Search results for: large language models (LLMS)

Authors: Derejaw Lake Melie, Alemu Kumlachew Tegegne

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The increasing prevalence of social media in Ethiopia has exacerbated societal challenges by fostering the proliferation of negative emotional posts and comments. Illicit use of social media has further exacerbated divisions among the population. Addressing these issues through manual identification and aggregation of emotions from millions of users for swift decision-making poses significant challenges, particularly given the rapid growth of Amharic language usage on social platforms. Consequently, there is a critical need to develop an intelligent system capable of automatically detecting and categorizing negative emotional content into social, religious, and political categories while also filtering out toxic online content. This paper aims to leverage sentiment analysis techniques to achieve automatic detection and filtering of negative emotional content from Amharic social media texts, employing a comparative study of deep learning algorithms. The study utilized a dataset comprising 29,962 comments collected from social media platforms using comment exporter software. Data pre-processing techniques were applied to enhance data quality, followed by the implementation of deep learning methods for training, testing, and evaluation. The results showed that CNN, GRU, LSTM, and Bi-LSTM classification models achieved accuracies of 83%, 50%, 84%, and 86%, respectively. Among these models, Bi-LSTM demonstrated the highest accuracy of 86% in the experiment.

Keywords: negative emotion, emotion detection, social media filtering sentiment analysis, deep learning.

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Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

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Authors: Nicolò Vaiana, Mariacristina Spizzuoco, Giorgio Serino

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In this paper, the results of experimental tests performed on a Helical Wire Rope Isolator (HWRI) are presented in order to describe the dynamic and static behavior of the selected metal device in three different displacements ranges, namely small, relatively large, and large displacements ranges, without and under the effect of a vertical load. A testing machine, allowing to apply horizontal displacement or load histories to the tested bearing with a constant vertical load, has been adopted to perform the dynamic and static tests. According to the experimental results, the dynamic behavior of the tested device depends on the applied displacement amplitude. Indeed, the HWRI displays a softening and a hardening stiffness at small and relatively large displacements, respectively, and a stronger nonlinear stiffening behavior at large displacements. Furthermore, the experimental tests reveal that the application of a vertical load allows to have a more flexible device with higher damping properties and that the applied vertical load affects much less the dynamic response of the metal device at large displacements. Finally, a decrease in the static to dynamic effective stiffness ratio with increasing displacement amplitude has been observed.

Keywords: base isolation, earthquake engineering, experimental hysteresis loops, wire rope isolators

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Authors: McKenzie S. Braley, Lesley Jessiman

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

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

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Authors: John Mambambo

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Debates on the link between Bantu languages are often epitomized by animated theoretical critiques, including the language zoning and groupings. This evaluative, qualitative inquiry hovers above theoretical critiques to offer the sparsely studied ChiShona and isiXhosa code-switching nexus, a yawning gap in scholarship. Using interviews, questionnaires and observations, data germane to the study were collected from a purposively selected group of Shona speakers who had resided in Xhosa-speaking communities for not less than a year. Deploying Myers-Scotton’s Markedness theory, the paper gazes into the pragmatic linguistic affinity that is affirmed through the Shona-Xhosa code-switching in Cape Town. The assorted social variables motivating bilingual speakers to code-switch in Cape Town are also explored in this study. The study unveils that Shona speakers are motivated to code-switch by the linguistic affinity between ChiShona and isiXhosa. Other socio-political justifications also give an impetus to this phenomenon. The Matrix Language Frame Model affirms that ChiShona is the base while isiXhosa is the embedded language during code-switching. This paper is a momentous advancement of the extant literature on code-switching. It is a unique contribution to the nexus between ChiShona and isiXhosa languages, providing fresh insights into the discourse on African language comparison studies.

Keywords: code-switching, chishona, isiXhosa, bilingualism

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Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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Authors: Yuh-Jen Wu, Chun-Min Lin

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Homophonic words are common in Mandarin Chinese which belongs to the tonal language family. Using homophonic cues to study foreign languages is one of the learning techniques of mnemonics that can aid the retention and retrieval of information in the human memory. When learning difficult foreign words, some learners transpose them with words in a language they are familiar with to build an association and strengthen working memory. These phonological clues are beneficial means for novice language learners. In the classroom, if mnemonic skills are used at the appropriate time in the instructional sequence, it may achieve their maximum effectiveness. For Chinese-speaking students, proper use of Chinese-English homophonic word pairs may help them learn difficult vocabulary. In this study, a database program is developed by employing Visual Basic. The database contains two corpora, one with Chinese lexical items and the other with English ones. The Chinese corpus contains 59,053 Chinese words that were collected by a web crawler. The pronunciations of this group of words are compared with words in an English corpus based on WordNet, a lexical database for the English language. Words in both databases with similar pronunciation chunks and batches are detected. A total of approximately 1,000 Chinese lexical items are located in the preliminary comparison. These homophonic word pairs can serve as a valuable tool to assist Chinese-speaking students in learning and memorizing new English vocabulary.

Keywords: Chinese, corpus, English, homophonic words, vocabulary

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Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

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Authors: Rajendra Chetty

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The paper aims to address two aspects of postgraduate studies: interdisciplinary research and creative models of supervision. Interdisciplinary research can be viewed as a key imperative to solve complex problems. While excellent research requires a context of disciplinary strength, the cutting edge is often found at the intersection between disciplines. Interdisciplinary research foregrounds a team approach and information, methodologies, designs, and theories from different disciplines are integrated to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline. Our aim should also be to generate research that transcends the original disciplines i.e. transdisciplinary research. Complexity is characteristic of the knowledge economy, hence, postgraduate research and engaged scholarship should be viewed by universities as primary vehicles through which knowledge can be generated to have a meaningful impact on society. There are far too many ‘ordinary’ studies that fall into the realm of credentialism and certification as opposed to significant studies that generate new knowledge and provide a trajectory for further academic discourse. Secondly, the paper will look at models of supervision that are different to the dominant ‘apprentice’ or individual approach. A reflective practitioner approach would be used to discuss a range of supervision models that resonate well with the principles of interdisciplinarity, growth in the postgraduate sector and a commitment to engaged scholarship. The global demand for postgraduate education has resulted in increased intake and new demands to limited supervision capacity at institutions. Team supervision lodged within large-scale research projects, working with a cohort of students within a research theme, the journal article route of doctoral studies and the professional PhD are some of the models that provide an alternative to the traditional approach. International cooperation should be encouraged in the production of high-impact research and institutions should be committed to stimulating international linkages which would result in co-supervision and mobility of postgraduate students and global significance of postgraduate research. International linkages are also valuable in increasing the capacity for supervision at new and developing universities. Innovative co-supervision and joint-degree options with global partners should be explored within strategic planning for innovative postgraduate programmes. Co-supervision of PhD students is probably the strongest driver (besides funding) for collaborative research as it provides the glue of shared interest, advantage and commitment between supervisors. The students’ field serves and informs the co-supervisors own research agendas and helps to shape over-arching research themes through shared research findings.

Keywords: interdisciplinarity, internationalisation, postgraduate, supervision

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Authors: Sabyasachi Mukhopadhyay, Joseph Ogutu, Gundula Bartzke, Hans-Peter Piepho

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Rainfall is a critical component of climate governing vegetation growth and production, forage availability and quality for herbivores. However, reliable rainfall measurements are not always available, making it necessary to predict rainfall values for particular locations through time. Predicting rainfall in space and time can be a complex and challenging task, especially where the rain gauge network is sparse and measurements are not recorded consistently for all rain gauges, leading to many missing values. Here, we develop a flexible Bayesian model for predicting rainfall in space and time and apply it to Narok County, situated in southwestern Kenya, using data collected at 23 rain gauges from 1965 to 2015. Narok County encompasses the Maasai Mara ecosystem, the northern-most section of the Mara-Serengeti ecosystem, famous for its diverse and abundant large mammal populations and spectacular migration of enormous herds of wildebeest, zebra and Thomson's gazelle. The model incorporates geographical and meteorological predictor variables, including elevation, distance to Lake Victoria and minimum temperature. We assess the efficiency of the model by comparing it empirically with the established Gaussian process, Kriging, simple linear and Bayesian linear models. We use the model to predict total monthly rainfall and its standard error for all 5 * 5 km grid cells in Narok County. Using the Monte Carlo integration method, we estimate seasonal and annual rainfall and their standard errors for 29 sub-regions in Narok. Finally, we use the predicted rainfall to predict large herbivore biomass in the Maasai Mara ecosystem on a 5 * 5 km grid for both the wet and dry seasons. We show that herbivore biomass increases with rainfall in both seasons. The model can handle data from a sparse network of observations with many missing values and performs at least as well as or better than four established and widely used models, on the Narok data set. The model produces rainfall predictions consistent with expectation and in good agreement with the blended station and satellite rainfall values. The predictions are precise enough for most practical purposes. The model is very general and applicable to other variables besides rainfall.

Keywords: non-stationary covariance function, gaussian process, ungulate biomass, MCMC, maasai mara ecosystem

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Elif Aykin Dincer, Mustafa Erbas

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The vacuum drying behavior of beef slices (10 x 4 x 0.2 cm3) was experimentally investigated at the temperature of 60, 70, and 80°C under 25 mbar ultimate vacuum pressure and the mathematical models (Lewis, Page, Midilli, Two-term, Wangh and Singh and Modified Henderson and Pabis) were used to fit the vacuum drying of beef slices. The increase in drying air temperature resulted in a decrease in drying time. It took approximately 206, 180 and 157 min to dry beef slices from an initial moisture content to a final moisture content of 0.05 kg water/kg dry matter at 60, 70 and 80 °C of vacuum drying, respectively. It is also observed that the drying rate increased with increasing drying temperature. The coefficients (R2), the reduced chi-square (x²) and root mean square error (RMSE) values were obtained by application of six models to the experimental drying data. The best model with the highest R2 and, the lowest x² and RMSE values was selected to describe the drying characteristics of beef slices. The Page model has shown a better fit to the experimental drying data as compared to other models. In addition, the effective moisture diffusivities of beef slices in the vacuum drying at 60 - 80 °C varied in the range of 1.05 – 1.09 x 10-10 m2/s. Consequently, this results can be used to simulate vacuum drying process of beef slices and improve efficiency of the drying process.

Keywords: beef slice, drying models, effective diffusivity, vacuum

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Authors: Marta Cordero-Gracia, Mariola Gomez, Olivier Blesbois, Marina Carrion

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One of the difficulties in icing simulations is for extended periods of exposure, when very large ice shapes are created. As well as being large, they can have complex shapes, such as a double horn. For icing simulations, these configurations are currently computed in several steps. The icing step is stopped when the ice shapes become too large, at which point a new mesh has to be created to allow for further CFD and ice growth simulations to be performed. This can be very costly, and is a limiting factor in the simulations that can be performed. A way to avoid the costly human intervention in the re-meshing step of multistep icing computation is to use mesh deformation instead of re-meshing. The aim of the present work is to apply an interpolation method based on Radial Basis Functions (RBF) to transfer deformations from surface mesh to volume mesh. This deformation tool has been developed specifically for icing problems. It is able to deal with localized, sharp and large deformations, unlike the tools traditionally used for more smooth wing deformations. This tool will be presented along with validation on typical two-dimensional icing shapes.

Keywords: ice accretion, interpolation, mesh deformation, radial basis functions

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Authors: Alemaw Kefale, Aramde Fetene, Hayal Desta

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This study analyzed the users' and experts' views on the green space quality and planning models in Debre Berhan (DB) and Debre Markos (DM) cities in Ethiopia. A questionnaire survey was conducted on 350 park users (148 from DB and 202 from DM) to rate the accessibility, size, shape, vegetation cover, social and cultural context, conservation and heritage, community participation, attractiveness, comfort, safety, inclusiveness, and maintenance of green spaces using a Likert scale. A key informant interview was held with 13 experts in DB and 12 in DM. Descriptive statistics and tests of independence of variables using the chi-square test were done. A statistically significant association existed between the perception of green space quality attributes and users' occupation (χ² (160, N = 350) = 224.463, p < 0.001), age (χ² (128, N = 350) = 212.812, p < 0.001), gender (χ² (32, N = 350) = 68.443, p < 0.001), and education level (χ² (192, N = 350) = 293.396, p < 0.001). 61.7 % of park users were unsatisfied with the quality of urban green spaces. The users perceived dense vegetation cover as "good," with a mean value of 3.41, while the remaining were perceived as "medium with a mean value of 2.62 – 3.32". Only quantitative space standards are practiced as a green space planning model, while other models are unfamiliar and never used in either city. Therefore, experts need to be aware of and practice urban green models during urban planning to ensure that new developments include green spaces to accommodate the community's and the environment's needs.

Keywords: urban green space, quality, users and experts, green space planning models, Ethiopia

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Authors: Safa Kaka

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As more and more students are travelling to different countries to study and, in particular, to study English, the question of what motivates them to make such a large move has come under question. This is particularly pertinent in the case of Arab students who make up nearly 15% of the foreign student body in the UK. Given that the cultural differences between the UK and Arab nations are extremely wide, the decision to come to this country to study English must be driven by strong motivational forces. Numerous previous studies have considered what motivates foreign students to travel to the UK and other countries for their education or language learning but the specific motivators of Arab students have yet to be explored. This study undertakes to close that gap by examining the concepts and theories of motivation, both in general terms and in relation to English learning and foreign study. 70 Arab students currently studying in the UK were asked to participate in an online questionnaire which asked about their motivations for coming to the UK and for studying and learning English. A further six individuals were interviewed on a face to face basis. The outcomes have indicated that the factors which motivate the decision to come to the UK are similar to those that motivate the desire to learn English. In particular a motivation for self-improvement, career advancement and potential future benefits were cited by a number of respondents. Other indications were the ease of accessibility to the UK as an English speaking country, a motivation to experience different cultures and lifestyles and even political freedoms. Overall the motivations of Arab students were not found to be conspicuously different from those of other foreign students, although it was noted that their motivations did change, both positively and negatively following a period of time in the country. These changes were based on the expectations of the students pre-arrival and their actual experience of the country and its teaching approaches and establishments and were, as indicated both good and bad. The implications for the Arab student population and UK educational establishments are reviewed and future research pathways highlighted.

Keywords: motivation, Arab learners of English, language teaching, applied linguistics

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Authors: Mamta Rajbhar, Sanjay K. Mohanty

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India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.

Keywords: Fertility, HDI, Uttar Pradesh

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Authors: Forrest Kaatz, Adhemar Bultheel

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Au-Cu and Pt-M (M = Fe, Co, and Ni) nanocluster alloys are currently being investigated worldwide by many researchers for their interesting catalytic and nanophase properties. The low-temperature behavior of the phase diagrams is not well understood for alloys with nanometer sizes and shapes. These systems have similar bulk phase diagrams with the L12 (Au3Cu, Pt3M, AuCu3, and PtM3) structurally ordered intermetallics and the L10 structure for the AuCu and PtM intermetallics. We consider three models for low temperature ordering in the phase diagrams of Au–Cu and Pt–M nanocluster alloys. These models are valid for sizes ~ 5 nm and approach bulk values for sizes ~ 20 nm. We study the phase transition in nanoclusters with cubic, octahedral, and cuboctahedral shapes, covering the compositions of interest. These models are based on studying the melting temperatures in nanoclusters using the regular solution, mixing model for alloys. Experimentally, it is extremely challenging to determine thermodynamic data on nano–sized alloys. Reasonable agreement is found between these models and recent experimental data on nanometer clusters in the Au–Cu and Pt–M nanophase systems. From our data, experiments on nanocubes about 5 nm in size, of stoichiometric AuCu and PtM composition, could help differentiate between the models. Some available evidence indicates that ordered intermetallic nanoclusters have better catalytic properties than disordered ones. We conclude with a discussion of physical mechanisms whereby ordering could improve the catalytic properties of nanocluster alloys.

Keywords: catalytic reactions, gold nanoalloys, phase transitions, platinum nanoalloys

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Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

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The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

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Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

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The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19^th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

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Authors: Saeed Moarrefi, Shou-Han Zhou, Liyuan Fan

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Coupling with solid oxide fuel cells, methane dry reforming is a promising pathway for energy production while mitigating carbon emissions. However, the influence of carbon dioxide and electrochemical reactions on the internal dry reforming reaction within the fuel cells remains debatable, requiring accurate kinetic models to describe the internal reforming behaviors. We employed the Power-Law and Langmuir Hinshelwood–Hougen Watson models in an electrolyte-supported solid oxide fuel cell with a NiO-GDC-YSZ anode. The current density used in this study ranges from 0 to 1000 A/m2 at 973 K to 1173 K to estimate various kinetic parameters. The influence of the electrochemical reactions on the adsorption terms, the equilibrium of the reactions, the activation energy, the pre-exponential factor of the rate constant, and the adsorption equilibrium constant were studied. This study provides essential parameters for future simulations and highlights the need for a more detailed examination of reforming kinetic models.

Keywords: dry reforming kinetics, Langmuir Hinshelwood–Hougen Watson, power-law, SOFC

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Authors: Wei Hing Rosenkvist

Abstract:

In the past few decades, concerns and demands of promoting student intercultural communicative competence in foreign language education have been increasing along with the rapid growth of information technologies and globalization in the 21st century. In Sweden, related concepts such as internationalization, global citizenship, multiculturalism, and intercultural communication, are also keywords that would be found in the written learning objectives of foreign language education at all levels. Being one of the leading higher institutes in distance education in Europe, Dalarna University clearly states that after completion of the teacher education program, students shall understand the needs for integrating internationalization, intercultural and global perspective in teaching and learning in Swedish schools and implement their studies to promote education in an international and global context. Even though many teachers and educators agree with the institutes’ mission and vision about the importance of internationalization and the need to increase student understanding of intercultural and global perspectives, they might find this objective unattainable and restricted due to the nature of the subject and their knowledge of intercultural competence. When conducting a comprehensive Chinese language course for the students who are going to become Chinese foreign language teachers, the researcher found that all the learning objectives are linguistic oriented while grammatical components dominate the entire course. Apparently, there is a gap between the learning objectives of the course and the DU’s mission of fostering an international learner with intercultural and globalized perspectives. How to include this macro-learning objective in a foreign language course is a great challenge to the educator. Although scholars from different academic domains have provided different theoretical frameworks and approaches for developing student intercultural competence, research that focuses on the didactic perspectives of developing student intercultural competence in teaching Chinese as a foreign language education (CFL) is limited, and practical examples are rare. This challenge has motivated the researcher to conduct an action research study that aims at integrating DU’s macro-learning objective in a current CFL course through different didactic practices to develop the student's intercultural competence. This research study aims to, firstly, illustrate the cross-cultural knowledge integrated into the present Chinese language course for developing intercultural competence. Secondly, it investigates different didactic means that can be utilized to deliver cross-cultural knowledge to student teachers in the present course without generating dramatic disturbance of the syllabus. Thirdly, it examines the effectiveness of these didactic means in enhancing student-teacher intercultural competence regarding the need for integrating and implementing internationalization, intercultural and global perspectives in teaching and learning in Swedish schools. Last but not least, it intends to serve as a practical example for developing the student teachers’ intercultural competence in foreign language education in DU and fill in the research gap of this academic domain worldwide.

Keywords: action research, intercultural competence, Chinese as a foreign language education, teacher education

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Authors: Hela Fathallah

Abstract:

With 6,500 spoken languages all over the world but 80 percent of online content available only in 10 languages – English, Chinese, Spanish, Japanese, Arabic, Portuguese, German, French, Russian, and Korean – language represents a barrier to the universal access to knowledge, information and services that the internet wants to provide. Translation and its related fields of localization, interpreting, globalization, and internationalization, remove that barrier for billions of people worldwide, unlocking new markets for technology companies, mobile device makers, service providers and language vendors as well. This paper gathers different surveys conducted in different regions of the world that demonstrate a growing demand for consumption of web content with distinctive values and in languages others than the aforementioned ones. It also adds new insights to the contribution of translation in languages preservation. The idea that English is the language of internet and that, in a globalized world, everyone should learn English to cope with new technologies is no longer true. This idea has reached its limits. It collides with cultural diversity and differences around the world and generates an accelerated rate of languages extinction. Studies prove that internet exacerbates this rate and web giants such as Facebook or Google are, today, facing the impact of such a misconception of globalization. For internet and dot-com companies, localization is the solution; they are spending a significant amount of time to understand what people want and to figure out how to provide it. They are committed to making their content accessible, if not in all the languages spoken today, at least in most of them, and to adapting it to most cultures. Technology has broken down the barriers of time and space, and it will break down the language barrier as well by undertaking a process of translation and localization and through a new definition of globalization that takes into consideration these two processes.

Keywords: globalization, internet, localization, translation

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Authors: Zakhile Somlata

Abstract:

In the context of international linguistic and cultural diversity, all languages can be used for all purposes. Africa in general and South Africa, in particular, is not an exception to multilingual and multicultural society. The multilingual and multicultural nature of South African society has a direct bearing to the heterogeneity of South African Universities in general. Universities as the centers of research, innovation, and transformation of the entire society should be at the forefront in leading multilingualism. The universities in South Africa had been using English and to a certain extent Afrikaans as the only academic languages during colonialism and apartheid regime. The democratic breakthrough of 1994 brought linguistic relief in South Africa. The Constitution of the Republic of South Africa recognizes 11 official languages that should enjoy parity of esteem for the realization of multilingualism. The elevation of the nine previously marginalized indigenous African languages as academic languages in higher education is central to multilingualism. It is high time that Afrocentric model instead of Eurocentric model should be the one which underpins education system in South Africa at all levels. Almost all South African universities have their language policies that seek to promote access and success of students through multilingualism, but the main dilemma is the implementation of language policies. This study is significant to respond to two objectives: (i) To evaluate how selected institutions use language policies for accessibility and success of students. (ii) To study how selected universities integrate African languages for both academic and administrative purposes. This paper reflects the language policy practices in one selected University of Technology (UoT) in South Africa. The UoT has its own language policy which depicts linguistic diversity of the institution and its commitment to promote multilingualism. Translanguaging pedagogy which accommodates minority languages' usage in the teaching and learning process plays a pivotal role in promoting multilingualism. This research paper employs mixed methods (quantitative and qualitative research) approach. Qualitative data has been collected from the key informants (insiders and experts), while quantitative data has been collected from a cohort of third-year students. A mixed methods approach with its convergent parallel design allows the data to be collected separately, analysed separately but with the comparison of the results. Language development initiatives have been discussed within the framework of language policy and policy implementation strategies. Theoretically, this paper is rooted in language as a problem, language as a right and language as a resource. The findings demonstrate that despite being a multilingual institution, there is a perpetuation of marginalization of African languages to be used as academic languages. Findings further display the hegemony of English. The promotion of status quo compromises the promotion of multilingualism, Africanization of Higher Education and intellectualization of indigenous African languages in South Africa under a democratic dispensation.

Keywords: afro-centric model, hegemony of English, language as a resource, translanguaging pedagogy

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Authors: Jane-Francis A. Abongdia, Thandiswa Mpiti

Abstract:

There is an international concern to develop children’s literacy skills. In many parts of the world, the need to become fluent in a second language is essential for gaining meaningful access to education, the labour market and broader social functioning. In spite of these efforts, the problem still continues. The level of English language proficiency is far from satisfactory and these goals are unattainable by others. The issue is more complex in South Africa as learners are immersed in a second language (L2) curriculum. South Africa is a prime example of a country facing the dilemma of how to effectively equip a majority of its population with English as a second language or first additional language (FAL). Given the multilingual nature of South Africa with eleven official languages, and the position and power of English, the study investigates teachers’ and learners’ experiences on isiXhosa and Afrikaans background learners’ writing in English First Additional Language (EFAL). Moreover, possible causes of writing difficulties and teacher’s practices for writing are explored. The theoretical and conceptual framework for the study is provided by studies on constructivist theories and sociocultural theories. In exploring these issues, a qualitative approach through semi-structured interviews, classroom observations, and document analysis were adopted. This data is analysed by critical discourse analysis (CDA). The study identified a weak correlation between teachers’ beliefs and their actual teaching practices. Although the teachers believe that writing is as important as listening, speaking, reading, grammar and vocabulary, and that it needs regular practice, the data reveal that they fail to put their beliefs into practice. Moreover, the data revealed that learners were disturbed by their home language because when they do not know a word they would write either the isiXhosa or the Afrikaans equivalent. Code-switching seems to have instilled a sense of “dependence on translations” where some learners would not even try to answer English questions but would wait for the teacher to translate the questions into isiXhosa or Afrikaans before they could attempt to give answers. The findings of the study show a marked improvement in the writing performance of learners who used the process approach in writing. These findings demonstrate the need for assisting teachers to shift away from focusing only on learners’ performance (testing and grading) towards a stronger emphasis on the process of writing. The study concludes that the process approach to writing could enable teachers to focus on the various parts of the writing process which can give more freedom to learners to experiment their language proficiency. It would require that teachers develop a deeper understanding of the process/genre approaches to teaching writing advocated by CAPS. All in all, the study shows that both learners and teachers face numerous challenges relating to writing. This means that more work still needs to be done in this area. The present study argues that teachers teaching EFAL learners should approach writing as a critical and core aspect of learners’ education. Learners should be exposed to intensive writing activities throughout their school years.

Keywords: constructivism, English second language, language of learning and teaching, writing

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Authors: Jayashree Aanand, Gajjam

Abstract:

The grammatical tradition in Sanskrit literature emphasizes the importance of the correct use of Sanskrit words or linguistic units (sādhu śabda) that brings the meritorious values, denying the attribution of the same religious merit to the incorrect use of Sanskrit words (asādhu śabda) or the vernacular or corrupt forms (apa-śabda or apabhraṁśa), even though they may help in communication. The current research, the culmination of the doctoral research on sentence definition, studies the difference among the comprehension of both correct and incorrect word forms in Sanskrit and Marathi languages in India. Based on the total of 19 experiments (both web-based and classroom-controlled) on approximately 900 Indian readers, it is found that while the incorrect forms in Sanskrit are comprehended with lesser accuracy than the correct word forms, no such difference can be seen for the Marathi language. It is interpreted that the incorrect word forms in the native language or in the language which is spoken daily (such as Marathi) will pose a lesser cognitive load as compared to the language that is not spoken on a daily basis but only used for reading (such as Sanskrit). The theoretical base for the research problem is as follows: among the three main schools of Language Science in ancient India, the Vaiyākaraṇas (Grammarians) hold that the corrupt word forms do have their own expressive power since they convey meaning, while as the Mimāṁsakas (the Exegesists) and the Naiyāyikas (the Logicians) believe that the corrupt forms can only convey the meaning indirectly, by recalling their association and similarity with the correct forms. The grammarians argue that the vernaculars that are born of the speaker’s inability to speak proper Sanskrit are regarded as degenerate versions or fallen forms of the ‘divine’ Sanskrit language and speakers who could not use proper Sanskrit or the standard language were considered as Śiṣṭa (‘elite’). The different ideas of different schools strictly adhere to their textual dispositions. For the last few years, sociolinguists have agreed that no variety of language is inherently better than any other; they are all the same as long as they serve the need of people that use them. Although the standard form of a language may offer the speakers some advantages, the non-standard variety is considered the most natural style of speaking. This is visible in the results. If the incorrect word forms incur the recall of the correct word forms in the reader as the theory suggests, it would have added one extra step in the process of sentential cognition leading to more cognitive load and less accuracy. This has not been the case for the Marathi language. Although speaking and listening to the vernaculars is the common practice and reading the vernacular is not, Marathi readers have readily and accurately comprehended the incorrect word forms in the sentences, as against the Sanskrit readers. The primary reason being Sanskrit is spoken and also read in the standard form only and the vernacular forms in Sanskrit are not found in the conversational data.

Keywords: experimental sociolinguistics, grammaticality and meaningfulness, Marathi, Sanskrit

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Authors: Mohan Li

Abstract:

Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: David M Gilstrap

Abstract:

In an online course with a large enrollment, the potential exists for the instructor to become overburdened with having to respond to students’ emails, which consequently decreases the instructor’s efficiency in teaching the course. Repetition of instructions is an effective way of reducing confusion among students, which in turn increases their efficiencies, as well. World of Turf is the largest online course at Michigan State University, which employs Brightspace as its management system (LMS) software. Recently, the LMS upgraded its capabilities to utilize agents, which are auto generated email notifications to students based on certain criteria. Agents are additional tools that can enhance course design. They can be run on-demand or according to a schedule. Agents can be timed to effectively remind students of approaching deadlines. The content of these generated emails can also include reinforced instructions. With a large online course, even a small percentage of students that either do not read or do not comprehend the course syllabus or do not notice instructions on course pages can result in numerous emails to the instructor, often near the deadlines for assignments. Utilizing agents to decrease the number of emails from students has enabled the instructor to efficiently instruct more than one thousand students per semester without any graduate student teaching assistants.

Keywords: agents, Brightspace, large enrollment, learning management system, repetition of instructions

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Authors: Samuel Ntsanwisi

Abstract:

This study investigates the transformative role of Artificial Intelligence (AI) and Virtual Reality (VR) in the preservation of endangered African languages. The study is contextualized within the film and television industry, highlighting disparities in screen representation for certain languages in South Africa, underscoring the need for increased visibility and preservation efforts; with globalization and cultural shifts posing significant threats to linguistic diversity, this research explores approaches to language preservation. By leveraging AI technologies, such as speech recognition, translation, and adaptive learning applications, and integrating VR for immersive and interactive experiences, the study aims to create a framework for teaching and passing on endangered African languages. Through digital documentation, interactive language learning applications, storytelling, and community engagement, the research demonstrates how these technologies can empower communities to revitalize their linguistic heritage. This study employs a dual-method approach, combining a rigorous literature review to analyse existing research on the convergence of AI, VR, and language preservation with primary data collection through interviews and surveys with ten filmmakers. The literature review establishes a solid foundation for understanding the current landscape, while interviews with filmmakers provide crucial real-world insights, enriching the study's depth. This balanced methodology ensures a comprehensive exploration of the intersection between AI, VR, and language preservation, offering both theoretical insights and practical perspectives from industry professionals.

Keywords: language preservation, endangered languages, artificial intelligence, virtual reality, interactive learning

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Authors: Ylva Fältholm, Cathrine Norberg

Abstract:

One of the major threats identified to successful future mining is that women do not find the industry attractive. Many attempts have been made, for example in Sweden and Australia, to create organizational structures and mining communities attractive to both genders. Despite such initiatives, many mining areas are developing into gender-segregated fly-in/fly out communities dominated by men with both social and economic consequences. One of the challenges facing many mining companies is thus to break traditional gender patterns and structures. To do this increased knowledge about gender in the context of mining is needed. Since language both constitutes and reproduces knowledge, increased knowledge can be gained through an exploration and description of the mining discourse from a gender perspective. The aim of this study is to explore what conceptual ideas are activated in connection to the physical/geographical mining area and to work within the mining industry. We use a combination of critical discourse analysis implying close reading of selected texts, such as policy documents, interview materials, applications and research and innovation agendas, and analyses of linguistic patterns found in large language corpora covering millions of words of contemporary language production. The quantitative corpus data serves as a point of departure for the qualitative analysis of the texts, that is, suggests what patterns to explore further. The study shows that despite technological and organizational development, one of the most persistent discourses about mining is the conception of dangerous and unfriendly areas infused with traditional notions of masculinity ideals and manual hard work. Although some of the texts analyzed highlight gender issues, and describe gender-equalizing initiatives, such as wage-mapping systems, female networks and recruitment efforts for women executives, and thereby render the discourse less straightforward, it is shown that these texts are not unambiguous examples of a counter-discourse. They rather illustrate that discourses are not stable but include opposing discourses, in dialogue with each other. For example, many texts highlight why and how women are important to mining, at the same time as they suggest that gender and diversity are all about women: why mining is a problem for them, how they should be, and what they should do to fit in. Drawing on a constitutive view of discourse, knowledge about such conflicting perceptions of women is a prerequisite for succeeding in attracting women to the mining industry and thereby contributing to the development of future mining.

Keywords: discourse, corpus linguistics, gender, mining

Procedia PDF Downloads 264

Authors: Wei Hing Rosenkvist

Abstract:

In the past few decades, concerns and demands of promoting student intercultural communicative competence in foreign language education have been increasing along with the rapid growth of information technologies and globalization in the 21st century. In Sweden, related concepts such as internationalization, global citizenship, multiculturalism, and intercultural communication etc., are also keywords that would be found in the written learning objectives of the foreign language education in all levels. Being one of the leading higher institutes in distance education in Europe, Dalarna University clearly states that after completion of the teacher education program, students shall understand the needs for integrating internationalization, intercultural and global perspective in teaching and learning in Swedish schools and implement their own studies to promote education in an international and global context. Despite the fact that many teachers and educators agree with the institutes’ mission and vision about the importance of internationalization and the need of increasing student understanding of intercultural and global perspective, they might find this objective unattainable and restricted due to the nature of the subject and their personal knowledge of intercultural competence. When conducting a comprehensive Chinese language course for the students who are going to become Chinese foreign language teachers, the researcher found that all the learning objectives are linguistic oriented while grammatical components dominate the entire course. Apparently, there is a gap between the learning objectives of the course and the DU’s mission of fostering an international learner with intercultural and globalized perspectives. How to include this macro-learning objective in a foreign language course is a great challenge to the educator. Although scholars from different academic domains have provided different theoretical frameworks and approaches for developing student intercultural competence, research that focuses on the didactic perspectives of developing student intercultural competence in teaching Chinese as a foreign language education (CFL) is limited and practical examples are rare. This has motivated the researcher to conduct an action research study that aims at integrating DU’s macro-learning objective in a current CFL course through different didactic practices with a purpose of developing the teacher student intercultural competence. This research study aims to, firstly, illustrate the cross-cultural knowledge integrated into the present Chinese language course for developing intercultural competence. Secondly, it investigates different didactic means that can be utilized to deliver cross-cultural knowledge to student teachers in the present course without generating dramatic disturbance of the syllabus. Thirdly, it examines the effectiveness of these didactic means in enhancing teacher student intercultural competence regarding the need for integrating and implementing internationalization, intercultural and global perspectives in teaching and learning in Swedish schools. Last but not least, it intends to serve as a practical example for developing the student teachers’ intercultural competence in foreign language education in DU and fill in the research gap of this academic domain worldwide.

Keywords: intercultural competence, foreign language education, action research, teacher education

Procedia PDF Downloads 119