms of class conflict in the Nigerian state, are brought to public notice. Though Boko Haram insurgency is ideological laden, the manifestation of the inherent ideologies requires extensive scholarly attention in order deconstruct the veiled ideologies. Therefore, the thrust of this study is to critically investigate identity (mis)representation as a basis for ideological mapping in discourses on Boko Haram in Nigeria, adopting critical discourse analytical tools supported with insights from systemic functional linguistics and critical discourse analysis. The data for this study consist of articles on Boko Haram in Nigerian newspapers published in English. The data selection is purposive and aimed at responding to challenges that are inherent in Nigeria's multifaithism and multiculturalism, and their effects on the construction of narratives on Boko Haram. The study reveals that identity manipulation is a constructive device for ideological mapping, realised through labeling, agency activation, and transitivity. Identity representation in discourses on Boko Haram depicted four dichotomous binarities using exclusion, generalisation, contrasting and attribution.

Keywords: identity representation, ideology, Boko Haram, newspapers

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Authors: Rehin Sulay, Anandhu Krishna, Jintumol Mathew, Vibin Ipe Thomas

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N-Nitrosodimethyl amine, the simplest member of the N-Nitrosoamine family, is a carcinogenic and mutagenic agent that has gained considerable research interest owing to its toxic nature. Ozonation of industrially important hydrazines such as unsymmetrical dimethylhydrazine (UDMH) or monomethylhydrazine (MMH) has been associated with NDMA formation and accumulation in the environment. UDMH/MMH - ozonation also leads to several other transformation products such as acetaldehyde dimethyl hydrazone (ADMH), tetramethyl tetra azene (TMT), diazomethane, methyl diazene, etc, which can be either precursors or competitors for NDMA formation.In this work, we explored the formation mechanism of ADMH and TMT from UDMH-ozonation and their further oxidation to NDMA using the second-order Moller Plesset perturbation theory employing the 6-311G(d) basis set. We have also investigated how MMH selectively forms methyl diazene and diazomethane under normal conditions and NDMA in the presence of excess ozone. Our calculations indicate that the reactions proceed via an initial H abstraction from the hydrazine –NH2 group followed by the oxidation of the generated N-radical species. The formation of ADMH from the UDMH-ozone reaction involves an acetaldehyde intermediate, which then reacts with a second UDMH molecule to generate ADMH. The preferable attack of ozone molecule on N=C bond of ADMH generates DMAN intermediate, which subsequently undergoes oxidation to form NDMA. Unlike other transformation products, TMT formation occurs via the dimerization of DMAN. Though there exist a N=N bonds in the TMT, which are preferable attacking sites for ozone, experimental studies show the lower yields of NDMA formation, which corroborates with the high activation barrier required for the process(42kcal/mol).Overall, our calculated results agree well with the experimental observations and rate constants. Computational calculations bring insights into the electronic nature and kinetics of the elementary reactions of this pathway, enabled by computed energies of structures that are not possible to access experimentally.

Keywords: reaction mechanism, ozonation, substituted hydrazine, transition state

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Authors: Pakenam Shiha, Nadine Lacsina

Abstract:

Systematic and in-depth analysis of ESL learners’ lexical errors, in general, and of collocation errors, in particular, are relatively rare. Analysis as such proves crucial in understanding how ESL learners construct and use these fixed expressions. Collocational competence of ESL learners is necessary for achieving a native-like proficiency level, which is one of the objectives of foundation programs. This study aims to examine the collocational competence of 50 Saudi foundation program students and identify the collocation errors that they often make. Furthermore, using a questionnaire, the challenges that students encounter in learning collocations and the ways in which their L1 affects their ability to recognize these expressions are identified. To identify the lexical errors and the collocational competence of the students a collocation test was administered. The 150-item lexical collocation test consists of verb-noun and adjective-noun structures. Results of the study reveal that there is a significant difference between the scores of students in the verb-noun and adjective-noun structures. The majority of errors were recorded in the adjective-noun structures due to the students’ L1 influence on the English collocations and the inability to distinguish between synonyms. Moreover, some challenges that students encountered were problems in translation, non-exposure to certain collocations, and degree of L1-L2 difference. All in all, the findings of this study can be interpreted in relation to the student's proficiency level and L2 instruction. Other findings of the study provide insights into language pedagogy—specifically strategies to help students learn collocations more effectively.

Keywords: collocations, ESL, applied linguistics, lexical collocations

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Authors: Artem Nuriev, Olga Zaitseva

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This paper is devoted to the study of a viscous incompressible flow around a circular cylinder performing harmonic oscillations, especially the steady streaming phenomenon. The research methodology is based on the asymptotic explanation method combined with the computational bifurcation analysis. Present studies allow to identify several regimes of the secondary streaming with different flow structures. The results of the research are in good agreement with experimental and numerical simulation data.

Keywords: oscillating cylinder, secondary streaming, flow regimes, asymptotic and bifurcation analysis

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