Search results for: language learning

Authors: Mane Varosyan, Diana Tumanyan, Agnesa Martirosyan

Abstract:

There are many catastrophic events that end with dire consequences, and to avoid them, people should be well-armed with the necessary information about these situations. During the last years, Serious Games have increasingly gained popularity for training people for different types of emergencies. The major discussed problem is the usage of gamification in education. Moreover, it is mandatory to understand how and what kind of gamified e-learning modules promote engagement. As the theme is emergency, we also find out people’s behavior for creating the final approach. Our proposed solution is an educational video game, “EZZRA”.

Keywords: gamification, education, emergency, serious games, game design, virtual reality, digitalisation

Procedia PDF Downloads 80

Authors: Kim Alvin De Lara

Abstract:

The research aimed to assess the level of acceptability of the developed activity sheets in Science 5 integrating climate change adaptation of grade 5 science teachers in the District of Pililla school year 2016-2017. In this research, participants were able to recognize and understand the importance of environmental education in improving basic education and integrating them in lessons through localization and contextualization. The researcher conducted the study to develop a material to use by Science teachers in Grade 5. It served also as a self-learning resource for students. The respondents of the study were the thirteen Grade 5 teachers teaching Science 5 in the District of Pililla. Respondents were selected purposively and identified by the researcher. A descriptive method of research was utilized in the research. The main instrument was a checklist which includes items on the objectives, content, tasks, contextualization and localization of the developed activity sheets. The researcher developed a 2-week lesson in Science 5 for 4th Quarter based on the curriculum guide with integration of climate change adaptation. The findings revealed that majority of respondents are female, 31 years old and above, 10 years above in teaching science and have units in master’s degree. With regards to the level of acceptability, the study revealed developed activity sheets in science 5 is very much acceptable. In view of the findings, lessons in science 5 must be contextualized and localized to improve to make the curriculum responds, conforms, reflects, and be flexible to the needs of the learners, especially the 21st century learners who need to be holistically and skillfully developed. As revealed by the findings, it is more acceptable to localized and contextualized the learning materials for pupils. Policy formation and re-organization of the lessons and competencies in Science must be reviewed and re-evaluated. Lessons in science must also be integrated with climate change adaptation since nowadays, people are experiencing change in climate due to global warming and other factors. Through developed activity sheets, researcher strongly supports environmental education and believes this to serve as a way to instill environmental literacy to students.

Keywords: activity sheets, climate change adaptation, contextualization, localization

Procedia PDF Downloads 333

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

Procedia PDF Downloads 146

Authors: V. Mantey, N. Findlay, I. Maddox

Abstract:

The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

Procedia PDF Downloads 174

Authors: Rafik Massoudi

Abstract:

Irish identity continues to be discussed in various fields including social science, culture, literary humanities as well as political debates. In this context, Irishness had been usurped for a long time by the hegemonic power of the British Empire. That is why, Irish writers, in general, and Seamus Heaney along with William Butler Yeats, in particular, endeavored to retrieve this lost identity by shedding light on Irish history, folklore, communal traditions, landscape, indigenous people, language as well as culture. In this context, we may speak of a decolonizing attempt that allowed these writers to represent the autonomous Irish subjectivity by establishing an ethical relationship based on an extraordinary approach to the represented alterity. This article, indeed, places itself within the arena of postmodern, postcolonial discussions of the issue of identity and, particularly, of Irishness.

Keywords: identity, Irishess, narration, postcolonialism

Procedia PDF Downloads 331

Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

Abstract:

Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

Procedia PDF Downloads 173

Authors: Elineuda Do Socorro Santos Picanço Sousa, Ana Kerlly Souza da Costa

Abstract:

This paper presents the analysis of the information society as a plural, inclusive and participatory society, where it is necessary to give all citizens, especially young people, the right skills in order to develop skills so that they can understand and use information through of contemporary technologies; well as carry out a critical analysis, using and producing information and all sorts of messages and / or informational language codes. This conviction inspired this article, whose aim is to present current trends in the use of technology in distance education applied as an alternative and / or supplement to classroom teaching for Youth and Adults, concepts and actions, seeking to contribute to its development in the state of Amapá and specifically, the Center for Professional of Amapá Teaching Professor Josinete Oliveira Barroso - CEPAJOB.

Keywords: youth and adults education, Ead. Professional Education, online courses, CEPAJOB

Procedia PDF Downloads 647

Authors: Dong Seop Lee, Byung Sik Kim

Abstract:

In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 134

Authors: Ahmed Makhoukh

Abstract:

Quality assurance (QA) has recently become a common practice, which is endorsed by most Higher Education (HE) institutions worldwide, due to the pressure of internal and external forces. One of the aims of this quality movement is to make the contribution of university education to socio-economic development highly significant. This entails that graduates are currently required have a high-quality profile, i.e., to be competent and master the 21st-century skills needed in the labor market. This wave of change, mostly imposed by globalization, has the effect that university education should be learner-centered in order to satisfy the different needs of students and meet the expectations of other stakeholders. Such a shift of focus on the student learning outcomes has led HE institutions to reconsider their strategic planning, their mission, the curriculum, the pedagogical competence of the academic staff, among other elements. To ensure that the overall institutional performance is on the right way, a QA system should be established to assume this task of checking regularly the extent to which the set of standards of evaluation are strictly respected as expected. This operation of QA has the advantage of proving the accountability of the institution, gaining the trust of the public with transparency and enjoying an international recognition. This is the case of Doha Institute (DI) for Graduate Studies, in Qatar, the object of the present study. The significance of this contribution is to show that the conception of quality has changed in this digital age, and the need to integrate a department responsible for QA in every HE institution to ensure educational quality, enhance learners and achieve academic leadership. Thus, to undertake the issue of QA in DI for Graduate Studies, an elite university (in the academic sense) that focuses on a small and selected number of students, a qualitative method will be adopted in the description and analysis of the data (document analysis). In an attempt to investigate the extent to which QA is achieved in Doha Institute for Graduate Studies, three broad indicators will be evaluated (input, process and learning outcomes). This investigation will be carried out in line with the UK Quality Code for Higher Education represented by Quality Assurance Agency (QAA).

Keywords: accreditation, higher education, quality, quality assurance, standards

Procedia PDF Downloads 150

Authors: Derek O Reilly, Piotr Milczarski, Shane Dowdall, Artur Hłobaż, Krzysztof Podlaski, Hiram Bollaert

Abstract:

Learning through creation of contextual games is a very promising way/tool for interdisciplinary and international group projects. During 2013 and 2014 we took part and organized two intensive students projects in different conditions. The projects enrolled 68 students and 12 mentors from 5 countries. In the paper we want to share our experience how to strengthen the chances to succeed in short (12-15 days long) student projects. In our case almost all teams prepared working prototype and the results were highly appreciated by external experts.

Keywords: contextual games, mobile games, GGULIVRR, walkabout, Erasmus intensive programme

Procedia PDF Downloads 506

Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

Abstract:

The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

Procedia PDF Downloads 331

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 174

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 165

Authors: Victor Abu

Abstract:

Background: Social justice ideals are considered as the foundation of nursing practice. These ideals are not always clearly integrated into nursing professional standards or curricula. This hinders concerted global nursing agendas for becoming aware of social injustice or engaging in action for social justice to improve the health of individuals and groups. Aim and objectives: The aim was to create an educational framework for empowering nursing students for social justice awareness and action. This purpose was attained by understanding the meaning of social justice, the effect of social injustice, the visibility of social justice learning, and ways of integrating social justice in nursing education and practice. Methods: Critical interpretive methodologies and constructivist grounded theory research designs guided the processes of recruiting nursing students (n = 11) and nurse educators (n = 11) at a London nursing university to participate in interviews and focus groups, which were analysed by coding systems. Findings: Firstly, social justice was described as ethical practices that enable individuals and groups to have good access to health resources. Secondly, social injustice was understood as unfair practices that caused minimal access to resources, social deprivation, and poor health. Thirdly, social justice learning was considered to be invisible in nursing education due to a lack of explicit modules, educator knowledge, and organisational support. Lastly, explicit modules, educating educators, and attracting leaders’ support were suggested as approaches for the visible integration of social justice in nursing education and practice. Discussion: This research proposes approaches for nursing awareness and action for the development of critical active nurse-learner, critical conscious nurse-educator, and servant nurse leader. The framework on Awareness for Social Justice Action (ASJA) created in this research is an approach for empowering nursing students for social justice practices. Conclusion: This research contributes to and advocates for greater nursing scholarship to raise the spotlight on social justice in the profession.

Keywords: social justice, nursing practice, nursing education, nursing curriculum, social justice awareness, social justice action, constructivist grounded theory

Procedia PDF Downloads 64

Authors: C. Fortin, D. Tokmeninova, O. Ushakova

Abstract:

Among 500 Russian universities Skolkovo Institute of Science and Technology (Skoltech) is one of the youngest (established in 2011), quite small and vastly international, comprising 20 percent of international students and 70 percent of faculty with significant academic experience at top-100 universities (QS, THE). The institute has emerged from close collaboration with MIT and leading Russian universities. Skoltech is an entirely English speaking environment. Skoltech curriculum plans of ten Master programs are based on the CDIO learning outcomes model. However, despite the Institute’s unique focus on industrial innovations and startups, one of the main challenges has become an evident large proportion of nearly half of MSc graduates entering PhD programs at Skoltech or other universities rather than industry or entrepreneurship. In order to increase the share of students joining the industrial sector after graduation, Skoltech started implementing a number of unique practices with a focus on employers’ expectations incorporated into the curriculum redesign. In this sense, extended knowledge exchange with industrial partners via collaboration in learning activities, industrial projects and assessments became essential for students’ headway into industrial and entrepreneurship pathways. Current academic curriculum includes the following types of components based on extended knowledge exchange with industrial partners: innovation workshop, industrial immersion, special industrial tracks, MSc defenses. Innovation workshop is a 4 week full time diving into the Skoltech vibrant ecosystem designed to foster innovators, focuses on teamwork, group projects, and sparks entrepreneurial instincts from the very first days of study. From 2019 the number of mentors from industry and startups significantly increased to guide students across these sectors’ demands. Industrial immersion is an exclusive part of Skoltech curriculum where students after the first year of study spend 8 weeks in an industrial company carrying out an individual or team project and are guided jointly by both Skoltech and company supervisors. The aim of the industrial immersion is to familiarize students with relevant needs of Russian industry and to prepare graduates for job placement. During the immersion a company plays the role of a challenge provider for students. Skoltech has started a special industrial track comprising deep collaboration with IPG Photonics – a leading R&D company and manufacturer of high-performance fiber lasers and amplifiers for diverse applications. The track is aimed to train a new cohort of engineers and includes a variety of activities for students within the “Photonics” MSc program. It is expected to be a successful story and used as an example for similar initiatives with other Russian high-tech companies. One of the pathways of extended knowledge exchange with industrial partners is an active involvement of potential employers in MSc Defense Committees to review and assess MSc thesis projects and to participate in defense procedures. The paper will evaluate the effect and results of the above undertaken measures.

Keywords: Curriculum redesign, knowledge exchange model, learning outcomes framework, stakeholder engagement

Procedia PDF Downloads 83

Authors: Melanie Kerschner

Abstract:

Language is our main means of social interaction. News journalism, especially opinion discourse, holds a powerful position in this context. Editorials can be regarded as encounters of different, partially contradictory relationships between discourse participants constructed through the editorial voice. Their primary goal is to shape public opinion by commenting on events already addressed by other journalistic genres in the given newspaper. In doing so, the author tries to establish a consensus over the negotiated matter (i.e. the news event) with the reader. At the same time, he/she claims authority over the “correct” description and evaluation of an event. Yet, how can the relationship and the interaction between the discourse participants, i.e. the journalist, the reader and the news actors represented in the editorial, be best visualized and studied from a cross-cultural perspective? The present research project attempts to give insights into the role of (media) culture in British, Italian and German editorials. For this purpose the presenter will propose a basic framework: the so called “pyramid of discourse participants”, comprising the author, the reader, two types of news actors and the semantic macro-structure (as meta-level of analysis). Based on this framework, the following questions will be addressed: • Which strategies does the author employ to persuade the reader and to prompt him to give his opinion (in the comment section)? • In which ways (and with which linguistic tools) is editorial opinion expressed? • Does the author use adjectives, adverbials and modal verbs to evaluate news actors, their actions and the current state of affairs or does he/she prefer nominal labels? • Which influence do language choice and the related media culture have on the representation of news events in editorials? • In how far does the social context of a given media culture influence the amount of criticism and the way it is mediated so that it is still culturally-acceptable? The following culture-contrastive study shall examine 45 editorials (i.e. 15 per media culture) from six national quality papers that are similar in distribution, importance and the kind of envisaged readership to make valuable conclusions about culturally-motivated similarities and differences in the coverage and assessment of news events. The thematic orientation of the editorials will be the NSA scandal and the reactions of various countries, as this topic was and still is relevant to each of the three media cultures. Starting out from the “pyramid of discourse participants” as underlying framework, eight different criteria will be assigned to the individual discourse participants in the micro-analysis of the editorials. For the purpose of illustration, a single criterion, referring to the salience of authorial opinion, will be selected to demonstrate how the pyramid of discourse participants can be applied as a basis for empirical analysis. Extracts from the corpus shall furthermore enhance the understanding.

Keywords: Micro-analysis of editorials, culture-contrastive research, media culture, interaction between discourse participants, evaluation

Procedia PDF Downloads 522

Authors: A. V. Dolzhikova

Abstract:

The article deals with the problems of labour migration in the Russian Federation in the context of Russia's national security, provides the typology of migrants residing in the territory of the Russian Federation and analyzes the risk factors. The author considers the structure of migration flows and the terms of legal, economic and socio-cultural adaptation of migrants in the Russian Federation. In this connection, the status of the Russian migration legislation, the concept of the comprehensive exam in Russian as a foreign language, history of Russia and the basics of the Russian Federation legislation for foreign citizens which was introduced in Russia on January 1, 2015, are analyzed. The article discloses its role as the adaptation strategy and the factor of Russia's migration security.

Keywords: comprehensive exam, migration policy, migration legislation, Russia's national security

Procedia PDF Downloads 372

Authors: Abeer Karaali

Abstract:

This paper will seek to clarify important key terms such as home schooling and home education as well as the legalities attached to such terms. It will reflect on the recent proposed changes to terminology in NSW, Australia. The various pedagogical approaches to home education will be explored including their prominence in the Australian context. There is a strong focus on literature from Australia. The historical background of home education in Australia will be explained as well as the difference between distance education and home education. The statistics related to home education in Australia will be explored in the scope and compared to the US. The future of home education in Australia will be discussed.

Keywords: alternative education, e-learning, home education, home schooling, online resources, technology

Procedia PDF Downloads 410

Authors: Selim M. Khan

Abstract:

Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

Procedia PDF Downloads 99

Authors: Minh-Thuan Nguyen, Phuong-Thai Nguyen, Van-Vinh Nguyen, Quang-Minh Nguyen

Abstract:

Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the qualify of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.

Keywords: GPT-2, product description, transformer, task-adaptive, language model, pretraining

Procedia PDF Downloads 202

Authors: Gürkan Dağbaşı

Abstract:

Translation is a vitally important activity like as the expression the thought and emotions of humanbeing, providing reciprocal cultural transfer, shaping future by establishing a connection with the past, and like as being exist in an other language. Translation is also an important instrument providing cross-cultural coalescence between nations. Although the first translations from Arabic to Turkish was restricted to only religious texts, over time, the importance of translation was found out via translations of works about literature. Later on, some literature genres like novel and poems were also translated from Arabic to Turkish. Works of many men of Arabic literature were translated to Turkish, including Nejib Mahfuz, owner of Nobel Prize, Tawfiq al-Hakim, Adonis, Gibran Khalil Gibran and etc. In this study, novels and poems translated from Arabic to Turkish between 1980-2015 years are examined.

Keywords: poem, novel, Arabic, translation

Procedia PDF Downloads 381

Authors: Ganga Brahma

Abstract:

Boro employs verbs hooked up with morphemes which lead verbs to adjust with their arguments and hence, affecting the whole of sentence structures. This paper is based on few such syntactic parameters which are usually considered as argument decreasing parameters in linguistic works. Passivizing of few transitive clauses which are usually construed from the verbs occurring with certain morphemes and representation in middle constructions are few of such strategies which lead to conceptualizing of decreasing of syntactic arguments from a sentence. This paper focuses on the mentioned linguistic strategies and attempts to describe the linguistic processes as for how these parameters work in languages especially by concentrating on a particular Tibeto-Burman language i.e. Boro. Boro is a Tibeto-Burman language widely spoken in parts of the north-eastern regions of India. It has an agglutinative nature in forming words as well as clauses. There is a morpheme ‘za’ which means ‘to happen, become’ in Boro whose appearances with verb roots denotes an idea of the subject being passivized. Passivization, usually has notions that it is a reversed representation of its active sentence forms in the terms of argument placements. (However, it is not accountably true as passives and actives have some distinct features of their own and independent of one and the other.) This particular work will concentrate on the semantics of passivization at the same time along with its syntactic reality. The verb khɑo meaning ‘to steal’ offers a sense of passivization with the appearance of the morpheme zɑ which means ‘to happen, become’ (e.g Zunu-ɑ lama-ɑo phɯisɑ khɑo-zɑ-bɑi; Junu-NOM road-LOC money steal-PASS-PRES: Junu got her money stolen on the road). The focus, here, is more on the argument placed at the subject position (i.e. Zunu) and the event taken place. The semantics of such construction asks for the agent because without an agent the event could not have taken place. However, the syntactic elements fill the slots of relegated or temporarily deleted agent which, infact, is the actual subject cum agent in its active representation. Due to the event marker ‘zɑ’ in this presentation it affords to reduce one participant from such a situation which in actual is made up of three participants. Hence, the structure of di-transitive construction here reduces to mono-transitive structure. Unlike passivization, middle construction does not allow relegation of the agents. It permanently deletes agents. However, it also focuses on the fore-grounded subject and highlighting on the changed states on the subjects which happens to be the underlying objects of their respective transitive structures (with agents). This work intends to describe how these two parameters which are different at their semantic realization can meet together at a syntactic level in order to create a linguistic parameter that decreases participants from their actual structures which are with more than one participant.

Keywords: argument-decrease, middle-construction, passivization, transitivity-intransitivity

Procedia PDF Downloads 239

Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

Abstract:

Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

Procedia PDF Downloads 120

Authors: Lou J. Pino, Mark Campbell, Matthew J. Kennedy, Ashleigh C. Kennedy

Abstract:

A concussion is complex and nuanced, with cognitive rest being a key component of recovery. Cognitive overexertion during rehabilitation from a concussion is associated with delayed recovery. However, daily living imposes cognitive demands that may be unavoidable and difficult to quantify. Therefore, a portable tool capable of alerting patients before cognitive overexertion occurs could allow patients to maintain their quality of life while preventing symptoms and recovery setbacks. EEG allows for a sensitive measure of cognitive exertion. Clinical 32-lead EEG headsets are not practical for day-to-day concussion rehabilitation management. However, there are now commercially available and affordable portable EEG headsets. Thus, these headsets can potentially be used to continuously monitor cognitive exertion during mental tasks to alert the wearer of overexertion, with the aim of preventing the occurrence of symptoms to speed recovery times. The objective of this study was to test an algorithm for predicting cognitive exertion from EEG data collected from a portable headset. EEG data were acquired from 10 participants (5 males, 5 females). Each participant wore a portable 4 channel EEG headband while completing 10 tasks: rest (eyes closed), rest (eyes open), three levels of the increasing difficulty of logic puzzles, three levels of increasing difficulty in multiplication questions, rest (eyes open), and rest (eyes closed). After each task, the participant was asked to report their perceived level of cognitive exertion using the NASA Task Load Index (TLX). Each participant then completed a second session on a different day. A customized machine learning model was created using data from the first session. The performance of each model was then tested using data from the second session. The mean correlation coefficient between TLX scores and predicted cognitive exertion was 0.75 ± 0.16. The results support the efficacy of the algorithm for predicting cognitive exertion. This demonstrates that the algorithms developed in this study used with portable EEG devices have the potential to aid in the concussion recovery process by monitoring and warning patients of cognitive overexertion. Preventing cognitive overexertion during recovery may reduce the number of symptoms a patient experiences and may help speed the recovery process.

Keywords: cognitive activity, EEG, machine learning, personalized recovery

Procedia PDF Downloads 225

Authors: Marius Zemp

Abstract:

Evidentials indicate how the speaker obtained the information conveyed in a statement. Detailed diachronic-functional accounts of evidential contrasts found in the Greater Himalayan Region (GHR) reveal that contrasting evidentials are not only defined against each other but also that most of them once had different aspecto-temporal (TA) values which must have aligned when their contrast was conventionalized. Based on these accounts, the present paper sheds light on hitherto unidentified mechanisms of grammatical change. The main insights of the present study were facilitated by ‘functional reconstruction’, which (i) revolves around morphemes which appear to be used in divergent ways within a language and/or across different related languages, (ii) persistently devises hypotheses as to how these functional divergences may have developed, and (iii) retains those hypotheses which most plausibly and economically account for the data. Based on the dense and detailed grammatical literature on the Tibetic language family, the author of this study is able to reconstruct the initial steps by which its evidentiality systems developed: By the time Proto-Tibetan started to be spread across much of Central Asia in the 7th century CE, verbal concatenations with and without a connective -s had become common. As typical for resultative constructions around the globe, Proto-Tibetan *V-s-’dug ‘was there, having undergone V’ (employing the simple past of ’dug ‘stay, be there’) allowed both for a perfect reading (‘the state resulting from V holds at the moment of speech’) and an inferential reading (‘(I infer from its result that) V has taken place’). In Western Tibetic, *V-s-’dug grammaticalized in its perfect meaning as it became contrasted with perfect *V-s-yod ‘is there, having undergone V’ (employing the existential copula yod); that is, *V-s-’dug came to mean that the speaker directly witnessed the profiled result of V, whereas *V-s-yod came to mean that the speaker does not depend on direct evidence of the result, as s/he simply knows that it holds. In Eastern Tibetic, on the other hand, V-s-’dug grammaticalized in its inferential past meaning as it became contrasted with past *V-thal ‘went past V-ing’ (employing the simple past of thal ‘go past’); that is, *V-s-’dug came to mean that the profiled past event was inferred from its result, while *V-thal came to mean that it was directly witnessed. Hence, depending on whether it became contrasted with a perfect or a past construction, resultative V-s-’dug grammaticalized either its direct evidential perfect or its inferential past function. This means that in both cases, evidential readings of constructions with distinct but overlapping TA-values became contrasted, and in order for their contrasting meanings to grammaticalize, the constructions had to agree on their tertium comparationis, which was their shared TA-value. By showing that other types of evidential contrasts in the GHR are also TA-aligned, while no single markers (or privative contrasts) are found to have grammaticalized evidential functions, the present study suggests that, at least in this region of the world, evidential meanings grammaticalize only in equipollent contrasts, which always end up TA-aligned.

Keywords: evidential contrasts, functional-diachronic accounts, grammatical change, himalayan languages, tense/aspect-alignment

Procedia PDF Downloads 132

Authors: Zilungile Sosibo

Abstract:

Constructivism in teacher education is growing tremendously in both the developed and developing world. Proponents of constructivism emphasize active engagement of students in the teaching and learning process. In an effort to keep students engaged while they learn to learn, teachers use a variety of methods to incorporate constructivism in the teaching-learning situations. One area that has a potential for realizing constructivism in the classroom is self-assessment. Sadly, students are rarely involved in the assessment of their work. Instead, the most knowing teacher dominates this process. Student involvement in self-assessments has a potential to teach student teachers to become objective assessors of their students’ work by the time they become credentialed. This is important, as objectivity in assessments is a much-needed skill in the classroom contexts within which teachers deal with students from diverse backgrounds and in which biased assessments should be avoided at all cost. The purpose of the study presented in this paper was to investigate whether student teachers acquired the skills of administering self-assessments objectively after they had been immersed in a formal training program and participated in four sets of self-assessments. The objectives were to determine the extent to which they had mastered the skills of objective self-assessments, their growth and development in this area, and the challenges they encountered in administering self-assessments objectively. The research question was: To what extent did student teachers acquire objectivity in self-assessments after their theoretical and practical engagement in this activity? Data were collected from student teachers through participant observation and semi-structured interviews. The design was a qualitative case study. The sample consisted of 39 final-year student teachers enrolled in a Bachelor of Education teacher education program at a university in South Africa. Results revealed that the formal training program and participation in self-assessments had a minimal effect on students’ acquisition of objectivity in self-assessments, due to the factors associated with self-aggrandizement and hegemony, the latter resulting from gender, religious and racial differences. These results have serious implications for the need to incorporate self-assessments in the teacher-education curriculum, as well as for extended formal training programs for student teachers on assessment in general.

Keywords: objectivity, self-assessment, student teachers, teacher education curriculum

Procedia PDF Downloads 279

Authors: Javiera Espinosa, Patricia López, Noelia Santos, Nadia Loro, Esther Moraleda

Abstract:

In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profile. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder, and on the other hand, many investigations show a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: disability, language, speech, down syndrome

Procedia PDF Downloads 77

Authors: A. Raj Kumar, S. Bilaloglu

Abstract:

Stroke is a leading cause of adult disability worldwide. We depend on our hands for our activities of daily living(ADL). Although many patients regain the ability to walk, they continue to experience long-term hand motor impairments. As the number of individuals with young stroke is increasing, there is a critical need for effective approaches for rehabilitation of hand function post-stroke. Motor relearning for dexterity requires task-specific kinesthetic, tactile and visual feedback. However, when a stroke results in both sensory and motor impairment, it becomes difficult to ascertain when and what type of sensory substitutions can facilitate motor relearning. In an ideal situation, real-time task-specific data on the ability to learn and data-driven feedback to assist such learning will greatly assist rehabilitation for dexterity. We have found that kinesthetic and tactile information from the unaffected hand can assist patients re-learn the use of optimal fingertip forces during a grasp and lift task. Measurement of fingertip grip force (GF), load forces (LF), their corresponding rates (GFR and LFR), and other metrics can be used to gauge the impairment level and progress during learning. Currently ATI mini force-torque sensors are used in research settings to measure and compute the LF, GF, and their rates while grasping objects of different weights and textures. Use of the ATI sensor is cost prohibitive for deployment in clinical or at-home rehabilitation. A cost effective mechatronic device is developed to quantify GF, LF, and their rates for stroke rehabilitation purposes using off-the-shelf components such as load cells, flexi-force sensors, and an Arduino UNO microcontroller. A salient feature of the device is its integration with an interactive gaming environment to render a highly engaging user experience. This paper elaborates the integration of kinesthetic and tactile sensing through computation of LF, GF and their corresponding rates in real time, information processing, and interactive interfacing through augmented reality for visual feedback.

Keywords: feedback, gaming, kinesthetic, rehabilitation, tactile

Procedia PDF Downloads 242

Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

Abstract:

Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

Procedia PDF Downloads 53

Authors: Yusri Yusof, Chen Wong Keong

Abstract:

This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

Procedia PDF Downloads 537