Search results for: multidisciplinary learning

Authors: Elionai Moura, José A. Cunha, César Analide

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This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

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Authors: Caroline Bradbury-Jones, Maria Clark, Eleanor Molloy, Nicki Ward

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Background: Significant developments in the protection of Lesbian, Gay, Bisexual, Transgender and Queer (LGBTQ) rights culminated in their inclusion in the Equality Act 2010. This provides legal protection against discrimination including the Public Sector Equality Duty requiring public bodies to consider all individuals when carrying out their day-to-day work. In the UK, whilst the Higher Education sector has made some commitment to eliminating discrimination and addressing LGBTQ inclusivity, there are two particular problems specifically affecting students on professional programmes: -All students will come into contact with LGBTQ patients/clients/students and need to be equipped to respond appropriately to their diverse needs but evidence suggests that this is not always the case. -Many LGBTQ students have specific concerns on professional placements; often ‘going back in the closet’ or feeling uncertain how to respond to questions about their personal lives and being reticent to challenge discrimination against LGBTQ patients/clients/students for fear of reprisal. Study aim: To investigate how best to prepare all students to deal with the issue of gender and sexual diversity and to support LGBTQ students in negotiating (non) disclosure in practice placements. Methods: This multi-method study was conducted in 2017 in the UK. It comprised a student survey, focus group interview with students and a national benchmarking exercise. Findings: Preliminary findings are that there is considerable variation across professional programmes regarding the preparation of students to respond to LGBTQ issues. Similarly, there is considerable difference between the level of preparedness experienced by students irrespective of whether they identify as LGBTQ. Discussion: Nationally there are a number of ‘best practice’ examples that we share in this presentation. These contain important details and guidance about how to better prepare university students for professional practice, and to contribute to eliminating discrimination and addressing LGBTQ inclusivity. Conclusions: The presentation will appeal to delegates who are interested in the equality agenda regarding LGBTQ people. The study findings will be discussed and debated to explore their impact on higher education and learning and to identify ways to integrate best practice into professional curricula across the UK and beyond.

Keywords: diversity, equality, practice, sexuality, students, university

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Authors: Yi-Ju Lee

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This study identified the hypothesized relationships among tourist emotion, creative experience, and behavioral intention of handmade ancient candy in Tainan, Taiwan. A face-to-face questionnaire survey was administered in Anping, Tainan. The result also revealed significant positive relationships between emotion, creative experience and behavioral intention in handmade activities. This paper provides additional suggestions for enhancing behavioral intention and guidance regarding creative tourism.

Keywords: creative tourism, sense of achievement, unique learning, interaction with instructors

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Motion recognition from videos is actually a very complex task due to the high variability of motions. This paper describes the challenges of human motion recognition, especially motion representation step with relevant features. Our descriptor vector is inspired from Laban Movement Analysis method. We propose discriminative features using the Random Forest algorithm in order to remove redundant features and make learning algorithms operate faster and more effectively. We validate our method on MSRC-12 and UTKinect datasets.

Keywords: discriminative LMA features, features reduction, human motion recognition, random forest

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Authors: Comfort Aina

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Modern English, as we all know it to be a foreign language to many, will require training and re-training on the path of the teacher and learners alike. As a teacher, you cannot give that which you do not have. Teachers, many of whom are non-native speakers, are required to be competent in solving problems occurring in the teaching and learning processes. They should be conscious of up to date information about new approaches, methods, techniques as well as they should be capable in the use of information and communication technology (ICT) and, of course, should work on the improvement of their language components and competence. For teachers to be successful in these goals, they need to be encouraged and motivated. So, for EFL teachers to be successful, they are enrolled to in-service teacher training, ICT training, some of the training they undergo and the benefits accrued to it will be the focus of the paper.

Keywords: training, management, method, english language, EFL teachers

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Authors: S. MacDonald, A. Manuel, R. Law, N. Bandruak, A. Dubrowski, V. Curran, J. Smith-Young, K. Simmons, A. Warren

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High fidelity human patient simulation has been used for many years by health sciences education programs to foster critical thinking, engage learners, improve confidence, improve communication, and enhance psychomotor skills. Unfortunately, there is a paucity of research on the use of high fidelity human patient simulation to foster teamwork among nursing, medicine and pharmacy undergraduate students. This study compared the impact of high fidelity and low fidelity simulation education on teamwork among nursing, medicine and pharmacy students. For the purpose of this study, two innovative teaching scenarios were developed based on the care of an adult patient experiencing acute anaphylaxis: one high fidelity using a human patient simulator and one low fidelity using case based discussions. A within subjects, pretest-posttest, repeated measures design was used with two-treatment levels and random assignment of individual subjects to teams of two or more professions. A convenience sample of twenty-four (n=24) undergraduate students participated, including: nursing (n=11), medicine (n=9), and pharmacy (n=4). The Interprofessional Teamwork Questionnaire was used to assess for changes in students’ perception of their functionality within the team, importance of interprofessional collaboration, comprehension of roles, and confidence in communication and collaboration. Student satisfaction was also assessed. Students reported significant improvements in their understanding of the importance of interprofessional teamwork and of the roles of nursing and medicine on the team after participation in both the high fidelity and the low fidelity simulation. However, only participants in the high fidelity simulation reported a significant improvement in their ability to function effectively as a member of the team. All students reported that both simulations were a meaningful learning experience and all students would recommend both experiences to other students. These findings suggest there is merit in both high fidelity and low fidelity simulation as a teaching and learning approach to foster teamwork among undergraduate nursing, medicine and pharmacy students. However, participation in high fidelity simulation may provide a more realistic opportunity to practice and function as an effective member of the interprofessional health care team.

Keywords: acute anaphylaxis, high fidelity human patient simulation, low fidelity simulation, interprofessional education

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Authors: Catherine Alex Agbor

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The modern Nigerian society is dynamic, divided in zones based on economic, political and educational resources often shared across the zones. The Six Geopolitical Zones in Nigeria is a major division in modern Nigeria, created during the regime of president Ibrahim Badamasi Babangida. They are North Central, North East, North West, South East, South South and South West. However, the zone used in this study is known as former South-Eastern State of Akwa-Ibom State and Cross-River State; former Rivers State of Bayelsa State and Rivers State; and former Mid-Western Region, Nigeria of Delta State and Edo State. Many reforms have taken place overtime, particularly in the education sector. Education is constantly presenting new ideas and innovative approaches which act to facilitate the rapid exchange of knowledge and provide quality basic education for learners. The Federal Government of Nigeria in accordance with its National Council on Education directed the Nigerian Educational Research and Development Council to restructure its basic education curriculum with the hope to enable the nation meet national and global developmental goals. One of the goals of the 9-year Basic Education Programme is developing in the entire citizenry a strong consciousness for education and a strong commitment to its vigorous promotion. Another is ensuring the acquisition of appropriate levels of literacy, numeracy, manipulative, communicative and life-skills as well as the ethical, moral and civic values for laying a solid foundation for lifelong learning. Therefore, this article at the introductory stage is aimed to describe some key issues in Nigeria’s experience in the basic education curriculum. In this study, particular attention is paid to this very recent educational policy of the Nigerian government known as Universal Basic Education, its challenges and what can be done to make the policy achieve its desired objectives. It progresses to analyze modern requirements for second language teaching; and presents the challenges of second language teaching in Nigeria. Finally, it reports a study which investigated special efforts for appropriate achievement of quality education in language classroom in the south-south zone of Nigeria. One fundamental research question was posed on what educational practices can contribute to current understanding of the structure of language curriculum. More explicitly, the study was designed to analyze the extent to which quality content contributes to current understanding of the structure of school curriculum in the zone. Otherwise stated, it investigated how student-centred educational practices impact on their learning of French language. One hundred and eighty (180) participants (teachers) were purposefully sampled for the study. Qualitative technique was used to elicit information from participants. The qualitative method used was Focus Group Discussion (FGD). Participants were divided into six groups comprising of 30 teachers from each zone. Group discussions were based mainly on curriculum contents and practices. Information from participants revealed that the curriculum content, among others is inadequate and should be re-examined. Recommendations were proffered as a panacea to concrete implementation of the basic education in Nigeria.

Keywords: basic education, quality contents, second language, south-south states

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Authors: Christina Tafadzwa

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Global HIV and AIDS trends show that Sub-Saharan Africa is the hardest-hit region, and women are disproportionately affected and infected by HIV. The trend is conspicuous in South Africa, where adolescent girls and young women (AGYW), female university students included, bear the burden of HIV infection. Although the female condom (FC) is the only female-oriented HIV and AIDS technology that provides dual protection against unwanted pregnancy and HIV, its uptake and use remain erratic, especially among the youth and young women in institutions of higher learning. This paper explores empirical evidence from the University of Venda (UniVen), which is in the rural areas of Limpopo Province in South Africa, and also among higher learning institutions experiencing low uptake and use of the FC. A phenomenological approach consisting of in-depth interviews was utilized to collect data from a total of 20 female university students at UniVen who were purposively sampled based on their participation in HIV and AIDS dialogues and campaigns conducted on campus. The findings that were analysed thematically revealed that notions of rurality and sociocultural beliefs surrounding women's sexual and reproductive health are key structural factors that influence the low use and uptake of the FC at the rural university. The evidence thus far revealed that female students are discouraged from collecting or initiating FC because of cultural dictates or prescripts which place the responsibility to collect and initiate condom use on men. Hence the inference that UniVen female students' realities are compounded by notions of rurality and society's patriarchal nature that intersect and limit women's autonomy in matters of sex. Guided by the women empowerment theory, this paper argues that such practices take away UniVen female students' agency to decide on their sexual and reproductive health. The normalisation of socio-cultural and harmful gender practices is also a retrogression in the women's health agenda. The paper recommends a holistic approach that engages traditional and community leaders, particularly men, to unlearn and uproot harmful gender norms and patriarchal elements that hinder the promotion and use of the FC.

Keywords: female condom, UniVen, socio-cultural factors, female students, HIV and AIDS

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Authors: Liliana O. Martínez, Juan E González, Manuel Ramírez-Aranda, Ana Cervantes-Herrera

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A serious game category mobile application called Math Dominoes is presented. The main objective of this applications is to strengthen the teaching-learning process of solving algebraic equations and is based on the board game "Double 6" dominoes. Math Dominoes allows the practice of solving first, second-, and third-degree algebraic equations. This application is aimed to students who seek to strengthen their skills in solving algebraic equations in a dynamic, interactive, and fun way, to reduce the risk of failure in subsequent courses that require mastery of this algebraic tool.

Keywords: algebra, equations, dominoes, serious games

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Authors: Jiraporn Weenuttranon

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The objectives of the consumer behavior of bakery products in Bangkok are to study consumer behavior of the bakery product, to study the essential factors that could possibly affect the consumer behavior and to study recommendations for the development of the bakery products. This research is a survey research. Populations are buyer’s bakery products in Bangkok. The probability sample size is 400. The research uses a questionnaire for self-learning by using information technology. The researcher created a reliability value at 0.71 levels of significance. The data analysis will be done by using the percentage, mean, and standard deviation and testing the hypotheses by using chi-square.

Keywords: consumer, behavior, bakery, standard deviation

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Authors: Alice Khachian, Shoaleh Bigdeli, Azita Shoghie, Leili Borimnejad

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Background and aim: The hidden curriculum is crucial in nursing education and can determine professionalism and professional competence. It has a significant effect on their moral performance in relation to patients. The present study was conducted with the aim of identifying the hidden curriculum components in the nursing and midwifery faculty. Methodology: The ethnographic study was conducted over two years using the Spradley method in one of the nursing schools located in Tehran. In this focused ethnographic research, the approach of Lincoln and Goba, i.e., transferability, confirmability, and dependability, was used. To increase the validity of the data, they were collected from different sources, such as participatory observation, formal and informal interviews, and document review. Two hundred days of participatory observation, fifty informal interviews, and fifteen formal interviews from the maximum opportunities and conditions available to obtain multiple and multilateral information added to the validity of the data. Due to the situation of COVID, some interviews were conducted virtually, and the activity of professors and students in the virtual space was also monitored. Findings: The components of the hidden curriculum of the faculty are: the atmosphere (physical environment, organizational structure, rules and regulations, hospital environment), the interaction between activists, and teaching-learning activities, which ultimately lead to “A disconnection between goals, speech, behavior, and result” had revealed. Conclusion: The mutual effects of the atmosphere and various actors and activities on the process of student development, since the students have the most contact with their peers first, which leads to the most learning, and secondly with the teachers. Clinicians who have close and person-to-person contact with students can have very important effects on students. Students who meet capable and satisfied professors on their way become interested in their field and hope for their future by following the mentor of these professors. On the other hand, weak and dissatisfied professors lead students to feel abandoned, and by forming a colony of peers with different backgrounds, they distort the personality of a group of students and move away from family values, which necessitates a change in some cultural practices at the faculty level.

Keywords: hidden curriculum, nursing education, ethnography, nursing

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Jane O`Halloran

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Japanese university students have traditionally shown antipathy towards English due to a generally unsatisfactory language-learning experience at the secondary level with a focus on grammar and translation rather than communication. The situation has become urgent, however, due to the rapid decline in the Japanese population, which will present both difficulties and opportunities as employees will increasingly be forced to use English in the workplace. For university lecturers, the challenge is to overcome the students` apathy and convince them of the need for English in the increasingly diverse workplaces they will be entering. This article will illustrate how English teachers and content teachers at a private science university came together to address this quandary.

Keywords: student motivation, CLIL, globalization, demographics

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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The link between man and food plays, in the social and economic system, a central role where cultural and multidisciplinary aspects intertwine: food is not only nutrition, but also communication, culture, politics, environment, science, ethics, fashion. This multi-dimensionality has many implications in the food economy. In recent years, the consumer became more conscious about his food choices, involving a consistent change in consumption models. This change concerns several aspects: awareness of food system issues, employment of socially and environmentally conscious decision-making, food choices based on different characteristics than nutritional ones i.e. origin of food, how it’s produced, and who’s producing it. In this frame the ‘consumption choices’ and the ‘interests of the citizen’ become one part of the others. The figure of the ‘Citizen Consumer’ is born, a responsible and ethically motivated individual to change his lifestyle, achieving the goal of sustainable consumption. Simultaneously the branding, that before was guarantee of the product quality, today is questioned. In order to meet these needs, Agri-Food companies are developing specific product lines that follow two main philosophies: ‘Back to basics’ and ‘Less is more’. However, the issue of ethical behavior does not seem to find an adequate on market offer. Most likely due to a lack of attention on the communication strategy used, very often based on market logic and rarely on ethical one. The label in its classic concept of ‘clean labeling’ can no longer be the only instrument through which to convey product information and its evolution towards a concept of ‘clear label’ is necessary to embrace ethical and transparent concepts in progress the process of democratization of the Food System. The implementation of a voluntary traceability path, relying on the technological models of the Internet of Things or Industry 4.0, would enable the Agri-Food Supply Chain to collect data that, if properly treated, could satisfy the information need of consumers. A change of approach is therefore proposed towards Agri-Food traceability that is no longer intended as a tool to be used to respond to the legislator, but rather as a promotional tool useful to tell the company in a transparent manner and then reach the slice of the market of food citizens. The use of mobile technology can also facilitate this information transfer. However, in order to guarantee maximum efficiency, an appropriate communication model based on the ethical communication principles should be used, which aims to overcome the pipeline communication model, to offer the listener a new way of telling the food product, based on real data collected through processes traceability. The Citizen Consumer is therefore placed at the center of the new model of communication in which he has the opportunity to choose what to know and how. The new label creates a virtual access point capable of telling the product according to different point of views, following the personal interests and offering the possibility to give several content modalities to support different situations and usability.

Keywords: agri food traceability, agri-food transparency, clear label, food system, internet of things

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Authors: Robbi Beyer, Tiffanye Vargas, Margaret Flores

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Within the United States, youths with hidden disabilities (specific learning disabilities, attention deficit hyperactivity disorder, emotional behavioral disorders, mild intellectual disabilities and speech/language disorders) can often be part of the kindergarten through twelfth grade school population. Because individuals with hidden disabilities have no apparent physical disability, learning difficulties may be overlooked and these youths may be mistakenly labeled as unmotivated, or defiant because they don't understand and follow directions, or maintain enough attention to remember and perform. These behaviors are considered especially challenging for youth sport coaches to manage and they often find it difficult to successfully select and deliver effective accommodations for the athletes. These deficits can be remediated and compensated through the use of research-validated strategies and instructional methods. However, while these techniques are commonly included in teacher preparation, they rarely, if ever, are included in coaching preparation. Therefore, the purpose of this presentation is to summarize consecutive research studies that examined coaching education within the United States for youth athletes with hidden disabilities. Each study utilized a questionnaire format to collect data from coaches on attitudes, efficacy and solutions for addressing challenging behaviors. Results indicated that although the majority of coaches’ attitudes were positive and they perceived themselves confident in working with athletes who have hidden disabilities, there were significant differences in the understanding of appropriate teaching strategies and techniques for this population. For example, when asked to describe a videotaped situation of why an athlete is not performing correctly, coaches often found the athlete to be at fault, as opposed to considering the possibility of faulty directions, or the need for accommodations in teaching/coaching style. When considering coaches’ preparation, 83% of participants declared they were inadequately prepared to coach athletes with hidden disabilities and 92% strongly supported improved preparation for coaches. The comprehensive examination of coaches’ perceptions and efficacy in working with youth athletes with hidden disabilities has provided valuable insight and highlights the need for continued research in this area.

Keywords: health, hidden disabilties, physical activity, youth recreational sports

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Authors: Chrysi K. Nikoloutsou, Gianna Th. Siapati

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The pandemic limitations have altered architectural education as the discourse shifted towards virtual studios and blended learning. In addition, lockdown conditions and remote working have affected habitation. Adaptability is now a key factor. The architectural studio needs to adjust to these new terms both in education and in inhabitation. This paper will investigate the operation of an architectural studio in relation to how one experiences their house due to the pandemic, based on a literature review and qualitative research methods (interviews & workshops with students). Zenetos’ prophetic ideas of ‘Electronic Urbanism’ and ‘tele-activities’ are now more present than ever.

Keywords: architectural education, pandemic, residential design, studio pedagogy

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Authors: H. Hussain, N. H. Mohamad

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Practical experiences have been one of the successful criteria for the Project Management course for the art and design students. There are series of events that the students have to undergo as part of their practical exercises in the learning context for Project Management courses. These series have been divided into few mini programs that involved the whole individual in each group. Therefore, the events have been one of the bench marks for these students. Through the practical experience, the task that has been given to individual has been performed according to the needs of professional practice and ethics.

Keywords: practical experience, project management, art and design students, events, programs

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

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Authors: Theresa Veach, Erin Crisp

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It has been shown that traditional students flourish as a function of several factors including level of academic challenge, student/faculty interactions, active/collaborative learning, enriching educational experiences, and supportive campus environment. With the increase in demand for remote or online courses, factors that result in academic flourishing in the virtual classroom have become more crucial to understand than ever before. This study seeks to give insight into those factors that impact student learning, overall student wellbeing, and flourishing among college students enrolled in an online program. 4160 unique students participated in the completion of End of Course Survey (EOC) before final grades were released. Quantitative results from the survey are used by program directors as a measure of student satisfaction with both the curriculum and the faculty. In addition, students also submitted narrative comments in an open comment field. No prompts were given for the comment field on the survey. The purpose of this analysis was to report on the qualitative data available with the goal of gaining insight into what matters to students. Survey results from July 1st, 2016 to December 1st, 2016 were compiled into spreadsheet data sets. The analysis approach used involved both key word and phrase searches and reading results to identify patterns in responses and to tally the frequency of those patterns. In total, just over 25,000 comments were included in the analysis. Preliminary results indicate that it is the professor-student relationship, frequency of feedback and overall engagement of both instructors and students that are indicators of flourishing in college programs offered in an online format. This qualitative study supports the notion that college students flourish with regard to 1) education, 2) overall student well-being and 3) program satisfaction when overall engagement of both the instructor and the student is high. Ways to increase engagement in the online college environment were also explored. These include 1) increasing student participation by providing more project-based assignments, 2) interacting with students in meaningful ways that are both high in frequency and in personal content, and 3) allowing students to apply newly acquired knowledge in ways that are meaningful to current life circumstances and future goals.

Keywords: college, engagement, flourishing, online

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Authors: Babesse Saad, Ameddah Djemeleddine

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In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.

Keywords: rollover, single unit heavy vehicle, neural networks, nonlinear side force

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Authors: B. Selma

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The aim of this study is to test the feasibility of SIPINA method to predict the harmfulness parameters controlling the seismic response. The approach developed takes into consideration both the focal depth and the peak ground acceleration. The parameter to determine is displacement. The data used for the learning of this method and analysis nonlinear seismic are described and applied to a class of models damaged to some typical structures of the existing urban infrastructure of Jassy, Romania. The results obtained indicate an influence of the focal depth and the peak ground acceleration on the displacement.

Keywords: SIPINA algorithm, seism, focal depth, peak ground acceleration, displacement

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Authors: Gongbing Shan, Shiming Li, Zhao Zhang, Bingjun Wan

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Badminton originated in ancient civilizations in Europe and Asia more than 2000 years ago. Presently, it is played almost everywhere with estimated 220 million people playing badminton regularly, ranging from professionals to recreational players; and it is the second most played sport in the world after soccer. In Asia, the popularity of badminton and involvement of people surpass soccer. Unfortunately, scientific researches on badminton skills are hardly proportional to badminton’s popularity. A search of literature has shown that the literature body of biomechanical investigations is relatively small. One of the dominant skills in badminton is the forehand overhead smash, which consists of 1/5 attacks during games. Empirical evidences show that one has to adjust the body position in relation to the coming shuttlecock to produce a powerful and accurate smash. Therefore, positioning is a fundamental aspect influencing smash quality. A search of literature has shown that there is a dearth/lack of study on this fundamental aspect. The goals of this study were to determine the influence of positioning and training experience on smash quality in order to discover information that could help learn/acquire the skill. Using a 10-camera, 3D motion capture system (VICON MX, 200 frames/s) and 15-segment, full-body biomechanical model, 14 skilled and 15 novice players were measured and analyzed. Results have revealed that the body positioning has direct influence on the quality of a smash, especially on shuttlecock release angle and clearance height (passing over the net) of offensive players. The results also suggest that, for training a proper positioning, one could conduct a self-selected comfort position towards a statically hanged shuttlecock and then step one foot back – a practical reference marker for learning. This perceptional marker could be applied in guiding the learning and training of beginners. As one gains experience through repetitive training, improved limbs’ coordination would increase smash quality further. The researchers hope that the findings will benefit practitioners for developing effective training programs for beginners.

Keywords: 3D motion analysis, biomechanical modeling, shuttlecock release speed, shuttlecock release angle, clearance height

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Authors: Jun Seung Woo, Shin Dong Ho

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The Image Captioning models with Attention technology have developed significantly compared to previous models, but it is still unsatisfactory in recognizing images. We perform an extensive search over seven interesting Convolutional Neural Networks(CNN) architectures to analyze the behavior of different models for image captioning. We compared seven different CNN Architectures, according to batch size, using on public benchmarks: MS-COCO datasets. In our experimental results, DenseNet and InceptionV3 got about 14% loss and about 160sec training time per epoch. It was the most satisfactory result among the seven CNN architectures after training 50 epochs on GPU.

Keywords: deep learning, image captioning, CNN architectures, densenet, inceptionV3

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Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Juliane Toce, Steven Holochwost

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A substantial and growing literature has demonstrated that arts education benefits young children’s socioemotional and cognitive development. Less is known about the capacity of arts-integrated instruction to yield benefits to similar domains, particularly among demographically and socioeconomically diverse groups of young children. However, the small literature on this topic suggests that arts-integrated instruction may foster young children’s socioemotional and cognitive development by presenting opportunities to 1) engage in instructional content in diverse ways, 2) experience and regulate strong emotions, 3) experience growth-oriented feedback, and 4) engage in collaborative work with peers. Start with the Art is a new program of arts-integrated instruction currently being implemented in four schools in a school district that serves students from a diverse range of backgrounds. The program employs a co-teaching model in which teaching artists and classroom teachers engage in collaborative lesson planning and instruction over the course of the academic year and is currently the focus of an impact study featuring a randomized-control design, as well as an implementation study, both of which are funded through an Educational Innovation and Research grant from the United States Department of Education. The paper will present the early results from the Start with the Art implementation study. These results will provide an overview of the extent to which the program was implemented in accordance with design, with a particular emphasis on the degree to which the four opportunities enumerated above (e.g., opportunities to engage in instructional content in diverse ways) were presented to students. There will be a review key factors that may influence the fidelity of implementation, including classroom teachers’ reception of the program and the extent to which extant conditions in the classroom (e.g., the overall level of classroom organization) may have impacted implementation fidelity. With the explicit purpose of creating a program that values and meets the needs of the teachers and students, Start with the Art incorporates the feedback from individuals participating in the intervention. Tracing its trajectory from inception to ongoing development and examining the adaptive changes made in response to teachers' transformative experiences in the post-pandemic classroom, Start with the Art continues to solicit input from experts in integrating artistic content into core curricula within educational settings catering to students from under-represented backgrounds in the arts. Leveraging the input from this rich consortium of experts has allowed for a comprehensive evaluation of the program’s implementation. The early findings derived from the implementation study emphasize the potential of arts-integrated instruction to incorporate restorative practices. Such practices serve as a crucial support system for both students and educators, providing avenues for children to express themselves, heal emotionally, and foster social development, while empowering teachers to create more empathetic, inclusive, and supportive learning environments. This all-encompassing analysis spotlights Start with the Art’s adaptability to any learning environment through the program’s effectiveness, resilience, and its capacity to transform - through art - the classroom experience within the ever-evolving landscape of education.

Keywords: arts-integration, social emotional learning, diverse learners, co-teaching, teaching artists, post-pandemic teaching

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Authors: Abdul Rawuf Hussein, Rusnani Abdul Kadir, Mona Adlina Binti Adanan

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Guidance program has been an essential approach in helping professions from many institutions of learning as well as communities, organizations, and clinical settings. Although the term varies depending on the approaches, objectives, and theories, the core and central element is typically developmental in nature. In this conceptual paper, the researcher will review literature on the concept of group guidance, its impact on students’ and individual’s development, developing a guidance module and proposing a synthesised framework for group guidance program.

Keywords: concept, framework, group guidance, module development

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Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating

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Authors: Konstantina Georgali

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The present study explores Greek teachers’ understandings of typical language development and of language difficulties. Its core aim was to highlight that teachers need to have a thorough understanding of educational linguistics, that is of how language figures in education. They should also be aware of how language should be taught so as to promote language development for all students while at the same time support the needs of children with language difficulties in an inclusive ethos. The study, thus argued that language can be a dynamic learning mechanism in the minds of all children and a powerful teaching tool in the hands of teachers and provided current research evidence to show that structural and morphological particularities of native languages- in this case, of the Greek language- can be used by teachers to enhance children’s understanding of language and simultaneously improve oral language skills for children with typical language development and for those with language difficulties. The research was based on a Sequential Exploratory Mixed Methods Design deployed in three consecutive and integrative phases. The first phase involved 18 exploratory interviews with teachers. Its findings informed the second phase involving a questionnaire survey with 119 respondents. Contradictory questionnaire results were further investigated in a third phase employing a formal testing procedure with 60 children attending Y1, Y2 and Y3 of primary school (a research group of 30 language impaired children and a comparison group of 30 children with typical language development, both identified by their class teachers). Results showed both strengths and weaknesses in teachers’ awareness of educational linguistics and of language difficulties. They also provided a different perspective of children’s language needs and of language teaching approaches that reflected current advances and conceptualizations of language problems and opened a new window on how best they can be met in an inclusive ethos. However, teachers barely used teaching approaches that could capitalize on the particularities of the Greek language to improve language skills for all students in class. Although they seemed to realize the importance of oral language skills and their knowledge base on language related issues was adequate, their practices indicated that they did not see language as a dynamic teaching and learning mechanism that can promote children’s language development and in tandem, improve academic attainment. Important educational implications arose and clear indications of the generalization of findings beyond the Greek educational context.

Keywords: educational linguistics, inclusive ethos, language difficulties, typical language development

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Authors: Cristobal García

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The visual inspection of bolted joints in wind turbines is dangerous, expensive, and impractical due to the non-possibility to access the platform by workboat in certain sea state conditions, as well as the high costs derived from the transportation of maintenance technicians to offshore platforms located far away from the coast, especially if helicopters are involved. Consequently, the wind turbine operators have the need for simpler and less demanding techniques for the analysis of the bolts tightening. Vibration-based structural health monitoring is one of the oldest and most widely-used means for monitoring the health of onshore and offshore wind turbines. The core of this work is to find out if the modal parameters can be efficiently used as a key performance indicator (KPIs) for the assessment of joint bolts in a 1:50 scale tower of a floating offshore wind turbine (12 MW). A non-destructive vibration test is used to extract the vibration signals of the towers with different damage statuses. The procedure can be summarized in three consecutive steps. First, an artificial excitation is introduced by means of a commercial shaker mounted on the top of the tower. Second, the vibration signals of the towers are recorded for 8 s at a sampling rate of 20 kHz using an array of commercial accelerometers (Endevco, 44A16-1032). Third, the natural frequencies, damping, and overall vibration mode shapes are calculated using the software Siemens LMS 16A. Experiments show that the natural frequencies, damping, and mode shapes of the tower are directly dependent on the fixing conditions of the towers, and therefore, the variations of both parameters are a good indicator for the estimation of the static axial force acting in the bolt. Thus, this vibration-based structural method proposed can be potentially used as a diagnostic tool to evaluate the tightening torques of the bolted joints with the advantages of being an economical, straightforward, and multidisciplinary approach that can be applied for different typologies of connections by operation and maintenance technicians. In conclusion, TSI, in collaboration with the consortium of the FIBREGY project, is conducting innovative research where vibrations are utilized for the estimation of the tightening torque of a 1:50 scale steel-based tower prototype. The findings of this research carried out in the context of FIBREGY possess multiple implications for the assessment of the bolted joint integrity in multiple types of connections such as tower-to-nacelle, modular, tower-to-column, tube-to-tube, etc. This research is contextualized in the framework of the FIBREGY project. The EU-funded FIBREGY project (H2020, grant number 952966) will evaluate the feasibility of the design and construction of a new generation of marine renewable energy platforms using lightweight FRP materials in certain structural elements (e.g., tower, floating platform). The FIBREGY consortium is composed of 11 partners specialized in the offshore renewable energy sector and funded partially by the H2020 program of the European Commission with an overall budget of 8 million Euros.

Keywords: SHM, vibrations, connections, floating offshore platform

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