Search results for: virtual case-based learning

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

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Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

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Authors: Yi-Ju Lee

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

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

Procedia PDF Downloads 334

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

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

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

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Authors: Comfort Aina

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

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

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Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi

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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.

Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems

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

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

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

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Authors: Catherine Alex Agbor

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

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

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Authors: Christina Tafadzwa

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

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

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

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

Keywords: algebra, equations, dominoes, serious games

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Authors: Ayat Ayman Abdelaziz Ibrahim Amayem, Hassan Abdel-Salam, Zeyad El-Sayad

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Nowadays, ICTs have spread extensively in everyday life in an unprecedented way. A great attention is paid to the ICTs while ignoring the social aspect. With the immersive invasion of internet as well as smart phones’ applications and digital social networking, people become more socially connected through virtual spaces instead of meeting in physical public spaces. Thus, this paper aims to find the ways of implementing ICTs in public spaces to regain their status as attractive places for people, incite meetings in real life and create sustainable lively city centers. One selected example of urban space in the city center of Alexandria is selected for the study. Alexandria represents a large metropolitan city subjected to rapid transformation. Improving the quality of its public spaces will have great effects on the whole well-being of the city. The major roles that ICTs can play in the public space are: culture and art, education, planning and design, games and entertainment, and information and communication. Based on this classification various examples and proposals of ICTs interventions in public spaces are presented and analyzed to encourage good old fashioned social interaction by creating the New Social Public Place of this Digital Era. The paper will adopt methods such as questionnaire for evaluating the people’s willingness to accept the idea of using ICTs in public spaces, their needs and their proposals for an attractive place; the technique of observation to understand the people behavior and their movement through the space and finally will present an experimental design proposal for the selected urban space. Accordingly, this study will help to find design principles that can be adopted in the design of future public spaces to meet the needs of the digital era’s users with the new concepts of social life respecting the rules of place-making.

Keywords: Alexandria sustainable city center, digital place-making, ICTs, social interaction, social networking, urban places

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Authors: Jiraporn Weenuttranon

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

Keywords: consumer, behavior, bakery, standard deviation

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Authors: Xingyu Gao, Qiang Wu

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

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

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Authors: Jane O`Halloran

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

Keywords: student motivation, CLIL, globalization, demographics

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Authors: Robbi Beyer, Tiffanye Vargas, Margaret Flores

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

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

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Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

Procedia PDF Downloads 382

Authors: H. Hussain, N. H. Mohamad

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

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

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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

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

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Authors: Fotis I. Giasemis, Alexandros Sopasakis

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This study focuses on detecting traffic anomalies using generative models applied to real-time observations. By integrating a Graph Neural Network with an attention-based mechanism within the Spatiotemporal Generative Adversarial Network framework, we enhance the capture of both spatial and temporal dependencies in traffic data. Leveraging minute-by-minute observations from cameras distributed across Gothenburg, our approach provides a more detailed and precise anomaly detection system, effectively capturing the complex topology and dynamics of urban traffic networks.

Keywords: traffic, anomaly detection, GNN, GAN

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Authors: Babesse Saad, Ameddah Djemeleddine

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

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

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Authors: B. Selma

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

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

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

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

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

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Authors: Jun Seung Woo, Shin Dong Ho

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

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

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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

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

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Authors: Rasha Ali Dheyab

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In today's increasingly interconnected and technologically-driven world, communication has evolved beyond traditional verbal exchanges. This paper delves into the fascinating realm of multimodal communication, a dynamic field at the intersection of linguistics, gesture studies, and technology. The study of how humans convey meaning through a combination of spoken language, gestures, facial expressions, and digital platforms has gained prominence as our modes of interaction continue to diversify. This exploration begins by examining the foundational theories in linguistics and gesture studies, tracing their historical development and mutual influences. It further investigates the role of nonverbal cues, such as gestures and facial expressions, in augmenting and sometimes even altering the meanings conveyed by spoken language. Additionally, the paper delves into the modern technological landscape, where emojis, GIFs, and other digital symbols have emerged as new linguistic tools, reshaping the ways in which we communicate and express emotions. The interaction between traditional and digital modes of communication is a central focus of this study. The paper investigates how technology has not only introduced new modes of expression but has also influenced the adaptation of existing linguistic and gestural patterns in online discourse. The emergence of virtual reality and augmented reality environments introduces yet another layer of complexity to multimodal communication, offering new avenues for studying how humans navigate and negotiate meaning in immersive digital spaces. Through a combination of literature review, case studies, and theoretical analysis, this paper seeks to shed light on the intricate interplay between language, gesture, and technology in the realm of multimodal communication. By understanding how these diverse modes of expression intersect and interact, we gain valuable insights into the ever-evolving nature of human communication and its implications for fields ranging from linguistics and psychology to human-computer interaction and digital anthropology.

Keywords: multimodal communication, linguistics ., gesture studies., emojis., verbal communication., digital

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Authors: Yaghoubi N., Moore Z., Van Der Veen S. M., Pidcoe P. E., Thomas J. S., Dexheimer B.

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Optoelectronic 3D motion capture systems, such as the Vicon kinematic system, are widely utilized in biomedical research to track joint motion. These systems are considered powerful and accurate measurement tools with <2 mm average error. However, these systems are costly and may be difficult to implement and utilize in a clinical setting. 3D virtual reality (VR) is gaining popularity as an affordable and accessible tool to investigate motor control and perception in a controlled, immersive environment. The HTC Vive VR system includes puck-style trackers that seamlessly integrate into its VR environments. These affordable, wireless, lightweight trackers may be more feasible for clinical kinematic data collection. However, the accuracy of HTC Vive Trackers (3.0), when compared to optoelectronic 3D motion capture systems, remains unclear. In this preliminary study, we compared the HTC Vive Tracker system to a Vicon kinematic system in a simulated lumbar flexion task. A 6-DOF robot arm (SCORBOT ER VII, Eshed Robotec/RoboGroup, Rosh Ha’Ayin, Israel) completed various reaching movements to mimic increasing levels of hip flexion (15°, 30°, 45°). Light reflective markers, along with one HTC Vive Tracker (3.0), were placed on the rigid segment separating the elbow and shoulder of the robot. We compared position measures simultaneously collected from both systems. Our preliminary analysis shows no significant differences between the Vicon motion capture system and the HTC Vive tracker in the Z axis, regardless of hip flexion. In the X axis, we found no significant differences between the two systems at 15 degrees of hip flexion but minimal differences at 30 and 45 degrees, ranging from .047 cm ± .02 SE (p = .03) at 30 degrees hip flexion to .194 cm ± .024 SE (p < .0001) at 45 degrees of hip flexion. In the Y axis, we found a minimal difference for 15 degrees of hip flexion only (.743 cm ± .275 SE; p = .007). This preliminary analysis shows that the HTC Vive Tracker may be an appropriate, affordable option for gross motor motion capture when the Vicon system is not available, such as in clinical settings. Further research is needed to compare these two motion capture systems in different body poses and for different body segments.

Keywords: lumbar, vivetracker, viconsystem, 3dmotion, ROM

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Authors: Juliane Toce, Steven Holochwost

Abstract:

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

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

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

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

Keywords: concept, framework, group guidance, module development

Procedia PDF Downloads 532

Authors: Steven W. Carruthers

Abstract:

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

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

Procedia PDF Downloads 196

Authors: Konstantina Georgali

Abstract:

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

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

Procedia PDF Downloads 385

Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 149