Search results for: machine language

Authors: ShuPei Wang, Yina Patterson

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This article outlines strategies for improving oral expression to advance proficiency in speaking and listening skills through structured argumentation. The objective is to empower students to effectively use the target language to express opinions and construct compelling arguments. This empowerment is achieved by honing learners' debating and questioning skills, which involves increasing their familiarity with vocabulary and phrases relevant to debates and deepening their understanding of the cultural context surrounding pertinent issues. Through this approach, students can enhance their ability to articulate complex concepts and discern critical points, surpassing superficial comprehension and enabling them to engage in the target language actively and competently.

Keywords: debate, teaching and materials design, spoken expression, listening proficiency, critical thinking

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Warsa Melles

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This study examines the way second-generation Eritrean immigrants living in the French-speaking part of Switzerland behave linguistically and culturally. The aim of this research is to demonstrate how the participants deal with their bilingualism (Tigrinya and French). More precisely, how does their language use correlates with their socio-cultural attitudes and how do these aspects (re)construct their identity? Data for this research was collected via, questionnaires and semi-structured interviews. Participants were asked to answer questions regarding their linguistic habits, their perception on being bilingual and their cultural identity. The major findings demonstrate that generation 2 relates more with the host country’s language since French is used as the main language in their daily interactions. On the other hand, due to the fact that they have never lived in Eritrea yet were raised by Eritrean born parents in a foreign country, it is more difficult for them to unanimously identify with just one culture. In that sense, intergenerational transmission plays a major role in the perception of identity. All the participants have at least a basic knowledge of Tigrinya, but the use of languages varies according to the purpose. Proficiency in the native language and sense of belonging can be correlated with the frequency of visits to Eritrea. In conclusion, the question of identity in the second-generation Eritrean community cannot be given a categorical and clear-cut answer instead, the new-self image that this social group aims to build is shaped by different factors that are essential to take into consideration.

Keywords: biculturalism, identity, language, migration

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Authors: Toumi Khamari

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This abstract presents an ecolinguistic investigation of the role of language in cultivating environmental consciousness within the Algerian context. Grounded in the field of applied linguistics, this study aims to explore how language shapes perceptions, attitudes, and behaviors related to the environment in Algeria. By examining linguistic practices and discourse patterns, this research sheds light on the potential for language to inspire ecological sustainability and foster environmental awareness. Employing a qualitative research design, the study incorporates discourse analysis and ethnographic methods to analyze language use and its environmental implications. Drawing from Algerian linguistic and cultural contexts, we investigate the unique ways in which language reflects and influences environmental consciousness among Algerian individuals and communities. This research explores the impact of linguistic features, metaphors, and narratives on environmental perceptions, addressing the complex interplay between language, culture, and the natural world. Previous studies have emphasized the significance of language in shaping environmental ideologies and worldviews. In the Algerian context, linguistic representations of nature, such as traditional proverbs and indigenous knowledge, hold immense potential in cultivating a harmonious relationship between humans and the environment. This research delves into the multifaceted connections between language, cultural heritage, and ecological sustainability, aiming to identify linguistic practices that promote environmental stewardship and conservation in Algeria. Furthermore, the study investigates the effectiveness of ecolinguistic interventions tailored to the Algerian context. By examining the impact of eco-education programs, eco-literature, and language-based environmental campaigns, we aim to uncover the potential of language as a catalyst for transformative environmental change. These interventions seek to engage Algerian individuals and communities in dialogue, empowering them to take active roles in environmental advocacy and decision-making processes. Through this research, we contribute to the field of ecolinguistics by shedding light on the Algerian perspective and its implications for environmental consciousness. By understanding the linguistic dynamics at play and leveraging Algeria's rich linguistic heritage, we can foster environmental awareness, encourage sustainable practices, and nurture a deeper appreciation for Algeria's unique ecological landscapes. Ultimately, this research seeks to inspire a collective commitment to environmental stewardship and contribute to the global discourse on language, culture, and the environment.

Keywords: eco-linguistics, environmental consciousness, language and culture, Algeria and North Africa

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Authors: Eyup Bayram Guzel, Osman Tunc

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People have been fairly interested in what technology offers to them around a scope of human necessities and it has become a part of human life. In this study, experimental studies were reviewed for the purpose of how technology helps language learners improve their phonemic awareness, reading comprehension and vocabulary development skills. As a conclusion, experimental studies demonstrated that students showed significant improvements up to 70% in phonological awareness, while they demonstrated up to 76% of improvements in reading comprehension and up to 77% in vocabulary development. The use of computer-assisted technologies and its positive outcomes were encouraged to be used more widely in order to meet the diverse needs of students.

Keywords: technology, phonemic awareness, reading comprehension, vocabulary development

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Authors: Dharmendra Jariwala, Robin Christian

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Thermal exposure is a common problem in every manufacturing industry where heat is used in the manufacturing process. In developing countries like India, a lack of awareness regarding the proper work environmental condition is observed among workers. Improper planning of factory building, arrangement of machineries, ventilation system, etc. play a vital role in the rise of temperature within the manufacturing areas. Due to the uncontrolled thermal stress, workers may be subjected to various heat illnesses from mild disorder to heat stroke. Heat stress is responsible for the health risk and reduction in production. Wet Bulb Globe Temperature (WBGT) index and relative humidity are used to evaluate heat stress conditions. WBGT index is a weighted average of natural wet bulb temperature, globe temperature, dry bulb temperature, which are measured with standard instrument QuestTemp 36 area stress monitor. In this study textile processing units have been selected in the industrial estate in the Surat city. Based on the manufacturing process six locations were identified within the plant at which process was undertaken at 120°C to 180°C. These locations were jet dying machine area, stenter machine area, printing machine, looping machine area, washing area which generate process heat. Office area was also selected for comparision purpose as a sixth location. Present Study was conducted in the winter season and summer season for day and night shift. The results shows that average WBGT index was found above Threshold Limiting Value (TLV) during summer season for day and night shift in all three industries except office area. During summer season highest WBGT index of 32.8°C was found during day shift and 31.5°C was found during night shift at printing machine area. Also during winter season highest WBGT index of 30°C and 29.5°C was found at printing machine area during day shift and night shift respectively.

Keywords: relative humidity, textile industry, thermal stress, WBGT

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Authors: Janos Farkas, Maria Czeller, Ildiko Tar

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A remarkable feature of today’s language teaching is the learners’ language learning motivation. It is always considered as a very important factor and has been widely discussed and investigated. This paper aims to present a research study conducted in higher education institutions among students majoring in business and administration in Hungary. The aim of the research was to investigate the motivational factors of students learning languages for business purposes and set up a multivariate statistical model of language learning motivation, and examine the model's main components by different social background variables. The research question sought to answer the question of whether the motivation of students of business learning LSP could be characterized through some main components. The principal components of LSP have been created, and the correlations with social background variables have been explored. The main principal components of learning a language for business purposes were "professional future", "abroad", "performance", and "external". In the online voluntary questionnaire, 28 questions were asked about students’ motivational attitudes. 449 students have filled in the questionnaire. Descriptive statistical calculations were performed, then the difference between the highest and lowest mean was analyzed by one-sample t-test. The assessment of LSP learning was examined by one-way analysis of variance and Tukey post-hoc test among students of parents with different qualifications. The correlations between student motivation statements and various social background variables and other variables related to LSP learning motivation (gender, place of residence, mother’s education, father’s education, family financial situation, etc.) have also been examined. The attitudes related to motivation were seperated by principal component analysis, and then the different language learning motivation between socio-economic variables and other variables using principal component values were examined using an independent two-sample t-test. The descriptive statistical analysis of language learning motivation revealed that students learn LSP because this knowledge will come in handy in the future. It can be concluded that students consider learning the language for business purposes to be essential and see its future benefits. Therefore, LSP teaching has an important role and place in higher education. The results verify the second linguistic motivational self-system where the ideal linguistic self embraces the ideas and desires that the foreign language learner wants to achieve in the future. One such desire is to recognize that students will need technical language skills in the future, and it is a powerful motivation for them to learn a language.

Keywords: higher education, language learning motivation, LSP, statistical analysis

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

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The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Malihe Shahidan, Azin Madhi, Meisam Shahbaz

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In recent decades, the role of supply chains in sustaining businesses and establishing their superiority in the market has been under focus. The realization of the goals and strategies of a business enterprise is largely dependent on the cooperation of the chain, including suppliers, distributors, retailers, etc. Supply chains can potentially be disrupted by both internal and external factors. In this paper, resilience strategies have been identified and analyzed in three levels: sourcing, producing, and distributing by considering economic depression as a current risk factor for the machine-made rugs industry. In this study, semi-structured interviews for data gathering and thematic analysis for data analysis are applied. Supply chain data has been gathered from seven rug factories before and after the economic depression through semi-structured interviews. The identified strategies were derived from literature review and validated by collecting data from a group of eighteen industry and university experts, and the results were analyzed using statistical tests. Finally, the outsourcing of new products and products in the new market, the development and completion of the product portfolio, the flexibility in the composition and volume of products, the expansion of the market to price-sensitive, direct sales, and disintermediation have been determined as strategies affecting supply chain resilience of machine-made rugs' industry during an economic depression.

Keywords: distribution, economic depression, machine-made rug, outsourcing, production, sourcing, supply chain, supply chain resilience

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Authors: Laura de Almeida

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This paper aims to present research involving the translation of classical books originally in English and translated into the Portuguese language. The objective is to analyze the linguistic varieties evident and how they appear in the other language the work was translated into. We based our study on the sociolinguistics theory, more specifically, the study of the Black English Vernacular. Our methodology is built on collecting data from the speech characters of the Black English Vernacular from some books such as The Adventures of Huckleberry Finn by Mark Twain. On doing so, we compare the two versions of a book and how they reflected the linguistic variety. Our purpose is to show that some translators do not worry when dealing with linguistic variety. In other words, they just translate the story without taking into account some important linguistic aspects which need attention, such as language variation.

Keywords: classical books, linguistic variation, sociolinguistics, translation

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Authors: Youhang Zhou, Weimin Zeng, Qi Xie

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Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

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Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Bo Ning Lyu

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Blog assisted language learning (BALL) has been trialed by educators in language teaching with the development of Web 2.0 technology. Understanding the development trend of related research helps grasp the whole picture of the use of blog in language education. This paper reviews current research related to blogs enhanced language learning based on bibliometric analysis, aiming at (1) identifying the most frequently used keywords and their co-occurrence, (2) clustering research topics based on co-citation analysis, (3) finding the most frequently cited studies and authors and (4) constructing the co-authorship network. 330 articles were searched out in Web of Science, 225 peer-viewed journal papers were finally collected according to selection criteria. Bibexcel and VOSviewer were used to visualize the results. Studies reviewed were published between 2005 to 2016, most in the year of 2014 and 2015 (35 papers respectively). The top 10 most frequently appeared keywords are learning, language, blog, teaching, writing, social, web 2.0, technology, English, communication. 8 research themes could be clustered by co-citation analysis: blogging for collaborative learning, blogging for writing skills, blogging in higher education, feedback via blogs, blogging for self-regulated learning, implementation of using blogs in classroom, comparative studies and audio/video blogs. Early studies focused on the introduction of the classroom implementation while recent studies moved to the audio/video blogs from their traditional usage. By reviewing the research related to BALL quantitatively and objectively, this paper reveals the evolution and development trends as well as identifies influential research, helping researchers and educators quickly grasp this field overall and conducting further studies.

Keywords: blog, bibliometric analysis, language learning, literature review

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Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

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Authors: Amey Kulkarni, Paavan Shetty, Amol Patil, B. Rajiv

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Fuel Efficiency plays a very important role in overall performance of an automobile. In this paper study of fuel efficiency of heavy construction, compaction machine is done. The fuel Consumption trials are performed in order to obtain the consumption of fuel in performing certain set of actions by the compactor. Usually, Heavy Construction machines are put to work in locations where refilling the fuel tank is not an easy task and also the fuel is consumed at a greater rate than a passenger automobile. So it becomes important to have a fuel efficient machine for long working hours. The fuel efficiency is the most important point in determining the future scope of the product. A heavy construction compaction machine operates in five major roles. These five roles are traveling, Static working, High-frequency Low amplitude compaction, Low-frequency High amplitude compaction, low idle. Fuel consumption readings for 1950 rpm, 2000 rpm & 2350 rpm of the engine are taken by using differential fuel flow meter and are analyzed. And the optimum RPM setting which fulfills the fuel efficiency, as well as engine performance criteria, is considered. Also, other factors such as rear end gears, Intake and exhaust restriction for an engine, vehicle operating techniques, air drag, Tribological aspects, Tires are considered for increasing the fuel efficiency of the compactor. The fuel efficiency of compactor can be precisely calculated by using Differential Fuel Flow Meter. By testing the compactor at different combinations of Engine RPM and also considering other factors such as rear end gears, Intake and exhaust restriction of an engine, vehicle operating techniques, air drag, Tribological aspects, The optimum solution was obtained which lead to significant improvement in fuel efficiency of the compactor.

Keywords: differential fuel flow meter, engine RPM, fuel efficiency, heavy construction compaction machine

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Authors: Marthadale Acibo Semacio

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Speaking skill is a crucial part of English language teaching and learning. This actually shows the great importance of this skill in English language classes. Through speaking, ideas and thoughts are shared with other people, and a smooth interaction between people takes place. The study examined the levels of speaking proficiency of the control and experimental groups on pronunciation, grammatical accuracy, and fluency. As a quasi-experimental study, it also determined the presence or absence of significant changes in their speaking proficiency levels in terms of pronouncing the words correctly, the accuracy of grammar and fluency of a language given the two methods to the groups of students in the English language, using the traditional and audio-lingual methods. Descriptive and inferential statistics were employed according to the stated specific problems. The study employed a video presentation with prior information about it. In the video, the teacher acts as model one, giving instructions on what is going to be done, and then the students will perform the activity. The students were paired purposively based on their learning capabilities. Observing proper ethics, their performance was audio recorded to help the researcher assess the learner using the modified speaking rubric. The study revealed that those under the traditional method were more fluent than those in the audio-lingual method. With respect to the way in which each method deals with the feelings of the student, the audio-lingual one fails to provide a principle that would relate to this area and follows the assumption that the intrinsic motivation of the students to learn the target language will spring from their interest in the structure of the language. However, the speaking proficiency levels of the students were remarkably reinforced in reading different words through the aid of aural media with their teachers. The study concluded that using an audio-lingual method of teaching is not a stand-alone method but only an aid of the teacher in helping the students improve their speaking proficiency in the English Language. Hence, audio-lingual approach is encouraged to be used in teaching English language, on top of the chalk-talk or traditional method, to improve the speaking proficiency of students.

Keywords: audio-lingual, speaking, grammar, pronunciation, accuracy, fluency, proficiency

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Authors: Carmela Perta

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Following the example of both International and European legislation, on 15 December 1999 the national law 482/99 Regulations regarding the protection of historic language minorities was approved, providing a national framework for the preservation and renaissance of minority languages «The Italian Republic sustains the language and culture of people speaking Albanian, Catalan, German, Greek, Slovene, Croatian, French, Francoprovençal, Friulan, Ladin, Occitan and Sard». The legislation made it possible to use these languages in education, in public offices, in local government, in the judicial system, in mass media, and allowed for the reinstatement of place and personal names. However, several practical problems have emerged, particularly those concerning the variety that should be used in education, in official documents and in other formal domains, i.e. the local variety, the standard of reference (if there is any), or an over regional koinè. In minority settings, it might seem eminently sensible to use the ready made standard of reference, accepting the Ausbausprache, rather than the language as practice, that is the local variety. However, this process seems to be pointless, as is demonstrated by the results of a fieldwork that was carried out in a small town in the South of Italy where members speak Faetar, the local variety of Francoprovençal. Here the language is largely used by the community members in all domains, moreover a deep sense of loyalty towards the variety they use and a manifested minority identity can be observed analysing the speakers’ attitudes. However, these positive attitudes are towards the vehicle for their distinctive history and culture, and not for an “external” standard, a system which local authorities and planners are trying to introduce in the community. In other words, according to the speakers' reactions, there is little point in struggling to maintain a language, if what is conserved is not the group’s language but another.

Keywords: maintenance, minority languages, endangered languages, francoprovençal

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: block rotor test, DC test, no load test, virtual environment, voltage source inverter

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Authors: Olga Bernikova, Oleg Redkin

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Islamic Studies and the Arabic language are indivisible from each other starting from the appearance of Islam and formation of the Classical language. The present paper demonstrates correlation among linguistics and religion in historical perspective with regard to peculiarities of the Arabic language which distinguish it from the other prophetic languages. Islamic Studies and Linguistics are indivisible from each other starting from the invent of Islam and formation of the Classical language. In historical perspective, the Arabic language has been and remains a tool for the expression of Islamic rhetoric being a prophetic language. No other language in the world has preserved its stability for more than 14 centuries. Islam is considered to be one of the most important factors which secure this stability. The analysis and study of the text of Qurʾān are of special importance for those who study Islamic civilization, its role in the destinies of the mankind, its values and virtues. Without understanding of the polyphony of this sacred text, indivisible unity of its form and content it is impossible to understand social developments both in the present and the past. Since the first years of Islam Qurʾān had been in the center of attention of Muslim scholars, and in the center of attention of theologians, historians, philologists, jurists, mathematicians. Only quite recently it has become an object of analysis of the specialists of computer technologies. In Arabic and Islamic studies mediaeval texts i.e. textual documents are considered the main source of information. Hence the analysis of the multiplicity of various texts and finding of interconnections between them help to set scattered fragments of the riddle into a common and eloquent picture of the past, which reflects the state of the society on certain stages of its development. The text of the Qurʾān like any other phenomenon is a multifaceted object that should be studied from different points of view. As a result, this complex study will allow obtaining a three-dimensional image rather than a flat picture alone.

Keywords: Arabic, Islamic studies, linguistics, religion

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

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Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA

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In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.

Keywords: BER, DWT, extreme leaning machine (ELM), PSNR

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Authors: Anna Maria Re

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Taking advantage of the ecolinguistic theoretical and practical analysis, the work intends the prophetic, punctual, and at times disturbing language used by David Quammen in Spillover, questioning it from an ecological perspective and contributing to the search for new stories. In the famous volume, the author illustrates a literary history of the great epidemics and pandemics, demonstrating that viruses are nature's inevitable response to man's assault on ecosystems. In doing so, he introduces new words, which have tamed our anxieties in recent years since writing as a human artistic expression can mirror the human conscience. Writing in the Anthropocene, coining a new reference lexicon with respect to what is happening, means offering a form to the idea of survival of the planet, imagining the human being grappling with an environment whose conformation he himself has helped to change with a language that is no longer effective in describing the world as we have known it and that quickly needs a radical overhaul. Following the methodology proposed in Ecolinguistics: language, ecology and the stories we live by, the analysis in the paper will enhance the language that encodes new stories based on: ideologies, framings, metaphors, evaluations, identities, convictions, and salience.

Keywords: Anthropocene, pandemic, spillover, virus, zoonosis

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Authors: Sonia Pajaron, Flaviano Sentina, Ranulfo Etulle

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Learning a second language calls for a total commitment from the learner whose response is necessary to successfully send and receive linguistic messages. It is relevant to virtually every aspect of human behaviour which is even more challenging when the components on -affective domains- are involved in second language learning. This study investigated the association between the identified affective attributes and second language performance of the one hundred seventeen (117) randomly selected third year maritime students. A descriptive-correlational method was utilized to generate data on their affective attributes while composition writing (2 series) and IELTS-based interview was done for speaking test. Additionally, to establish the respondents’ English language profile, data on their high school grades (GPA), entrance exam results in English subject (written) as well as in the interview was extracted as baseline information. Data were subjected to various statistical treatment (average means, percentages and pearson-r moment coefficient correlation) and found out that, Nautical Science and Marine Engineering students were found to have average high school grade, entrance test results, both written and in the interview turned out to be very satisfactory at 50% passing percentage. Varied results were manifested in their affective attributes towards learning the second language. On attitude, nautical science students had true positive attitude while marine engineering had only a moderate positive one. Secondly, the former were positively motivated to learn English while the latter were just moderately motivated. As regards anxiety, both groups embodied a moderate level of anxiety in the English language. Finally, data showed that nautical science students exuded real confidence while the marine engineering group had only moderate confidence with the second language. Respondents’ English academic achievement (GWA) was significantly correlated with confidence and speaking with anxiety towards the second language among the students from the nautical science group with moderate positive and low negative degree of correlation, respectively. On the other hand, the marine engineering students’ speaking test result was significantly correlated with anxiety and self-confidence with a moderate negative and low positive degree of correlation, respectively while writing was significantly correlated with motivation bearing a low positive degree of correlation.

Keywords: affective attributes, second language, second language performance, anxiety, attitude, self-confidence and motivation

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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Authors: Qiang Guo, Ruying Qi

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This project aims to trace the developmental patterns of a child's Mandarin and English from China to Australia from age 3; 03 till 5; 06. In childhood bilingual studies, there is an assumption that age 3 is the dividing line between simultaneous bilinguals and sequential bilinguals. Determining similarities and differences between Bilingual First Language Acquisition, Early Second Language Acquisition, and Second Language Acquisition is of great theoretical significance. Studies on Bilingual First Language Acquisition, hereafter, BFLA in the past three decades have shown that the grammatical development of bilingual children progresses through the same developmental trajectories as their monolingual counterparts. Cross-linguistic interaction does not show changes of the basic grammatical knowledge, even in the weaker language. While BFLA studies show consistent results under the conditions of adequate input and meaningful interactional context, the research findings of Early Second Language Acquisition (ESLA) have demonstrated that this cohort proceeds their early English differently from both BFLA and SLA. The different development could be attributed to the age of migration, input pattern, and their Environmental Languages (Lε). In the meantime, the dynamic relationship between the two languages is an issue to invite further attention. The present study attempts to fill this gap. The child in this case study started acquiring L1 Mandarin from birth in China, where the environmental language (Lε) coincided with L1 Mandarin. When she migrated to Australia at 3;06, where the environmental language (Lε) was L2 English, her Mandarin exposure was reduced. On the other hand, she received limited English input starting from 1; 02 in China, where the environmental language (Lε) was L1 Mandarin, a non-English environment. When she relocated to Australia at 3; 06, where the environmental language (Lε) coincided with L2 English, her English exposure significantly increased. The child’s linguistic profile provides an opportunity to explore: (1) What does the child’s English developmental route look like? (2) What does the L1 Mandarin developmental pattern look like in different environmental languages? (3) How do input and environmental language interact in shaping the bilingual child’s linguistic repertoire? In order to answer these questions, two linguistic areas are selected as the focus of the investigation, namely, subject realization and wh-questions. The chosen areas are contrastive in structure but perform the same semantic functions in the two linguistically distant languages and can serve as an ideal testing ground for exploring the developmental path in the two languages. The longitudinal case study adopts a combined approach of qualitative and quantitative analysis. Two years’ Mandarin and English data are examined, and comparisons are made with age-matched monolinguals in each language in CHILDES. To the author’s best knowledge, this study is the first of this kind examining a Mandarin-English bilingual child's bilingual development at a critical age, in different input patterns, and in different environmental languages (Lε). It also expands the scope of the theory of Lε, adding empirical evidence on the relationship between input and Lε in bilingual acquisition.

Keywords: bilingual development, age, input, environmental language (Le)

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Authors: Chandra Gupt Porwal, Preeti C. Porwal

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Transient data reveals much about the machine's condition that steady-state data cannot. New technologies make this information much more available for evaluating the mechanical integrity of a machine train. Recent surveys at various stations indicate that simplicity is preferred over completeness in machine audits throughout the power generation industry. This is most clearly shown by the number of rotating machinery predictive maintenance programs in which only steady-state vibration amplitude is trended while important transient vibration data is not even acquired. Efforts have been made to explain what transient data is, its importance, the types of plots used for its display, and its effective utilization for analysis. In order to demonstrate the value of measuring transient data and its practical application in rotating machinery for resolving complex and persistent issues with turbine generators, the author presents a few case studies that highlight the presence of rotor instabilities due to the shaft moving towards the bearing centre in a 100 MM LMZ unit located in the Northern Capital Region (NCR), heavy misalignment noticed—especially after 2993 rpm—caused by loose coupling bolts, which prevented the machine from being synchronized for more than four months in a 250 MW KWU unit in the Western Region (WR), and heavy preload noticed at Intermediate pressure turbine (IPT) bearing near HP- IP coupling, caused by high points on coupling faces at a 500 MW KWU unit in the Northern region (NR), experienced at Indian power plants.

Keywords: transient data, steady-state-data, intermediate -pressure-turbine, high-points

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Authors: Anna Kesoyan

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The present paper deals with the syntax-related problems of translation from English into Armenian. Although Syntax is a part of grammar, syntax-related problems of translation are studied separately during the process of translation. Translation from one language to another is widely accepted as a challenging problem. This becomes even more challenging when the source and target languages are widely different in structure and style, as is the case with English and Armenian. Syntax-related problems of translation from English into Armenian are mainly connected with the syntactical structures of these languages, and particularly, with the word order of the sentence. The word order of the sentence of the Armenian language, which is a synthetic language, is usually characterized as “rather free”, and the word order of the English language, which is an analytical language, is characterized “fixed”. The following research examines the main translation means, particularly, syntactical transformations as the translator has to take real steps while trying to solve certain syntax-related problems. Most of the means of translation are based on the transformation of grammatical components of the sentence, without changing the main information of the text. There are several transformations that occur during translation such as word order of the sentence, transformations of certain grammatical constructions like Infinitive participial construction, Nominative with the Infinitive and Elliptical constructions which have been covered in the following research.

Keywords: elliptical constructions, nominative with the infinitive constructions, fixed and free word order, syntactic structures

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Authors: Fatima Al-Aswadi, Chan Yong

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With the large volume of unstructured data that increases day by day on the web, the motivation of representing the knowledge in this data in the machine processable form is increased. Ontology is one of the major cornerstones of representing the information in a more meaningful way on the semantic Web. The goal of Ontology learning from text is to elicit and represent domain knowledge in the machine readable form. This paper aims to give a follow-up review on the ontology learning systems from text and some of their defects. Furthermore, it discusses how far the ontology learning process will enhance in the future.

Keywords: concept discovery, deep learning, ontology learning, semantic relation, semantic web

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Authors: Yusri Yusof, Kamran Latif

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Computer Numeric Control (CNC) machine has been widely used in the industries since its inception. Currently, in CNC technology has been used for various operations like milling, drilling, packing and welding etc. with the rapid growth in the manufacturing world the demand of flexibility in the CNC machines has rapidly increased. Previously, the commercial CNC failed to provide flexibility because its structure was of closed nature that does not provide access to the inner features of CNC. Also CNC’s operating ISO data interface model was found to be limited. Therefore, to overcome that problem, Open Architecture Control (OAC) technology and STEP-NC data interface model are introduced. At present the Personal Computer (PC) has been the best platform for the development of open-CNC systems. In this paper, both ISO data interface model interpretation, its verification and execution has been highlighted with the introduction of the new techniques. The proposed is composed of ISO data interpretation, 3D simulation and machine motion control modules. The system is tested on an old 3 axis CNC milling machine. The results are found to be satisfactory in performance. This implementation has successfully enabled sustainable manufacturing environment.

Keywords: CNC, ISO 6983, ISO 14649, LabVIEW, open architecture control, reconfigurable manufacturing systems, sustainable manufacturing, Soft-CNC

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