Search results for: best practices in online learning

Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Amin Salighehdar, Ziwen Ye, Mingzhe Liu, Ionut Florescu, Alan F. Blumberg

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Storm surge is an abnormal water level caused by a storm. Accurate prediction of a storm surge is a challenging problem. Researchers developed various ensemble modeling techniques to combine several individual forecasts to produce an overall presumably better forecast. There exist some simple ensemble modeling techniques in literature. For instance, Model Output Statistics (MOS), and running mean-bias removal are widely used techniques in storm surge prediction domain. However, these methods have some drawbacks. For instance, MOS is based on multiple linear regression and it needs a long period of training data. To overcome the shortcomings of these simple methods, researchers propose some advanced methods. For instance, ENSURF (Ensemble SURge Forecast) is a multi-model application for sea level forecast. This application creates a better forecast of sea level using a combination of several instances of the Bayesian Model Averaging (BMA). An ensemble dressing method is based on identifying best member forecast and using it for prediction. Our contribution in this paper can be summarized as follows. First, we investigate whether the ensemble models perform better than any single forecast. Therefore, we need to identify the single best forecast. We present a methodology based on a simple Bayesian selection method to select the best single forecast. Second, we present several new and simple ways to construct ensemble models. We use correlation and standard deviation as weights in combining different forecast models. Third, we use these ensembles and compare with several existing models in literature to forecast storm surge level. We then investigate whether developing a complex ensemble model is indeed needed. To achieve this goal, we use a simple average (one of the simplest and widely used ensemble model) as benchmark. Predicting the peak level of Surge during a storm as well as the precise time at which this peak level takes place is crucial, thus we develop a statistical platform to compare the performance of various ensemble methods. This statistical analysis is based on root mean square error of the ensemble forecast during the testing period and on the magnitude and timing of the forecasted peak surge compared to the actual time and peak. In this work, we analyze four hurricanes: hurricanes Irene and Lee in 2011, hurricane Sandy in 2012, and hurricane Joaquin in 2015. Since hurricane Irene developed at the end of August 2011 and hurricane Lee started just after Irene at the beginning of September 2011, in this study we consider them as a single contiguous hurricane event. The data set used for this study is generated by the New York Harbor Observing and Prediction System (NYHOPS). We find that even the simplest possible way of creating an ensemble produces results superior to any single forecast. We also show that the ensemble models we propose generally have better performance compared to the simple average ensemble technique.

Keywords: Bayesian learning, ensemble model, statistical analysis, storm surge prediction

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Authors: Jinhui Bak, Bumjin Kim

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The purpose of this study is to analyze how the scientific and mathematical fields (STEM) and liberal arts (A) work together in the STEAM program. In the future STEAM programs that have been designed and developed, the humanities will act not just as a 'tool' for science technology and mathematics, but as a 'core' content to have an equivalent status. STEAM was first introduced to the Republic of Korea in 2011 when the Ministry of Education emphasized fostering creative convergence talent. Many programs have since been developed under the name STEAM, but with the majority of programs focusing on technology education, arts and humanities are considered secondary. As a result, arts is most likely to be accepted as an option that can be excluded from the teachers who run the STEAM program. If what we ultimately pursue through STEAM education is in fostering STEAM literacy, we should no longer turn arts into a tooling area for STEM. Based on this consciousness, this study analyzed over 160 STEAM programs in middle and high schools, which were produced and distributed by the Ministry of Education and the Korea Science and Technology Foundation from 2012 to 2017. The framework of analyses referenced two criteria presented in the related prior studies: normative convergence and technological convergence. In addition, we divide Arts into fine arts and liberal arts and focused on Korean Language Course which is in liberal arts and analyzed what kind of curriculum standards were selected, and what kind of process the Korean language department participated in teaching and learning. In this study, to ensure the reliability of the analysis results, we have chosen to cross-check the individual analysis results of the two researchers and only if they are consistent. We also conducted a reliability check on the analysis results of three middle and high school teachers involved in the STEAM education program. Analyzing 10 programs selected randomly from the analyzed programs, Cronbach's α .853 showed a reliable level. The results of this study are summarized as follows. First, the convergence ratio of the liberal arts was lowest in the department of moral at 14.58%. Second, the normative convergence is 28.19%, which is lower than that of the technological convergence. Third, the language and achievement criteria selected for the program were limited to functional areas such as listening, talking, reading and writing. This means that the convergence of Korean language departments is made only by the necessary tools to communicate opinions or promote scientific products. In this study, we intend to compare these results with the STEAM programs in the United States and abroad to explore what elements or key concepts are required for the achievement criteria for Korean language and curriculum. This is meaningful in that the humanities field (A), including Korean, provides basic data that can be fused into 'equivalent qualifications' with science (S), technical engineering (TE) and mathematics (M).

Keywords: Korean STEAM Programme, liberal arts, STEAM curriculum, STEAM Literacy, STEM

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Authors: Al Sayed Al Soudy, Valeria Maselli, Gianluca Polese, Anna Di Cosmo

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Cephalopods are considered as a model organism with a rich behavioral repertoire. Sophisticated behaviors were widely studied and described in different species such as Octopus vulgaris, who has evolved the largest and more complex nervous system among invertebrates. In O. vulgaris, cognitive abilities in problem-solving tasks and learning abilities are associated with long-term memory and spatial memory, mediated by highly developed sensory organs. They are equipped with sophisticated eyes, able to discriminate colors even with a single photoreceptor type, vestibular system, ‘lateral line analogue’, primitive ‘hearing’ system and olfactory organs. They can recognize chemical cues either through direct contact with odors sources using suckers or by distance through the olfactory organs. Cephalopods are able to detect widespread waterborne molecules by the olfactory organs. However, many volatile odorant molecules are insoluble or have a very low solubility in water, and must be perceived by direct contact. O. vulgaris, equipped with many chemosensory neurons located in their suckers, exhibits a peculiar behavior that can be provocatively described as 'smell by touch'. The aim of this study is to establish the priority given to chemical vs. visual perception in food choice. Materials and methods: Three different types of food (anchovies, clams, and mussels) were used, and all sessions were recorded with a digital camera. During the acclimatization period, Octopuses were exposed to the three types of food to test their natural food preferences. Later, to verify if food preference is maintained, food was provided in transparent screw-jars with pierced lids to allow both visual and chemical recognition of the food inside. Subsequently, we tested alternatively octopuses with food in sealed transparent screw-jars and food in blind screw-jars with pierced lids. As a control, we used blind sealed jars with the same lid color to verify a random choice among food types. Results and discussion: During the acclimatization period, O. vulgaris shows a higher preference for anchovies (60%) followed by clams (30%), then mussels (10%). After acclimatization, using the transparent and pierced screw jars octopus’s food choices resulted in 50-50 between anchovies and clams, avoiding mussels. Later, guided by just visual sense, with transparent but not pierced jars, their food preferences resulted in 100% anchovies. With pierced but not transparent jars their food preference resulted in 100% anchovies as first food choice, the clams as a second food choice result (33.3%). With no possibility to select food, neither by vision nor by chemoreception, the results were 20% anchovies, 20% clams, and 60% mussels. We conclude that O. vulgaris uses both chemical and visual senses in an integrative way in food choice, but if we exclude one of them, it appears clear that its food preference relies on chemical sense more than on visual perception.

Keywords: food choice, Octopus vulgaris, olfaction, sensory organs, visual sense

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Authors: Kim Haekyoung, Au Yunkyoung

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As digital technology continues to advance and become more widely accessible, young children are also growing up experiencing various media from infancy. In this changing environment, educating young children on media literacy has become an increasingly important task. With the diversification of media, it has become more necessary for children to understand, utilize, and critically explore the meaning of multimodal texts, which include text, images, and sounds connected to each other. Early childhood is a period when media literacy can bloom, and educational and policy support are needed to enable young children to express their opinions, communicate, and participate fully. However, most current media literacy education for young children focuses solely on teaching how to use media, with limited practical application and utilization. Therefore, this study aims to develop an inquiry-based media literacy education program for young children using topic-specific media content and explore the program's potential and impact on children's media literacy learning. Based on a theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perception of media literacy education for young children, this study developed a media literacy education program for young children considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, social communication). To verify the effectiveness of the program, it was implemented with 20 five-year-old children from C City S Kindergarten, starting from March 24 to May 26, 2022, once a week for a total of 6 sessions. To explore quantitative changes before and after program implementation, repeated-measures analysis of variance was conducted, and qualitative analysis was used to analyze observed changes in the process. significant improvement in media literacy levels, such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication. The developed inquiry-based media literacy education program for young children in this study can be effectively applied to enhance children's media literacy education and help improve their media literacy levels. Observed changes in the process also confirmed that children improved their ability to learn various topics, express their thoughts, and communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can help children develop the ability to safely and effectively use media in their media environment. Based on exploring the potential and impact of the inquiry-based media literacy education program for young children, this study confirmed positive changes in children's media literacy levels as a result of the program's implementation. These findings suggest that beyond education on how to use media, it can help develop children's ability to safely and effectively use media in their media environment. Furthermore, to improve children's media literacy levels and create a safe media environment, a variety of content and methodologies are needed, and continuous development and evaluation of educational programs are anticipated.

Keywords: young children, media literacy, media literacy education program, media content

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Authors: Pui-sze Yeung, Connie Suk-han Ho, David Wai-ock Chan, Kevin Kien-hoa Chung

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Background: Recent findings have shown that transcription skills play a unique and significant role in Chinese word reading and spelling (i.e. word dictation), and written composition development. The interrelationships among component skills of transcription, word reading, word spelling, and written composition in Chinese have rarely been examined in the literature. Is the contribution of component skills of transcription to Chinese written composition mediated by word level skills (i.e., word reading and spelling)? Methods: The participants in the study were 249 Chinese children in Grade 1, Grade 3, and Grade 5 in Hong Kong. They were administered measures of general reasoning ability, orthographic knowledge, stroke sequence knowledge, word spelling, handwriting fluency, word reading, and Chinese narrative writing. Orthographic knowledge- orthographic knowledge was assessed by a task modeled after the lexical decision subtest of the Hong Kong Test of Specific Learning Difficulties in Reading and Writing (HKT-SpLD). Stroke sequence knowledge: The participants’ performance in producing legitimate stroke sequences was measured by a stroke sequence knowledge task. Handwriting fluency- Handwriting fluency was assessed by a task modeled after the Chinese Handwriting Speed Test. Word spelling: The stimuli of the word spelling task consist of fourteen two-character Chinese words. Word reading: The stimuli of the word reading task consist of 120 two-character Chinese words. Written composition: A narrative writing task was used to assess the participants’ text writing skills. Results: Analysis of covariance results showed that there were significant between-grade differences in the performance of word reading, word spelling, handwriting fluency, and written composition. Preliminary hierarchical multiple regression analysis results showed that orthographic knowledge, word spelling, and handwriting fluency were unique predictors of Chinese written composition even after controlling for age, IQ, and word reading. The interaction effects between grade and each of these three skills (orthographic knowledge, word spelling, and handwriting fluency) were not significant. Path analysis results showed that orthographic knowledge contributed to written composition both directly and indirectly through word spelling, while handwriting fluency contributed to written composition directly and indirectly through both word reading and spelling. Stroke sequence knowledge only contributed to written composition indirectly through word spelling. Conclusions: Preliminary hierarchical regression results were consistent with previous findings about the significant role of transcription skills in Chinese word reading, spelling and written composition development. The fact that orthographic knowledge contributed both directly and indirectly to written composition through word reading and spelling may reflect the impact of the script-sound-meaning convergence of Chinese characters on the composing process. The significant contribution of word spelling and handwriting fluency to Chinese written composition across elementary grades highlighted the difficulty in attaining automaticity of transcription skills in Chinese, which limits the working memory resources available for other composing processes.

Keywords: orthographic knowledge, transcription skills, word reading, writing

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Authors: Amar Ghelani

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People with auditory verbal hallucinations (AVH) who seek support from mental health services commonly report feeling unheard and invalidated in their interactions with social workers and psychiatric professionals. Current mental health training and clinical approaches have proven to be inadequate in addressing the complex nature of voice hearing. Childhood trauma is a key factor in the development of AVH and can render people more vulnerable to hearing both supportive and/or disturbing voices. Lived experiences of racism, poverty, and immigration are also associated with development of what is broadly classified as psychosis. Despite evidence affirming the influence of environmental factors on voice hearing, the Western biomedical system typically conceptualizes this experience as a symptom of genetically-based mental illnesses which requires diagnosis and treatment. Overemphasis on psychiatric medications, referrals, and directive approaches to people’s problems has shifted clinical interventions away from assessing and addressing problems directly related to AVH. The Maastricht approach offers voice hearers and mental health workers an alternative and respectful starting point for understanding and coping with voices. The approach was developed by voice hearers in partnership with mental health professionals and entails an innovative method to assess and create meaning from voice hearing and related life stressors. The objectives of the approach are to help people who hear voices: (1) understand the problems and/or people the voices may represent in their history, and (2) cope with distress and find solutions to related problems. The Maastricht approach has also been found to help voice hearers integrate emotional conflicts, reduce avoidance or fear associated with AVH, improve therapeutic relationships, and increase a sense of control over internal experiences. The proposed oral presentation will be guided by a recovery-oriented theoretical framework which suggests healing from psychological wounds occurs through social connections and community support systems. The presentation will start with a brainstorming exercise to identify participants pre-existing knowledge of the subject matter. This will lead into a literature review on the relations between trauma, intersectionality, and AVH. An overview of the Maastricht approach and review of research related to its therapeutic risks and benefits will follow. Participants will learn trauma-informed coping skills and questions which can help voice hearers make meaning from their experiences. The presentation will conclude with a review of resources and learning opportunities where participants can expand their knowledge of the Hearing Voices Movement and Maastricht approach.

Keywords: Maastricht interview, recovery, therapeutic assessment, voice hearing

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Authors: Christian Andrä, Luisa Zimmermann, Christina Müller

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Introduction: The positive relation between physical activity and cognition is commonly known. Relevant studies show that in everyday school life active breaks can lead to improvement in certain abilities (e.g. attention and concentration). A beneficial effect is in particular attributed to moderate activity. It is still unclear whether active breaks are beneficial after relatively short phases of cognitive load and whether the postulated effects of activity really have an immediate impact. The objective of this study was to verify whether an active break after 18 minutes of cognitive load leads to enhanced attention/concentration performance, compared to inactive breaks with voluntary mobile phone activity. Methodology: For this quasi-experimental study, 36 students [age: 14.0 (mean value) ± 0.3 (standard deviation); male/female: 21/15] of a secondary school were tested. In week 1, every student’s maximum heart rate (Hfmax) was determined through maximum effort tests conducted during physical education classes. The task was to run 3 laps of 300 m with increasing subjective effort (lap 1: 60%, lap 2: 80%, lap 3: 100% of the maximum performance capacity). Furthermore, first attention/concentration tests (D2-R) took place (pretest). The groups were matched on the basis of the pretest results. During week 2 and 3, crossover testing was conducted, comprising of 18 minutes of cognitive preload (test for concentration performance, KLT-R), a break and an attention/concentration test after a 2-minutes transition. Different 10-minutes breaks (active break: moderate physical activity with 65% Hfmax or inactive break: mobile phone activity) took place between preloading and transition. Major findings: In general, there was no impact of the different break interventions on the concentration test results (symbols processed after physical activity: 185.2 ± 31.3 / after inactive break: 184.4 ± 31.6; errors after physical activity: 5.7 ± 6.3 / after inactive break: 7.0. ± 7.2). There was, however, a noticeable development of the values over the testing periods. Although no difference in the number of processed symbols was detected (active/inactive break: period 1: 49.3 ± 8.8/46.9 ± 9.0; period 2: 47.0 ± 7.7/47.3 ± 8.4; period 3: 45.1 ± 8.3/45.6 ± 8.0; period 4: 43.8 ± 7.8/44.6 ± 8.0), error rates decreased successively after physical activity and increased gradually after an inactive break (active/inactive break: period 1: 1.9 ± 2.4/1.2 ± 1.4; period 2: 1.7 ± 1.8/ 1.5 ± 2.0, period 3: 1.2 ± 1.6/1.8 ± 2.1; period 4: 0.9 ± 1.5/2.5 ± 2.6; p= .012). Conclusion: Taking into consideration only the study’s overall results, the hypothesis must be dismissed. However, more differentiated evaluation shows that the error rates decreased after active breaks and increased after inactive breaks. Obviously, the effects of active intervention occur with a delay. The 2-minutes transition (regeneration time) used for this study seems to be insufficient due to the longer adaptation time of the cardio-vascular system in untrained individuals, which might initially affect the concentration capacity. To use the positive effects of physical activity for teaching and learning processes, physiological characteristics must also be considered. Only this will ensure optimum ability to perform.

Keywords: active breaks, attention/concentration test, cognitive performance capacity, heart rate, physical activity

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Authors: Belinda du Plooy, Ruth Albertyn, Christel Troskie-De Bruin, Ella Belcher

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In the academy, scholarliness or intellectual craftsmanship is considered the highest level of achievement, culminating in being consistently successfully published in impactful, peer-reviewed journals and books. Scholarliness implies rigorous methods, systematic exposition, in-depth analysis and evaluation, and the highest level of critical engagement and reflexivity. However, being a scholar does not happen automatically when one becomes an academic or completes graduate studies. A graduate qualification is an indication of one’s level of research competence but does not necessarily prepare one for the type of scholarly writing for publication required after a postgraduate qualification has been conferred. Scholarly writing for publication requires a high-level skillset and a specific mindset, which must be intentionally developed. The rite of passage to become a scholar is an iterative process with liminal spaces, thresholds, transitions, and transformations. The journey from researcher to published author is often fraught with rejection, insecurity, and disappointment and requires resilience and tenacity from those who eventually triumph. It cannot be achieved without support, guidance, and mentorship. In this article, the authors use collective auto-ethnography (CAE) to describe the phases and types of liminality encountered during the liminal journey toward scholarship. The authors speak as long-time facilitators of Writing for Academic Publication (WfAP) capacity development events (training workshops and writing retreats) presented at South African universities. Their WfAP facilitation practice is structured around experiential learning principles that allow them to act as critical reading partners and reflective witnesses for the writer-participants of their WfAP events. They identify three essential facilitation features for the effective holding of a generative, liminal, and transformational writing space for novice academic writers in order to enable their safe passage through the various liminal spaces they encounter during their scholarly development journey. These features are that facilitators should be agents of disruption and liminality while also guiding writers through these liminal spaces; that there should be a sense of mutual trust and respect, shared responsibility and accountability in order for writers to produce publication-worthy scholarly work; and that this can only be accomplished with the continued application of high levels of sensitivity and discernment by WfAP facilitators. These are key features for successful WfAP scholarship training events, where focused, individual input triggers personal and professional transformational experiences, which in turn translate into high-quality scholarly outputs.

Keywords: academic writing, liminality, scholarship, scholarliness, threshold experience, writing for publication

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Authors: Rose Veitch

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Learning outcomes-based qualifications have been heralded as the means to raise vocational education and training (VET) standards, meet the needs of the changing workforce, and establish equivalence with existing academic qualifications. Characterized by explicit, measurable performance statements and atomistically specified assessment criteria, the outcomes model has been adopted by many VET systems worldwide since its inception in the United Kingdom in the 1980s. Debate to date centers on how the outcomes model treats knowledge. Flaws have been identified in terms of the overemphasis of end-points, neglect of process and a failure to treat curricula coherently. However, much of this censure has evaluated the outcomes model from a theoretical perspective; to date, there has been scant empirical research to support these criticisms. Various issues therefore remain unaddressed. This study investigates how the outcomes model impacts the teaching of subject literacies. This is of particular concern for subjects on the academic-vocational boundary such as Business Studies, since many of these students progress to higher education in the United Kingdom. This study also explores the extent to which the outcomes model is compatible with borderline vocational subjects. To fully understand if this qualification model is fit for purpose in the 16-18 year-old phase, it is necessary to investigate how teachers interpret their qualification specifications in terms of curriculum, pedagogy and assessment. Of particular concern is the nature of the interaction between the outcomes model and teachers’ understandings of their subject-procedural knowledge, and how this affects their capacity to embed literacy into their teaching. This present study is part of a broader doctoral research project which seeks to understand if and how content-area, disciplinary literacy and genre approaches can be adapted to outcomes-based VET qualifications. This qualitative research investigates the ‘what’ and ‘how’ of literacy embedding from the perspective of in-service teacher development in the 16-18 phase of education. Using ethnographic approaches, it is based on fieldwork carried out in one Further Education college in the United Kingdom. Emergent findings suggest that the outcomes model is not fit for purpose in the context of borderline vocational subjects. It is argued that the outcomes model produces inferior qualifications due to compositional fallacy; the sum of a subject’s components do not add up to the whole. Findings indicate that procedural knowledge, largely unspecified by some outcomes-based qualifications, is where subject-literacies are situated, and that this often gets lost in ‘delivery’. It seems that the outcomes model provokes an atomistic treatment of knowledge amongst teachers, along with the privileging of propositional knowledge over procedural knowledge. In other words, outcomes-based VET is a hostile environment for subject-literacy embedding. It is hoped that this research will produce useful suggestions for how this problem can be ameliorated, and will provide an empirical basis for the potential reforms required to address these issues in vocational education.

Keywords: literacy, outcomes-based, qualification design, vocational education

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Authors: Veena Easvaradoss, Ebenezer Joseph, Sumathi Chandrasekaran, Sweta Jain, Aparna Anna Mathai, Senta Christy

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Working memory refers to a cognitive processing space where information is received, managed, transformed, and briefly stored. It is an operational process of transforming information for the execution of cognitive tasks in different and new ways. Many class room activities require children to remember information and mentally manipulate it. While the impact of chess training on intelligence and academic performance has been unequivocally established, its impact on working memory needs to be studied. This study, funded by the Cognitive Science Research Initiative, Department of Science & Technology, Government of India, analyzed the effect of one-year chess training on the working memory of children. A pretest–posttest with control group design was used, with 52 children in the experimental group and 50 children in the control group. The sample was selected from children studying in school (grades 3 to 9), which included both the genders. The experimental group underwent weekly chess training for one year, while the control group was involved in extracurricular activities. Working memory was measured by two subtests of WISC-IV INDIA. The Digit Span Subtest involves recalling a list of numbers of increasing length presented orally in forward and in reverse order, and the Letter–Number Sequencing Subtest involves rearranging jumbled alphabets and numbers presented orally following a given rule. Both tasks require the child to receive and briefly store information, manipulate it, and present it in a changed format. The Children were trained using Winning Moves curriculum, audio- visual learning method, hands-on- chess training and recording the games using score sheets, analyze their mistakes, thereby increasing their Meta-Analytical abilities. They were also trained in Opening theory, Checkmating techniques, End-game theory and Tactical principles. Pre equivalence of means was established. Analysis revealed that the experimental group had significant gains in working memory compared to the control group. The present study clearly establishes a link between chess training and working memory. The transfer of chess training to the improvement of working memory could be attributed to the fact that while playing chess, children evaluate positions, visualize new positions in their mind, analyze the pros and cons of each move, and choose moves based on the information stored in their mind. If working-memory’s capacity could be expanded or made to function more efficiently, it could result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess training, cognitive development, executive functions, school children, working memory

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Authors: Vesna Vulić

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Croatia has made large steps forward in the development of higher education over the past 10 years. Purposes and objectives of the tertiary education system are focused on the personal development of young people so that they obtain competences for employment on a flexible labour market. The most frequent tensions between the tertiary institutions and employers are complaints that the current tertiary education system still supplies students with an abundance of theoretical knowledge and not enough practical skills. Polytechnics and schools of professional higher education should deliver professional education and training that will satisfy the needs of their local communities. The 21^st century sets demand on undergraduates as well as their lecturers to strive for the highest standards. The skills students acquire during their studies should serve the needs of their future professional careers. In this context, teaching English for Specific Purposes (ESP) presents an enormous challenge for teachers. They have to cope with teaching the language in classes with a large number of students, limitations of time, inadequate equipment and teaching material; most frequently, this leads to focusing on specialist vocabulary neglecting the development of skills and competences required for future employment. Globalization has transformed the labour market and set new standards a perspective employee should meet. When knowledge of languages is considered, new generic skills and competences are required. Not only skillful written and oral communication is needed, but also information, media, and technology literacy, learning skills which include critical and creative thinking, collaborating and communicating, as well as social skills. The aim of this paper is to evaluate the needs of two groups of ESP first year Undergraduate Professional Administrative Study students taking ESP as a mandatory course: 47 first-year Undergraduate Professional Administrative Study students, 21 first-year employed part-time Undergraduate Professional Administrative Study students and 30 graduates with a degree in Undergraduate Professional Administrative Study with various amounts of work experience. The survey adopted a quantitative approach with the aim to determine the differences between the groups in their perception of the four language skills and different areas of law, as well as getting the insight into students' satisfaction with the current course and their motivation for studying ESP. Their perceptions will be compared to the results of the questionnaire conducted among sector professionals in order to examine how they perceive the same elements of the ESP course content and to what extent it fits into their working environment. The results of the survey indicated that there is a strong correlation between acquiring work experience and the level of importance given to particular areas of law studied in an ESP course which is in line with our initial hypothesis. In conclusion, the results of the survey should help lecturers in re-evaluating and updating their ESP course syllabi.

Keywords: English for Specific Purposes (ESP), language skills, motivation, needs analysis

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Authors: Giovanna Bimonte, Luigi Senatore, Francesco Saverio Tortoriello, Ilaria Veronesi

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The education process considers capabilities not only to be seen as a means to a certain end but rather as an effective purpose. Sen's capability approach challenges human capital theory, which sees education as an ordinary investment undertaken by individuals. A complex reality requires complex thinking capable of interpreting the dynamics of society's changes to be able to make decisions that can be rational for private, ethical and social contexts. Education is not something removed from the cultural and social context; it exists and is structured within it. In Italy, the "Mathematical High School Project" is a didactic research project is based on additional laboratory courses in extracurricular hours where mathematics intends to bring itself in a dialectical relationship with other disciplines as a cultural bridge between the two cultures, the humanistic and the scientific ones, with interdisciplinary educational modules on themes of strong impact in younger life. This interdisciplinary mathematics presents topics related to the most advanced technologies and contemporary socio-economic frameworks to demonstrate how mathematics is not only a key to reading but also a key to resolving complex problems. The recent developments in mathematics provide the potential for profound and highly beneficial changes in mathematics education at all levels, such as in socio-economic decisions. The research project is built to investigate whether repeated interactions can successfully promote cooperation among students as rational choice and if the skill, the context and the school background can influence the strategies choice and the rationality. A Laboratory on Game Theory as mathematical theory was conducted in the 4th year of the Mathematical High Schools and in an ordinary scientific high school of the Scientific degree program. Students played two simultaneous games of repeated Prisoner's Dilemma with an indefinite horizon, with two different competitors in each round; even though the competitors in each round will remain the same for the duration of the game. The results highlight that most of the students in the two classes used the two games with an immunization strategy against the risk of losing: in one of the games, they started by playing Cooperate, and in the other by the strategy of Compete. In the literature, theoretical models and experiments show that in the case of repeated interactions with the same adversary, the optimal cooperation strategy can be achieved by tit-for-tat mechanisms. In higher education, individual capacities cannot be examined independently, as conceptual framework presupposes a social construction of individuals interacting and competing, making individual and collective choices. The paper will outline all the results of the experimentation and the future development of the research.

Keywords: game theory, interdisciplinarity, mathematics education, mathematical high school

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Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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One of the most common pieces of equipment still used today for pruning, felling, and processing trees is the chainsaw in forestry. However, chainsaw use highlights dangers and one of the highest rates of accidents in both professional and non-professional work. Felling is proportionally the most dangerous phase, both in severity and frequency, because of the risk of being hit by the plant the operator wants to cut down. To avoid this, a correct sequence of chainsaw cuts must be taught concerning the different conditions of the tree. Virtual reality (VR) makes it possible to virtually simulate chainsaw use without danger of injury. The limitations of the existing applications are as follow. The existing platforms are not symmetrical collaborative because the trainee is only in virtual reality, and the trainer can only see the virtual environment on a laptop or PC, and this results in an inefficient teacher-learner relationship. Therefore, most applications only involve the use of a virtual chainsaw, and the trainee thus cannot feel the real weight and inertia of a real chainsaw. Finally, existing applications simulate only a few cases of tree felling. The objectives of this research were to implement and test a symmetrical collaborative training application based on VR and mixed reality (MR) with the overlap between real and virtual chainsaws in MR. The research and training platform was developed for the Meta quest 2 head-mounted display. The research and training platform application is based on the Unity 3D engine, and Present Platform Interaction SDK (PPI-SDK) developed by Meta. PPI-SDK avoids the use of controllers and enables hand tracking and MR. With the combination of these two technologies, it was possible to overlay a virtual chainsaw with a real chainsaw in MR and synchronize their movements in VR. This ensures that the user feels the weight of the actual chainsaw, tightens the muscles, and performs the appropriate movements during the test allowing the user to learn the correct body posture. The chainsaw works only if the right sequence of cuts is made to felling the tree. Contact detection is done by Unity's physics system, which allows the interaction of objects that simulate real-world behavior. Each cut of the chainsaw is defined by a so-called collider, and the felling of the tree can only occur if the colliders are activated in the right order simulating a safe technique felling. In this way, the user can learn how to use the chainsaw safely. The system is also multiplayer, so the student and the instructor can experience VR together in a symmetrical and collaborative way. The platform simulates the following tree-felling situations with safe techniques: cutting the tree tilted forward, cutting the medium-sized tree tilted backward, cutting the large tree tilted backward, sectioning the trunk on the ground, and cutting branches. The application is being evaluated on a sample of university students through a special questionnaire. The results are expected to test both the increase in learning compared to a theoretical lecture and the immersive and telepresence of the platform.

Keywords: chainsaw, collaborative symmetric virtual reality, mixed reality, operator training

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Authors: Vijaya Kumar, Vidayasagar Pagilla, Abraham Joshua, Rakshith Kedambadi, Prasanna Mithra

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Background: Post stroke rehabilitation are aimed to accelerate for optimal sensorimotor recovery, functional gain and to reduce long-term dependency. Intensive physical therapy interventions can enhance this recovery as experience-dependent neural plastic changes either directly act at cortical neural networks or at distal peripheral level (muscular components). Neuromuscular Electrical Stimulation (NMES), a traditional bottom-up approach, mirror therapy (MT), a relatively new top down approach have found to be an effective adjuvant treatment methods for lower extremity motor and functional recovery in stroke rehabilitation. However there is a scarcity of evidence to compare their therapeutic gain in stroke recovery.Aim: To compare the efficacy of neuromuscular electrical stimulation (NMES) and mirror therapy (MT) in very early phase of post stroke rehabilitation addressed to lower extremity motor recovery and balance. Design: observer blinded Randomized Clinical Trial. Setting: Neurorehabilitation Unit, Department of Physical Therapy, Tertiary Care Hospitals. Subjects: 32 acute stroke subjects with first episode of unilateral stroke with hemiparesis, referred for rehabilitation (onset < 3 weeks), Brunnstorm lower extremity recovery stages ≥3 and MMSE score more than 24 were randomized into two group [Group A-NMES and Group B-MT]. Interventions: Both the groups received eclectic approach to remediate lower extremity recovery which includes treatment components of Roods, Bobath and Motor learning approaches for 30 minutes a day for 6 days. Following which Group A (N=16) received 30 minutes of surface NMES training for six major paretic muscle groups (gluteus maximus and medius,quadriceps, hamstrings, tibialis anterior and gastrocnemius). Group B (N=16) was administered with 30 minutes of mirror therapy sessions to facilitate lower extremity motor recovery. Outcome measures: Lower extremity motor recovery, balance and activities of daily life (ADLs) were measured by Fugyl Meyer Assessment (FMA-LE), Berg Balance Scale (BBS), Barthel Index (BI) before and after intervention. Results: Pre Post analysis of either group across the time revealed statistically significant improvement (p < 0.001) for all the outcome variables for the either group. All parameters of NMES had greater change scores compared to MT group as follows: FMA-LE (25.12±3.01 vs. 23.31±2.38), BBS (35.12±4.61 vs. 34.68±5.42) and BI (40.00±10.32 vs. 37.18±7.73). Between the groups comparison of pre post values showed no significance with FMA-LE (p=0.09), BBS (p=0.80) and BI (p=0.39) respectively. Conclusion: Though either groups had significant improvement (pre to post intervention), none of them were superior to other in lower extremity motor recovery and balance among acute stroke subjects. We conclude that eclectic approach is an effective treatment irrespective of NMES or MT as an adjunct.

Keywords: balance, motor recovery, mirror therapy, neuromuscular electrical stimulation, stroke

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Authors: Masoume Pourmohamadreza-Tajrishi, Parviz Azadfallah

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Autism spectrum disorders (ASD) involve myriad aberrant perceptual, cognitive, linguistic, and social behaviors. The term spectrum emphasizes that the disabilities associated with ASD fall on a continuum from relatively mild to severe. People with ASD may display stereotyped behaviors such as twirling, spinning objects, flapping the hands, and rocking. The individuals with ASD exhibit communication problems due to repetitive/restricted behaviors. Children with ASD who lack the motivation to learn, who do not enjoy physical challenges, or whose sensory perception results in confusing or unpleasant feedback from movement may not become sufficiently motivated to practice motor activities. As a result, they may show both a delay in developing certain motor skills. Additionally, attention is an important component of learning. As far as children with ASD have problems in joint attention, many education-based programs are needed to consider some aspects of attention and motor activities development for students with ASD. These programs focus on the basic movement skills that are crucial for the future development of the more complex skills needed in games, dance, sports, gymnastics, active play, and recreational physical activities. The purpose of the present research was to determine the effectiveness of therapeutic exercise on motor skills and attention of male students with ASD. This was an experimental study with a control group. The population consisted of 8-10 year-old male students with ASD and 30 subjects were selected randomly from an available center suitable for the children with ASD. They were evaluated by the Basic Motor Ability Test (BMAT) and Persian version of computerized Stroop color-word test and randomly assigned to an experimental and control group (15 students in per group). The experimental group participated in 16 therapeutic exercise sessions and received therapeutic exercise program (twice a week; each lasting for 45 minutes) designed based on the Spark motor program while the control group did not. All subjects were evaluated by BMAT and Stroop color-word test after the last session again. The collected data were analyzed by using multivariate analysis of covariance (MANCOVA). The results of MANCOVA showed that experimental and control groups had a significant difference in motor skills and at least one of the components of attention (correct responses, incorrect responses, no responses, the reaction time of congruent words and reaction time of incongruent words in the Stroop test). The findings showed that the therapeutic exercise had a significant effect on motor skills and all components of attention in students with ASD. We can conclude that the therapeutic exercise led to promote the motor skills and attention of students with ASD, so it is necessary to design or plan such programs for ASD students to prevent their communication or academic problems.

Keywords: Attention, autism spectrum disorder, motor skills, therapeutic exercise

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Authors: Anna Öqvist, Malin Malmström

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Attaining a higher level of education has become an increasingly important prerequisite for people’s economic and social independence and mobility. Young people who do not pursue higher education are not as attractive as potential employees in the modern work environment. Although completing a higher education degree is not a guarantee for getting a job, it substantially increases the chances for employment and, consequently, the chances for a better life. Despite this, it’s a fact that in several regions in Sweden, fewer students are choosing to engage in higher education. Similar trends have been emphasized in, for instance, the US where high dropout patterns among young people have been noted. This is a threat to future employment and industry development in these regions because the future employment base for society is dependent upon students’ willingness to invest in higher education. Much of prior studies have focused on the role of parents’ involvement in their children’s’ school work and the positive influence parents involvement have on their children’s school performance. Parental influence on education in general has been a topic of interest among those concerned with optimal developmental and educational outcomes for children and youth in pre-, secondary- and high school. Across a range of studies, there has emerged a strong conclusion that parental influence on child and youths education generally benefits children's and youths learning and school success. Arguably then, we could expect that parents influence on whether or not to pursue a higher education would be of importance to understand young people’s choice to engage in higher education. Accordingly, understanding what drives students’ intentions to pursue higher education is an essential component of motivating students to aspire to make the most of their potential in their future work life. Drawing on the theory of planned behavior, this study examines the role of parents influence on students’ attitudes about whether higher education can be beneficial to their future work life. We used a qualitative approach by collecting interview data from 18 high school students in Sweden to capture students’ cognitive and motivational mechanisms (attitudes) to influence intentions to engage in higher education. We found that parents may positively or negatively influence students’ attitudes and subsequently a student's intention to pursue higher education. Accordingly, our results show that parents’ own attitudes and expectations on their children are keys for influencing students’ attitudes and intentions for higher education. Further, our finding illuminates the mechanisms that drive students in one direction or the other. As such, our findings show that the same categories of arguments are used for driving students’ attitudes and intentions in two opposite directions, namely; financial arguments and work life benefits arguments. Our results contribute to existing literature by showing that parents do affect young people’s intentions to engage in higher studies. The findings contribute to the theory of planned behavior and have implications for the literature on higher education and educational psychology and also provide guidance on how to inform students about facts of higher studies in school.

Keywords: higher studies, intentions, parents influence, theory of planned behavior

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Authors: Matthew Yeager, Christopher Willy, John Bischoff

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The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

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Authors: Chiu-Yin Leung

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This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Moen Torill, Rismark Marit, Astrid M. Solvberg

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In Norway, every municipality shall provide an educational psychological service, EPS, to support kindergartens and schools in their work with children and youths with special needs. The EPS focus its work on individuals, aiming to identify special needs and to give advice to teachers and parents when they ask for it. In addition, the service also give priority to prevention and system intervention in kindergartens and schools. To master these big tasks university courses are established to support EPS counsellors' continuous learning. There is, however, a need for more in-depth and systematic knowledge on how they experience the courses they attend. In this study, EPS counsellors’ reflection logs during a particular course are investigated. The research question is: what are the content and priorities of the reflections that are communicated in the logs produced by the educational psychological counsellors during a post-graduate course? The investigated course is a credit course organized over a one-year period in two one-semester modules. The altogether 55 students enrolled in the course work as EPS counsellors in various municipalities across Norway. At the end of each day throughout the course period, the participants wrote reflection logs about what they had experienced during the day. The data material consists of 165 pages of typed text. The collaborating researchers studied the data material to ascertain, differentiate and understand the meaning of the content in each log. The analysis also involved the search for similarity in content and development of analytical categories that described the focus and primary concerns in each of the written logs. This involved constant 'critical and sustained discussions' for mutual construction of meaning between the co-researchers in the developing categories. The process is inspired by Grounded Theory. This means that the concepts developed during the analysis derived from the data material and not chosen prior to the investigation. The analysis revealed that the concept 'Useful' frequently appeared in the participants’ reflections and, as such, 'Useful' serves as a core category. The core category is described through three major categories: (1) knowledge sharing (concerning direct and indirect work with students with special needs) with colleagues is useful, (2) reflections on models and theoretical concepts (concerning students with special needs) are useful, (3) reflection on the role as EPS counsellor is useful. In all the categories, the notion of useful occurs in the participants’ emphasis on and acknowledgement of the immediate and direct link between the university course content and their daily work practice. Even if each category has an importance and value of its own, it is crucial that they are understood in connection with one another and as interwoven. It is the connectedness that gives the core category an overarching explanatory power. The knowledge from this study may be a relevant contribution when it comes to designing new courses that support continuing professional development for EPS counsellors, whether for post-graduate university courses or local courses at the EPS offices or whether in Norway or other countries in the world.

Keywords: constructing and circulating knowledge, educational-psychological counsellor, higher education, professional development

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Authors: Maria V. Mishatkina

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The modelling of dialogical environment is an essential feature of modern education. The dialogue of cultures is a foundation and an important prerequisite for a formation of a human’s main moral qualities such as an ability to understand another person, which is manifested in such values as tolerance, respect, mutual assistance and mercy. A formation of a modern expert occurs in an educational environment that is significantly different from what we had several years ago. Nowadays university education has qualitatively new characteristics. They may be observed in Peoples’ Friendship University of Russia (RUDN University), a top Russian higher education institution which unites representatives of more than 150 countries. The content of its educational strategies is not an adapted cultural experience but material between science and innovation. Besides, RUDN University’s profiles and specialization are not equal to the professional structures. People study not a profession in a strict sense but a basic scientific foundation of an activity in different socio-cultural areas (science, business and education). RUDN University also provides a considerable unit of professional education components. They are foreign languages skills, economic, political, ethnic, communication and computer culture, theory of information and basic management skills. Moreover, there is a rich social life (festive multicultural events, theme parties, journeys) and prospects concerning the inclusive approach to education (for example, a special course ‘Social Pedagogy: Issues of Tolerance’). In our research, we use such methods as analysis of modern and contemporary scientific literature, opinion poll (involving students, teachers and research workers) and comparative data analysis. We came to the conclusion that knowledge transfer of RUDN student in the activity happens through making goals, problems, issues, tasks and situations which simulate future innovative ambiguous environment that potentially prepares him/her to dialogical way of life. However, all these factors may not take effect if there is no ‘personal inspiration’ of students by communicative and dialogic values, their participation in a system of meanings and tools of learning activity that is represented by cooperation within the framework of scientific and pedagogical schools dialogue. We also found out that dominating strategies of ensuring the quality of education are those that put students in the position of the subject of their own education. Today these strategies and approaches should involve such approaches and methods as task, contextual, modelling, specialized, game-imitating and dialogical approaches, the method of practical situations, etc. Therefore, University in the modern sense is not only an educational institution, but also a generator of innovation, cooperation among nations and cultural progress. RUDN University has been performing exactly this mission for many decades.

Keywords: dialogical developing situation, dialogue of cultures, readiness for dialogue, university graduate

Procedia PDF Downloads 219

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Sergio J. Calleja, Adria Roca, José D. Santotoribio

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Pancreatic endocrine diseases include pathologies like insulin resistance (IR), prediabetes, and type 2 diabetes mellitus (DM2). Some of them are highly prevalent in the U.S.—40% of U.S. adults have IR, 38% of U.S. adults have prediabetes, and 12% of U.S. adults have DM2—, as reported by the National Center for Biotechnology Information (NCBI). Building upon this imperative, the objective of the present study was to develop a non-invasive test for the assessment of the patient’s pancreatic endocrine function and to evaluate its accuracy in detecting various pancreatic endocrine diseases, such as IR, prediabetes, and DM2. This approach to a routine blood and urine test is based around serum and urine biomarkers. It is made by the combination of several independent public algorithms, such as the Adult Treatment Panel III (ATP-III), triglycerides and glucose (TyG) index, homeostasis model assessment-insulin resistance (HOMA-IR), HOMA-2, and the quantitative insulin-sensitivity check index (QUICKI). Additionally, it incorporates essential measurements such as the creatinine clearance, estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio (ACR), and urinalysis, which are helpful to achieve a full image of the patient’s pancreatic endocrine disease. To evaluate the estimated accuracy of this test, an iterative process was performed by a machine learning (ML) algorithm, with a training set of 9,391 patients. The sensitivity achieved was 97.98% and the specificity was 99.13%. Consequently, the area under the receiver operating characteristic (AUROC) curve, the positive predictive value (PPV), and the negative predictive value (NPV) were 92.48%, 99.12%, and 98.00%, respectively. The algorithm was validated with a randomized controlled trial (RCT) with a target sample size (n) of 314 patients. However, 50 patients were initially excluded from the study, because they had ongoing clinically diagnosed pathologies, symptoms or signs, so the n dropped to 264 patients. Then, 110 patients were excluded because they didn’t show up at the clinical facility for any of the follow-up visits—this is a critical point to improve for the upcoming RCT, since the cost of each patient is very high and for this RCT almost a third of the patients already tested were lost—, so the new n consisted of 154 patients. After that, 2 patients were excluded, because some of their laboratory parameters and/or clinical information were wrong or incorrect. Thus, a final n of 152 patients was achieved. In this validation set, the results obtained were: 100.00% sensitivity, 100.00% specificity, 100.00% AUROC, 100.00% PPV, and 100.00% NPV. These results suggest that this approach to a routine blood and urine test holds promise in providing timely and accurate diagnoses of pancreatic endocrine diseases, particularly among individuals aged 40 and above. Given the current epidemiological state of these type of diseases, these findings underscore the significance of early detection. Furthermore, they advocate for further exploration, prompting the intention to conduct a clinical trial involving 26,000 participants (from March 2025 to December 2026).

Keywords: algorithm, diabetes, laboratory medicine, non-invasive

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Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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Authors: Kalliopi Kanaki, Michael Kalogiannakis

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Nowadays, in the digital era, the early acquisition of basic programming skills and knowledge is encouraged, as it facilitates students’ exposure to computational thinking and empowers their creativity, problem-solving skills, and cognitive development. More and more researchers and educators investigate the introduction of computational thinking in K-12 since it is expected to be a fundamental skill for everyone by the middle of the 21st century, just like reading, writing and arithmetic are at the moment. In this paper, a doctoral research in the process is presented, which investigates the infusion of computational thinking into science curriculum in early childhood education. The whole attempt aims to develop young children’s computational thinking by introducing them to the fundamental concepts of object-oriented programming in an enjoyable, yet educational framework. The backbone of the research is the digital environment PhysGramming (an abbreviation of Physical Science Programming), which provides children the opportunity to create their own digital games, turning them from passive consumers to active creators of technology. PhysGramming deploys an innovative hybrid schema of visual and text-based programming techniques, with emphasis on object-orientation. Through PhysGramming, young students are familiarized with basic object-oriented programming concepts, such as classes, objects, and attributes, while, at the same time, get a view of object-oriented programming syntax. Nevertheless, the most noteworthy feature of PhysGramming is that children create their own digital games within the context of physical science courses, in a way that provides familiarization with the basic principles of object-oriented programming and computational thinking, even though no specific reference is made to these principles. Attuned to the ethical guidelines of educational research, interventions were conducted in two classes of second grade. The interventions were designed with respect to the thematic units of the curriculum of physical science courses, as a part of the learning activities of the class. PhysGramming was integrated into the classroom, after short introductory sessions. During the interventions, 6-7 years old children worked in pairs on computers and created their own digital games (group games, matching games, and puzzles). The authors participated in these interventions as observers in order to achieve a realistic evaluation of the proposed educational framework concerning its applicability in the classroom and its educational and pedagogical perspectives. To better examine if the objectives of the research are met, the investigation was focused on six criteria; the educational value of PhysGramming, its engaging and enjoyable characteristics, its child-friendliness, its appropriateness for the purpose that is proposed, its ability to monitor the user’s progress and its individualizing features. In this paper, the functionality of PhysGramming and the philosophy of its integration in the classroom are both described in detail. Information about the implemented interventions and the results obtained is also provided. Finally, several limitations of the research conducted that deserve attention are denoted.

Keywords: computational thinking, early childhood education, object-oriented programming, physical science courses

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Authors: Christo Swart, Lidia Pottas, David Maree

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Background: It is a sine qua non that the South African educational system finds itself in a profound crisis and that traditional school leadership styles are outdated and hinder quality education. New thinking is mandatory to improve the status quo and school leadership has an immense role to play to improve the current situation. It is believed that the servant leadership paradigm, when practiced by school leadership, may have a significant influence on the school environment in totality. This study investigates the private school segment in search of constructive answers to assist with the educational crises in South Africa. It is assumed that where school leadership can augment a supportive and empowering environment for teachers to constructively engage in their teaching and learning activities - then many challenges facing by school system may be subjugated in a productive manner. Aim: The aim of this study is fourfold. To outline the constructs of servant leadership which are perceived by teachers of private schools as priorities to enhance a successful school environment. To describe the constructs of organizational climate which are observed by teachers of private schools as priorities to enhance a successful school environment. To investigate whether the participants perceived a link between the constructs of servant leadership and organizational climate. To consider the process to be followed to introduce the constructs of SL and OC the school system in general as perceived by participants. Method: This study utilized a qualitative approach to explore the mediation between school leadership and the organizational climate in private schools in the search for amicable answers. The participants were purposefully selected for the study. Focus group interviews were held with participants from primary and secondary schools and a focus group discussion was conducted with principals of both primary and secondary schools. The interview data were transcribed and analyzed and identical patterns of coded data were grouped together under emerging themes. Findings: It was found that the practice of servant leadership by school leadership indeed mediates a constructive and positive school climate. It was found that the constructs of empowerment, accountability, humility and courage – interlinking with one other - are prominent of servant leadership concepts that are perceived by teachers of private schools as priorities for school leadership to enhance a successful school environment. It was confirmed that the groupings of training and development, communication, trust and work environment are perceived by teachers of private schools as prominent features of organizational climate as practiced by school leadership to augment a successful school environment. It can be concluded that the participants perceived several links between the constructs of servant leadership and organizational climate that encourage a constructive school environment and that there is a definite positive consideration and motivation that the two concepts be introduced to the school system in general. It is recommended that school leadership mentors and guides teachers to take ownership of the constructs of servant leadership as well as organizational climate and that public schools be researched and consider to implement the two paradigms. The study suggests that aspirant teachers be exposed to leadership as well as organizational paradigms during their studies at university.

Keywords: empowering environment for teachers and learners, new thinking required, organizational climate, school leadership, servant leadership

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Authors: Elham Koohi, Silvio Jose Gumiere, Hossein Bonakdari, Saeid Homayouni

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Water used in agricultural crops can be managed by irrigation scheduling based on soil moisture levels and plant water stress thresholds. Automated irrigation scheduling limits crop physiological damage and yield reduction. Knowledge of crop water stress monitoring approaches can be effective in optimizing the use of agricultural water. Understanding the physiological mechanisms of crop responding and adapting to water deficit ensures sustainable agricultural management and food supply. This aim could be achieved by analyzing and diagnosing crop characteristics and their interlinkage with the surrounding environment. Assessments of plant functional types (e.g., leaf area and structure, tree height, rate of evapotranspiration, rate of photosynthesis), controlling changes, and irrigated areas mapping. Calculating thresholds of soil water content parameters, crop water use efficiency, and Nitrogen status make irrigation scheduling decisions more accurate by preventing water limitations between irrigations. Combining Remote Sensing (RS), the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning Algorithms (MLAs) can improve measurement accuracies and automate irrigation scheduling. This paper is a review structured by surveying about 100 recent research studies to analyze varied approaches in terms of providing high spatial and temporal resolution mapping, sensor-based Variable Rate Application (VRA) mapping, the relation between spectral and thermal reflectance and different features of crop and soil. The other objective is to assess RS indices formed by choosing specific reflectance bands and identifying the correct spectral band to optimize classification techniques and analyze Proximal Optical Sensors (POSs) to control changes. The innovation of this paper can be defined as categorizing evaluation methodologies of precision irrigation (applying the right practice, at the right place, at the right time, with the right quantity) controlled by soil moisture levels and sensitiveness of crops to water stress, into pre-processing, processing (retrieval algorithms), and post-processing parts. Then, the main idea of this research is to analyze the error reasons and/or values in employing different approaches in three proposed parts reported by recent studies. Additionally, as an overview conclusion tried to decompose different approaches to optimizing indices, calibration methods for the sensors, thresholding and prediction models prone to errors, and improvements in classification accuracy for mapping changes.

Keywords: agricultural crops, crop water stress detection, irrigation scheduling, precision agriculture, remote sensing

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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Authors: Angelis P. Barlampas

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Learning Objectives: The purpose of this study is to inform briefly the reader about the applications of AI in chest radiology. Background: Currently, there are 190 FDA-approved radiology AI applications, with 42 (22%) pertaining specifically to thoracic radiology. Imaging findings OR Procedure details Aids of AI in chest radiology1: Detects and segments pulmonary nodules. Subtracts bone to provide an unobstructed view of the underlying lung parenchyma and provides further information on nodule characteristics, such as nodule location, nodule two-dimensional size or three dimensional (3D) volume, change in nodule size over time, attenuation data (i.e., mean, minimum, and/or maximum Hounsfield units [HU]), morphological assessments, or combinations of the above. Reclassifies indeterminate pulmonary nodules into low or high risk with higher accuracy than conventional risk models. Detects pleural effusion . Differentiates tension pneumothorax from nontension pneumothorax. Detects cardiomegaly, calcification, consolidation, mediastinal widening, atelectasis, fibrosis and pneumoperitoneum. Localises automatically vertebrae segments, labels ribs and detects rib fractures. Measures the distance from the tube tip to the carina and localizes both endotracheal tubes and central vascular lines. Detects consolidation and progression of parenchymal diseases such as pulmonary fibrosis or chronic obstructive pulmonary disease (COPD).Can evaluate lobar volumes. Identifies and labels pulmonary bronchi and vasculature and quantifies air-trapping. Offers emphysema evaluation. Provides functional respiratory imaging, whereby high-resolution CT images are post-processed to quantify airflow by lung region and may be used to quantify key biomarkers such as airway resistance, air-trapping, ventilation mapping, lung and lobar volume, and blood vessel and airway volume. Assesses the lung parenchyma by way of density evaluation. Provides percentages of tissues within defined attenuation (HU) ranges besides furnishing automated lung segmentation and lung volume information. Improves image quality for noisy images with built-in denoising function. Detects emphysema, a common condition seen in patients with history of smoking and hyperdense or opacified regions, thereby aiding in the diagnosis of certain pathologies, such as COVID-19 pneumonia. It aids in cardiac segmentation and calcium detection, aorta segmentation and diameter measurements, and vertebral body segmentation and density measurements. Conclusion: The future is yet to come, but AI already is a helpful tool for the daily practice in radiology. It is assumed, that the continuing progression of the computerized systems and the improvements in software algorithms , will redder AI into the second hand of the radiologist.

Keywords: artificial intelligence, chest imaging, nodule detection, automated diagnoses

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