Search results for: young children with learning disabilities

Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Pil Kyoo Jo, Jee Young Kim, Yu Jin Oh, Sohyun Park, Young Ha Joo, Hye Suk Kim, Semi Kang

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When convenience drives daily food choices, the increased consumption of processed foods may be associated with the increased intakes of sodium and fat and further with the onset of chronic diseases. The purpose of this study was to investigate the levels of sodium, saturated fat, and calories intakes through processed foods and the dietary patterns among adult populations in South Korea. We used the nationally representative data from the 5th Korea National Health and Nutrition Examination Survey (KNHANES, 2010-2012) and a cross-sectional survey on the eating behaviors among university students(N=893, 380 men, 513 women) aged from 20 to 24 years. Results showed that South Koreans consumed 43.5% of their total food consumption from processed foods. The 24-hour recalls data showed that 77% of sodium, 60% of fats, 59% of saturated fat, and 44% of calories were consumed from processed food. The intake of processed foods increased by 1.7% in average since 2008 annually. Only 33% of processed food that respondents consumed had nutrition labeling. The data from university students showed that students selected processed foods in convenience store when eating alone compared to eating with someone else. Given the convenience and lack of time, more people will consume processed foods and it may impact their overall dietary intake and further their health. In order to help people to make healthier food choices, regulations and policies to reduce the potentially unhealthy nutrients of processed foods should be strengthened. This research was supported by the National Research Foundation of Korea for 2011 Korea-Japan Basic Scientific Cooperation Program. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2015S1A5B6037369).

Keywords: sodium, fat, processed foods, diet trends

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Authors: Kevin R. Wilson, Roger Mantie

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Community arts-based learning and participatory education are pedagogical techniques that serve to be advantageous for students, curriculum development, and local communities. Using an interpretive approach to examine the significance of this arts-informed research in relation to the eight ‘design imperatives’ proposed as the new model for measuring quality in scholarship for Arizona State University as ‘A New American University’, the purpose of this study was to investigate personal, social, and cultural benefits resulting from student engagement in interdisciplinary community-based projects. Students from a graduate level music education class at the ASU Tempe campus (n=7) teamed with students from an undergraduate level community development class at the ASU Downtown Phoenix campus (n=14) to plan, facilitate, and evaluate seven community-based projects in several locations around the Phoenix-metro area. Data was collected using photo evidence, student reports, and evaluative measures designed by the students. The effectiveness of each project was measured in terms of their ability to meet the eight design imperatives to: 1) leverage place; 2) transform society; 3) value entrepreneurship; 4) conduct use-inspired research; 5) enable student success; 6) fuse intellectual disciplines; 7) be socially embedded; and 8) engage globally. Results indicated that this community arts-based project sufficiently captured the essence of each of these eight imperatives. Implications for how the nature of this interdisciplinary initiative allowed for the eight imperatives to manifest are provided, and project success is expounded upon in relation to utility of each imperative. Discussion is also given for how this type of service learning project formatted within the ‘New American University’ model for measuring quality in academia can be a beneficial pedagogical tool in higher education.

Keywords: community arts-based learning, participatory education, pedagogy, service learning

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Authors: May Ling González-Ruiz, Ana Cristina Solís-Solís

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Everyday more people can thrive towards the dream of pursuing a university diploma. This can be more attainable for some than for others who may face different types of limitations. Even though not all limitations come from within the individual but most of the times they come from without it may include the environment, the support of the person’s family, the school – its infrastructure, administrative procedures, and attitudes. This is a qualitative type of research that is developed through a case study. It is based on the experiences of two students who are visually impaired and who have attended a public university in Costa Rica. We enquire about the experiences of these two students in the English as a Foreign Language courses at the university scenario. An in-depth analysis of their lived experiences is presented. Their values, attitudes, and expectations serve as the guiding elements for this research. Findings are presented in light of the Social Justice Approach to inclusive education. Some of the most salient aspects found have to do with the attitudes the students used to face challenges; others point at those elements that may have hindered the learning experience of the persons observed and to those that encouraged them to continue their journey and successfully achieve a diploma.

Keywords: inclusion, case study, visually impaired student, learning experience, social justice approach

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Authors: Anju Vaidya

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Sanitation is concerned with proper disposal of human excreta, waste water and promotion of hygiene. Lack of sanitation impacts our environment affecting our finance, schooling, health, and thus exacerbating poverty, discrimination and exclusion of the marginalized group. Sanitation can be a route and one of the most important factor to reach the goals of all Millennium Development goals. This study aims at exploring what are the rights to sanitation of the people, how it is enacted and what challenges are being faced while implementing the right to sanitation in South-Asian countries (India, Nepal, Pakistan, Bangladesh, Srilanka) at government, non-government and international level. This study also aims at finding how right sanitation is interlinked with children rights. The available reports submitted by government and civil society organizations working in South-Asian countries from the website of the Office of High Commissioner for Human Rights that were submitted under International covenant on economic, social and cultural rights and Convention on rights of the child have been selected and analyzed. The study uses Literature review to analyze these UN documents submitted from 2000 to 2015 in the context of South-Asian countries. Preliminary insight reveals that sanitation is recognized as one of the important factor to attain adequate standard of living. It has been found that inadequate sanitation has been a major factor that affects all aspects of life and one of its devastating impacts is increased child mortality. Many efforts have been made at national and international level in South-Asian countries to improve the state of sanitation and sanitation services. Various approaches such as Community led Total Sanitation, School led Total Sanitation, establishing Open Defecation free zone, water supply services and other sanitation and hygiene awareness programs are being launched. Despite different efforts and programs being implemented, sanitation and hygiene practices and behavior change remains to be a big challenge. Disparity in access and imbalance between urban and rural services and geographical regions, inadequate financing, clear policy framework and fragile functionality are some of the significant challenges faced while implementing these programs. Children are one of the most vulnerable group that are affected to a large extent. The study brings into light varied approaches that are being made and challenges that are being faced by government, non-government and civil society organizations while implementing the programs and strategies related to sanitation. It also highlights the relation of sanitation as a human right with child rights. This can help the stakeholders and policymakers better understand that improving sanitation situation is a process that requires learning, planning and behavior change and achieving sanitation coverage targets and motivating behavior change requires additional tools based on participation, non-discrimination and process approaches for planning and feedback.

Keywords: challenges, child rights, open defecation, sanitation as a human right

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Authors: Oren Shtayermman

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The current investigation expended on research among parents caring for a child who is diagnosed with an autism spectrum disorder (ASD). An online web survey was used to collect data from 253 parents caring for a child with a diagnosis of ASD. Both parents reported on elevated levels of parental stress associated with caring for the child on the spectrum. In addition, lower levels of marital satisfaction were found in both parents. About 13% of the parents in the sample met the diagnostic criteria for Major Depressive Disorder and About 15% of the parents met the diagnostic criteria for Generalized Anxiety Disorder. Although the majority of the sample was females (94%) significant differences were found between males and females in relation to meeting the diagnostic criteria for Major Depressive Disorder and for Generalized Anxiety Disorder. Higher levels of stress were associated with higher number of Generalized Anxiety Disorder symptoms and higher number of Major Depressive Disorder symptoms. Findings from this study indicate how vulnerable parents and especially females are in relation to caring to a child diagnosed with ASD. Educational Objectives: At the conclusion of the paper, the readers should be able to: -Identify levels of stress and marital satisfaction among parents caring for a child diagnosed with autism spectrum disorder, -Recognize the impact of stress on the development of mental health issues, -Name the two most common mood and anxiety related disorders associated with caring for a child diagnosed with an autism spectrum disorder.

Keywords: autism, stress, parents, children

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Arosha Rashmi De Silva, Ananda Chandrasekara

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This study seeks to comprehensively examine the influence of fast-food consumption and physical activity levels on the body weight of young employees within the private sector of Sri Lanka. The escalating popularity of fast food has raised concerns about its nutritional content and associated health ramifications. To investigate this phenomenon, a cohort of 100 individuals aged between 25 and 45, employed in Sri Lanka's private sector, participated in this research. These participants provided socio-demographic data through a standardized questionnaire, enabling the characterization of their backgrounds. Additionally, participants disclosed their frequency of fast-food consumption and engagement in physical activities, utilizing validated assessment tools. The collected data was meticulously compiled into an Excel spreadsheet and subjected to rigorous statistical analysis. Descriptive statistics, such as percentages and proportions, were employed to delineate the body weight status of the participants. Employing chi-square tests, our study identified significant associations between fast-food consumption, levels of physical activity, and body weight categories. Furthermore, through binary logistic regression analysis, potential risk factors contributing to overweight and obesity within the young employee cohort were elucidated. Our findings revealed a disconcerting trend, with 6% of participants classified as underweight, 32% within the normal weight range, and a substantial 62% categorized as overweight or obese. These outcomes underscore the alarming prevalence of overweight and obesity among young private-sector employees, particularly within the bustling urban landscape of Colombo, Sri Lanka. The data strongly imply a robust correlation between fast-food consumption, sedentary behaviors, and higher body weight categories, reflective of the evolving lifestyle patterns associated with the nation's economic growth. This study emphasizes the urgent need for effective interventions to counter the detrimental effects of fast-food consumption. The implementation of awareness campaigns elucidating the adverse health consequences of fast food, coupled with comprehensive nutritional education, can empower individuals to make informed dietary choices. Workplace interventions, including the provision of healthier meal alternatives and the facilitation of physical activity opportunities, are essential in fostering a healthier workforce and mitigating the escalating burden of overweight and obesity in Sri Lanka

Keywords: fast food consumption, obese, overweight, physical activity level

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Authors: I. A. Libata

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The present study was carried out to determine the attitudes of Secondary School Students towards Biology in Birnin Kebbi metropolis. The population of the study is 2680 SS 2 Secondary School Students in Birnin Kebbi metropolis. Proportionate random sampling was used in selecting the samples. Oppinnionnaire was the only instrument used in the study. The instrument was subjected to test-retest reliability. The reliability index of the instrument was 0.69. Overall scores of the Students were analyzed and a mean score was determined, the mean score of students was 85. There were no significant differences between the attitudes of male and female students. The results also revealed that there was significant difference between the attitude of science and art students. The results also revealed that there was significant difference between the attitude of public and private school students. The study also reveals that majority of students in Birnin Kebbi Metropolis have positive attitudes towards biology. Based on the findings of this study, the researcher recommended that teachers should motivate students, which they can do through their teaching styles and by showing them the relevance of the learning topics to their everyday lives. Government and the school management should create the learning environment that helps motivate students not only to come to classes but also want to learn and enjoy learning Biology.

Keywords: attitudes, students, Birnin-Kebbi, metropolis

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Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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Authors: Inkeri Jaaskelainen

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The aim of this study is to shed light on what is it like to study in apprenticeship training using intermediate (or even lower level) Finnish. The aim is to find out and describe these students' experiences and feelings while acquiring a profession in Finnish as it is important to understand how immigrant background adult learners learn and how their needs could be better taken into account. Many students choose apprenticeships and start vocational training while their language skills in Finnish are still very weak. At work, students should be able to simultaneously learn Finnish and do vocational studies in a noisy, demanding, and stressful environment. Learning and understanding new things is very challenging under these circumstances, and sometimes students get exhausted and experience a lot of stress - which makes learning even more difficult. Students are different from each other, and so are their ways to learn. Both duties at work and school assignments require reasonably good general language skills, and, especially at work, language skills are also a safety issue. The empirical target of this study is a group of students with an immigrant background who studied in various fields with intensive L2 support in 2016–2018 and who by now have completed a vocational upper secondary qualification. The interview material for this narrative study was collected from those who completed apprenticeship training in 2019–2020. The data collection methods used are a structured thematic interview, a questionnaire, and observational data. Interviewees with an immigrant background have an inconsistent cultural and educational background - some have completed an academic degree in their country of origin while others have learned to read and write only in Finland. The analysis of the material utilizes thematic analysis, which is used to examine learning and related experiences. Learning a language at work is very different from traditional classroom teaching. With evolving language skills, at an intermediate level at best, rushing and stressing makes it even more difficult to understand and increases the fear of failure. Constant noise, rapidly changing situations, and uncertainty undermine the learning and well-being of apprentices. According to preliminary results, apprenticeship training is well suited to the needs of an adult immigrant student. In apprenticeship training, students need a lot of support for learning and understanding a new communication and working culture. Stress can result in, e.g., fatigue, frustration, and difficulties in remembering and understanding. Apprenticeship training can be seen as a good path to working life. However, L2 support is a very important part of apprenticeship training, and it indeed helps students to believe that one day they will graduate and even get employed in their new country.

Keywords: apprenticeship training, vocational basic degree, Finnish learning, wee-being

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Authors: Paola Molteni, Luigi d’Alonzo

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Background: Sensory issues are now considered one of the key aspects in defining and diagnosing autism, changing the perspectives on behavioural analysis and intervention in mainstream educational services. However, Italian teachers’ training is yet not specific on the topic of autism and its sensory-related effects and this research investigates the teacher’s capability in understanding the student’s needs and his/her challenging behaviours considering sensory perceptions. Objectives: The research aims to analyse mainstream schools teachers’ awareness on students’ sensory perceptions and how this affects classroom inclusion and learning process. The research questions are: i) Are teachers able to identify student’s sensory issues?; ii) Are trained teachers more able to identify sensory problems then untrained ones?; iii) What is the impact of sensory issues on inclusion in mainstream classrooms?; iv) What should teachers know about autistic sensory dimensions? Methods: This research was designed as a pilot study that involves a multi-methods approach, including action and collaborative research methodology. The designed research allows the researcher to catch the complexity of a province school district (from kindergarten to high school) through a deep detailed analysis of selected aspects. The researcher explored the questions described above through 133 questionnaires and 6 focus groups. The qualitative and quantitative data collected during the research were analysed using the Interpretative Phenomenological Analysis (IPA). Results: Mainstream schools teachers are not able to confidently recognise sensory issues of children included in the classroom. The research underlines: how professionals with no specific training on autism are not able to recognise sensory problems in students on the spectrum; how hearing and sight issues have higher impact on classroom inclusion and student’s learning process; how a lack of understanding is often followed by misinterpretations of the impact of sensory issues and challenging behaviours. Conclusions: As this research has shown, promoting and enhancing the importance of understanding sensory issues related to autism is fundamental to enable mainstream schools teachers to define educational and life-long plans able to properly answer the student’s needs and support his/her real inclusion in the classroom. This study is a good example of how the educational research can meet and help the daily practice in working with people on the autism spectrum and support the training design for mainstream school teachers: the emerging need of designed preparation on sensory issues is fundamental to be considered when planning school district in-service training programmes, specifically declined for inclusive services.

Keywords: autism spectrum condition, scholastic inclusion, sensory overload, teacher's training

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Authors: Rohan Roberts

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The purpose of this project was to collaborate with a group of high-functioning, more-able students (aged 15-18) to promote STEM Education and a love for science by bringing a cosmic perspective into the classroom and high school environment. This was done using 21st century science of learning, a focus on the latest research on Neuroeducation, and modern pedagogical methods based on Howard Gardner's theory of Multiple Intelligences, Bill Lucas’ theory of New Smarts, and Sir Ken Robinson’s recommendations on encouraging creativity. The result was an increased sense of passion, excitement, and wonder about science in general, and about the marvels of space and the universe in particular. In addition to numerous unique and innovative science-based initiatives, clubs, workshops, and science trips, this project also saw a marked rise in student-teacher collaboration in science learning and in student engagement with the general public through the press, social media, and community-based initiatives. This paper also outlines the practical impact that bringing a cosmic perspective into the classroom has had on the lives, interests, and future career prospects of the students involved in this endeavour.

Keywords: cosmic perspective, gifted and talented, neuro-education, STEM education

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Authors: Medan Isaeva, Anna Degtyareva

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Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Colleen Cleveland, W. Adam Baldowski

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In the dynamic realm of online education, the integration of games and entertainment has emerged as a powerful strategy to captivate learners, drive active participation, and cultivate meaningful learning experiences. This abstract presents an overview of the upcoming conference, "Game On," dedicated to exploring the transformative impact of gamification, interactive simulations, and multimedia content in the digital learning landscape. Introduction: The conference aims to blur the traditional boundaries between education and entertainment, inspiring learners of diverse ages and backgrounds to actively engage in their online learning journeys. By leveraging the captivating elements of games and entertainment, educators can enhance motivation, retention, and deep understanding among virtual classroom participants. Conference Highlights: Commencing with an exploration of theoretical foundations drawing from educational psychology, instructional design, and the latest pedagogical research, participants will gain valuable insights into the ways gamified elements elevate the quality of online education. Attendees can expect interactive sessions, workshops, and case studies showcasing best practices and innovative strategies, including game-based assessments and virtual reality simulations. Inclusivity and Diversity: The conference places a strong emphasis on inclusivity, accessibility, and diversity in the integration of games and entertainment for educational purposes. Discussions will revolve around accommodating diverse learning styles, overcoming potential challenges, and ensuring equitable access to engaging educational content for all learners. Educational Transformation: Educators, instructional designers, and e-learning professionals attending "Game On" will acquire practical techniques to elevate the quality of their online courses. The conference promises a stimulating and informative exploration of blending education with entertainment, unlocking the untapped potential of games and entertainment in online education. Conclusion: "Game On" invites participants to embark on a journey that transforms online education by harnessing the power of entertainment. This event promises to be a cornerstone in the evolution of virtual learning, offering valuable insights for those seeking to create a more engaging and effective online educational experience. Join us as we explore new horizons, pushing the boundaries of online education through the fusion of games and entertainment.

Keywords: online education, games, entertainment, psychology, therapy, pop culture

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Authors: Inezia Aurelia, Soebowo Musa

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Many firms still fail to develop organizational agility. There are more than 40% of organizations think that they are low/not agile in facing market change. Organizational culture plays an important role in developing the organizations to be adaptive in order to manage the VUCA effectively. This study examines the relationships of organizational culture towards participative leadership, employee satisfaction, employee work motivation, organizational learning, and absorptive capacity in developing organizational agility in managing the VUCA environment. 263 employees located from international chemical-based company offices across the globe who have worked for more than three years were the respondents in this study. This study showed that organizational clan culture promotes the development of participative leadership, which it has an empowering effect on people in the organization resulting in employee satisfaction. The study also confirms the role of organizational culture in creating organizational behavior within the organization that fosters organizational learning, absorptive capacity, and organizational agility, while the study also found that the relationship between participative leadership and employee work motivation is not significant.

Keywords: absorptive capacity, employee satisfaction, employee work motivation, organizational agility, organizational culture, organizational learning, participative leadership

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Authors: Shaan Khosla, Jon Krohn

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In a recruiting context, machine learning models are valuable for recommendations: to predict the best candidates for a vacancy, to match the best vacancies for a candidate, and compile a set of similar candidates for any given candidate. While useful to create these models, validating their accuracy in a recommendation context is difficult due to a sparsity of data. In this report, we use network graph data to generate useful representations for candidates and vacancies. We use candidates and vacancies as network nodes and designate a bi-directional link between them based on the candidate interviewing for the vacancy. After using node2vec, the embeddings are used to construct a validation dataset with a ranked order, which will help validate new recommender systems.

Keywords: AI, machine learning, NLP, recruiting

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Authors: Hirokatsu Kawashima

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In an attempt to elucidate relationships between listening to music and pronunciation learning, a classroom-based investigation was conducted with Japanese EFL learners (n=45). The subjects were instructed to listen to English songs they liked on YouTube, especially paying attention to phonologically similar vowel and consonant minimal pair words (e.g., live and leave). This kind of activity, which included taking notes, was regularly carried out in the classroom, and the same kind of task was given to the subjects as homework in order to reinforce the in-class activity. The duration of these activities was eight weeks, after which the program was evaluated on a 9-point scale (1: the lowest and 9: the highest) by learners’ self-evaluation. The main questions for this evaluation included 1) how good the learners had been at pronouncing vowel and consonant minimal pair words originally, 2) how often they had listened to songs good for pronouncing vowel and consonant minimal pair words, 3) how frequently they had moved their mouths to vowel and consonant minimal pair words of English songs, and 4) how much they thought the program would support and enhance their pronunciation learning of phonologically similar vowel and consonant minimal pair words. It has been found, for example, A) that the evaluation of this program is by no means low (Mean: 6.51 and SD: 1.23), suggesting that listening to music may support and enhance pronunciation learning, and B) that listening to consonant minimal pair words in English songs and moving the mouth to them are more related to the program’s evaluation (r =.69, p=.00 and r =.55, p=.00, respectively) than listening to vowel minimal pair words in English songs and moving the mouth to them (r =.45, p=.00 and r =.39, p=.01, respectively).

Keywords: minimal pair, music, pronunciation, song

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Authors: Saifunnahar

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As a former English colony, the relationship of Bangladesh with the English language goes a long way back. English is taught as a compulsory subject in Bangladesh from an early age starting from grade 1 and continuing through the 12th, yet, students are not competent enough to communicate in English proficiently. To improve students’ English language competency, the Bangladesh Ministry of Education introduced communicative language teaching (CLT) methods in English classrooms in the 1990s. It has been decades since this effort was taken, but the students’ level of proficiency is still not satisfactory. The main reason behind this failure is that CLT-based teaching-learning methods have not been effectively implemented. Very little research has been conducted to address the issues English as a foreign language (EFL) classrooms are facing to carry out CLT methodologies in secondary schools (grades 6 to 10) in Bangladesh. Though the secondary level is crucial for students’ language learning and retention, EFL classrooms are marked with various issues that make teaching-learning harder for teachers and students. This study provides an overview of the status of CLT in EFL classrooms and the reasons behind failing to implement CLT in secondary schools in Bangladesh through an analysis of the qualitative data collected from different literature. Based on the findings, effective approaches have been recommended to employ CLT in EFL classrooms.

Keywords: Bangladesh, communicative language teaching, English as a foreign language, secondary schools, pedagogy

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Aminath Waseela, Vinesh Chandra, Shaun Nykvist,

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The success of technology integration initiatives hinges on the knowledge and skills of teachers to effectively integrate technology in classroom teaching. Consequently, gaining an understanding of teachers' technology knowledge and its integration can provide useful insights on strategies that can be adopted to enhance teaching and learning, especially in developing country contexts where research is scant. This paper extends existing knowledge on teachers' use of technology by developing a conceptual framework that recognises how three key types of knowledge; content, pedagogy, technology, and their integration are at the crux of teachers' technology use while at the same time is amenable to empirical studies. Although the aforementioned knowledge is important for effective use of technology that can result in enhanced student engagement, literature on how this knowledge leads to effective technology use and enhanced student engagement is limited. Thus, this theoretical paper proposes a framework to explore teachers' knowledge through the lens of the Technological Pedagogical and Content Knowledge (TPACK); the integration of technology in classroom teaching through the Substitution Augmentation Modification and Redefinition (SAMR) model and how this affects students' learning through the Bloom's Digital Taxonomy (BDT) lens. Studies using this framework could inform the design of professional development to support teachers to develop skills for effective use of available technology that can enhance student learning engagement.

Keywords: information and communication technology, ICT, in-service training, small island developing states, SIDS, student engagement, technology integration, technology professional development training, technological pedagogical and content knowledge, TPACK

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Authors: Xiaoheng Tan, Xianfang Li, Tan Guo, Yuchuan Liu, Zhijun Yang, Hongye Li, Kai Fu, Yufang Wu, Heling Gong

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The image data collected in reality often have high dimensions, and it contains noise and redundant information. Therefore, it is necessary to extract the compact feature expression of the original perceived image. In this process, effective use of prior knowledge such as data structure distribution and sample label is the key to enhance image feature discrimination and robustness. Based on the above considerations, this paper proposes a local preserving discriminant feature learning model based on graph optimization. The model has the following characteristics: (1) Locality preserving constraint can effectively excavate and preserve the local structural relationship between data. (2) The flexibility of graph learning can be improved by constructing a new local geometric structure graph using label information and the nearest neighbor threshold. (3) The L₂,₁ norm is used to redefine LDA, and the diagonal matrix is introduced as the scale factor of LDA, and the samples are selected, which improves the robustness of feature learning. The validity and robustness of the proposed algorithm are verified by experiments in two public image datasets.

Keywords: feature extraction, graph optimization local preserving projection, linear discriminant analysis, L₂, ₁ norm

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Authors: Jolien Rijlaarsdam, Charlotte A. M. Cecil, J. Marieke Buil, Pol A. C. Van Lier, Edward D. Barker

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Although there is mounting evidence that the experience of being bullied associates with both internalizing and externalizing symptoms, it is not known yet whether the identified associations are specific to these symptoms or shared between them. The primary focus of this study is to assess the prospective associations of bullying exposure with both general and specific (i.e., internalizing, externalizing) factors of psychopathology. This study included data from 6,210 children participating in the Avon Longitudinal Study of Parents and Children (ALSPAC). Child bullying was measured by self-report at ages 8 and 10 years. Child psychopathology symptoms were assessed by parent-interview, using the Development and Well-being Assessment (DAWBA) at ages 7 and 13 years. Bullying exposure is significantly associated with the general psychopathology factor in early adolescence. In particular, chronically victimized youth exposed to multiple forms of bullying (i.e., both overt and relational) showed the highest levels of general psychopathology. Bullying exposure is also associated with both internalizing and externalizing factors from the correlated-factors model. However, the effect estimates for these factors decreased considerably in size and dropped to insignificant for the internalizing factor after extracting the shared variance that belongs to the general factor of psychopathology. In an integrative longitudinal model, higher levels of general psychopathology at age seven are associated with bullying exposure at age eight, which, in turn, is associated with general psychopathology at age 13 through its two-year continuity. Findings suggest that exposure to bullying is a risk factor for a more general vulnerability to psychopathology through mutually influencing relationships.

Keywords: bullying exposure, externalizing, general psychopathology, internalizing, longitudinal

Procedia PDF Downloads 132

Authors: Ruth Nsibirano

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Online mode of delivery in higher institutions of learning, popularly known in some circles as e-Learning or distance education is a new phenomenon that is steadily taking root in African universities but specifically at Makerere University. For slightly over a decade, the Department of Open and Distance Learning has been offering the first generation mode of distance education. In this, learning and teaching experiences were based on the use of hard copy materials circulated through postal services in a rather correspondence mode. There were more challenges to this including high dropout rates, limited support to the learners and sustainability issues. Fortunately, the Department was supported by the Norwegian Government through a NORHED grant to “leapfrog” to the fifth generation of distance education that makes more use of educational technologies and tools. The capacity of faculty staff was gradually enhanced through a series of training to handle the upgraded structure of fifth generation distance education. The trained staff was then tasked to develop modules befitting an online delivery mode, for use on the program. This paper will present attitudes, experiences of the course writers with a view of sharing the good practices that enabled them leap from e-faculty trainees to distinct online course writers. This perspective will hopefully serve as building blocks to enhance the capacity of other upcoming distance education programs in low capacity universities and also promote the uptake of e-Education on the continent and beyond. Methodologically the findings were collected through individual interviews with the 30 course writers. In addition, semi structured questionnaires were designed to collect data on the profile, challenges and lessons from the writers. Findings show that the attitudes of course writers on project supported activities are so much tagged to the returns from their committed efforts. In conclusion, therefore, it is strategically useful to assess and selectively choose which individual to nominate for involvement at the initial stages.

Keywords: distance education, online course content, staff attitudes, best practices in online learning

Procedia PDF Downloads 240

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Sherelle Lou Sumera Icutan, Sheila P. Cayabyab, Mary Jane Laruan, Paulo V. Cenas, Agustina R. Tactay

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This study critically analyzed the recent theses and dissertations of the Basic Education Curriculum (BEC) teachers who finished their graduate programs in selected higher educational institutions in Region I and CAR to be able to come up with a unified result from the varied results of the analyzed research works. All theses and dissertations completed by the educators/teachers/school personnel in the secondary and elementary public and private schools in Region 1 and CAR from AY 2003–2004 to AY 2007–2008 were classified first–as to work or non-work related; second–as to the different aspects of the curriculum: implementation, content, instructional materials, assessment instruments, learning, teaching, and others; third–as to being eligible for meta-analysis or not. Only studies found eligible for meta-analysis were subjected to the procedure. Aside from documentary analysis, the statistical treatments used in meta-analysis include the standardized effect size, Pearson’s correlation (r), the chi-square test of homogeneity and the inverse of the Fisher transformation. This study found out that the BEC-teachers usually probe on work-related researchers with topics that are focused on the learning performances of the students and on factors related to teaching. The development of instructional materials and assessment of implemented programs are also equally explored. However, there are only few researches on content and assessment instrument. Research findings on the areas of learning and teaching are the only aspects that are meta-analyzable. The research findings across studies in Region I and CAR of BEC teachers that focused on similar variables correlated to teaching do not vary significantly. On the contrary, research findings across studies in Region I and CAR that focused on variables correlated to learning performance significantly vary. Within each region, variations on the findings of research works related to learning performance that considered similar variables still exist. The combined finding on the effect size or relationship of the variables that are correlated to learning performance are low which means that effect is small but definite while the combined findings on the relationship of the variables correlated to teaching are slight or almost negligible.

Keywords: meta-analysis, BEC teachers, work-related research,

Procedia PDF Downloads 414

Authors: Tsung Chieh Ma, I-Ling Chen

Abstract:

Disclosing family origins to adoptees is an important topic in the adoption process. Adoption agencies usually educate adoptive parents on how to disclose to adoptees, but many adoptive parents worry that the disclosure will affect the parent–child relationship. Thus, how adoptees would like to receive the disclosure and whether they subjectively feel that the parent–child relationship is affected are both topics worthy of further discussion. This research takes a qualitative approach and connects with adoption agencies to interview six adoptees who are now adults. The purpose of the interviews is to learn about their experience receiving disclosures and their subjective feelings after learning of their family origins. The aim is to reveal the changes disclosure brought to the parent–child relationship and whether common concerns are raised due to the adoptive status. We also want to know about factors that affect their identification with their adopted status so that we can consequently give advice to other adoptive families. in this study finds that adoptees see disclosure as a process rather than an isolated event. The majority want to be told their family origin as early and proactively as possible and expect to learn the reasons they were given up for adoption and taken in as adoptees. The disclosure does not necessarily influence the parent–child relationship, and adoptees care more about the positive experiences they had with adoptive parents in their childhood. Moreover, adopted children seek contact with their original family mostly to understand why they were given up for adoption. The effects of disclosure depend on how the adoptive parents or other significant people in the lives of adoptees interpret the identity of the adoptees. That is, their response and attitude toward the identity have a lasting impact on the adoptees. The study suggests that early disclosure gives adoptees a chance to internalize the experience in the process and find self-identification.

Keywords: adoption, adoptees, disclosure of family origins, parent–child relationship, self-identity

Procedia PDF Downloads 65