Search results for: online language instruction

Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Villiam C. Ambong, Kevin G. Banawag, Wynne Shane B. Bugatan, Mark Alvin Jay R. Carpio, Hwan Hee Choi, Moses Kevin L. Chungalao

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This survey research investigated the perception of primary school teachers on the efficacy of MTB-MLE in SLU-LES, Baguio City. SLU-LES has a total of 21 primary school teachers who served as the respondents of this study in an attempt to answer three major questions regarding the efficacy of MTB-MLE among primary school teachers. A questionnaire was used in collecting the data which were analyzed using weighted mean and ANOVA. The questionnaire was validated by a statistician and it was administered to a school which does not differ from the intended respondents for further validation of the items. Findings revealed from the intended respondents that they perceive MTB-MLE as effective; however, they do not prefer the use of Mother Tongue as medium of instruction. A research of the same topic was conducted in Ibadan, Nigeria by Dr. David O. Fakeye and although his respondents were students; the results came out that the respondents do perceive MTB-MLE to be efficacious. The results of this study also showed that years of teaching experience and number of languages spoken by the teachers have no bearing on the preference of the respondents between MT medium and English medium given that the respondents are in a melting pot community. Comparative studies between rural schools and urban schools are encouraged. Future researches should include questions that elicit reasons of the respondents on the efficacy of mother tongue as well as their preference between mother tongue medium and English.

Keywords: mother tongue, primary teachers, perception, multilingual education

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Authors: Emilee M. Cruz

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Teachers take part in short-term teaching fellowships abroad, and their preparation before, during, and after the experience is critical to affecting teachers’ feelings of success in the international classroom. A program evaluation of the teacher preparation within TALMA: The Israel Program for Excellence in English (TALMA) full-year teaching fellowship was conducted. A questionnaire was developed that examined professional development, deliberate reflection, and cultural and language immersion offered before, during, and after the short-term experience. The evaluation also surveyed teachers’ feelings of preparedness for the Israeli classroom and any recommendations they had for future teacher preparation within the fellowship program. The review suggests the TALMA program includes integrated professional learning communities between fellows and Israeli co-teachers, more opportunities for immersive Hebrew language learning, a broader professional network with Israelis, and opportunities for guided discussion with the TALMA community continued participation in TALMA events and learning following the full-year fellowship. Similar short-term international programs should consider the findings in the design of their participation preparation programs. The review also offers direction for future program evaluation of short-term participant preparation, including the need for frequent response item updates to match current offerings and evaluation of participant feelings of preparedness before, during, and after the full-year fellowship.

Keywords: educational program evaluation, international teaching, short-term teaching, teacher beliefs, teaching fellowship, teacher preparation

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Authors: Sarina Zainab Shirazi

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Abstract— With the advent of globalization, different countries have liberalized their trade policies to enhance economic integration and developmental processes but the advantages accrued vary greatly from region to region. This study specifically examines European Union (EU) and Association for South East Asian Nations (ASEAN), two regions that show contrasting integration patterns. EU shows most successful integrations versus the slower paced integration in the ASEAN region. A comprehensive panel data empirical investigation of EU and ASEAN in the context of economy size, geographical distances, language, ethnicity, common border and regional trade agreements (RTA) is conducted for a period of 1985 – 2015. The empirical investigation through the augmented gravity equation shows that the real effectiveness for enhanced intra-regional trade is significant when specific examination of export and import components is conducted in the presence of non-tariff barriers. These barriers surface in the form of terms of trade openness, inflation, exchange rate, common borders, common language, ethnic similarity, and presence of a formal regional trade agreement (RTA). Thus, these factors can be utilized by the EU and ASEAN regions in order to formulate effective policy tools to enhance trade within their respective spheres of influence.

Keywords: Association for South East Asian Nations, European Union, Gravity Model, Regional Trade

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Authors: S. Nakayama

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For non-native English speakers, using English modal auxiliary verbs appropriately can be among the most challenging tasks. This research sought to identify differences in modal verb usage between Japanese non-native English speakers (JNNS) and native speakers (NS) from two different perspectives: frequency of use and distribution of verb phrase structures (VPS) where modal verbs occur. This study can contribute to the identification of JNNSs' interlanguage with regard to modal verbs; the main aim is to make a suggestion for the improvement of teaching materials as well as to help language teachers to be able to teach modal verbs in a way that is helpful for learners. To address the primary question in this study, usage of nine central modals (‘can’, ‘could’, ‘may’, ‘might’, ‘shall’, ‘should’, ‘will’, ‘would’, and ‘must’) by JNNS was compared with that by NSs in the International Corpus Network of Asian Learners of English (ICNALE). This corpus is one of the largest freely-available corpora focusing on Asian English learners’ language use. The ICNALE corpus consists of four modules: ‘Spoken Monologue’, ‘Spoken Dialogue’, ‘Written Essays’, and ‘Edited Essays’. Among these, this research adopted the ‘Written Essays’ module only, which is the set of 200-300 word essays and contains approximately 1.3 million words in total. Frequency analysis revealed gaps as well as similarities in frequency order. Specifically, both JNNSs and NSs used ‘can’ with the most frequency, followed by ‘should’ and ‘will’; however, usage of all the other modals except for ‘shall’ was not identical to each other. A log-likelihood test uncovered JNNSs’ overuse of ‘can’ and ‘must’ as well as their underuse of ‘will’ and ‘would’. VPS analysis revealed that JNNSs used modal verbs in a relatively narrow range of VPSs as compared to NSs. Results showed that JNNSs used most of the modals with bare infinitives or the passive voice only whereas NSs used the modals in a wide range of VPSs including the progressive construction and the perfect aspect, both of which were the structures where JNNSs rarely used the modals. Results of frequency analysis suggest that language teachers or teaching materials should explain other modality items so that learners can avoid relying heavily on certain modals and have a wide range of lexical items to reflect their feelings more accurately. Besides, the underused modals should be more stressed in the classroom because they are members of epistemic modals, which allow us to not only interject our views into propositions but also build a relationship with readers. As for VPSs, teaching materials should present more examples of the modals occurring in a wide range of VPSs to help learners to be able to express their opinions from a variety of viewpoints.

Keywords: corpus linguistics, Japanese learners of English, modal auxiliary verbs, International Corpus Network of Asian Learners of English

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Authors: Jonathan J. Foo, Keng Hao Chew

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Interest in virtual reality (VR) technologies as virtual learning environments have been on the rise in recent years. With thanks to the aggressively competitive consumer electronics environment, VR technology has been made affordable and accessible to the average person with developments like Google Cardboard and Oculus Go. While the promise of virtual access to unique virtual learning environments with the benefits of experiential learning sounds extremely attractive, there are still concerns over user comfort in the psychomotor, cognitive, and affective domains. Reports of motion sickness and short durations create doubt and have stunted its growth. In this paper, a multidimensional framework is proposed for the evaluation of VR learning environments within the three dimensions: tactual quality, didactic quality, and autodidactic quality. This paper further proposes a mixed-methods experimental research plan that sets out to evaluate a virtual reality training simulator in the context of amateur sports fencing. The study will investigate if an immersive VR learning environment can effectively simulate an authentic learning environment suitable for instruction, practice, and assessment while providing the user comfort in the tactual, didactic, and autodidactic dimensions. The models and recommendations developed for this study are designed in the context of fencing, but the potential impact is a guide for the future design and evaluation of all VR developments across sports and technical classroom education.

Keywords: autodidactic quality, didactic quality, tactual quality, virtual reality

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Authors: Toshiki Ito, Takahiro Yamane, Yuki Adachi, Yoshiko Kato, Eiji Tsuda, Kousaku Nagasaka, Keigo Yoshida, Yoshiko Kawasaki, Naoki Aizawa, Kyouhei Nishi, Tetsuko Kato

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The epidemic of the coronavirus (COVID-19), first reported in Wuhan at the end of 2019, has drastically changed our daily lives. Under these circumstances, counseling, which provides psychological support to people, was also greatly affected. The structure of counseling, which had generally been implicitly common practice to be conducted in person, was greatly shaken. The author wondered how counseling can be conducted in situations where it is impossible to meet face-to-face. This is where telepsychological support (online counseling) came into use. The authors found that there were the following problems in telepsychological support: (1) anxiety about whether the communication is appropriate, (2) difficulty in understanding the client's situation and condition, (3) inability to perceive what was normally perceived in person, (4) difficulty in adjusting to severely ill clients, (5) difficulty in dealing with emergency situations, etc. In this study, we interviewed psychologists who had been accustomed to telepsychological support for more than two years after the Corona disaster began to clarify how they had or had not overcome the problems of telepsychological support identified in the above studies. We also aim to consider the unique possibilities of how telepsychological support, a new technique of psychological support, can be implemented to provide more effective and meaningful support in society after the end of the Corona disaster (post-Corona society). Thirteen psychologists who are currently providing telepsychological support in the Corona Disaster will be interviewed, and semi-structured interviews will be conducted for one hour per person. In order to empirically examine how the problems in telepsychological support had been overcome or not through the interview survey, the authors asked (1) how they overcame their anxiety about whether they were able to communicate appropriately, (2) how they devised ways to overcome it, (3) how they overcame the difficulty in adapting to heavy clients in terms of the level of the disease, (4) how they overcame the difficulty in dealing with emergency situations. The interviews were analyzed using Thematic Analysis, a qualitative analysis method commonly used in qualitative research overseas. The authors found that some devices and perspectives were newly discovered as a result of two years of practice of telepsychological support and that psychologists in this study considered face-to-face interviews and telepsychological support to be separate and were flexible enough to use them when available and to move to face-to-face interviews when not appropriate.

Keywords: telepsychology, COVID-19, Corona, psychologist

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Authors: Dana Zelicha

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The objective of this paper is to present innovative mindfulness tools specifically designed by OWBA—The Well Being Agency for organisations and corporate wellness programmes. The OWBA Mindfulness Tools (OWBA-MT) consist of practical mindfulness exercises to educate and train employees and business leaders to think, feel, and act more mindfully. Among these cutting-edge interventions are Mindful Meetings, Mindful Decision Making and Unitasking activities, intended to cultivate mindful communication and compassion in the workplace and transform organisational culture. In addition to targeting CEO’s and leaders within large corporations, OWBA-MT is also directed at the needs of specific populations such as entrepreneurs’ resilience and women empowerment. The goals of the OWBA-MT are threefold: to inform, inspire and implement. The first goal is to inform participants about the relationship between workplace stress, distractibility and miscommunication in the framework of mindfulness. The second goal is for the audience to be inspired to share those practices with other members of their organisation. The final objective is to equip participants with the tools to foster a compassionate, mindful and well-balanced work environment. To assess these tools, a 6-week case study was conducted as part of an employee wellness programme for a large international corporation. The OWBA-MT were introduced in a workshop forum once-a-week, with participants practicing these tools both in the office and at home. The workshops occurred 1 day a week (2 hours each), with themes and exercises varying weekly. To reinforce practice at home, participants received reflection forms and guided meditations online. Materials were sent via-email at the same time each day to ensure consistency and participation. To evaluate the effectiveness of the mindfulness intervention, improvements in four categories were measured: listening skills, mindfulness levels, prioritising skills and happiness levels. These factors were assessed using online self-reported questionnaires administered at the start of the intervention, and then again 4-weeks following completion. The measures included the Mindfulness Attention Awareness Scale (MAAS), Listening Skills Inventory (LSI), Time Management Behaviour Scale (TMBS) and a modified version of the Oxford Happiness Questionnaire (OHQ). All four parameters showed significant improvements from the start of the programme to the 4-week follow-up. Participant testimonials exhibited high levels of satisfaction and the overall results indicate that the OWBA-MT intervention substantially impacted the corporation in a positive way. The implications of these results suggest that OWBA-MT can improve employees’ capacities to listen and work well with others, to manage time effectively, and to experience enhanced satisfaction both at work and in life. Although corporate mindfulness programmes have proven to be effective, the challenge remains the low engagement levels at home in between training sessions and to implement the tools beyond the scope of the intervention. OWBA-MT has offered an innovative approach to enforce engagement levels at home by sending daily online materials outside the workshop forum with a personalised response. The limitations also noteworthy to consider for future research include the afterglow effect and lack of generalisability, as this study was conducted on a small and fairly homogenous sample.

Keywords: corporate mindfulness, listening skills, mindful leadership, mindfulness tools, organisational well being

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Authors: Aşina Gülerarslan, M. Faik Özdengül

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The new economic, social and political world order has led to the emergence of a wide range of persuasion strategies and practices based on an ever expanding marketing axis that involves organizations, ideas and persons as well as products and services. It is seen that since the 1990's, a wide variety of competitive marketing ideas have been offered systematically to target audiences in the field of politics as in other fields. When the components of marketing are taken into consideration, all kinds of communication efforts involving “political leaders”, who are conceptualized as products in terms of political marketing, serve a process of social persuasion, which cannot be restricted to election periods only, and a manageable “image”. In this context, image, which is concerned with how the political product is perceived, involves not only the political discourses shared with the public but also all kinds of biographical information about the leader, the leader’s specific way of living and routines and his/her attitudes and behaviors in their private lives, and all these are regarded as components of the “product image”. While on the one hand the leader’s verbal or supra-verbal references serve the way the “spirit of the product” is perceived –just as in brand positioning- they also show their self-esteem levels, in other words how they perceive themselves on the other hand. Indeed, their self-esteem levels are evaluated in three fundamental categories in the “Functional Analysis”, namely parent, child and adult, and it is revealed that the words, tone of voice and body language a person uses makes it easy to understand at what self-esteem level that person is. In this context, words, tone of voice and body language, which provide important clues as to the “self” of the person, are also an indication of how political leaders evaluate both “themselves” and “the mass/audience” in the communication they establish with their audiences. When the matter is taken from the perspective of Turkey, the levels of self-esteem in the relationships that the political leaders establish with the masses are also important in revealing how our society is seen from the perspective of a specific leader. Since the leader is a part of the marketing strategy of a political party as a product, this evaluation is significant in terms of the forms of relationships between political institutions in our country with the society. In this study, the self-esteem level in the documentary entitled “Master’s Story”, where Recep Tayyip Erdoğan’s life history is told, is analyzed in the context of words, tone of voice and body language. Within the scope of the study, at what level of self-esteem Recep Tayyip Erdoğan was in the “Master’s Story”, a documentary broadcast on Beyaz TV, was investigated using the content analysis method. First, based on the Functional Analysis Literature, a transactional approach scale was created regarding parent, adult and child self-esteem levels. On the basis of this scale, the prime minister’s self-esteem level was determined in three basic groups, namely “tone of voice”, “the words he used” and “body language”. Descriptive analyses were made to the data within the framework of these criteria and at what self-esteem level the prime minister spoke throughout the documentary was revealed.

Keywords: political marketing, leader image, level of self-esteem, transactional approach

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Authors: Georgios Alexandropoulos

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This study examines the rhetorical practice of "The consolation to himself upon the departure of the excellent Sallust" written by Flavius Claudius Julian the emperor. Its purpose is to describe the way that Julian uses the language as to have favorable effects on public through certain communicative and rhetorical functions.

Keywords: discourse analysis, Byzantine rhetoric,

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Authors: Ian D. Walker

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This paper describes the creation and teaching of an undergraduate course aimed at promoting critical thinking among the students in the course. The class, Robots in Business and Society, taught at Clemson University, is open to all undergraduate students of any discipline. It is taught as part of Clemson’s online class program and is structured to promote critical thinking via a series of interactive discussion boards and assignments. Critical thinking is measured via pre- and post-testing using a benchmark standardized test. The paper will detail the class organization, and describe and discuss the results and lessons learned with respect to improvement of student critical thinking from three offerings of the class.

Keywords: critical thinking, pedagogy, robotics, undergraduate teaching

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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Authors: Wei Sun, Yan Dong

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There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: robotics, computational thinking, programming, young children, flow chart

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Authors: Jose Marie E. Ocdenaria, Riceli C. Mendoza

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Culturally, languages meet, merge, share, exchange, appropriate, donate, and divide in and to and from each other. Further, this type of recurrence manifests in East Asian cultures, where language influence diffuses across geographical proximities. Historically, China has notable impacts on Japan’s culture. For instance, Japanese borrowed words from China and their way of reading and writing. This qualitative and descriptive employing contrastive analysis study addressed the true and false cognates of Japanese-Philippine languages and Chinese-Philippine languages. It involved a rich collection of data from various sources like textual pieces of evidence or corpora to gain a deeper understanding of true and false cognates between L1 and L2. Cognates of Japanese-Philippine languages and Chinese-Philippine languages were analyzed contrastively according to orthography, phonology, and semantics. The words presented were the roots; however, derivatives, reduplications, and variants of stress were included when they shed emphases on the comparison. The basis of grouping the cognates was its phonetic-semantic resemblance. Based on the analysis, it revealed that there are words which may have several types of lexical relationship. Further, the study revealed that the Japanese language has more false cognates in the Philippine languages, particularly in Tagalog and Cebuano. On the other hand, there are more true cognates of Chinese in Tagalog. It is the hope of this study to provide a significant contribution to a diverse audience. These include the teachers and learners of foreign languages such as Japanese and Chinese, future researchers and investigators, applied linguists, curricular theorists, community, and publishers.

Keywords: Contrastive Analysis, Japanese, Chinese and Philippine languages, Qualitative and descriptive study, True and False Cognates

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Authors: Minjuan Sun

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Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by the business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the "thin-file" issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Keywords: credit score, digital footprint, Fintech, machine learning

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Authors: Dammak Saida, Mbarek Sonia

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This paper aims to examine the impact of public interest commitment, the attitude towards independence enforcement, and organizational ethical culture on auditors' ethical behavior. It also tests the moderating effect of gender diversity on these relationships. The sample consisted of 100 Tunisian chartered accountants. An online survey was used to collect the data. Data analysis techniques used to test hypotheses The findings of this study provide practical implications for accounting professionals, regulators, and audit firms as they help understand auditors' beliefs and behaviors, which implies more effective mechanisms for improving their ethical values.

Keywords: public interest, independence, organizational culture, professional behavior, Tunisian auditors

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Martina Katalin Szabó, Bernadett Lipóczi, Csenge Guba, István Uveges

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In this study, an exhaustive analysis was carried out about the historical development of negative emotive intensifiers in the Hungarian language via NLP methods. Intensifiers are linguistic elements which modify or reinforce a variable character in the lexical unit they apply to. Therefore, intensifiers appear with other lexical items, such as adverbs, adjectives, verbs, infrequently with nouns. Due to the complexity of this phenomenon (set of sociolinguistic, semantic, and historical aspects), there are many lexical items which can operate as intensifiers. The group of intensifiers are admittedly one of the most rapidly changing elements in the language. From a linguistic point of view, particularly interesting are a special group of intensifiers, the so-called negative emotive intensifiers, that, on their own, without context, have semantic content that can be associated with negative emotion, but in particular cases, they may function as intensifiers (e.g.borzasztóanjó ’awfully good’, which means ’excellent’). Despite their special semantic features, negative emotive intensifiers are scarcely examined in literature based on large Historical corpora via NLP methods. In order to become better acquainted with trends over time concerning the intensifiers, The exhaustively analysed a specific historical corpus, namely the Magyar TörténetiSzövegtár (Hungarian Historical Corpus). This corpus (containing 3 millions text words) is a collection of texts of various genres and styles, produced between 1772 and 2010. Since the corpus consists of raw texts and does not contain any additional information about the language features of the data (such as stemming or morphological analysis), a large amount of manual work was required to process the data. Thus, based on a lexicon of negative emotive intensifiers compiled in a previous phase of the research, every occurrence of each intensifier was queried, and the results were stored in a separate data frame. Then, basic linguistic processing (POS-tagging, lemmatization etc.) was carried out automatically with the ‘magyarlanc’ NLP-toolkit. Finally, the frequency and collocation features of all the negative emotive words were automatically analyzed in the corpus. Outcomes of the research revealed in detail how these words have proceeded through grammaticalization over time, i.e., they change from lexical elements to grammatical ones, and they slowly go through a delexicalization process (their negative content diminishes over time). What is more, it was also pointed out which negative emotive intensifiers are at the same stage in this process in the same time period. Giving a closer look to the different domains of the analysed corpus, it also became certain that during this process, the pragmatic role’s importance increases: the newer use expresses the speaker's subjective, evaluative opinion at a certain level.

Keywords: historical corpus analysis, historical linguistics, negative emotive intensifiers, semantic changes over time

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Authors: Inas Hussein

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Communication in the modern world is increasingly becoming multimodal due to globalization and the digital space we live in which have remarkably affected how people communicate. Accordingly, Multimodal Discourse Analysis (MDA) is an emerging paradigm in discourse studies with the underlying assumption that other semiotic resources such as images, colours, scientific symbolism, gestures, actions, music and sound, etc. combine with language in order to  communicate meaning. One of the effective multimodal media that combines both verbal and non-verbal elements to create meaning is political cartoons. Furthermore, since political and social issues are mirrored in political cartoons, these are regarded as potential objects of discourse analysis since they not only reflect the thoughts of the public but they also have the power to influence them. The aim of this paper is to analyze some selected cartoons on the recognition of Jerusalem as Israel's capital by the American President, Donald Trump, adopting a multimodal approach. More specifically, the present research examines how the various semiotic tools and resources utilized by the cartoonists function in projecting the intended meaning. Ten political cartoons, among a surge of editorial cartoons highlighted by the Anti-Defamation League (ADL) - an international Jewish non-governmental organization based in the United States - as publications in different Arabic-language newspapers in Egypt, Saudi Arabia, UAE, Oman, Iran and UK, were purposively selected for semiotic analysis. These editorial cartoons, all published during 6^th–18^th December 2017, invariably suggest one theme: Jewish and Israeli domination of the United States. The data were analyzed using the framework of Visual Social Semiotics. In accordance with this methodological framework, the selected visual compositions were analyzed in terms of three aspects of meaning: representational, interactive and compositional. In analyzing the selected cartoons, an interpretative approach is being adopted. This approach prioritizes depth to breadth and enables insightful analyses of the chosen cartoons. The findings of the study reveal that semiotic resources are key elements of political cartoons due to the inherent political communication they convey. It is proved that adequate interpretation of the three aspects of meaning is a prerequisite for understanding the intended meaning of political cartoons. It is recommended that further research should be conducted to provide more insightful analyses of political cartoons from a multimodal perspective.

Keywords: Multimodal Discourse Analysis (MDA), multimodal text, political cartoons, visual modality

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

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Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

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Authors: Andrea Scapolo, Zaya Rustamova, Arturo Matute Castro

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The “Voices in Dissent” initiative aims at collecting and making available in a digital format, testimonies, letters, and other narratives produced by victims of political oppression from different geographical spaces across the Atlantic. By recovering silenced voices behind the official narratives, this open-access online database will provide indispensable tools for rewriting the history of authoritarian regimes from the margins as memory debates continue to provoke controversy among academic and popular transnational circles. In providing an extensive database of non-hegemonic discourses in a variety of political and social contexts, the project will complement the existing European and Latin-American studies, and invite further interdisciplinary and trans-national research. This digital resource will be available to academic communities and the general audience and will be organized geographically and chronologically. “Voices in Dissent” will offer a first comprehensive study of these personal accounts of persecution and repression against determined historical backgrounds and their impact on collective memory formation in contemporary societies. The digitalization of these texts will allow to run metadata analyses and adopt comparatist approaches for a broad range of research endeavors. Most of the testimonies included in our archive are testimonies of trauma: the trauma of exile, imprisonment, torture, humiliation, censorship. The research on trauma has now reached critical mass and offers a broad spectrum of critical perspectives. By putting together testimonies from different geographical and historical contexts, our project will provide readers and scholars with an extraordinary opportunity to investigate how culture shapes individual and collective memories and provides or denies resources to make sense and cope with the trauma. For scholars dealing with the epistemological and rhetorical analysis of testimonies, an online open-access archive will prove particularly beneficial to test theories on truth status and the formation of belief as well as to study the articulation of discourse. An important aspect of this project is also its pedagogical applications since it will contribute to the creation of Open Educational Resources (OER) to support students and educators worldwide. Through collaborations with our Library System, the archive will form part of the Digital Commons database. The texts collected in this online archive will be made available in the original languages as well as in English translation. They will be accompanied by a critical apparatus that will contextualize them historically by providing relevant background information and bibliographical references. All these materials can serve as a springboard for a broad variety of educational projects and classroom activities. They can also be used to design specific content courses or modules. In conclusion, the desirable outcomes of the “Voices in Dissent” project are: 1. the collections and digitalization of political dissent testimonies; 2. the building of a network of scholars, educators, and learners involved in the design, development, and sustainability of the digital archive; 3. the integration of the content of the archive in both research and teaching endeavors, such as publication of scholarly articles, design of new upper-level courses, and integration of the materials in existing courses.

Keywords: digital archive, dissent, open educational resources, testimonies, transatlantic studies

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Authors: Pia Kastl

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Potentials of blended learning are the flexibility of learning and the possibility to get in touch with lecturers and fellow students on site. By combining face-to-face sessions with digital self-learning units, the learning process can be optimized, and learning success increased. To examine wether blended learning outperforms online and face-to-face teaching, a theory-based questionnaire survey was conducted. The results show that the interaction and cooperation among students is poorly provided in blended learning, and face-to-face teaching performs better in this respect. The aim of this article is to identify concrete suggestions students have for improving cooperation and interaction in blended learning courses. For this purpose, interviews were conducted with students from various academic disciplines in face-to-face, online, or blended learning courses (N= 60). The questions referred to opinions and suggestions for improvement regarding the course design of the respective learning environment. The analysis was carried out by qualitative content analysis. The results show that students perceive the interaction as beneficial to their learning. They verbalize their knowledge and are exposed to different perspectives. In addition, emotional support is particularly important in exam phases. Interaction and cooperation were primarily enabled in the face-to-face component of the courses studied, while there was very limited contact with fellow students in the asynchronous component. Forums offered were hardly used or not used at all because the barrier to asking a question publicly is too high, and students prefer private channels for communication. This is accompanied by the disadvantage that the interaction occurs only among people who already know each other. Creating contacts is not fostered in the blended learning courses. Students consider optimization possibilities as a task of the lecturers in the face-to-face sessions: Here, interaction and cooperation should be encouraged through get-to-know-you rounds or group work. It is important here to group the participants randomly to establish contact with new people. In addition, sufficient time for interaction is desired in the lecture, e.g., in the context of discussions or partner work. In the digital component, students prefer synchronous exchange at a fixed time, for example, in breakout rooms or an MS Teams channel. The results provide an overview of how interaction and cooperation can be implemented in blended learning courses. Positive design possibilities are partly dependent on subject area and course. Future studies could tie in here with a course-specific analysis.

Keywords: blended learning, higher education, hybrid teaching, qualitative research, student learning

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Authors: Sawitree Wongkittirungrueang

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The objectives of this research were: 1) to study the effect of social stories on social interaction of students with autism. The sample was Pratomsuksa level 5 student with autism, Khon Kaen University Demonstration School, who was diagnosed by the Physician as High Functioning Autism since he was able to read, write, calculate and was studying in inclusive classroom. However, he still had disability in social interaction to participate in social activity group and communication. He could not learn how to develop friendship or create relationship. He had inappropriate behavior in social context. He did not understand complex social situations. In addition, he did seemed not know time and place. He was not able to understand feeling of oneself as well as the others. Consequently, he could not express his emotion appropriately. He did not understand or express his non-verbal language for communicating with friends. He lacked of common interest or emotion with nearby persons. He greeted inappropriately or was not interested in greeting. In addition, he did not have eye contact. He used inadequate language etc. He was elected by Purposive Sampling. His parents were willing to allow them to participate in this study. The research instruments were the lesson plan of social stories, and the picture book of social stories. The instruments used for data collection, were the social interaction evaluation of autistic students. This research was Quasi Experimental Research as One Group Pre-test, Post-test Design. For the Pre-test, the experiment was conducted by social stories. Then, the Post-test was implemented. The statistic used for data analysis, included the Mean, and Standard Deviation. The research findings were shown by Graph. The findings revealed hat the autistic students taught by social stories indicated better social interaction after being taught by social stories.

Keywords: social story, autism spectrum disorder (ASD), autism, social interaction

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

Procedia PDF Downloads 285

Authors: Simon Quick, John Lyle

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Psychology-based research has been a characteristic of empirical enquiry in sport coaching for over fifty years and cognitive function is widely accepted as a fundamental component of sport coaching expertise. Within the academic literature, much empirical research on coaches’ cognitions has tended to adopt retrospective approaches, such as post-session interviews or stimulated recall, thus capturing coaches’ cognitions after the incident, training session or competition. Such methods are prone to a variety of issues, including memory decay and the reordering of accounts. The aim of this research was to overcome the limitations that exist with retrospective approaches and, rather, to capture coaching cognitions in situ using Think Aloud Protocol. Data that were captured was broken down into meaning units and analysed using a Thematic Analysis. Situated in the practice of 6 experienced rugby coaches, findings revealed that Think Aloud Protocol generated rich data, although problematic in a site of enquiry confounded by multiple social interactions and requiring coaches to provide frequent instruction and feedback. The resultant interaction between cognition and action is conceptualised by the tentative offering of a model that situates these elements in conjunction with cognitive triggers and thresholds. The implications of these findings can help academics and coaches to understand the dynamic relationship between types of coaching cognitions and the complexity of the coaching environment.

Keywords: sports coaching, Psychology, Pedagogy, cognition

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Authors: Elizabeth M. Seabrook, Nikki S. Rickard

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Examining time-dependent measures of emotion such as variability, instability, and inertia, provide critical and complementary insights into mental health status. Observing changes in the pattern of emotional expression over time could act as a tool to identify meaningful shifts between psychological well- and ill-being. From a practical standpoint, however, examining emotion dynamics day-to-day is likely to be burdensome and invasive. Utilizing social media data as a facet of lived experience can provide real-world, temporally specific access to emotional expression. Emotional language on social media may provide accurate and sensitive insights into individual and community mental health and well-being, particularly with focus placed on the within-person dynamics of online emotion expression. The objective of the current study was to examine the dynamics of emotional expression on the social network platform Facebook for active users and their relationship with psychological well- and ill-being. It was expected that greater positive and negative emotion variability, instability, and inertia would be associated with poorer psychological well-being and greater depression symptoms. Data were collected using a smartphone app, MoodPrism, which delivered demographic questionnaires, psychological inventories assessing depression symptoms and psychological well-being, and collected the Status Updates of consenting participants. MoodPrism also delivered an experience sampling methodology where participants completed items assessing positive affect, negative affect, and arousal, daily for a 30-day period. The number of positive and negative words in posts was extracted and automatically collated by MoodPrism. The relative proportion of positive and negative words from the total words written in posts was then calculated. Preliminary analyses have been conducted with the data of 9 participants. While these analyses are underpowered due to sample size, they have revealed trends that greater variability in the emotion valence expressed in posts is positively associated with greater depression symptoms (r(9) = .56, p = .12), as is greater instability in emotion valence (r(9) = .58, p = .099). Full data analysis utilizing time-series techniques to explore the Facebook data set will be presented at the conference. Identifying the features of emotion dynamics (variability, instability, inertia) that are relevant to mental health in social media emotional expression is a fundamental step in creating automated screening tools for mental health that are temporally sensitive, unobtrusive, and accurate. The current findings show how monitoring basic social network characteristics over time can provide greater depth in predicting risk and changes in depression and positive well-being.

Keywords: emotion, experience sampling methods, mental health, social media

Procedia PDF Downloads 250

Authors: Margareth S. Zanchetta, Kateryna Metersky, Valerie Tan, Charissa Cordon, Stephanie Lucchese, Yana Siganevich, Prasha Sivasundaram, Truong Binh Nguyen, Imran Qureshi

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Due to a new area of practice, Canadian nurses possess knowledge gaps regarding the use of cannabis-based therapies by clients/patients. Education related to medical cannabis (MC) and recreational cannabis (RC) is required to promote nurses’ competency and confidence in supporting clients/patients using MC/RC toward the improvement of health outcomes. A team composed of nursing researchers and undergraduate/graduate students implemented a national survey to explore this theme with the population of undergraduate, graduate (MN and NP), and Post-Diploma (RN Bridging) nursing students enrolled in Canadian Universities Nursing Programs. Upon Research Ethics Board approval, survey recruitment was supported by major nursing stakeholders. The research questions were : (a) Which are the most preferred sources of information on MC/RC for nursing students? (b) Which are the factors and preferred learning modalities that could increase interest in learning about MC/RC, and (c) What are the future career plans among nursing students, and how would they consider the prospective use of cannabis in their practice? The survey was available from Sept. 2022 to Feb. 2023, hosted by a remote platform. An original questionnaire (English-French) was composed of 18 multiple choice questions and 2 open-ended questions. Sociodemographic information and closed-ended responses were compiled as descriptive statistics, while narrative accounts will be analysed through thematic analysis. Respondents (n=153) were from 7 Canadian provinces, national (99%) and international students (1%); the majority of respondents (61%) were in the age range of 21-30 years old. Results indicated that respondents perceive a gap in the undergraduate curriculum on the topics of MC/RC (91%) and that their learning needs include regulations (90%), data on effectiveness (88%), dosing best practices (86%), contraindications (83%), and clinical and medical indications (76%). Respondents reported motivation to learn more about MC/RC through online lectures/videos (65%), e-learning modules or online interactive training (61%), workshops (51%), webinars (36%), and social media (35%). Their primary career-related motivations regarding MC/RC knowledge include enhancing nursing practice (76%), learning about this growing scope of practice (61%), keeping up-to-date responding to scientific curiosity (59%), learning about evidence-based practice (59%), and utilizing alternative forms of medical treatment (37%). Respondents indicated that the integration of topics on cannabis in any course in the undergraduate and/or graduate curriculum would increase their desire to learn about MC/RC as equally as exposure within a clinical setting (75%). The emerging trend in the set of narrative responses (n=130) suggests that respondents believe educational MC/RC content should be integrated into core nursing courses. Respondents also urged educators to be well-informed about evidence-based practice related to MC/RC and to reflect upon stigma and biases surrounding its use. Future knowledge dissemination and translation activities include scholarly products and presentations to stimulate discussion amongst nursing faculty and students, as well as nurses in clinical settings. The goal is to mobilise talents and build collaboration for the development of a socially responsive curriculum on MC/RC competency to address the education-related expectations of all these social actors.

Keywords: Canada, medical cannabis, nursing education, nursing graduate student, nursing undergraduate student, online survey, recreational cannabis

Procedia PDF Downloads 90

Authors: A. Afrashi

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Introduction: Synaesthesia is a term denoting the perception or description of the perception of one sense modality in terms of another. In literature, synaesthesia refers to a technique adopted by writers to present ideas, characters or places in such a manner that they appeal to more than one sense like hearing, seeing, smell etc. at a given time. In everyday language too we find many examples of synaesthesia. We commonly hear phrases like ‘loud colors’, ‘frozen silence’ and ‘warm colors’, ‘bitter cold’ etc. Empirical cognitive studies have proved that synaesthetic representations both in literature and everyday languages are constrained ie. they do not map randomly among sensory domains. From the beginning of the 20th century Synaesthesia has been a research domain both in literature and structural linguistics. However the exploration of cognitive mechanisms motivating synaesthesia, have made it an important topic in 21st century cognitive linguistics and literary studies. Synaesthetic metaphors are linguistic representations of those mental mechanisms, the study of which reveals invaluable facts about perception, cognition and conceptualization. According to the main tenets of cognitive approach to language and literature, unified and similar cognitive mechanisms are active both in everyday language and literature, and synaesthesia is one of those cognitive mechanisms. Main objective of the present research is to answer the following questions: What types of sense transfers are accessible in Persian synaesthetic metaphors. How are these types of sense transfers cognitively explained. What are the results of cross-linguistic comparative study of synaestetic metaphors based on the existing observations? Methodology: The present research employs a cognitive - corpus based method, and the theoretical framework adopted to analyze linguistic synaesthesia is the contemporary theory of metaphor, where conceptual metaphor is the result of systemic mappings across cognitive domains. Persian Language Data- base (PLDB) in the Institute for Humanities and Cultural Studies which consists mainly of Persian modern prose, is searched for synaesthetic metaphors. Then for each metaphorical structure, the source and target domains are determined. Then sense transfers are identified and the types of synaesthetic metaphors recognized. Findings: Persian synaesthetic metaphors conform to the hierarchical distribution principle, according to which transfers tend to go from touch to taste to smell to sound and to sight, not vice versa. In other words mapping from more accessible or basic concepts onto less accessible or less basic ones seems more natural. Furthermore the most frequent target domain in Persian synaesthetic metaphors is sound. Certain characteristics of Persian synaesthetic metaphors are comparable with existing related researches carried on English, French, Hungarian and Chinese synaesthetic metaphors. Conclusion: Cognitive corpus based approaches to linguistic synaesthesia, are applicable to stylistics and literary criticism and this recent research domain is an efficient approach to study cross linguistic variations to find out which of the five senses is dominant cross linguistically and cross culturally as the target domain in metaphorical mappings , and so forth receiving dominance in conceptualizations.

Keywords: cognitive semantics, conceptual metaphor, synaesthesia, corpus based approach

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Authors: Alan C. Lin, Ricky N. Joevan

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This paper focuses on developing a system to transfer mold base plates and standard parts faster during the stage of injection mold design. This system not only provides a way to compare the file version, but also it utilizes Siemens NX 10 to isolate the updated information into a single executable file (.dll), and then, the file can be transferred without the need of transferring the whole file. By this way, the system can help the user to download only necessary mold base plates and standard parts, and those parts downloaded are only the updated portions.

Keywords: CAD, injection molding, mold base, data retrieval

Procedia PDF Downloads 302