Search results for: intercultural learning

Authors: Humaira Irfan Khan

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The paper discusses that Pakistan is a multilingual, multicultural, and multiethnic society. The findings from quantitative and qualitative data collected in two public universities look at the importance of English language and the role and status of national and regional languages in the country. The evidence implies that postgraduate students having diverse linguistic, cultural, ethnic, socio-economic, and educational backgrounds display negative attitudes towards the use of English language for academic and interactive functions in universities. It is also discovered that language anxiety of postgraduate students is an outcome of their language learning difficulties. It is suggested that considering the academic needs of students, universities should introduce a language proficiency course to enable them to use English with confidence.

Keywords: Multilingualism, Ethnicity, Cultural Diversity, Importance of English, National language, Regional languages, Language Anxiety

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Authors: L. M. H. Mustonen, S. A. Heikkilä

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The focus of the paper is to describe team teaching as a HAMK’s pedagogical method, and its impacts to the teachers work. Background: Traditionally it is thought that teaching is a job where one mostly works alone. More and more teachers feel that their work is getting more stressful. Solutions to these problems have been sought in Häme University of Applied sciences’ (From now on referred to as HAMK). HAMK has made a strategic change to move to the group oriented working of teachers. Instead of isolated study courses, there are now larger 15 credits study modules. Implementation: As examples of the method, two cases are presented: technical project module and summer studies module, which was integrated into the EU development project called Energy Efficiency with Precise Control. In autumn 2017, technical project will be implemented third time. There are at least three teachers involved in it and it is the first module of the new students. Main focus is to learn the basic skills of project working. From communicational viewpoint, they learn the basics of written and oral reporting and the basics of video reporting skills. According to our quality control system, the need for the development is evaluated in the end of the module. There are always some differences in each implementation but the basics are the same. The other case summer studies 2017 is new and part of a larger EU project. For the first time, we took a larger group of first to third year students from different study programmes to the summer studies. The students learned professional skills and also skills from different fields of study, international cooperation, and communication skills. Benefits and challenges: After three years, it is possible to consider what the changes mean in the everyday work of the teachers - and of course – what it means to students and the learning process. The perspective is HAMK’s electrical and automation study programme: At first, the change always means more work. The routines born after many years and the course material used for years may not be valid anymore. Teachers are teaching in modules simultaneously and often with some subjects overlapping. Finding the time to plan the modules together is often difficult. The essential benefit is that the learning outcomes have improved. This can be seen in the feedback given by both the teachers and the students. Conclusions: A new type of working environment is being born. A team of teachers designs a module that matches the objectives and ponders the answers to such questions as what are the knowledge-based targets of the module? Which pedagogical solutions will achieve the desired results? At what point do multiple teachers instruct the class together? How is the module evaluated? How can the module be developed further for the next execution? The team discusses openly and finds the solutions. Collegiate responsibility and support are always present. These are strengthening factors of the new communal university teaching culture. They are also strong sources of pleasure of work.

Keywords: pedagogical development, summer studies, team teaching, well-being at work

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Authors: Marie-Laure Mimoun-Sorel

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Scholars concerned with the destiny of human species point out that our future will not only depend on progress made in technology and sciences but above all it will depend on human progress understood as quality of being. Teachers are significant force in developing a knowledgeable, creative, productive and democratic society. The values that underpin their profession are integrity, respect and responsibility. Therefore, being a teacher in the context of the 21st century requires embracing a Transdisciplinary Attitude which is about venturing within, between, across and beyond disciplines in order to bring forth quality of being in every learning process. In this article, the Transdisciplinary Attitude is defined and its benefits are shown through examples of Transdisciplinary inquiries in an Australian school. Finally, the conclusion invites to reflect on quality of teaching in regard to the development of individual autonomy, community participation and awareness of belonging to the human species.

Keywords: human progress, quality of being, quality of teaching, transdisciplinary attitude in education

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Authors: H. Nakamura

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This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: database business, electronic library, international strategic alliances, partner selection

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Authors: David S. Byrne

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The purpose of this paper is to understand how phone record analysis can enable identification of subjects in communication with a target of a terrorist plot. This study also sought to understand the advantages of the implementation of simulations to develop the skills of future intelligence analysts to enhance national security. Through the examination of phone reports which in essence consist of the call traffic of incoming and outgoing numbers (and not by listening to calls or reading the content of text messages), patterns can be uncovered that point toward members of a criminal group and activities planned. Through temporal and frequency analysis, conclusions were drawn to offer insights into the identity of participants and the potential scheme being undertaken. The challenge lies in the accurate identification of the users of the phones in contact with the target. Often investigators rely on proprietary databases and open sources to accomplish this task, however it is difficult to ascertain the accuracy of the information found. Thus, this paper poses two research questions: how effective are freely available web sources of information at determining the actual identification of callers? Secondly, does the identity of the callers enable an understanding of the lifestyle and habits of the target? The methodology for this research consisted of the analysis of the call detail records of the author’s personal phone activity spanning the period of a year combined with a hypothetical theory that the owner of said phone was a leader of terrorist cell. The goal was to reveal the identity of his accomplices and understand how his personal attributes can further paint a picture of the target’s intentions. The results of the study were interesting, nearly 80% of the calls were identified with over a 75% accuracy rating via datamining of open sources. The suspected terrorist’s inner circle was recognized including relatives and potential collaborators as well as financial institutions [money laundering], restaurants [meetings], a sporting goods store [purchase of supplies], and airline and hotels [travel itinerary]. The outcome of this research showed the benefits of cellphone analysis without more intrusive and time-consuming methodologies though it may be instrumental for potential surveillance, interviews, and developing probable cause for wiretaps. Furthermore, this research highlights the importance of building upon the skills of future intelligence analysts through phone record analysis via simulations; that hands-on learning in this case study emphasizes the development of the competencies necessary to improve investigations overall.

Keywords: hands-on learning, intelligence analysis, intelligence education, phone record analysis, simulations

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Authors: Quoc Hung Le Pham

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In the field of language study, classifier is an interesting research feature. In the world’s languages, some languages have classifier system, some do not. Mandarin Chinese and Vietnamese languages are a rich classifier system, however, because of the language system, the cognitive, cultural differences, so that the syntactic structure of classifier of them also dissimilar. When using Mandarin Chinese classifiers must collocate with nouns or verbs, in the lexical category it is not like nouns or verbs, belong to the open class. But some scholars believe that Mandarin Chinese measure words are similar to English and other Indo European languages. The word hanging on the structure and word formation (suffix), is a closed class. Compared to other languages, such as Chinese, Vietnamese, Thai and other Asian languages are still belonging to the classifier language’s second type, this type of language is classifier, it is in the majority of quantity must exist, and following deictic, anaphoric or quantity appearing together, not separation between its modified noun, also known as numeral classifier language. Main syntactic structure of Chinese classifiers are as follows: ‘quantity+measure+noun’, ‘pronoun+measure+noun’, ‘pronoun+quantity+measure+noun’, ‘prefix+quantity+measure +noun’, ‘quantity +adjective + measure +noun’, ‘ quantity (above 10 whole number), + duo (多)measure +noun’, ‘ quantity (around 10) + measure + duo (多) +noun’. Main syntactic structure of Vietnamese classifiers are: ‘quantity+measure+noun’, ‘ measure+noun+pronoun’, ‘quantity+measure+noun+pronoun’, ‘measure+noun+prefix+ quantity’, ‘quantity+measure+noun+adjective', ‘duo (多) +quanlity+measure+noun’, ‘quantity+measure+adjective+pronoun (quantity word could not be 1)’, ‘measure+adjective+pronoun’, ‘measure+pronoun’. In daily life, classifiers are commonly used, if Chinese learners failed to standardize this using catergory, because the negative impact might occur on their verbal communication. The richness of the Chinese classifier system contributes to the complexity in the study of the system by foreign learners, especially in the inter language of Vietnamese learners. As above mentioned, Vietnamese language also has a rich system of classifiers, however, the basic structure order of two languages are similar but both still have differences. These similarities and dissimilarities between Chinese and Vietnamese classifier systems contribute significantly to the common errors made by Vietnamese students while they acquire Chinese, which are distinct from the errors made by students from the other language background. This article from a comparative perspective of language, has an orientation towards Chinese and Vietnamese languages commonly used in classifiers semantics and structural form two aspects. This comparative study aims to identity Vietnamese students while learning Chinese classifiers may face some negative transference of mother language, beside that through the analysis of the classifiers questionnaire, find out the causes and patterns of the errors they made. As the preliminary analysis shows, Vietnamese students while learning Chinese classifiers made some errors such as: overuse classifier ‘ge’(个); misuse the other classifiers ‘*yi zhang ri ji’(yi pian ri ji), ‘*yi zuo fang zi’(yi jian fang zi), ‘*si zhang jin pai’(si mei jin pai); homonym words ‘dui, shuang, fu, tao’ (对、双、副、套), ‘ke, li’ (颗、粒).

Keywords: acquisition, classifiers, negative transfer, Vietnamse learners

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Authors: Caroline Spencer, Suzanne Cross, Dudley McArdle, Frank Archer

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Objectives: The evolution of the Victorian Compendium of Community-Based Resilience Building Case Studies and its capacity to help communities implement activities that encourage adaptation to disaster risk reduction and promote community resilience in rural and urban locations provide this paper's objectives. Background: Between 2012 and 2019, community groups presented at the Monash University Disaster Resilience Initiative (MUDRI) 'Advancing Community Resilience Annual Forums', provided opportunities for communities to impart local resilience activities, how to solve challenges and share unforeseen learning and be considered for inclusion in the Compendium. A key tenet of the Compendium encourages compiling and sharing of grass-roots resilience building activities to help communities before, during, and after unexpected emergencies. The online Compendium provides free access for anyone wanting to help communities build expertise, reduce program duplication, and save valuable community resources. Identifying case study features across the emergency phases and analyzing critical success factors helps communities understand what worked and what did not work to achieve success and avoid known barriers. International exemplars inform the Compendium, which represents an Australian first and enhances Victorian community resilience initiatives. Emergency Management Victoria provided seed funding for the Compendium. MUDRI matched this support and continues to fund the project. A joint Steering Committee with broad-based user input and Human ethics approval guides its continued growth. Methods: A thematic analysis of the Compendium identified case study features, including critical success factors. Results: The Compendium comprises 38 case studies, representing all eight Victorian regions. Case studies addressed emergency phases, before (29), during (7), and after (17) events. Case studies addressed all hazards (23), bushfires (11), heat (2), fire safety (1), and house fires (1). Twenty case studies used a framework. Thirty received funding, of which nine received less than $20,000 and five received more than $100,000. Twenty-nine addressed a whole of community perspective. Case studies revealed unique and valuable learning in diverse settings. Critical success factors included strong governance; board support, leadership, and trust; partnerships; commitment, adaptability, and stamina; community-led initiatives. Other success factors included a paid facilitator and local government support; external funding, and celebrating success. Anecdotally, we are aware that community groups reference Compendium and that its value adds to community resilience planning. Discussion: The Compendium offers an innovative contribution to resilience research and practice. It augments the seven resilience characteristics to strengthen and encourage communities as outlined in the Statewide Community Resilience Framework for Emergency Management; brings together people from across sectors to deliver distinct, yet connected actions to strengthen resilience as a part of the Rockefeller funded Resilient Melbourne Strategy, and supports communities and economies to be resilient when a shock occurs as identified in the recently published Australian National Disaster Risk Reduction Framework. Each case study offers learning about connecting with community and how to increase their resilience to disaster risks and to keep their community safe from unexpected emergencies. Conclusion: The Compendium enables diverse communities to adopt or adapt proven resilience activities, thereby preserving valuable community resources and offers the opportunity to extend to a national or international Compendium.

Keywords: case study, community, compendium, disaster risk reduction, resilience

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Authors: Maggie Mosher, Adam Carreon, Sean Smith

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A systematic literature review was conducted to explore the evidence base on the use of augmented reality (AR), virtual reality (VR), mixed reality (MR), and extended reality (XR) to present social skill instruction to school-age students with autism spectrum disorder (ASD). Specifically, the systematic review focus was on a. the participants and intervention agents using AR, VR, MR, and XR for social skill acquisition b. the social skills taught through these mediums and c. the social validity measures (i.e., goals, procedures, and outcomes) reported in these studies. Forty-one articles met the inclusion criteria. Researchers in six studies taught social skills to students through AR, in 27 studies through non-immersive VR, and in 10 studies through immersive VR. No studies used MR or XR. The primary targeted social skills were relationship skills, emotion recognition, social awareness, cooperation, and executive functioning. An intervention to improve many social skills was implemented by 73% of researchers, 17% taught a single skill, and 10% did not clearly state the targeted skill. The intervention was considered effective in 26 of the 41 studies (63%), not effective in four studies (10%), and 11 studies (27%) reported mixed results. No researchers reported information for all 17 social validity indicators. The social validity indicators reported by researchers ranged from two to 14. Social validity measures on the feelings toward and use of the technology were provided in 22 studies (54%). Findings indicated both AR and VR are promising platforms for providing social skill instruction to students with ASD. Studies utilizing this technology show a number of social validity indicators. However, the limited information provided on the various interventions, participant characteristics, and validity measures, offers insufficient evidence of the impact of these technologies in teaching social skills to students with ASD. Future research should develop a protocol for training treatment agents to assess the role of different variables (i.e., whether agents are customizing content, monitoring student learning, using intervention specific vocabulary in their day to day instruction). Sustainability may be increased by providing training in the technology to both treatment agents and participants. Providing scripts of instruction occurring within the intervention would provide the needed information to determine the primary method of teaching within the intervention. These variables play a role in maintenance and generalization of the social skills. Understanding the type of feedback provided would help researchers determine if students were able to feel rewarded for progressing through the scenarios or if students require rewarding aspects within the intervention (i.e., badges, trophies). AR has the potential to generalize instruction and VR has the potential for providing a practice environment for performance deficits. Combining these two technologies into a mixed reality intervention may provide a more cohesive and effective intervention.

Keywords: autism, augmented reality, social and emotional learning, social skills, virtual reality

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Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Objective: The aim of the study is to examine the relationship between visual agnosia and learning delay in Yemeni children. Method: A total of 80 subjects (experimental group= 60, 30 males and 30 females and control group= 20, 10 males and 10 females) in two institutions (old and new). The age of all subjects at hand ranges between 6- and 12 years old. Pre and post-tests were administered. Results: Outline results show severe effects on the performance of the children due to visual agnosia this effect was benign in the group that received the treatment, and this can be clearly seen in their results in the post-test compared to the other group that did not receive the treatment and outcomes in general can be better understood in light of the control group.

Keywords: visual, agnosia, linguistics, abilities, effects, psychoneurolinguistics

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

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Authors: Juliette MacDonald, Jun Li, Wenji Xiang, Mingwei Zhao

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Shanghai International College of Fashion and Innovation (SCF) was created as a result of a collaborative partnership agreement between the University of Edinburgh and Donghua University. The College provides two programmes: Fashion Innovation and Fashion Interior Design and the overarching curriculum has the intention of developing innovation and creativity within an international learning, teaching, knowledge exchange and research context. The research problem presented here focuses on the multi-national/cultural faculty in the team, the challenges arising from difficulties in communication and the associated limitations of management frameworks. The teaching faculty at SCF are drawn from China, Finland, Korea, Singapore and the UK with input from Flying Faculty from Fashion and Interior Design, Edinburgh College of Art (ECA), for 5 weeks each semester. Rather than fully replicating the administrative and pedagogical style of one or other of the institutions within this joint partnership the aim from the outset was to create a third way which acknowledges the quality assurance requirements of both Donghua and Edinburgh, the academic and technical needs of the students and provides relevant development and support for all the SCF-based staff and Flying Academics. It has been well acknowledged by those who are involved in teaching across cultures that there is often a culture shock associated with transnational education but that the experience of being involved in the delivery of a curriculum at a Joint Institution can also be very rewarding for staff and students. It became clear at SCF that if a third way might be achieved which encourages innovative approaches to fashion education whilst balancing the expectations of Chinese and western concepts of education and the aims of two institutions, then it was going to be necessary to construct a framework which developed close working relationships for the entire teaching team, so not only between academics and students but also between technicians and administrators at ECA and SCF. The attempts at co-construction and integration are built on the sharing of cultural and educational experiences and knowledge as well as provision of opportunities for reflection on the pedagogical purpose of the curriculum and its delivery. Methods on evaluating the effectiveness of these aims include a series of surveys and interviews and analysis of data drawn from teaching projects delivered to the students along with graduate successes from the last five years, since SCF first opened its doors. This paper will provide examples of best practice developed by SCF which have helped guide the faculty and embed common core values and aims of co-construction regulations and management, whilst building a pro-active TNE (Trans-National Education) team which enhances the learning experience for staff and students alike.

Keywords: cultural co-construction, educational team management, multi-cultural challenges, TNE integration for teaching teams

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Authors: A. Degale Desta, Tamirat Kebamo

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Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Katherine O'Grady-Bray

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For some deaf children, reading books can be a challenge. Frank Barnes School (FBS) provides guided reading time with Teachers of the Deaf, in which they read books with deaf children using a bilingual approach. The vocabulary and context of the story is explained to deaf children in BSL so they develop skills bridging English and BSL languages. However, the success of this practice is only achieved if the person is fluent in both languages. FBS piloted a scheme to convert an Oxford Reading Tree (ORT) book into an e-book that can be read using tablets. Deaf readers at FBS have access to both languages (BSL and English) during lessons and outside the classroom. The pupils receive guided reading sessions with a Teacher of the Deaf every morning, these one to one sessions give pupils the opportunity to learn how to bridge both languages e.g. how to translate English to BSL and vice versa. Generally, due to our pupils’ lack of access to incidental learning, gaining new information about the world around them is limited. This highlights the importance of quality time to scaffold their language development. In some cases, there is a shortfall of parental support at home due to poor communication skills or an unawareness of how to interact with deaf children. Some families have a limited knowledge of sign language or simply don’t have the required learning environment and strategies needed for language development with deaf children. As the majority of our pupils’ preferred language is BSL we use that to teach reading and writing English. If this is not mirrored at home, there is limited opportunity for joint reading sessions. Development of the e-Book required planning and technical development. The overall production took time as video footage needed to be shot and then edited individually for each page. There were various technical considerations such as having an appropriate background colour so not to draw attention away from the signer. Appointing a signer with the required high level of BSL was essential. The language and pace of the sign language was an important consideration as it was required to match the age and reading level of the book. When translating English text to BSL, careful consideration was given to the nonlinear nature of BSL and the differences in language structure and syntax. The e-book was produced using Apple’s ‘iBook Author’ software which allowed video footage of the signer to be embedded on pages opposite the text and illustration. This enabled BSL translation of the content of the text and inferences of the story. An interpreter was used to directly ‘voice over’ the signer rather than the actual text. The aim behind the structure and layout of the e-book is to allow parents to ‘read’ with their deaf child which helps to develop both languages. From observations, the use of e-books has given pupils confidence and motivation with their reading, developing skills bridging both BSL and English languages and more effective reading time with parents.

Keywords: bilingual book, e-book, BSL and English, bilingual e-book

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach can overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, statistical moments, indexing, similarity distance, histograms intersection

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Authors: M. Maier, I. Dedigama, J. Majasan, Y. Wu, Q. Meyer, L. Castanheira, G. Hinds, P. R. Shearing, D. J. L. Brett

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Increasing the efficiency of electrolyser technology is commonly seen as one of the main challenges on the way to the Hydrogen Economy. There is a significant lack of understanding of the different states of operation of polymer electrolyte membrane water electrolysers (PEMWE) and how these influence the overall efficiency. This in particular means the two-phase flow through the membrane, gas diffusion layers (GDL) and flow channels. In order to increase the efficiency of PEMWE and facilitate their spread as commercial hydrogen production technology, new analytic approaches have to be found. Acoustic emission (AE) offers the possibility to analyse the processes within a PEMWE in a non-destructive, fast and cheap in-situ way. This work describes the generation and analysis of AE data coming from a PEM water electrolyser, for, to the best of our knowledge, the first time in literature. Different experiments are carried out. Each experiment is designed so that only specific physical processes occur and AE solely related to one process can be measured. Therefore, a range of experimental conditions is used to induce different flow regimes within flow channels and GDL. The resulting AE data is first separated into different events, which are defined by exceeding the noise threshold. Each acoustic event consists of a number of consequent peaks and ends when the wave diminishes under the noise threshold. For all these acoustic events the following key attributes are extracted: maximum peak amplitude, duration, number of peaks, peaks before the maximum, average intensity of a peak and time till the maximum is reached. Each event is then expressed as a vector containing the normalized values for all criteria. Principal Component Analysis is performed on the resulting data, which orders the criteria by the eigenvalues of their covariance matrix. This can be used as an easy way of determining which criteria convey the most information on the acoustic data. In the following, the data is ordered in the two- or three-dimensional space formed by the most relevant criteria axes. By finding spaces in the two- or three-dimensional space only occupied by acoustic events originating from one of the three experiments it is possible to relate physical processes to certain acoustic patterns. Due to the complex nature of the AE data modern machine learning techniques are needed to recognize these patterns in-situ. Using the AE data produced before allows to train a self-learning algorithm and develop an analytical tool to diagnose different operational states in a PEMWE. Combining this technique with the measurement of polarization curves and electrochemical impedance spectroscopy allows for in-situ optimization and recognition of suboptimal states of operation.

Keywords: acoustic emission, gas diffusion layers, in-situ diagnosis, PEM water electrolyser

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Authors: Abdullah Khuwaileh

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While teaching and translating vocabulary is no longer a neglected area in ELT in general and in translation in particular, the psychology of its acquisition has been a neglected area. Our paper aims at exploring some of the learning and translating conditions under which vocabulary is acquired and translated properly. To achieve this objective, two teaching methods (experiments) were applied on 4 translators to measure their acquisition of a number of transparent vocabulary items. Some of these items were knowingly chosen from 'deceptively transparent words'. All the data, sample, etc., were taken from Jordan University of Science and Technology (JUST) and Yarmouk University, where the researcher is employed. The study showed that translators might translate transparent words inaccurately, particularly if these words are uncontextualised. It was also shown that the morphological structures of words may lead translators or even EFL learners to misinterpretations of meaning.

Keywords: english, transparent, word, processing, translation

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Authors: Mustafa M. Donma, Orkide Donma

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The impact of metabolic syndrome (MetS) on cognition and functions of the brain is being investigated. Iron deficiency and deficiencies of B9 (folate) as well as B12 (cobalamin) vitamins are best-known nutritional anemias. They are associated with cognitive disorders and learning difficulties. The antidepressant effects of vitamin D are known and the deficiency state affects mental functions negatively. The aim of this study is to investigate possible correlations of MetS with serum brain-derived neurotrophic factor (BDNF), iron, folate, cobalamin and vitamin D in pediatric patients. 30 children, whose age- and sex-dependent body mass index (BMI) percentiles vary between 85 and 15, 60 morbid obese children with above 99^th percentiles constituted the study population. Anthropometric measurements were taken. BMI values were calculated. Age- and sex-dependent BMI percentile values were obtained using the appropriate tables prepared by the World Health Organization (WHO). Obesity classification was performed according to WHO criteria. Those with MetS were evaluated according to MetS criteria. Serum BDNF was determined by enzyme-linked immunosorbent assay. Serum folate was analyzed by an immunoassay analyzer. Serum cobalamin concentrations were measured using electrochemiluminescence immunoassay. Vitamin D status was determined by the measurement of 25-hydroxycholecalciferol [25-hydroxy vitamin D3, 25(OH)D] using high performance liquid chromatography. Statistical evaluations were performed using SPSS for Windows, version 16. The p values less than 0.05 were accepted as statistically significant. Although statistically insignificant, lower folate and cobalamin values were found in MO children compared to those observed for children with normal BMI. For iron and BDNF values, no alterations were detected among the groups. Significantly decreased vitamin D concentrations were noted in MO children with MetS in comparison with those in children with normal BMI (p ≤ 0.05). The positive correlation observed between iron and BDNF in normal-BMI group was not found in two MO groups. In THE MetS group, the partial correlation among iron, BDNF, folate, cobalamin, vitamin D controlling for waist circumference and BMI was r = -0.501; p ≤ 0.05. None was calculated in MO and normal BMI groups. In conclusion, vitamin D should also be considered during the assessment of pediatric MetS. Waist circumference and BMI should collectively be evaluated during the evaluation of MetS in children. Within this context, BDNF appears to be a key biochemical parameter during the examination of obesity degree in terms of mental functions, cognition and learning capacity. The association observed between iron and BDNF in children with normal BMI was not detected in MO groups possibly due to development of inflammation and other obesity-related pathologies. It was suggested that this finding may contribute to mental function impairments commonly observed among obese children.

Keywords: brain-derived neurotrophic factor, iron, vitamin B9, vitamin B12, vitamin D

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

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Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Si Chen, Quanhong Jiang

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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.

Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

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This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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Authors: Subham Ghosh, Arnab Nandi

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Background: The proliferation of Wireless Body Area Networks (WBAN) and Internet of Things (IoT) applications demonstrates the potential for continuous monitoring of physical changes in the body. These technologies are vital for health monitoring tasks, such as identifying coughing and breathing activities, which are necessary for disease diagnosis and management. Monitoring activities such as coughing and deep breathing can provide valuable insights into a variety of medical issues. Wearable radio-based antenna sensors, which are lightweight and easy to incorporate into clothing or portable goods, provide continuous monitoring. This mobility gives it a substantial advantage over stationary environmental sensors like as cameras and radar, which are constrained to certain places. Furthermore, using compressive techniques provides benefits such as reduced data transmission speeds and memory needs. These wearable sensors offer more advanced and diverse health monitoring capabilities. Methodology: This study analyzes the feasibility of using a semi-flexible antenna operating at 2.4 GHz (ISM band) and positioned around the neck and near the mouth to identify three activities: coughing, deep breathing, and idleness. Vector network analyzer (VNA) is used to collect time-varying complex reflection coefficient data from perturbed antenna nearfield. The reflection coefficient (S11) conveys nuanced information caused by simultaneous variations in the nearfield radiation of three activities across time. The signatures are sparsely represented with gaussian windowed Gabor spectrograms. The Gabor spectrogram is used as a sparse representation approach, which reassigns the ridges of the spectrogram images to improve their resolution and focus on essential components. The antenna is biocompatible in terms of specific absorption rate (SAR). The sparsely represented Gabor spectrogram pictures are fed into a lightweight deep learning (DL) model for feature extraction and classification. Two antenna locations are investigated in order to determine the most effective localization for three different activities. Findings: Cross-validation techniques were used on data from both locations. Due to the complex form of the recorded S11, separate analyzes and assessments were performed on the magnitude, phase, and their combination. The combination of magnitude and phase fared better than the separate analyses. Various sliding window sizes, ranging from 1 to 5 seconds, were tested to find the best window for activity classification. It was discovered that a neck-mounted design was effective at detecting the three unique behaviors.

Keywords: activity recognition, antenna, deep-learning, time-frequency

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Authors: Eleanor Nel

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Research output is an indicator of institutional performance (and quality), resulting in increased pressure on academic institutions to perform in the research arena. Research output is further utilised to obtain research funding. Resultantly, academic institutions face significant pressure from governing bodies to provide evidence on the return for research investments. Research output has thus become a substantial discourse within institutions, mainly due to the processes linked to evaluating research output and the associated allocation of research funding. This focus on research outputs often surpasses the development of robust, widely accepted tools to additionally measure research impact at institutions. A publication writing programme, for enhancing research output, was launched at a South African university in 2011. Significant amounts of time, money, and energy have since been invested in the programme. Although participants provided feedback after each session, no formal review was conducted to evaluate the research output directly associated with the programme. Concerns in higher education about training costs, learning results, and the effect on society have increased the focus on value for money and the need to improve training, research performance, and productivity. Furthermore, universities rely on efficient and reliable monitoring and evaluation systems, in addition to the need to demonstrate accountability. While publishing does not occur immediately, achieving a return on investment from the intervention is critical. A multi-method study, guided by the New World Kirkpatrick Model (NWKM), was conducted to determine the impact of the publication writing programme for the period of 2011 to 2018. Quantitative results indicated a total of 314 academics participating in 72 workshops over the study period. To better understand the quantitative results, an open-ended questionnaire and semi-structured interviews were conducted with nine participants from a particular faculty as a convenience sample. The purpose of the research was to collect information to develop a comprehensive framework for impact evaluation that could be used to enhance the current design and delivery of the programme. The qualitative findings highlighted the critical role of a multi-stakeholder strategy in strengthening support before, during, and after a publication writing programme to improve the impact and research outputs. Furthermore, monitoring on-the-job learning is critical to ingrain the new skills academics have learned during the writing workshops and to encourage them to be accountable and empowered. The NWKM additionally provided essential pointers on how to link the results more effectively from publication writing programmes to institutional strategic objectives to improve research performance and quality, as well as what should be included in a comprehensive evaluation framework.

Keywords: evaluation, framework, impact, research output

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Authors: Marc Sader, Michiel Stock, Bernard De Baets

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Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

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Authors: Judit Vilarmau

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Generative AI is emerging rapidly and transforming higher education in many ways, occasioning new challenges and disrupting traditional models and methods. The studies and authors explored remark on the impact on the ethics, curriculum, and pedagogical methods. Students are increasingly using generative AI for study, as a virtual tutor, and as a resource for generating works and doing assignments. This point is crucial for educators to make sure that students are using generative AI with ethical considerations. Generative AI also has relevant benefits for educators and can help them personalize learning experiences and promote self-regulation. Educators must seek and explore tools like ChatGPT to innovate without forgetting an ethical and pedagogical perspective. Eighteen studies were systematically reviewed, and the findings provide implementation guidelines with pedagogical and ethical considerations.

Keywords: ethics, generative artificial intelligence, guidelines, higher education, pedagogy

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Authors: Hee Soo Kim, Ha Young Kyung

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This paper examines the role of positive emotions in human psychology. By understanding Fredrickson and Lyubomirsky et al.’s on positive emotions, one can better understand people’s intuitive understanding, mental health and well-being. Fredrickson asserts that positive emotions create positive affects and personal resources, and Lyubomirsky et al. relate such positive resources to the creation of happiness and personal development. This paper finds that positive emotions play a significant role in the learning process, and they are instrumental in creating a long-lasting repertoire of personal resources and play an essential role in the development of the intuitive understanding of life variables, resilience in coping with life challenges, and ability to build more successful lives.

Keywords: Positive emotions, positive affects, personal resources, negative emotions, development

Procedia PDF Downloads 308