Search results for: language abilities

Authors: Defne Akinci Midas

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The aim of this study was to determine the minimum, and maximum number of words that would be sufficient to fulfill the writing task in the local English Proficiency Exam (EPE) produced and administered at the Middle East Technical University, Ankara, Turkey. The relationship between the number of words and the scores of the written products that had been awarded by two raters in three online EPEs administered in 2020 was examined. The means, standard deviations, percentages, range, minimum and maximum scores as well as correlations of the scores awarded to written products with the words that amount to 0-50, 51-100, 101-150, 151-200, 201-250, 251-300, and so on were computed. The results showed that the raters did not award a full score to texts that had fewer than 100 words. Moreover, the texts that had around 200 words were awarded the highest scores. The highest number of words that earned the highest scores was about 225, and from then onwards, the scores were either stable or lower. A positive low to moderate correlation was found between the number of words and scores awarded to the texts. We understand that the idea of ‘the longer, the better’ did not apply here. The results also showed that words between 101 to about 225 were sufficient to fulfill the writing task to fully display writing skills and language ability in the specific case of this exam.

Keywords: English proficiency exam, number of words, scoring, writing task

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Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

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In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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Authors: Benjamin Kaufmann, Michael Hofstätter, Nadine Raidl, Peter Supancic

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ZnO varistors are the leading overvoltage protection elements in today’s electronic industry. Their highly non-linear current-voltage characteristics, very fast response times, good reliability and attractive cost of production are unique in this field. There are challenges and questions unsolved. Especially, the urge to create even smaller, versatile and reliable parts, that fit industry’s demands, brings manufacturers to the limits of their abilities. Although, the varistor effect of sintered ZnO is known since the 1960’s, and a lot of work was done on this field to explain the sudden exponential increase of conductivity, the strict dependency on sinter parameters, as well as the influence of the complex microstructure, is not sufficiently understood. For further enhancement and down-scaling of varistors, a better understanding of the microscopic processes is needed. This work attempts a microscopic approach to investigate ZnO varistor performance. In order to cope with the polycrystalline varistor ceramic and in order to account for all possible current paths through the material, a preferably realistic model of the microstructure was set up in the form of three-dimensional networks where every grain has a constant electric potential, and voltage drop occurs only at the grain boundaries. The electro-thermal workload, depending on different grain size distributions, was investigated as well as the influence of the metal-semiconductor contact between the electrodes and the ZnO grains. A number of experimental methods are used, firstly, to feed the simulations with realistic parameters and, secondly, to verify the obtained results. These methods are: a micro 4-point probes method system (M4PPS) to investigate the current-voltage characteristics between single ZnO grains and between ZnO grains and the metal electrode inside the varistor, micro lock-in infrared thermography (MLIRT) to detect current paths, electron back scattering diffraction and piezoresponse force microscopy to determine grain orientations, atom probe to determine atomic substituents, Kelvin probe force microscopy for investigating grain surface potentials. The simulations showed that, within a critical voltage range, the current flow is localized along paths which represent only a tiny part of the available volume. This effect could be observed via MLIRT. Furthermore, the simulations exhibit that the electric power density, which is inversely proportional to the number of active current paths, since this number determines the electrical active volume, is dependent on the grain size distribution. M4PPS measurements showed that the electrode-grain contacts behave like Schottky diodes and are crucial for asymmetric current path development. Furthermore, evaluation of actual data suggests that current flow is influenced by grain orientations. The present results deepen the knowledge of influencing microscopic factors on ZnO varistor performance and can give some recommendations on fabrication for obtaining more reliable ZnO varistors.

Keywords: metal-semiconductor contact, Schottky diode, varistor, zinc oxide

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Authors: Tarik Elaujali

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This study examines a new media effective theory was developed by the author, it is called ‘The Effervescent Disk Theory’ (EDT). The theory main goal is to affect the unaffected audience who are either not exposing to a particular message or do not show interest in it. EDT suggest melting down messages that means to be affected within the media materials which are selected willingly by the audience themselves. A certain set of procedures to test EDT hypotheses were taken and illustrated in this study. A sample of 342 respondents (males & females) was collected from Tripoli University in Libya during the academic year 2013-2014. The designated sample is representing students who were failing to pass the English module for beginners’. This study aims to change the students’ negative notion about the importance of learning English, and to put their new idea into action. The theory seeks to affect audience cognition, emotions, and behaviors. EDT was applied in the present study alongside the media dependency theory. EDT hypotheses were confirmed, study results denoted that 73.6 percentage of the students responded positively and passed their English exam for beginners after being exposed selectively to their favorite TV program that contains a dissolved messages about the importance and vitality of learning English language.

Keywords: effervescent disk theory, selective exposure, media dependency, Libyan students

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Authors: Jugal Bhandari, K. Hari Priya

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The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

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Authors: Mehran Memari, Bita Asadi

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Second language (L2) classrooms in academic contexts usually consist of learners with diverse L2 proficiency levels. One solution for managing such heterogeneous classes and addressing individual needs of students is to improve learner autonomy by using technological innovations such as blogging. The focus of this study is on investigating the effects of blogging on improving the quality of Iranian university students' writings. For this aim, twenty-six Iranian university students participated in the study. Students in the experimental group (n=13) were required to blog daily while the students in the control group (n=13) were asked to write a daily schedule using paper and pencil. After a 3-month period of instruction, the five last writings of the students from both groups were rated by two experienced raters. Also, students' attitudes toward the traditional method and blogging were surveyed using a questionnaire and a semi-structured interview. The research results showed evidences in favor of the students who used blogging in their writing program. Also, although students in the experimental group found blogging more demanding than the traditional method, they showed an overall positive attitude toward the use of blogging as a way of improving their writing skills. The findings of the study have implications for the incorporation of computer-assisted learning in L2 academic contexts.

Keywords: blogging, computer-assisted learning, paper and pencil, writing

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Authors: Hsiao-Yung Wang

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This paper aims to elaborate the rhetorical strategies and its inherent dialectical tensions between transgender movement and gay movement in Taiwan; thereby, a radical/populist democratic model will be reproblematized for theorizing the internal dialogicity of the 'umbrella metaphor' of the so-called 'LGBT' label. Firstly, it examined how the representative gay community in Taiwan defined the category of 'LGBT' by its visual rhetoric of pride parade during the last two decades, and how the imaginary of 'transgender' was systematically precluded or even silenced by 'cisgender privilege' or 'cisnormativity' of the gay community in general. Secondly, it employed Laclau & Mouffe’s (1985) perspective of 'empty signifier' which derives from their radical democratic theorization and populist reason, to explore the rhetorical strategies and language tactics on which transgender activists relied for arguing or mapping both the cooperative and competitive relationship with cisgender allies intentionally. Based on research findings, this paper argued that a relationship between rather than an amalgamation of sexual orientation and gender identity should be recognized. Moreover, that resisting defining transgender as other and everyone else as normal could be the critical issue of LGBT community as a whole, especially while it proceeds toward to a radical/populist democracy.

Keywords: empty signifier, LGBT, populist reason, radical democracy, rhetoric, transgender

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Authors: Sangeeta Rai

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International education is Australia’s third largest export with significant revenue flowing to the economy in all state and territory jurisdictions. International students make significant economic, social and cultural contributions to all communities in which they are studying and often working. Among these international students are those from Nepal, who continue to seek Australian higher education in increasing numbers. This paper reports on findings from a literature review that highlights the gap in knowledge of the pedagogical issues that may need addressing in teaching Nepalese students in the higher education sector in Australia. Nepalese students bring to their studies a rich culture shaped by their country’s turbulent political and poor economic conditions. These factors may further contribute to their endeavors to seek education abroad to better themselves and their situation. This cohort of students faces various challenges undertaking their studies in Australia that may be due to factors including language, learning styles and engagement with peers. Hence, this paper highlights the importance of these students on Australian shores and forms the basis for further study on the issues and challenges that they face and those that need to be addressed by Australian educators.

Keywords: Nepalese students in Australia, challenges and coping mechanisms of Nepalese students, international students in Australia, socio-cultural background of Nepalese students

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Authors: Valdênia Carvalho e Almeida

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The goal of the present study is to investigate the semantic preference of the most frequent adjectives in research articles through a corpus-based analysis of texts published in journals in Applied Linguistics (AL). The corpus used in this study contains texts published in the period from 2014 to 2018 in the three journals: Language Learning and Technology; English for Academic Purposes, and TESOL Quaterly, totaling more than one million words. A corpus-based analysis was carried out on the corpus to identify the most frequent adjectives that co-occurred in the three journals. By observing the concordance lines of the adjectives and analyzing the words they associated with, the semantic preferences of each adjective were determined. Later, the AL corpus analysis was compared to the investigation of the same adjectives in a corpus of Chemistry. This second part of the study aimed to identify possible differences and similarities between the two corpora in relation to the use of the adjectives in research articles from both areas. The results show that there are some preferences which seem to be closely related not only to the academic genre of the texts but also to the specific domain of the discipline and, to a lesser extent, to the context of research in each journal. This research illustrates a possible contribution of Corpus Linguistics to explore the concept of semantic preference in more detail, considering the complex nature of the phenomenon.

Keywords: applied linguistics, corpus linguistics, chemistry, research article, semantic preference

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Authors: Jamil Ahmed

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Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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Authors: E. Verduci, I. Aguglia, A. Filocamo, I. Macrì, R. Scala, A. Vinci

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One of the first indicator of autism spectrum disorder (ASD) is a decreasing tendency or failure to respond to name (RTN) call. Despite RTN is important for social and language developmentand it’s a common target for early interventions for children with ASD, research on specific treatments is insufficient and does not consider the importance of the discrimination between the own name and other names. The purpose of the current study was to replicate an assessment and treatment model proposed by Conine et al. (2020) to teach children with ASD to respond to their own name and to not respond to other names (RTO). The model includes three different phases (baseline/screening, treatment, and generalization), and itgradually introduces the different treatment components, starting with the most naturalistic ones (such as social interaction) and adding more intrusive components (such as tangible reinforcements, prompt and fading procedures) if necessary. The participants of this study were three children with ASD diagnosis: D. (5 years old) with a low frequency of RTN, M. (7 years old) with a RTN unstable and no ability of discrimination between his name and other names, S. (3 years old) with a strong RTN but a constant response to other names. Moreover, the treatment for D. and M. consisted of social and tangible reinforcements (treatment T1), for S. the purpose of the treatment was to teach the discrimination between his name and the others. For all participants, results suggest the efficacy of the model to acquire the ability to selectively respond to the own name and the generalization of the behavior with other people and settings.

Keywords: response to name, autism spectrum disorder, progressive training, ABA

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: ShuHui Yang, ChingChing Lu

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Measuring event-related potentials (ERPs) has been fundamental to our understanding of how people process language. One specific ERP component, a P600, has been hypothesized to be associated with syntactic reanalysis processes. We, however, propose that the P600 is not restricted to reanalysis processes, but is the index of the structural pattern processing. To investigate the structural pattern processing, we utilized the effects of stimulus degradation in structural priming. To put it another way, there was no P600 effect if the structure of the prime was the same with the structure of the target. Otherwise, there would be a P600 effect if the structure were different between the prime and the target. In the experiment, twenty-two participants were presented with four sentences of Tang poetry. All of the first two sentences, being prime, were conducted with SVO+VP. The last two sentences, being the target, were divided into three types. Type one of the targets was SVO+VP. Type two of the targets was SVO+VPVP. Type three of the targets was VP+VP. The result showed that both of the targets, SVO+VPVP and VP+VP, elicited positive-going brainwave, a P600 effect, at 600~900ms time window. Furthermore, the P600 component was lager for the target’ VP+VP’ than the target’ SVO+VPVP’. That meant the more dissimilar the structure was, the lager the P600 effect we got. These results indicate that P600 was the index of the structure processing, and it would affect the P600 effect intensity with the degrees of structural heterogeneity.

Keywords: ERPs, P600, structural pattern, structural priming, Tang poetry

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Authors: N. Coskun

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Australia has received over 840,000 refugees since its establishment as a federation. Despite the long history of refugee intake, Australia appears to have prolonged problems in refugee education such as academic and social isolations of refugee background students (RBS), the discriminations towards RBS and the high number of RBS drop-outs. This paper examines the place of RBS in educational policies, which can help to identify the problems and set a foundation for solutions. This paper investigates the educational provisions for RBS in three stages. First, the paper identifies the needs of RBS through a comprehensive literature review, using the framework of Bronfenbrenner’s bio-ecological model. Second, the study explores the place of these needs in Australian national and state educational policies which are informed by multiculturalism. The findings conclude that social, academic and psychological needs of RBS hardly find a place in multicultural educational policies. The students and their specific needs are mostly invisible and are placed under a general category of newly arrived immigrants who learn English as a second language. Third, the study explores the possible reasons for the overlook on RBS and their needs with examining the general socio-political context surrounding refugees in Australia. The overall findings suggest that Australian multiculturalism policy in education are inadequate to address RBS' social, academic and psychological needs due to the disadvantaging socio-political context where refugees are placed.

Keywords: Australia, bio-ecological model, multiculturalism, refugee education

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Authors: Heather Clark, Jon Kelly

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Burnout among healthcare professionals has been elevated to a high level of concern. The descriptions of the healthcare workplace often include language such as, stressful, long hours, rotating shifts, weekends and holidays, and exhausting. New graduate healthcare professionals are being sent into the workplace with little to no coping skills, knowledge of signs and symptoms of burnout, or resources that are available. The authors of this study created a university course entitled 'coping in your profession' that enrolled registered nurses, licensed practical nurses, EMTs, nurse assistants, and medical assistants. The course addresses burnout, self-analysis, incivility, coping mechanisms, and organizational responsibilities for employee well-being. The students were surveyed using QualtricsXM that included a pre-course and post-course analysis. Pre-course results showed high levels of individual experiences with burnout and limited knowledge of resources to combat burnout. Post-course results included personal growth and that students’ perception of burnout can be prevented at both the individual and the organization levels. Students also indicated that few to no resources to combat burnout existed at their place of employment. Addressing burnout at the educational level helps prepare graduates with the knowledge and tools to combat burnout at the individual and organization level.

Keywords: burnout, coping, healthcare workers, incivility, resilience

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Authors: Youru Zhou

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This paper seeks to unveil the quality assurance practices in the Chinese translation industry. Since China’s reform and opening up, the Chinese language service industry has enjoyed impressively rapid growth. However, while still in its early stage of professionalization, the Chinese translation industry is also facing many challenges, such as the lack of clear admission requirements, a powerful regulation authority and a great number of qualified professionals. ‘How quality is assured’ means a great deal to translation in China at this stage. In order to examine the mechanisms in which quality is assured, this paper studied four international and national standards that have gained widespread adoption by Chinese translation companies and examined the content that is relevant to translation quality assurance. Case studies with six selected Chinese translation companies of different sizes were conducted to confirm and exemplify the descriptions on the standards. It has been found that quality in the industry is a relative concept which is mainly determined by the demand of clients. Furthermore, the procedures of translation can vary from task to task dependent on the agreement made between the service provider and clients. Finally, there are companies relying on expert-oriented mechanisms to assure the quality of translation, while other companies and standards insist on process-oriented ones.

Keywords: case study, Chinese translation industry, professional practice, translation quality assurance, translation standards

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Authors: Xue Xiao, Sun Hao, Liu Donghua

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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.

Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment

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Authors: Hafiz Sajjad Hussain, Asad Razzaq

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The study aims to explore the relationship between application of speech and discourse used by the political workers and their leaders for maintaining authoritative approach and dialog power. The representation of these relationships between ideology and language in the analysis of discourse and spoken text following Van Dijk Socio-Cognitive model. Media and political leaders are two pillars of a state and their role is so important for development and effects on the society. Media has become an industry in the recent years in the globe, and especially, the private sector developed a lot in the last decade in Pakistan. Media is the easiest way of communication with the large community in a short time and used discourse independently. The prime time of the news channels in Pakistan presents the political programs on most favorite story or incident of the day. The current program broadcasted by a private channel ARY News July 6, 2014 covered the most top story of the day. The son of Ex. CJ Arslan Iftikhar moves an application to Election Commission of Pakistan about the daughter of the most popular political leader and chairman PTI Imran Khan. This movement turns the whole scenario of the political parties and media got a hot issue form discussion. This study also shows that the ideology and meanings which are presented by the TV channels not always obvious for readers.

Keywords: electronic media, political discourse, ideology of media, power, authoritative approach

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Authors: Chi-Ying Yu

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Fashion design is, in fact, an aesthetic inquiry of fabric, style and human body. In recent years, close cooperation between the artistic circles and the fashion world has even brought fashion into the arena of contemporary art. This study offers a case study on the avant-garde fashion designer Alexander McQueen, investigating how he and his brand translate fashion into contemporary art at various levels. Firstly, in terms of his designs themselves, McQueen demonstrates through fashions his declarations on political and gender issues, demonstrating his unique barbarian aesthetics and creating an enchanting sublimity. Secondly, McQueen extends his fashion aesthetics into a cross-disciplinary performing method, and raises catwalk shows to the level of complete artistic experience. Finally, and also most importantly, the brand has been producing fashion movies for its seasonal design series. By means of an abstract, non-narrative visual language, these films essentially transform people’s experience of clothing – from the senses to the pure visual. This is not simply a cross-media artistic practice, but much more fundamentally a discourse on contemporary perceptual experience. From the case of Alexander McQueen, it can be argued that avant-garde fashion has broken through the boundary between design and art, issuing its own art manifesto through the field of art or non-art.

Keywords: Alexander McQueen, avant-garde fashion, contemporary art, fashion film

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Authors: Samad Sajjadi

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Machine translation is a new subject increasingly being used by academic writers, especially students and researchers whose native language is not English. There are numerous studies conducted on machine translation, but few investigations have assessed the accuracy of machine translation from Persian to English at lexical, semantic, and syntactic levels. Using Groves and Mundt’s (2015) Model of error taxonomy, the current study evaluated Persian-to-English translations produced by two famous online translators, Google Translate and Bing Translator. A total of 240 texts were randomly selected from different academic fields (law, literature, medicine, and mass media), and 60 texts were considered for each domain. All texts were rendered by the two translation systems and then by four human translators. All statistical analyses were applied using SPSS. The results indicated that Google translations were more accurate than the translations produced by the Bing Translator, especially in the domains of medicine (lexis: 186 vs. 225; semantic: 44 vs. 48; syntactic: 148 vs. 264 errors) and mass media (lexis: 118 vs. 149; semantic: 25 vs. 32; syntactic: 110 vs. 220 errors), respectively. Nonetheless, both machines are reasonably accurate in Persian-to-English translation of lexicons and syntactic structures, particularly from mass media and medical texts.

Keywords: machine translations, accuracy, human translation, efficiency

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Authors: Kefayatullah Wahidi

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This article examines the challenges and opportunities of intercultural communication in Afghanistan. Afghanistan, with its ancient history and location on the Silk Road, connects the great civilizations of the world. This country holds a sensitive strategic and geopolitical position in the Middle East. In Afghanistan, various ethnic groups live, each with distinct linguistic, religious, and racial cultures. In today's world, elements such as identity, religion, and culture form the main components of international political relations. In some cases, these factors can even overshadow the materialistic and self-interest-driven aspects of international relations. Therefore, we used a qualitative case study method (using interviews) for this research. In this context, we attempted to discuss the issues and problems related to the challenges and opportunities of intercultural communication, with the participation of a sample of 12 Afghan people. The findings of this research show that Afghanistan is facing many challenges in the field of intercultural communication. Cultural dissatisfaction, linguistic and religious differences, and cultural sanctions are among the major challenges that can cause tensions and a lack of mutual understanding. At the same time, intercultural communication is an opportunity to increase mutual understanding, cultural exchange, and constructive interactions. Please note that I have made some minor edits for clarity and grammar, but the overall content remains the same.

Keywords: cultural dissatisfactions, language differences, intercultural communication, Afghanistan

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Authors: Okikiola Olusanu

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The us/other relationship between the colonizer and the colonized, which continues to inform the oppression of Africans and highlights the intersectional oppression of postcolonial African women because of the colonialization of the identity of African women, inspired this poem. It reflects 'the body' and the 'embodied' as it journeys through the constructed distance between the white feminine body and colonized bodies in the context of travel. Through vivid imagery, repetition, and powerful language, this poem analyzes the effect of otherness on African women as they struggle with their internalized otherness and a poor sense of belonging, which hinges on the politics of difference which makes it impossible to complement the sameness of another within the liminal space of transition. This poem examines the discourse on the complexities of migration for the African woman by critically examining bodies, space, mobility, and how they interact. Our focus is on their relationship and how it affects African women's place and pace when moving to and through the First World. Through literary and feminist perspectives, this study aims to represent the portrait of the African woman and to decolonize the concept of border. It seeks to address the uniqueness of the African woman’s body, not as the same or different, but as distinct and wholesome to foster fairness, friendship, belonging, and equity in travel. To develop our argument and to establish our findings, we look at the dynamics of the oppression of the postcolonial African woman's body and her resistance.

Keywords: body, identity, African woman, decolonization

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Authors: Ved Kulkarni, Karthik Kini

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This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.

Keywords: data mining, language processing, artificial neural networks, sentiment analysis

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Authors: Sini George

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Active learning pedagogies are valued for their success in increasing 21st-century learners’ engagement, developing transferable skills like critical thinking or quantitative reasoning, and creating deeper and more lasting educational gains. 'Blended learning' is an active learning pedagogical approach in which direct instruction moves from the group learning space to the individual learning space, and the resulting group space is transformed into a dynamic, interactive learning environment where the educator guides students as they apply concepts and engage creatively in the subject matter. This project aimed to develop a blended learning instructional approach to teaching concepts around pharmaceutical calculations to year 1 pharmacy students. The wrong dose, strength or frequency of a medication accounts for almost a third of medication errors in the NHS therefore, progression to year 2 requires a 70% pass in this calculation test, in addition to the standard progression requirements. Many students were struggling to achieve this requirement in the past. It was also challenging to teach these concepts to students of a large class (> 130) with mixed mathematical abilities, especially within a traditional didactic lecture format. Therefore, short screencasts with voice-over of the lecturer were provided in advance of a total of four teaching sessions (two hours/session), incorporating core content of each session and talking through how they approached the calculations to model metacognition. Links to the screencasts were posted on the learning management. Viewership counts were used to determine that the students were indeed accessing and watching the screencasts on schedule. In the classroom, students had to apply the knowledge learned beforehand to a series of increasingly difficult set of questions. Students were then asked to create a question in group settings (two students/group) and to discuss the questions created by their peers in their groups to promote deep conceptual learning. Students were also given time for question-and-answer period to seek clarifications on the concepts covered. Student response to this instructional approach and their test grades were collected. After collecting and organizing the data, statistical analysis was carried out to calculate binomial statistics for the two data sets: the test grade for students who received blended learning instruction and the test grades for students who received instruction in a standard lecture format in class, to compare the effectiveness of each type of instruction. Student response and their performance data on the assessment indicate that the learning of content in the blended learning instructional approach led to higher levels of student engagement, satisfaction, and more substantial learning gains. The blended learning approach enabled each student to learn how to do calculations at their own pace freeing class time for interactive application of this knowledge. Although time-consuming for an instructor to implement, the findings of this research demonstrate that the blended learning instructional approach improves student academic outcomes and represents a valuable method to incorporate active learning methodologies while still maintaining broad content coverage. Satisfaction with this approach was high, and we are currently developing more pharmacy content for delivery in this format.

Keywords: active learning, blended learning, deep conceptual learning, instructional approach, metacognition, pharmaceutical calculations

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Authors: Zhai Yujia

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None of the scholars and researchers has ever stepped into this field, though there are quite a few papers worked on various topics relevant to cultural and economic globalization separately. Economic globalization is earlier than cultural globalization. Since the invention of currency, people have had the sense of making money for the purpose of living, supporting their families, or other personal reasons. Their strong desire for earning a living is one of the incentives to propel the trade, tourism and other related economic activities that provide the service within the homeland at first and expand into the whole world later, as the global markets grow and mature. The need for operation impels international communication or interaction. To achieve this, it is vital to realize or recognize other cultures to some degree, concluding language, customs, social etiquette and history of different nations. All this drives the cultural globalization process. In contrast, it is clear that the development of cultural globalization does accelerate the process of economic globalization in return. Under the guidance of Skopos theory (first proposed by Hans Vermeer, and its core principle is that the translation process is determined by the purpose), this paper aims to demonstrate that cultural globalization is not a process in isolation by analyzing its driving forces and retroaction thoroughly with an approach of overview. It intertwines with economic globalization. The two push each other to proper gradually during their development, serving as the indispensable parts of the globalization process.

Keywords: cultural globalization, driving forces, retroaction, Skopos theory

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Authors: Ana Serafimovic, Karthik Devarajan

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Non-negative matrix factorization approximates a high dimensional non-negative matrix V as the product of two non-negative matrices, W and H, and allows only additive linear combinations of data, enabling it to learn parts with representations in reality. It has been successfully applied in the analysis and interpretation of high dimensional data arising in neuroscience, computational biology, and natural language processing, to name a few. The objective of this paper is to assess a hybrid algorithm for non-negative matrix factorization with multiplicative updates. The method aims to minimize the symmetric version of Kullback-Leibler divergence known as intrinsic information and assumes that the noise is signal-dependent and that it originates from an arbitrary distribution from the exponential family. It is a generalization of currently available algorithms for Gaussian, Poisson, gamma and inverse Gaussian noise. We demonstrate the potential usefulness of the new generalized algorithm by comparing its performance to the baseline methods which also aim to minimize symmetric divergence measures.

Keywords: non-negative matrix factorization, dimension reduction, clustering, intrinsic information, symmetric information divergence, signal-dependent noise, exponential family, generalized Kullback-Leibler divergence, dual divergence

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Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

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This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

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Authors: Mohammed Salahat, Steve Wade

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This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: domain-driven design, soft domain-driven design, naked objects, soft language

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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