Search results for: English learning strategies

Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner

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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.

Keywords: card game, collective songwriting, community of practice, network, postdigital

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Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: E. Gopi, E. Devaindran

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Objective: Non-operative management of blunt splenic trauma have started to overtake the traditional splenectomy in recent years across the grade of splenic injury. The two main non-operative methods are observation and angioembolisation. However, the post management convalescence in these groups are still being investigated. The study attempts to quantify the clinical indicators among the two in particular complications, mortalities, conversions to operative management and duration of inpatient stay. Methodology: A systematic search was done via PUBMED, MEDLINE, and EMBASE. A total of 639 articles identified and subsequently 68 articles were identified post duplicates, full text, and inclusion and exclusion criteria. Main exclusions were non-English articles without English translation, pure observational or angioembolisation articles of which no comparison data could be identified and articles looking into pure hemodynamically unstable patients. Results: 24 non randomized controlled trial, 5 clinical control trial and 39 retrospective studies analyzing a total of 23700 patients with blunt splenic trauma. Discrepancies in data were noted in the group who had observational management versus angioembolisation in particular as data was compared among the classes of splenic rupture, the protocol of management in different centers, availability of angiogram suite, and the study design. Further variability was also noted in the angioembolisation arm as the preference for treatment differs between distal versus proximal splenic artery involvement. Overall the cumulative mortality in both observational and angioembolisation group were similar, 2.78% and 5.97% respectively. The cause of death however is not directly attributed to the management itself but rather patient comorbidities, other associated injuries and conversions to splenectomy leading to post splenectomy complications. The cumulative morbidity among each group appears to be same approximately 12% in observational versus 15% in angioembolisation. However, the type of complications varies with the observational group having higher rates of inpatient stay and intrabdominal hematoma infection and angioembolisation group developing more splenic infarcts and bleeds. There were significant disparity in reporting the actual data on duration of inpatient stay and complications to allow a statistically significant quantitative analysis to be done, 15 articles however are currently being considered. Conclusions: Observational management appears to be much effective in managing lower grade splenic trauma (grade 1 and 2) where else angioembolisation appears to play a bigger role in intermediate grades (grade 3-4) in ensuring splenic function preservation. Care has to be taken however in the angioembolisation group in view of distal splenic infarct group compromising splenic function. The cumulated data of 15 articles are now being considered for a meta-analysis.

Keywords: blunt splenic trauma, conservative, non-operative, angioembolisation

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Authors: Sara Blanc, José V. Benlloch-Dualde, Laura Grindei, Ana C. Torres, Angélica Monteiro

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This paper presents a study that leads a new experience by introducing digital learning applied to a case study focused on primary and secondary school garden-based education. The approach represents an example of interaction among different education and research agents at different countries and levels, such as universities, public and private research, and schools, to get involved in the implementation of education for sustainable development that will make students become more sensible to natural environment, more responsible for their consumption, more aware about waste reduction and recycling, more conscious of the sustainable use of natural resources and, at the same time, more ‘digitally competent’. The experience was designed attending to the European digital education context and OECD directives in transversal skills education. The paper presents the methodology carried out in the study as well as outcomes obtained from experience.

Keywords: school gardens, primary education, secondary education, science technology and innovation in education, digital learning, sustainable development goals, university, knowledge transference

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

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BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

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Authors: Irma Nool, Katriin Saueauk, Ebe Siimson, Vlada Žukova, Elise Gertrud Vellet

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Background: Asthma is one of themostcommonchronicdiseases in children, whichcansignificantlyaffectchildren, and challengetheirfamilies. The unpredictability, frequency, and control of asthma attacks have a profound effect on the daily lives of familieswithasthmaticchildren. Thereis a growing body of researchshowingthatthequality of life of parents and childrenislinkedtothedevelopment of asthma. Theoretical and clinicalstudiesprovethat a positive and well-functioningfamilysystemhelpstocopebetterwiththediagnosis of the chronic disease. The aim of theresearchwastodescribethecopingstrategies of parents of a childwithasthmaconcerningthechild'sillness. Method: Theresearchwasanempirical, quantitative, descriptive study. Thesamplewastheparents of a child with asthma at the Tallinn Children'sHospital, whose child was in inpatienttreatmentbetween 07.04.2021 and 12.09.2021. This is a convenient sample. 59 parentsrepliedtothequestionnaire. The questionnaire “CopingInventoryforStressfulSituations” wasusedtocollectthedata, whichwastranslatedinto Estonian and Russian using a back-and-forthtranslationtechnique. Thequestionnairewasanswered on a 5-point Likert scale. Dataanalysiswasperformedusing SPSS 26.0, descriptive statistics, with mean values and standard deviation. The Mann-Whitney U test wasusedtocomparefathers and motherscopingstrategies. PermissiontoconductresearchhasbeenobtainedfromtheEthicsCommitteeforHuman Research of theInstituteforHealthDevelopment. Results: The mean age of the respondents was 40 ± 6.2 years (median 40), withtheyoungestbeing 27 yearsold and the oldest being 57 yearsold. Of the respondents, 51 (86.4%) were mothers, and 8 (13.6%) werefathers. Parentsusedthemosttask-orientedcopingstrategies (mean 3.35 ± 0.602) and theleastemotion-orientedcopingstrategies (mean 1.97 ± 0.526). Mothersusedmoretask-orientedcopingstrategies (p = 0.001) than fathers. Fathersusedemotion-orientedcopingstrategiesless (p = 0.024) than mothers. mothersplantheirtimebetter (p = 0.043), focus on the problem and look at how to solve it (p = 0.007), and makeanefforttogetthingsdone (p = 0.045). mothersblamethemselvesmorefornotknowingwhattodo (p = 0.045) and worryaboutwhattheyshoulddo (p = 0.027). mothers look more at the goods displayed in the shop windows (p = 0.018) and go for a walk (p = 0.007) compared to fathers. Conclusions: The results of theresearchshowedthatproblem-orientedcopingstrategiesare used the most and there are differences in the behavior of fathers and mothers. Thisshouldbetakenintoaccountwhenprovidingfamily-centered nursing care.

Keywords: asthma, coping strategies, parents, family

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Authors: O. V. Vyazovska

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Behavioral efficiency is one of the main principles to be successful in nature. Accuracy of visual discrimination is determined by the attention, learning experience, and memory. In the experimental condition, pigeons’ responses to visual stimuli presented on the screen of the monitor are behaviorally manifested by pecking or not pecking the stimulus, by the number of pecking, reaction time, etc. The higher the probability of rewarding is, the more likely pigeons will respond to the stimulus. We trained 8 pigeons (Columba livia) on a stagewise go/no-go visual discrimination task.16 visual stimuli were created from all possible combinations of four binary dimensions: brightness (dark/bright), size (large/small), line orientation (vertical/horizontal), and shape (circle/square). In the first stage, we presented S+ and 4 S-stimuli: the first that differed in all 4-dimensional values from S+, the second with brightness dimension sharing with S+, the third sharing brightness and orientation with S+, the fourth sharing brightness, orientation and size. Then all 16 stimuli were added. Pigeons rejected correctly 6-8 of 11 new added S-stimuli at the beginning of the second stage. The results revealed that pigeons’ behavior at the beginning of the second stage was controlled by probabilities of rewarding for 4 dimensions learned in the first stage. More or fewer mistakes with dimension discrimination at the beginning of the second stage depended on the number S- stimuli sharing the dimension with S+ in the first stage. A significant inverse correlation between the number of S- stimuli sharing dimension values with S+ in the first stage and the dimensional learning rate at the beginning of the second stage was found. Pigeons were more confident in discrimination of shape and size dimensions. They made mistakes at the beginning of the second stage, which were not associated with these dimensions. Thus, the received results help elucidate the principles of dimensional stimulus control during learning compound multidimensional visual stimuli.

Keywords: visual go/no go discrimination, selective attention, dimensional stimulus control, pigeon

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Authors: Alexander K. Edwards

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Introduction: The moral dimension of teacher education globally has assumed a new paradigm of thinking based on the public gain (return-on-investments), value-creation (quality), professionalism (practice), and business strategies (innovations). Abundant literature reveals an interesting revolutionary trend in complimenting the raising of teachers and academic performances. Because of the global competition in the knowledge-creation and service areas, the C21st teacher at all levels is expected to be resourceful, strategic thinker, socially intelligent, relationship aptitude, and entrepreneur astute. This study is a significant contribution to practice and innovations to raise exemplary or primal teachers. In this study, the qualities needed were considered as ‘Quadrant Intelligence (Q-i)’ model for a primal teacher leadership beyond the classroom. The researcher started by examining the issue of the majority of teachers in Ghana Education Services (GES) in need of this Q-i to be effective and efficient. The conceptual framing became determinants of such Q-i. This is significant for global employability and versatility in teacher education to create premium and primal teacher leadership, which are again gaining high attention in scholarship due to failing schools. The moral aspect of teachers failing learners is a highly important discussion. In GES, some schools score zero percent at the basic education certificate examination (BECE). The question is what will make any professional teacher highly productive, marketable, and an entrepreneur? What will give teachers the moral consciousness of doing the best to succeed? Method: This study set out to develop a model for primal teachers in GES as an innovative way to highlight a premium development for the C21st business-education acumen through desk reviews. The study is conceptually framed by examining certain skill sets such as strategic thinking, social intelligence, relational and emotional intelligence and entrepreneurship to answer three main burning questions and other hypotheses. Then the study applied the causal comparative methodology with a purposive sampling technique (N=500) from CoE, GES, NTVI, and other teachers associations. Participants responded to a 30-items, researcher-developed questionnaire. Data is analyzed on the quadrant constructs and reported as ex post facto analyses of multi-variances and regressions. Multiple associations were established for statistical significance (p=0.05). Causes and effects are postulated for scientific discussions. Findings: It was found out that these quadrants are very significant in teacher development. There were significant variations in the demographic groups. However, most teachers lack considerable skills in entrepreneurship, leadership in teaching and learning, and business thinking strategies. These have significant effect on practices and outcomes. Conclusion and Recommendations: It is quite conclusive therefore that in GES teachers may need further instructions in innovations and creativity to transform knowledge-creation into business venture. In service training (INSET) has to be comprehensive. Teacher education curricula at Colleges may have to be re-visited. Teachers have the potential to raise their social capital, to be entrepreneur, and to exhibit professionalism beyond their community services. Their primal leadership focus will benefit many clienteles including students and social circles. Recommendations examined the policy implications for curriculum design, practice, innovations and educational leadership.

Keywords: emotional intelligence, entrepreneurship, leadership, quadrant intelligence (q-i), primal teacher leadership, strategic thinking, social intelligence

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Authors: Gabriel G. Gaft, Xayvinay Xiong, Amanda Sunday

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The emergent pandemic from COVID-19 virus has forced people to adjust to major changes. These changes include all elements of family and work life and required people to engage in novel behaviors. For many people, the social norms to which they have been accustomed no longer prevail. Not surprisingly, such enormous changes in daily life have been associated with greater problems in mental health; and research regarding ways in which mental health professionals can support people is more necessary than ever before. It is often useful to assess people’s reactions through surveys and utilize quantitative data to answer questions about coping strategies etc. It is also likely, however, that a host of individual factors are going to contribute to what might be considered 'good' or 'bad' coping mechanisms to a worldwide pandemic. To this end, qualitative studies—where the individual’s subjective experience is highlighted—are likely to provide more vital information for mental health professionals interested in supporting the particular person in front of them. This study reports on qualitative data, where X participants were asked questions about social distancing, coping strategies, and general attitudes towards social changes resulting from the COVID-19 pandemic. Informal interviews were conducted during the months of June-July 2020. Data were analyzed using Interpretative Phenomenological Analyses. Themes were identified first for each participant and then compared across different individual participants. Several findings emerged. First, all participants understood major health messages being imparted by governing bodies such as the CDC and WHO. The researchers feel this finding is important as it suggests health messages are at least being effectively communicated. Second, there was a clear trend for themes which highlighted the conflicting emotions participants felt about the changes they were expected to endure: positive and negative elements were identified, although a participant who had pre-existing conditions placed greater emphasis on the negative elements. One participant who was particularly interested in impression management also exclusively emphasized negative emotions. Third, participants who were able to reevaluate priorities—what Lazarus might call secondary appraisals—experienced social distancing as a positive rather than negative phenomenon. Finally, participants who were able to develop specific strategies—such as boundaries for work and self-care—reported themes of adjustment and contentment. Taken together, these findings suggest mental health practitioners can assist people to adjust more positively through specific techniques focusing on re-evaluation of life priorities and strategic coping skills.

Keywords: COVID-19, pandemic, phenomenology, virus

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Authors: Jing Zhao, Yongqing Bai, Qiaofang Shi, Huaihao Zhang

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Advances in software technology enable computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: upper-division undergraduate, computer-based learning, laboratory instruction, molecular modeling

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Authors: Richard Mababu Mukiur

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Leadership is an important drive that plays a key role in the success and development of organizations, particularly in the current context of digital transformation, highly competitivity and globalization. Leaders are persons that hold a dominant and privileged position within an organization, field, or sector of activities and are able to manage, motivate and exercise a high degree of influence over other in order to achieve the institutional goals. They achieve commitment and engagement of others to embrace change, and to make good decisions. Leadership studies in higher education institutions have examined how effective leaders hold their organizations, and also to find approaches which fit best in the organizations context for its better management, transformation and improvement. Moreover, recent studies have highlighted the impact of leadership styles on organizational performance and innovation capacities, since some styles give better results than others. Effective leadership is part of learning process that take place through day-to-day tasks, responsibilities, and experiences that influence the organizational performance, innovation and engagement of employees. The adoption of appropriate leadership styles can improve organization results and encourage learning process, team skills and performance, and employees' motivation and engagement. In the case of case of Information Technology sector, leadership styles are particularly crucial since this sector is leading relevant changes and transformations in the knowledge society. In this context, the main objective of this study is to analyze managers leadership styles with their relation to organizational performance and innovation that may be mediated by learning organization process and demographic variables. Therefore, it was hypothesized that the transformational and transactional leadership will be the main style adopted in Information Technology sector and will influence organizational performance and innovation capacity. A sample of 540 participants from Information technology sector has been determined in order to achieve the objective of this study. The Multifactor Leadership Questionnaire was administered as the principal instrument, Scale of innovation and Learning Organization Questionnaire. Correlations and multiple regression analysis have been used as the main techniques of data analysis. The findings indicate that leadership styles have a relevant impact on organizational performance and innovation capacity. The transformational and transactional leadership are predominant styles in Information technology sector. The effective leadership style tend to be characterized by the capacity of generating and sharing knowledge that improve organization performance and innovation capacity. Managers are adopting and adapting their leadership styles that respond to the new organizational, social and cultural challenges and realities of contemporary society. Managers who encourage innovation, foster learning process, share experience are useful to the organization since they contribute to its development and transformation. Learning process capacity and demographic variables (age, gender, and job tenure) mediate the relationship between leadership styles, innovation capacity and organizational performance. The transformational and transactional leadership tend to enhance the organizational performance due to their significant impact on team-building, employees' engagement and satisfaction. Some practical implications and future lines of research have been proposed.

Keywords: leadership styles, tranformational leadership, organisational performance, organisational innovation

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Authors: Geeta Gahlawat, Sanjeev Kumar Soni

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An imprudent use of environmentally hazardous petrochemical-based plastics and limited availability of fossil fuels have provoked research interests towards production of biodegradable plastics - polyhydroxyalkanoate (PHAs). However, the industrial application of PHAs based products is primarily restricted by their high cost of recovery and extraction protocols. Moreover, solvents used for the extraction and purification are toxic and volatile which causes adverse environmental hazards. Development of efficient downstream recovery strategies along with utilization of non-toxic solvents will accelerate their commercialization. In this study, various extraction strategies were designed for sustainable and cost-effective recovery of PHAs from Cupriavidus necator using non-toxic environment friendly solvents viz. 1,2-propylene carbonate, ethyl acetate, isoamyl alcohol, butyl acetate. The effect of incubation time i.e. 10, 30 and 50 min and temperature i.e. 60, 80, 100, 120°C was tested to identify the most suitable solvent. PHAs extraction using a recyclable solvent, 1,2 propylene carbonate, showed the highest recovery yield (90%) and purity (93%) at 120°C and 30 min incubation. Ethyl acetate showed the better capacity to recover PHAs from cells than butyl acetate. Extraction with ethyl acetate exhibited high recovery yield and purity of 96% and 92%, respectively at 100°C. Effect of non-toxic surfactant such as linear alkylbenzene sulfonic acid (LAS) was also studied at 40, 60 and 80°C, and detergent pH range of 3.0, 5.0, 7.0 and 9.0 for the extraction of PHAs from the cells. LAS gave highest yield of 86% and purity of 88% at temperature 80°C and 5.0 pH.

Keywords: polyhydroxyalkanoates, Cupriavidus necator, extraction, recovery yield

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: N. Z. van Hierden, Q. Yu, F. Gauvin

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Cement manufacturing is, because of its production process, among the highest contributors to CO₂ emissions worldwide. As cement is one of the major components in 3D printed concrete, achieving sustainability and carbon neutrality can be particularly challenging. To improve the sustainability of 3D printed materials, different CO₂-reducing strategies can be used, each one with a distinct level of impact and complexity. In this work, we focus on the development of these sustainable mixtures and finding alternatives. Promising alternatives for cement and clinker replacement include the use of recycled building materials, amongst which (calcined) bricks and roof tiles. To study the potential of recycled clay-based building materials, the application of calcinated clay itself is studied as well. Compared to cement, the calcination temperature of clay-based materials is significantly lower, resulting in reduced CO₂ output. Reusing these materials is therefore a promising solution for utilizing waste streams while simultaneously reducing the cement content in 3D concrete mixtures. In addition, waste streams can be locally sourced, thereby reducing the emitted CO₂ during transportation. In this research, various alternative binders are examined, such as calcined clay blends (LC3) from recycled tiles and bricks, or locally obtained clay resources. Using various experiments, a high potential for mix designs including these resources has been shown with respect to material strength, while sustaining decent printability and buildability. Therefore, the defined strategies are promising and can lead to a more sustainable, low-CO₂ mixture suitable for 3D printing while using accessible materials.

Keywords: cement replacement, 3DPC, circular building materials, calcined clay, CO₂ reduction

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Authors: Muna Al-Tarshi, Dobretsov Sergey, Wenresti Gallardo

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Marine litter pollution is a global concern that has wide-ranging ecological, societal, and economic implications, along with potential health risks for humans. In Oman, inadequate solid waste management has led to the accumulation of litter in mangrove ecosystems. However, there is a dearth of information on marine litter and microplastic pollution in Omani mangroves, impeding the formulation of effective mitigation strategies. To address this knowledge gap, we conducted a comprehensive assessment of marine litter and microplastics in mangrove sediments in the Sea of Oman. Our study measured the average abundance of marine litter, which ranged from 0.83±1.03 to 19.42±8.52 items/m2. Notably, plastics constituted the majority of litter, accounting for 73-96% of all items, with soft plastics being the most prevalent. Furthermore, we investigated microplastic concentrations in the sediments, finding levels ranging from 6 to 256 pieces /kg. Among the studied areas, afforested mangroves in Al-Sawadi exhibited the highest average abundance of microplastics (27.52±5.32 pieces/ kg), while the Marine Protected Area Al Qurum had the lowest average abundance (0.60±1.12 pieces /kg). These findings significantly contribute to our understanding of marine litter and microplastic pollution in Omani mangroves. They provide valuable baseline data for future monitoring initiatives and the development of targeted management strategies. Urgent action is needed to implement effective waste management practices and interventions to protect the ecological integrity of mangrove ecosystems in Oman and mitigate the risks associated with marine litter and microplastics.

Keywords: microplastics, anthropogenic marine litter, ftir, polymer, khawr, mangrove, sediment

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Authors: Abdul Wahed Al Zumor

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Saudi EFL Students majoring in English face difficulties in academic lectures listening comprehension in content courses like linguistics, applied linguistics or literature theories. To validate this assumption, a questionnaire assessing students' lecture comprehension experience was administered. The findings have shown that Saudi EFL learners face a great challenge in lecture comprehension at advanced levels. Literature has suggested a myriad of techniques which can enhance academic lecture comprehension. This study has used "reciprocal peer-questioning and responding technique" as an integral part of the academic lecture occupying the last ten minutes. Improvement in experimental students' scores in these courses has been noticed.

Keywords: EFL learners, lecture comprehension, content courses, peer questioning

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Authors: Sandra Hartl, Meena Chavan

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This paper presents the outcome of a four year Ph.D. research on cross-cultural conflict management in transnational business relationships. An important and complex problem about managing conflicts that arise across cultures in business relationships is investigated, and conflict resolution strategies are identified. This paper particularly focuses on transnational relationships within a Chinese, German and Middle Eastern framework. Unlike many papers on this issue which have been built on experiments with international MBA students, this research provides real-life cases of cross-cultural conflicts which are not easy to capture. Its uniqueness is underpinned as the real case data was gathered by interviewing top executives at management positions in large multinational corporations through a qualitative case study method approach. This paper makes a valuable contribution to the theory of cross-cultural conflicts, and despite the sensitivity, this research primarily presents real-time business data about breaches of contracts between two counterparties engaged in transnational operating organizations. The overarching aim of this research is to identify the degree of significance for the cultural factors and the communication factors embedded in cross-cultural business conflicts. It questions from a cultural perspective what factors lead to the conflicts in each of the cases, what the causes are and the role of culture in identifying effective strategies for resolving international disputes in an increasingly globalized business world. The results of 20 face to face interviews are outlined, which were conducted, recorded, transcribed and then analyzed using the NVIVO qualitative data analysis system. The outcomes make evident that the factors leading to conflicts are broadly organized under seven themes, which are communication, cultural difference, environmental issues, work structures, knowledge and skills, cultural anxiety and personal characteristics. When evaluating the causes of the conflict it is to notice that these are rather multidimensional. Irrespective of the conflict types (relationship or task-based conflict or due to individual personal differences), relationships are almost always an element of all conflicts. Cultural differences, which are a critical factor for conflicts, result from different cultures placing different levels of importance on relationships. Communication issues which are another cause of conflict also reflect different relationships styles favored by different cultures. In identifying effective strategies for solving cross-cultural business conflicts this research identifies that solutions need to consider the national cultures (country specific characteristics), organizational cultures and individual culture, of the persons engaged in the conflict and how these are interlinked to each other. Outcomes identify practical dispute resolution strategies to resolve cross-cultural business conflicts in reference to communication, empathy and training to improve cultural understanding and cultural competence, through the use of mediation. To conclude, the findings of this research will not only add value to academic knowledge of cross-cultural conflict management across transnational businesses but will also add value to numerous cross-border business relationships worldwide. Above all it identifies the influence of cultures and communication and cross-cultural competence in reducing cross-cultural business conflicts in transnational business.

Keywords: business conflict, conflict management, cross-cultural communication, dispute resolution

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Authors: Hortènsia Curell, Ana Fernández-Montraveta

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This paper presents the creation, development, and analysis of a corpus designed to study the presence of attitude markers and author’s stance in research articles in two different areas of linguistics (theoretical linguistics and sociolinguistics). These two disciplines are expected to behave differently in this respect, given the disparity in their discursive conventions. Attitude markers in this work are understood as the linguistic elements (adjectives, nouns and verbs) used to convey the writer's stance towards the content presented in the article, and are crucial in understanding writer-reader interaction and the writer's position. These attitude markers are divided into three broad classes: assessment, significance, and emotion. In addition to them, we also consider first-person singular and plural pronouns and possessives, modal verbs, and passive constructions, which are other linguistic elements expressing the author’s stance. The corpus, Corpus of Attitude in Academic Writing (CAAW), comprises a collection of 21 articles, collected from six journals indexed in JCR. These articles were originally written in English by a single native-speaker author from the UK or USA and were published between 2022 and 2023. The total number of words in the corpus is approximately 222,400, with 106,422 from theoretical linguistics (Lingua, Linguistic Inquiry and Journal of Linguistics) and 116,022 from sociolinguistics journals (International Journal of the Sociology of Language, Language in Society and Journal of Sociolinguistics). Together with the corpus, we present the tool created for the creation and storage of the corpus, along with a tool for automatic annotation. The steps followed in the compilation of the corpus are as follows. First, the articles were selected according to the parameters explained above. Second, they were downloaded and converted to txt format. Finally, examples, direct quotes, section titles and references were eliminated, since they do not involve the author’s stance. The resulting texts were the input for the annotation of the linguistic features related to stance. As for the annotation, two articles (one from each subdiscipline) were annotated manually by the two researchers. An existing list was used as a baseline, and other attitude markers were identified, together with the other elements mentioned above. Once a consensus was reached, the rest of articles were annotated automatically using the tool created for this purpose. The annotated corpus will serve as a resource for scholars working in discourse analysis (both in linguistics and communication) and related fields, since it offers new insights into the expression of attitude. The tools created for the compilation and annotation of the corpus will be useful to study author’s attitude and stance in articles from any academic discipline: new data can be uploaded and the list of markers can be enlarged. Finally, the tool can be expanded to other languages, which will allow cross-linguistic studies of author’s stance.

Keywords: academic writing, attitude, corpus, english

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Authors: Hope Amba Neji

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The study adopted a quasi-experimental design. Two schools were used for the experimental study, while one school was used for the control. The experimental groups were subjected to treatment for four weeks with chemistry museum artifacts and a visit as made to the museum so that learners would have real-life learning experiences with museum resources, while the control group was taught with the conventional method. The instrument for the study was a 20-item Chemistry Memory Test (CMT) and a 10-item Chemistry Interest Questionnaire (CIQ). The reliability was ascertained using (KR-20) and alpha reliability coefficient, which yielded a reliability coefficient of .83 and .81, respectively. Data obtained was analyzed using Analysis of Covariance (ANCOVA) and Analysis of variance (ANOVA) at 0.05 level of significance. Findings revealed that museum artifacts have a significant effect on students’ memory enhancement and interest in chemistry. It was recommended chemistry learning should be enhanced, motivating and real with museum artifacts, which significantly aid memory enhancement and interest in chemistry.

Keywords: museum artifacts, memory, chemistry, atitude

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Nien-Ming Hong, Kuei-Fang Huang

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Climate change is an important issue in future, which seriously affects water resources for a long term planning and management. Flood assessment is highly related with climate and land use. Increasing rainfall and urbanization will induce the inundated area in future. For adapting the impacts of climate change, a land use planning is a good strategy for reducing flood damage. The study is to build a trade-off process with different land use types. The Ta-Liao watershed is the study area with three types of land uses that are build-up, farm and forest. The build-up area is concentrated in the downstream of the watershed. Different rainfall amounts are applied for assessing the land use in 1996, 2005 and 2013. The adapted strategies are based on retarding the development of urban and a trade-off process. When a land changes from farm area to built-up area in downstream, this study is to search for a farm area and change it to forest/grass area or building a retention area in the upstream. For assessing the effects of the strategy, the inundation area is simulated by the Flo-2D model with different rainfall conditions and land uses. The results show inundation maps of several cases with land use change planning. The results also show the trade-off strategies and retention areas can decrease the inundated area and divide the inundated area, which are better than retarding urban development. The land use change is usually non-reverse and the planning should be constructed before the climate change.

Keywords: climate change, land use change, flood risk assessment, land use planning

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Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

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Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

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Authors: Michael Wendland

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This paper presents a framework to teach a methodical design approach by the help of using a mixture of game-based learning, design challenges and competitions as forms of direct assessment. In today’s world, developing products is more complex than ever. Conflicting goals of product cost and quality with limited time as well as post-pandemic part shortages increase the difficulty. Common design approaches for mechatronic products mitigate some of these effects by helping the users with their methodical framework. Due to the inherent complexity of these products, the number of involved resources and the comprehensive design processes, students very rarely have enough time or motivation to experience a complete approach in one semester course. But, for students to be successful in the industrial world, it is crucial to know these methodical frameworks and to gain first-hand experience. Therefore, it is necessary to teach these design approaches in a real-world setting and keep the motivation high as well as learning to manage upcoming problems. This is achieved by using a game-based approach and a set of design challenges that are given to the students. In order to mimic industrial collaboration, they work in teams of up to six participants and are given the main development target to design a remote-controlled robot that can manipulate a specified object. By setting this clear goal without a given solution path, a constricted time-frame and limited maximal cost, the students are subjected to similar boundary conditions as in the real world. They must follow the methodical approach steps by specifying requirements, conceptualizing their ideas, drafting, designing, manufacturing and building a prototype using rapid prototyping. At the end of the course, the prototypes will be entered into a contest against the other teams. The complete design process is accompanied by theoretical input via lectures which is immediately transferred by the students to their own design problem in practical sessions. To increase motivation in these sessions, a playful learning approach has been chosen, i.e. designing the first concepts is supported by using lego construction kits. After each challenge, mandatory online quizzes help to deepen the acquired knowledge of the students and badges are awarded to those who complete a quiz, resulting in higher motivation and a level-up on a fictional leaderboard. The final contest is held in presence and involves all teams with their functional prototypes that now need to contest against each other. Prices for the best mechanical design, the most innovative approach and for the winner of the robotic contest are awarded. Each robot design gets evaluated with regards to the specified requirements and partial grades are derived from the results. This paper concludes with a critical review of the proposed framework, the game-based approach for the designed prototypes, the reality of the boundary conditions, the problems that occurred during the design and manufacturing process, the experiences and feedback of the students and the effectiveness of their collaboration as well as a discussion of the potential transfer to other educational areas.

Keywords: design challenges, game-based learning, playful learning, methodical framework, mechatronics, student assessment, constructive alignment

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Authors: Mustafa Arikan, Ibrahim Ercan

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In this paper, protection of program formats was investigated in terms of program formats. Protection of program formats was studied in the French Law in the sense of competition law and CPI. Since the English Judicial system exhibits differences from the legal system of Continental Europe, its investigation bears a special significance. The subject was also handled in German Law at length. Indeed, German Law was investigated in detail within the overall framework of the study. Here, the court decisions in the German Law and the views in the doctrine were expressed in general. There are many court decisions in the American legal system concerning the subject. These decisions also present alternatives in terms of a solution to the problem.

Keywords: comparative law, protection of television programme formats, intellectual property, american legal system

Procedia PDF Downloads 314

Authors: Camille Perréard, Yoann Ladner, Fanny D'Orlyé, Stéphanie Descroix, Vélan Taniga, Anne Varenne, Cédric Guyon, Michael. Tatoulian, Frédéric Kanoufi, Cyrine Slim, Sophie Griveau, Fethi Bedioui

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The development of micro total analysis systems is of major interest for contaminant and biomarker analysis. As a lab-on-chip integrates all steps of an analysis procedure in a single device, analysis can be performed in an automated format with reduced time and cost, while maintaining performances comparable to those of conventional chromatographic systems. Moreover, these miniaturized systems are either compatible with field work or glovebox manipulations. This work is aimed at developing an analytical microsystem for trace and ultra trace quantitation in complex matrices. The strategy consists in the integration of a sample pretreatment step within the lab-on-chip by a confinement zone where selective ligands are immobilized for target extraction and preconcentration. Aptamers were chosen as selective ligands, because of their high affinity for all types of targets (from small ions to viruses and cells) and their ease of synthesis and functionalization. This integrated target extraction and concentration step will be followed in the microdevice by an electrokinetic separation step and an on-line detection. Polymers consisting of cyclic olefin copolymer (COC) or fluoropolymer (Dyneon THV) were selected as they are easy to mold, transparent in UV-visible and have high resistance towards solvents and extreme pH conditions. However, because of their low chemical reactivity, surface treatments are necessary. For the design of this miniaturized diagnostics, we aimed at modifying the microfluidic system at two scales : (1) on the entire surface of the microsystem to control the surface hydrophobicity (so as to avoid any sample wall adsorption) and the fluid flows during electrokinetic separation, or (2) locally so as to immobilize selective ligands (aptamers) on restricted areas for target extraction and preconcentration. We developed different novel strategies for the surface functionalization of COC and Dyneon, based on plasma, chemical and /or electrochemical approaches. In a first approach, a plasma-induced immobilization of brominated derivatives was performed on the entire surface. Further substitution of the bromine by an azide functional group led to covalent immobilization of ligands through “click” chemistry reaction between azides and terminal alkynes. COC and Dyneon materials were characterized at each step of the surface functionalization procedure by various complementary techniques to evaluate the quality and homogeneity of the functionalization (contact angle, XPS, ATR). With the objective of local (micrometric scale) aptamer immobilization, we developed an original electrochemical strategy on engraved Dyneon THV microchannel. Through local electrochemical carbonization followed by adsorption of azide-bearing diazonium moieties and covalent linkage of alkyne-bearing aptamers through click chemistry reaction, typical dimensions of immobilization zones reached the 50 µm range. Other functionalization strategies, such as sol-gel encapsulation of aptamers, are currently investigated and may also be suitable for the development of the analytical microdevice. The development of these functionalization strategies is the first crucial step in the design of the entire microdevice. These strategies allow the grafting of a large number of molecules for the development of new analytical tools in various domains like environment or healthcare.

Keywords: alkyne-azide click chemistry (CuAAC), electrochemical modification, microsystem, plasma bromination, surface functionalization, thermoplastic polymers

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Rena Upitis, Philip C. Abrami, Karen Boese

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The success of one-on-one music study relies heavily on the ability of the teacher to provide sufficient direction to students during weekly lessons so that they can successfully practice from one lesson to the next. Traditionally, these instructions are given in a paper notebook, where the teacher makes notes for the students after describing a task or demonstrating a technique. The ability of students to make sense of these notes varies according to their understanding of the teacher’s directions, their motivation to practice, their memory of the lesson, and their abilities to self-regulate. At best, the notes enable the student to progress successfully. At worst, the student is left rudderless until the next lesson takes place. Digital notebooks have the potential to provide a more interactive and effective bridge between music lessons than traditional pen-and-paper notebooks. One such digital notebook, Cadenza, was designed to streamline and improve teachers’ instruction, to enhance student practicing, and to provide the means for teachers and students to communicate between lessons. For example, Cadenza contains a video annotator, where teachers can offer real-time guidance on uploaded student performances. Using the checklist feature, teachers and students negotiate the frequency and type of practice during the lesson, which the student can then access during subsequent practice sessions. Following the tenets of self-regulated learning, goal setting and reflection are also featured. Accordingly, the present paper addressed the following research questions: (1) How does the use of the Cadenza digital music notebook engage students and their teachers?, (2) Which features of Cadenza are most successful?, (3) Which features could be improved?, and (4) Is student learning and motivation enhanced with the use of the Cadenza digital music notebook? The paper describes the results 10 months of field-testing of Cadenza, structured around the four research questions outlined. Six teachers and 65 students took part in the study. Data were collected through video-recorded lesson observations, digital screen captures, surveys, and interviews. Standard qualitative protocols for coding results and identifying themes were employed to analyze the results. The results consistently indicated that teachers and students embraced the digital platform offered by Cadenza. The practice log and timer, the real-time annotation tool, the checklists, the lesson summaries, and the commenting features were found to be the most valuable functions, by students and teachers alike. Teachers also reported that students progressed more quickly with Cadenza, and received higher results in examinations than those students who were not using Cadenza. Teachers identified modifications to Cadenza that would make it an even more powerful way to support student learning. These modifications, once implemented, will move the tool well past its traditional notebook uses to new ways of motivating students to practise between lessons and to communicate with teachers about their learning. Improvements to the tool called for by the teachers included the ability to duplicate archived lessons, allowing for split screen viewing, and adding goal setting to the teacher window. In the concluding section, proposed modifications and their implications for self-regulated learning are discussed.

Keywords: digital music technologies, electronic notebooks, self-regulated learning, studio music instruction

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Authors: Deepika Sudevan, Patrick Rozycki, Laurent Gornet

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This paper presents the experimental identification of the fatigue limit for pristine and impacted Carbon Fiber Reinforced Epoxy polymer (CFRP) woven composites based on the relatively new self-heating methodology for composites. CFRP composites of [0/90]8 and quasi isotropic configurations prepared using hand-layup technique are subjected to low energy impacts (20 J energy) simulating a barely visible impact damage (BVID). Runway debris strike, tool drop or hailstone impact can cause a BVID on an aircraft fuselage made of carbon composites and hence understanding the post-impact fatigue response of CFRP laminates is of immense importance to the aerospace community. The BVID zone on the specimens is characterized using X-ray Tomography technique. Both pristine and impacted specimens are subjected to several blocks of constant amplitude (CA) fatigue loading keeping R-ratio a constant but with increments in the mean loading stress after each block. The number of loading cycles in each block is a subjective parameter and it varies for pristine and impacted CFRP specimens. To monitor the temperature evolution during fatigue loading, thermocouples are pasted on the CFRP specimens at specific locations. The fatigue limit is determined by two strategies, first is by considering the stabilized temperature in every block and second is by considering the change in the temperature slope per block. The results show that both strategies can be adopted to determine the fatigue limit in both pristine and impacted CFRP composites.

Keywords: CFRP, fatigue limit, low energy impact, self-heating, WRM

Procedia PDF Downloads 218