Search results for: learning vocabulary

Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Qi Wang

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Accurate pronunciation is the first condition of communication. Compared with the alphabetic languages, Chinese is more difficult for the foreigners to study as a second language, due to the tonal language with the meaningful characters as the written system, especially speaking. This research first presents the statistics of the typical errors of the pronunciations, based on the data of our two- year program of graduate students, which shown 90% of their speaking with strong foreign accents and no obvious change of the pitches, even if they could speak Chinese fluently. Second part, analyzed the caused reasons in the learning and teaching processes. Third part, this result of this research, based the theory of Chinese prosodic words, shown that the earlier the students get trained on prosodics at the beginning and suprasegmentals at intermediate and advanced levels, the better effects for them to communicate in Chinese as a second language.

Keywords: second language, prosodic word, foot, suprasegmental

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Authors: Chananporn Areekul

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The purpose of this study was to study the experimental result of using board games for enhancing the active citizen of the undergraduate students. The research methodology of this study was the quasi experimental research. The sample was 30 undergraduate students that were chosen by the purposive sampling. The instruments were board games for enhancing the active citizen and the questionnaire for measuring the active citizen levels. The result of the mean difference test was found that there were statistically significant differences at the .05 level (t = 2.028, p = 0.047) between before and after using board game for enhancing the active citizen of undergraduate students.

Keywords: active citizen, board game, learning innovation, undergraduate students

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Authors: Yi-ju Ariel Wu

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Exploring The Effects of Immersive Virtual Reality on Increasing Willingness to Communicate, Oral Performance, and Reducing Speaking Anxiety for EFL Elementary Students from Taiwan

Keywords: Immersive Virtual Reality, EFL speaking, situated learning, pragmatics

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Authors: Juha Kettunen

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This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

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Authors: Ayşe Eldem, Fatih Başçiftçi

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Braille alphabet is an important tool that enables visually impaired individuals to have a comfortable life like those who have normal vision. For this reason, new applications related to the Braille alphabet are being developed. In this study, a new Refreshable Braille Display was developed to help visually impaired individuals learn the Braille alphabet easier. By means of this system, any text downloaded on a computer can be read by the visually impaired individual at that moment by feeling it by his/her hands. Through this electronic device, it was aimed to make learning the Braille alphabet easier for visually impaired individuals with whom the necessary tests were conducted.

Keywords: visually impaired individual, Braille, Braille display, refreshable Braille display, USB

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Areej R. Banjar, Abraham G. Campbell

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The use of Mixed Reality (MR) in teaching and training is growing popular and can improve students’ ability to perform technical procedures. This short paper outlines the creation of an interactive educational MR 3D application that aims to improve the quality of instruction for dentistry students. This application is called MRImplantology and aims to teach the fundamentals and preoperative planning of dental implant placement. MRImplantology uses cone-beam computed tomography (CBCT) images as the source for 3D dental models that dentistry students will be able to freely manipulate within a 3D MR world to aid their learning process.

Keywords: augmented reality, education, dentistry, cone-beam computed tomography CBCT, head mounted display HMD, mixed reality

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Authors: R. Bhagwan, M. Subbhan

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Nursing is a very challenging field in South Africa and due to the burden of disease it is critical that nursing students are prepared with the adequate knowledge and skills to deliver effective patient care. Despite this very little research has been done on the teaching strategies used by nurse educators to teach nursing students. It is in this context that a survey of all nurse educators at Nursing Colleges and Universities in Kwa-Zulu Natal was undertaken (n=300) to explore what current pedagogical strategies were being used and which more creative methodologies should be implemented in relation to specific nursing content. Findings revealed that most nurse educators still utlize the lecture approach, but although believe other methodologies such as e-learning are important have not done so because of inadequate training. The recommendations made are that more creative pedagogical strategies such as simultation, portfoloios and case studies be adopted.

Keywords: creative, teaching methodologies, dydactic, nursing

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: mathematics, motivation, secondary school, student, practical problem

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Authors: Ramin Javadzadeh

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The particle swarm optimization are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Particle swarm optimization is introduced for the first time to overcome its problems. The fuzzy cellular automata is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the Particle swarm optimization algorithms.

Keywords: cellular automata, cellular learning automata, local search, optimization, particle swarm optimization

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Yuqing Zou, Chunrui Zou, Yichong Cao

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Previous research has revealed relationships between self-efficacy (SE), engagement, and academic achievement among students in Western countries, but these relationships remain unknown in college math courses among college students in China. In addition, previous research has shown that test anxiety has a direct effect on engagement and academic achievement. However, how test anxiety affects the relationships between SE, engagement, and academic achievement is still unknown. In this study, the authors aimed to explore the mediating roles of behavioral engagement (BE), emotional engagement (EE), and cognitive engagement (CE) in the association between SE and academic achievement and the moderating role of test anxiety in college math courses. Our hypotheses are that the association between SE and academic achievement was mediated by engagement and that test anxiety played a moderating role in the association. To explore the research questions, the authors collected data through self-reported surveys among 147 students at a northwestern university in China. Self-reported surveys were used to collect data. The motivated strategies for learning questionnaire (MSLQ) (Pintrich, 1991), the metacognitive strategies questionnaire (Wolters, 2004), and the engagement versus disaffection with learning scale (Skinner et al., 2008) were used to assess SE, CE, and BE and EE, respectively. R software was used to analyze the data. The main analyses used were reliability and validity analysis of scales, descriptive statistics analysis of measured variables, correlation analysis, regression analysis, and structural equation modeling (SEM) analysis and moderated mediation analysis to look at the structural relationships between variables at the same time. The SEM analysis indicated that student SE was positively related to BE, EE, and CE and academic achievement. BE, EE, and CE were all positively associated with academic achievement. That is, as the authors expected, higher levels of SE led to higher levels of BE, EE, and CE, and greater academic achievement. Higher levels of BE, EE, and CE led to greater academic achievement. In addition, the moderated mediation analysis found that the path of SE to academic achievement in the model was as significant as expected, as was the moderating effect of test anxiety in the SE-Achievement association. Specifically, test anxiety was found to moderate the association between SE and BE, the association between SE and CE, and the association between EE and Achievement. The authors investigated possible mediating effects of BE, EE, and CE in the associations between SE and academic achievement, and all indirect effects were found to be significant. As for the magnitude of mediations, behavioral engagement was the most important mediator in the SE-Achievement association. This study has implications for college teachers, educators, and students in China regarding ways to promote academic achievement in college math courses, including increasing self-efficacy and engagement and lessening test anxiety toward math.

Keywords: academic engagement, self-efficacy, test anxiety, academic achievement, college math courses, behavioral engagement, cognitive engagement, emotional engagement

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Authors: Alhanouf Alharbi, Wafa Alotaibi

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This study aims to analyse students’ and teachers’ perceptions of using Plickers as a formative assessment tool in EFL classrooms. The study implements a mixed methods approach. First, a questionnaire was administered to 64 students from two schools in Almadinah, a Saudi city. Then, in structured interviews, two English teachers provided their opinions on the advantages and disadvantages of integrating Plickers into their classrooms. The findings reveal that both teachers and students believe that using Plickers positively impacts students’ learning. Moreover, the findings encourage teachers to integrate technology-based formative assessments in EFL classrooms. However, there are some drawbacks to using Plickers, such as technological issues. Finally, English teachers are recommended to engage all their students in a daily formative assessment by implementing Plickers in their classes.

Keywords: plickers, formative assessment, technology, students, EFL classroom

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Authors: R. Vishalakshi, P. Chaithra, M. Dakshayini

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An engineering degree is not a ticket that automatically provides a job. The competition for good jobs is going steep as the global economy and outsourcing is increasing. It is not sufficient to be simply more qualified. In this competitive world, it is important to stand out from everyone else. Going to college and getting a degree is the foremost important step. At the same time, students should be competent enough to face this technically growing and challenging world. So the classroom learning can be greatly enhanced by working with real-time applications. In this paper, we discuss how it can be realized by getting internships with the companies, where students actually get an opportunity to work in real work environment with live problems along with co-workers. Also presents case studies of how the practical industry work experience helps them in constructing their future carrier path.

Keywords: real work environment, industry work experience, internship, college students

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Authors: Georgia H. Mega

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Art street, a category of artwork displayed in public spaces, has been recognized as a potential tool for promoting reflective thinking in both adult and primary education. Educational techniques that encourage critical and creative thinking, as well as deeper reflection, have been developed and applied in educational curricula. This paper aims to explore the potential of art street in cultivating learners' reflective awareness toward multiculturalism. The main objective of this case study is to investigate the possibilities that art street offers in terms of developing learners' critical reflection, regardless of their age. The study compares two art street works from Greece and Norway, focusing on their common theme of multiculturalism. The study adopts a qualitative methodology, specifically a case study approach. This approach allows for an in-depth analysis of the two selected art street works and their impact on learners' reflective thinking. The study demonstrates that art street can effectively cultivate learners' reflective awareness of multiculturalism. The selected works of art, despite being created by different artists and displayed in different cities, share similar content and convey messages that facilitate reflective dialogue on cultural osmosis. Both adult and primary education approaches utilize the same art street works to achieve reflective awareness. This paper contributes to the existing literature on reflective learning processes by highlighting the potential of art street as a means for encouraging reflective thinking. It builds upon the theoretical frameworks of adult education theorists such as Freire and Mezirow, as well as those of primary education theorists such as Perkins and Project Zero. Data for this study were collected through observation and analysis of two art street works, one from Greece and one from Norway. These works were selected based on their common theme of multiculturalism. Analysis Procedures: The collected data were analyzed using qualitative analysis techniques. The researchers examined the content and messages conveyed by the selected art street works and explored their impact on learners' reflective thinking. The central question addressed in this study is whether art street can develop learners' critical reflection toward multiculturalism, regardless of their age. The findings of this study support the notion that art street can effectively cultivate learners' reflective awareness toward multiculturalism. The selected art street works, despite their differences in origin and location, share common themes that encourage reflective dialogue. The use of art street in both adult and primary education approaches showcases its potential as a tool for promoting reflective learning processes. Overall, this paper contributes to the understanding of art street as a means for reflective thinking in the field of adult and primary education.

Keywords: art street, educational techniques, multiculturalism, observation of artworks, reflective awareness

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Authors: Diogo Santos, Nelson Zagalo, Carla Morais

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No Man’s Sky (NMS) is a sci-fi video game about survival and exploration where players fly spaceships, search for elements, and use them to survive. NMS isn’t a serious game, and not all the science in the game is presented with scientific evidence. To find how players felt about the scientific content in the game and how they perceive the chemistry in it, a survey was sent to NMS’s players, from which were collected answers from 124 respondents from 23 countries. Chemophobia is still a phenomenon when chemistry or chemicals are a subject of discussion, but 68,9% of our respondents showed a positive attitude towards the presence of chemistry in NMS, with 57% stating that playing the video game motivated them to know more about science. 8% of the players stated that NMS often prompted conversations about the science in the video game between them and teachers, parents, or friends. These results give us ideas on how an entertainment game can potentially help scientists, educators, and science communicators reach a growing, evolving, vibrant, diverse, and demanding audience.

Keywords: digital games, science communication, chemistry, informal learning, No Man’s Sky

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Authors: Lisa Gray, Henry Kronner, Tameca Harris-Jackson, Mimi Sodhi, Ruth Gerritsen-McKane, Donette Considine

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The MSW Peer Mentorship Program (PMP) was developed as one of several approaches to foster student success. The key purposes of the PMP are to help new graduate students transition to a graduate program, facilitate relationship building between students, grow and sustain student satisfaction, and build a strong connection to the MSW program. This pilot program also serves as an additional source of support for students during the era of the Covid-19 pandemic. Further, the long-term goals of the program are to assist in student retention. Preliminary findings suggest that both mentors and mentees enrolled in PMP find the peer mentoring relationship to have a positive impact on their graduate learning experience.

Keywords: covid-19, mentorship, peer support, student success

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Authors: Stephanie Remedios, Linda Veronica Rios

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Background. Pediatric obesity is a serious health problem linked to multiple physical diseases and ailments, including diabetes, heart disease, and joint issues. While research has shown pediatric obesity can bring about an array of physical illnesses, it is less known how such a condition can affect children’s cognitive development. With childhood overweight and obesity prevalence rates on the rise, it is essential to understand the scope of their cognitive consequences. The present review of the literature tested the hypothesis that poor physical health, such as childhood obesity or malnutrition, negatively impacts a child’s cognitive development. Methodology. A systematic review was conducted to determine the relationship between poor physical health and lower cognitive functioning in children ages 4-16. Electronic databases were searched for studies dating back to ten years. The following databases were used: Science Direct, FIU Libraries, and Google Scholar. Inclusion criteria consisted of peer-reviewed academic articles written in English from 2012 to 2022 that analyzed the relationship between childhood malnutrition and obesity on cognitive development. A total of 17,000 articles were obtained, of which 16,987 were excluded for not addressing the cognitive implications exclusively. Of the acquired articles, 13 were retained. Results. Research suggested a significant connection between diet and cognitive development. Both diet and physical activity are strongly correlated with higher cognitive functioning. Cognitive domains explored in this work included learning, memory, attention, inhibition, and impulsivity. IQ scores were also considered objective representations of overall cognitive performance. Studies showed physical activity benefits cognitive development, primarily for executive functioning and language development. Additionally, children suffering from pediatric obesity or malnutrition were found to score 3-10 points lower in IQ scores when compared to healthy, same-aged children. Conclusion. This review provides evidence that the presence of physical activity and overall physical health, including appropriate diet and nutritional intake, has beneficial effects on cognitive outcomes. The primary conclusion from this research is that childhood obesity and malnutrition show detrimental effects on cognitive development in children, primarily with learning outcomes. Assuming childhood obesity and malnutrition rates continue their current trade, it is essential to understand the complete physical and psychological implications of obesity and malnutrition in pediatric populations. Given the limitations encountered through our research, further studies are needed to evaluate the areas of cognition affected during childhood.

Keywords: childhood malnutrition, childhood obesity, cognitive development, cognitive functioning

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Authors: Shan-Ken Chine

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This research aims to a one-year course run of String Music Appreciation, an international online course launched on the British open education platform. It explains how to present music teaching videos with three main features. They are music lesson explanations, instrumental playing demonstrations, and live music performances. The plan of this course is with four major themes and a total of 97 steps. In addition, the paper also uses the testing data provided by the education platform to analyze the performance of learners and to understand the operation of the course. It contains three test data in the statistics dashboard. They are course-run measures, total statistics, and statistics by week. The paper ends with a review of the course's star rating in this one-year run. The result of this course run will be adjusted when it starts again in the future.

Keywords: music online courses, MOOCs, ubiquitous learning, string music, general music education

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Authors: Chuang-Chun Chiou

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In this study, a systematic framework of graceful ageing has been used to explore the possible human resource utilization models for graceful ageing purpose. This framework is based on the Chinese culture. We call ‘Nine-old’ target. They are ageing gracefully with feeding, accomplishment, usefulness, learning, entertainment, care, protection, dignity, and termination. This study is focused on two areas: accomplishment and usefulness. We exam the current practices of initiatives and laws of promoting labor participation. That is to focus on how to increase Labor Force Participation Rate of the middle aged as well as the elderly and try to promote the elderly to achieve graceful ageing. Then we present the possible models that support graceful ageing.

Keywords: human resource utilization model, labor participation, graceful ageing, employment

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Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Kerryn Burgoyne

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Statement of the Problem: Women who suffer mental health issues, because of Autism Spectrum Disorder has a significant impact on their lives, especially if they’ve been bullied or discriminated against for the majority of their lives. Autism can impact one's mental health in many ways (child like behaviour), social anxieties or overload. The impact of mental health can also be experienced when the person does not have a good quality of life for themselves (eg employment, independent living skills), or have support from family/friends/society). Mental health issues were also suffered during COVID 19 Lockdown here in Melbourne Australia. It was stated by the Government at the time that people weren’t allowed to travel more than 5 km outside of their residential areas to prevent the spread of COVID to others. Medical appointments were an exception. Kerryn/KTalk will be doing a paper on this topic for the conference if accepted by the committee.

Keywords: Autism, mental health, living & learning, KTalk

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Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: aspect oriented programming, AspectJ, aspects, JU-nit, software testing

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Authors: Jezza Mae T. Francisco, Marianet R. Delos Santos, Crisjame C. Toribio

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This study aims to determine the reading preference for English enrichment and reading comprehension among primary students and the difference in the reading preference and comprehension for English enrichment among primary students. This study employed a Descriptive-Quantitative Correlational Research Design. This study yielded the following findings: (1) It reveals that primary students got fair on their reading comprehension, and (2) It shows that there is no significant relationship between the reading preference for English enrichment and reading comprehension of the students. It is safe to conclude that the students’ reading preference is growing evidently in various milieus. This can inform the English department curriculum planners to consider their students’ text preferences that interest them to maximize engagement within a dynamic interactive learning process.

Keywords: reading preferences, reading comprehension, primary student, English enrichment

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Authors: Mohsen Bahrami, Banafsheh Nikmehr, Yueqiang Song, Anuradha Koduru, Ayse K. Vuruskan, Hongkun Lu, Tamer M. Yalcinkaya

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In recent years, we have witnessed an explosion of studies aimed at using a combination of artificial intelligence (AI) and time-lapse imaging data on embryos to improve IVF outcomes. However, despite promising results, no study has used a matched cohort of transferred embryos which only differ in pregnancy outcome, i.e., embryos from a single clinic which are similar in parameters, such as: morphokinetic condition, patient age, and overall clinic and lab performance. Here, we used time-lapse data on embryos with known pregnancy outcomes to see if the rich spatiotemporal information embedded in this data would allow the prediction of the pregnancy outcome regardless of such critical parameters. Methodology—We did a retrospective analysis of time-lapse data from our IVF clinic utilizing Embryoscope 100% of the time for embryo culture to blastocyst stage with known clinical outcomes, including live birth vs nonpregnant (embryos with spontaneous abortion outcomes were excluded). We used time-lapse data from 200 elective single transfer embryos randomly selected from January 2019 to June 2021. Our sample included 100 embryos in each group with no significant difference in patient age (P=0.9550) and morphokinetic scores (P=0.4032). Data from all patients were combined to make a 4th order tensor, and feature extraction were subsequently carried out by a tensor decomposition methodology. The features were then used in a machine learning classifier to classify the two groups. Major Findings—The performance of the model was evaluated using 100 random subsampling cross validation (train (80%) - test (20%)). The prediction accuracy, averaged across 100 permutations, exceeded 80%. We also did a random grouping analysis, in which labels (live birth, nonpregnant) were randomly assigned to embryos, which yielded 50% accuracy. Conclusion—The high accuracy in the main analysis and the low accuracy in random grouping analysis suggest a consistent spatiotemporal pattern which is associated with pregnancy outcomes, regardless of patient age and embryo morphokinetic condition, and beyond already known parameters, such as: early cleavage or early blastulation. Despite small samples size, this ongoing analysis is the first to show the potential of AI methods in capturing the complex morphokinetic changes embedded in embryo time-lapse data, which contribute to successful pregnancy outcomes, regardless of already known parameters. The results on a larger sample size with complementary analysis on prediction of other key outcomes, such as: euploidy and aneuploidy of embryos will be presented at the meeting.

Keywords: IVF, embryo, machine learning, time-lapse imaging data

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Authors: Fadzilah Abdul Rahman

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Emotional development is developed between the parents and their child. Behavioural development is also developed between the parents and their child. Social Development is how parents can help their special needs child to adapt to society and to face challenges. In promoting a lifelong learning mindset, enhancing skill sets and readiness to face challenges, parents would be able to counter balance these challenges during their care giving process and better manage their expectations through understanding the hierarchy of needs modality towards a positive attitude, and in turn, improve their quality of life and participation in society. This paper aims to demonstrate how the hierarchy of needs can be applied in various situations of caregiving for parents with a special needs child.

Keywords: hierarchy of needs, parents, special needs, care-giving

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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