Search results for: Deep learning based segmentation

Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

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Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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Authors: Muhammad Mooneeb Ali

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Institutions, where religious knowledge is given are known as madrassas. They also give formal education along with religious education. This study will be a pioneer to explore if MALL can be beneficial for madrassa students or not in formal educational situations. For investigation, an experimental study was planned in Punjab where the sample size was 100 students, 10 each from 10 different madrassas of Punjab, who are studying at the intermediate level (i.e., 11th grade). The madrassas were chosen through a convenient sampling method, whereas the learners were chosen by a simple random sampling method. A pretest was conducted, and on the basis of the results, the learners were divided into two equal groups (experimental and controlled). After two months of treatment, a posttest was conducted, and the results of both groups were compared. The results indicated that the performance of the experimental group was significantly better than the control one. This indicates that MALL elevates the performance of Madrassa students.

Keywords: english language learners, madrassa students, formal education, mobile assisted language learning (MALL), Pakistan.

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Erva Akin

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– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.

Keywords: artificial intelligence, copyright, data governance, machine learning

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Authors: Mahmoud M. S. Albattah

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Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Keywords: highway design, satellite technologies, remote sensing, GIS, image segmentation, classification

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Authors: C. W. Kan

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Cotton fibre is a commonly-used natural fibre because of its good fibre strength, high moisture absorption behaviour and minimal static problems. However, one of the main drawbacks of cotton fibre is wrinkling after washing, which is recently overcome by wrinkle-resistant treatment. 1,2,3,4-butanetetracarboxylic acid (BTCA) could improve the wrinkle-resistant properties of cotton fibre. Although the BTCA process is an effective method for wrinkle resistant application of cotton fabrics, reduced fabric strength was observed after treatment. Therefore, this paper would explore the use of atmospheric pressure plasma treatment under different discharge powers as a pretreatment process to enhance the application of BTCA process on cotton fabric without generating adverse effect. The aim of this study is to provide learning information to the users to know how the atmospheric pressure plasma treatment can be incorporated in textile finishing process with positive impact.

Keywords: learning materials, atmospheric pressure plasma treatment, cotton, wrinkle-resistant, BTCA

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Jason Michael Crozier

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The wrestling territories of the mid-twentieth century in the United States are widely considered the birthplace of modern professional wrestling, and by many professional wrestlers, to be a beacon of hope for the easing of racial tensions during the civil rights era and beyond. The performers writing on this period speak of racial equality but fail to acknowledge the exploitation of black athletes as a racialized capital commodity who suffered the challenges of systemic racism, codified by a false narrative of aspirational exceptionalism and equality measured by audience diversity. The promoters’ ability to equate racial and capital exploitation with equality leads to a broader discussion of the history of Muscular Christianity in the United States and the exploitation of black bodies. Narratives of racial erasure that dominate the historical discourse when examining athleticism and exceptionalism redefined how blackness existed and how physicality and race are conceived of in sport and entertainment spaces. When discussing the implications of race and professional wrestling, it is important to examine the role of promotions as ‘imagined communities’ where the social agency of wrestlers is defined and quantified based on their ‘desired elements’ as a performer. The intentionally vague nature of this language masks a deep history of racialization that has been perpetuated by promoters and never fully examined by scholars. Sympathetic racism and the omission of cultural identity are also key factors in the limitations and racial barriers placed upon black athletes in the squared circle. The use of sympathetic racism within professional wrestling during the twentieth century defined black athletes into two distinct categorizations, the ‘black savage’ or the ‘black minstrel’. Black wrestlers of the twentieth century were defined by their strength as a capital commodity and their physicality rather than their knowledge of the business and in-ring skill. These performers had little agency in their ability to shape their own character development inside and outside the ring. Promoters would often create personas that heavily racialized the performer by tying them to a regional past or memory, such as that of slavery in the deep south using dog collar matches and adoring black characters in chains. Promoters softened cultural memory by satirizing the historic legacy of slavery and the black identity.

Keywords: sympathetic racism, social agency, racial commodification, stereotyping

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Aregamalage Sujeewa Vijayanthi Polgampala, Fang Huang

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This study explores the genesis and development of concept mapping as a useful tool for science education and its effectiveness as technique for teaching and learning and evaluation for secondary science in schools and the role played by National College of Education science teachers. Concept maps, when carefully employed and executed serves as an integral part of teaching method and measure of effectiveness of teaching and tool for evaluation. Research has shown that science concept maps can have positive influence on student learning and motivation. The success of concept maps played in an instruction class depends on the type of theme selected, the development of learning outcomes, and the flexibility of instruction in providing library unit that is equipped with multimedia equipment where learners can interact. The study was restricted to 6 male and 9 female respondents' teachers in third-year internship pre service science teachers in Gampaha district Sri Lanka. Data were collected through 15 item questionnaire provided to learners and in depth interviews and class observations of 18 science classes. The two generated hypotheses for the study were rejected, while the results revealed that significant difference exists between factors influencing teachers' choice of concept maps, its usefulness and problems hindering the effectiveness of concept maps for teaching and learning process of secondary science in schools. It was examined that concept maps can be used as an effective measure to evaluate students understanding of concepts and misconceptions. Even the teacher trainees could not identify, key concept is on top, and subordinate concepts fall below. It is recommended that pre service science teacher trainees should be provided a thorough training using it as an evaluation instrument.

Keywords: concept maps, evaluation, learning science, misconceptions

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Authors: Rizky Oktaviana

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The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

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Authors: Temesgen Yadeta, Abbi Lemma, Maina Faith, Adula Bekele Hunde

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Effective teaching plays a central role in students’ success in school. The main purpose of the study was to understand how engaging in a lesson study could help to develop secondary school mathematics teachers’ effective teaching practices to support students’ learning better. The research was conducted in Jimma City and employed design-based research with qualitative and quantitative data collected from two secondary schools and 12 mathematics teachers. A purposive sampling technique was used to select participants. Interviews, observations, document analysis, and questionnaires were the main sources of data. Qualitative data were analyzed through coding, categorizing, and thematizing supported by Atlas-ti qualitative data analysis software. Quantitative data were analyzed using mean, standard deviations, medians, and a Wilcoxon-ranked signed test supported by statistical packages for social sciences software. The findings of the study revealed that engaging in lesson study built mathematics teachers’ effective teaching practices. School leaders’ positive attitudes and initiative towards the lesson study were found to be supportive. Teachers’ collaboration, commitment with determination, and active participation during the study periods were also found to be supportive. Shortage of time and teachers’ high teaching load had constrained teachers’ active engagement in lesson study during study periods. In conclusion, the lesson study provided a more practical link between teachers’ professional learning activities and actual classroom practices. Therefore, it would be crucial to integrate lesson study into the present school-based teachers’ pedagogical capacity-building program in the country. It would also be beneficial to extend the merits of lesson study to other school subjects and more schools in the country based on their specific school contexts to build teachers’ effective teaching practices.

Keywords: effective teaching practices, lesson study, mathematics teachers, professional development, secondary school

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Raul G. Angeles

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The Philippine government instituted major reforms in its educational system. The Department of Education pushes the K to 12 program that makes kindergarten mandatory and adds two years of senior high school to the country's basic education. In essence, the students’ stay in basic education particularly those who are supposedly going to college is extended. The majority of the students expressed that they will be taking the Academic Track of the Senior High School curriculum specifically the Science, Technology, Engineering and Mathematics (STEM) and General Academic (GA) strands. Almost certainly, instruction should match the students' styles and thus through this descriptive study a city survey was conducted to explore the teaching strategies preferences of junior high school students and teachers who will be promoted to senior high school during the Academic Year 2016-2017. This study was conducted in selected public and private secondary schools in Metro Manila. Questionnaires were distributed to students and teachers; and series of follow-up interviews were also carried out to generate additional information. Preferences of students are centered on employing innovations such as technology, cooperative and problem-based learning. While the students will still be covered by basic education their interests in science are sparking to a point where the usual teaching styles may no longer work to them and for that cause, altering the teaching methods is recommended to create a teacher-student style matching. Other effective strategies must likewise be implemented.

Keywords: curriculum development, effective teaching strategies, problem-based learning, senior high school, science education, technology

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Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha

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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.

Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI

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Authors: Chen-Jung Chen, Yi-Chang Chen

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While traditional virtual reality and augmented reality only allow for small movement learning and cannot provide a truly immersive teaching experience to give it the illusion of movement, the new technology of both content creation and immersive interactive simulation of the metaverse can just reach infinite close to the natural teaching situation. However, the mixed reality virtual classroom of metaverse has not yet explored its theory, and it is rarely implemented in the situational simulation teaching of nursing education. Therefore, in the first year, the study will intend to use grounded theory and case study methods and in-depth interviews with nursing education and information experts. Analyze the interview data to investigate the uniqueness of metaverse development. The proposed analysis will lead to alternative theories and methods for the development of nursing education. In the second year, it will plan to integrate the metaverse virtual situation simulation technology into the alternate teaching strategy in the pediatric nursing technology course and explore the nursing students' use of this teaching method as the construction of personal technology and experience. By leveraging the unique features of distinct teaching platforms and developing processes to deliver alternative teaching strategies in a nursing technology teaching environment. The aim is to increase learning achievements without compromising teaching quality and teacher-student relationships in the post-pandemic era. A descriptive and convergent mixed methods design will be employed. Sixty third-grade nursing students will be recruited to participate in the research and complete the pre-test. The students in the experimental group (N=30) agreed to participate in 4 real-time mixed virtual situation simulation courses in self-practice after class and conducted qualitative interviews after each 2 virtual situation courses; the control group (N=30) adopted traditional practice methods of self-learning after class. Both groups of students took a post-test after the course. Data analysis will adopt descriptive statistics, paired t-tests, one-way analysis of variance, and qualitative content analysis. This study addresses key issues in the virtual reality environment for teaching and learning within the metaverse, providing valuable lessons and insights for enhancing the quality of education. The findings of this study are expected to contribute useful information for the future development of digital teaching and learning in nursing and other practice-based disciplines.

Keywords: metaverse, post-pandemic era, online virtual classroom, immersive teaching

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Authors: Khedidja Benaicha Mati

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The present research tries to highlight a very crucial issue which exists at the level of the faculty of Economics and Management at Chlef university. This issue is represented by the challenges and difficulties which face the teaching / learning process in the faculty on the part of the language teachers, the learners, and the administration staff, including mainly the absence of an agreed syllabus, lack of teaching materials, teachers’ qualifications and training, timing, coefficient, and lack of motivation and interest amongst students. All these negative factors make teaching and learning EFL rather ambiguous, ineffective and unsatisfactory. The students at the faculty of Economics and Management are looking for acquiring not only GE but also technical English to respond efficiently to the ongoing changes at the various levels most notably economy, business, technology, and sciences. Therefore, there is a need of ESP programmes which would focus on developing the communicative competence of the learners in their specific field of study or work. The aim of the present research is to explore the ways of improving the actual situation of teaching English in the faculty of Economics and to make the English courses more purposive, fulfilling and satisfactory. The sample population focused on second and third-year students of Economics from different specialties mainly commercial sciences, insurance and banking, accountancy, and management. This is done through a questionnaire which inquires students about their learning weaknesses, difficulties and challenges they encounter, and their expectations of the subject matter.

Keywords: faculty of economics and management, challenges, teaching/ learning process, EFL, GE, ESP, English courses, communicative competence

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Authors: Hoi Nga Ng, Kam Weng Boey, Chi Wai Kwan

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Supporters of Inclusive education proclaim that all students, regardless of disabilities or special educational needs (SEN), have the right to study in the normal school setting. It is asserted that students with SEN would benefit in academic performance and psychosocial adjustment via participation in common learning activities within the ordinary school system. When more and more students of SEN completed their early schooling, institute of higher education become the setting where students of SEN continue their learning. This study aimed to investigate the school well-being, social relationship, and academic self-concept of students of SEN in higher education. The Perception of Inclusion Questionnaire (PIQ) was used as the measuring instruments. PIQ was validated and incorporated in a questionnaire designed for online survey. Participation was voluntary and anonymous. A total of 90 students with SEN and 457 students without SEN responded to the online survey. Results showed no significant differences in school well-being and social relationship between students with and without SEN, but students with SEN, particularly those with learning and development impairment and those with mental illness and emotional problems, were significantly poorer in academic self-concept. Implications of the findings were discussed.

Keywords: ccademic self-concept, school well-being, social relationship, special educational needs

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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Authors: Song Qingfeng

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This research aims to seek the relationship between social media usage and overtourism from the perspective of tourists based on the theory of Maslow’s hierarchy needs. A questionnaire is formulated to collect data from 400 tourists who have visited the Hangzhou city in China in the last 12 months. Structural Equation Model (SEM) is employed to analysis data. The finding is that social media usage aggravates overtourism. Specifically, social media is used by tourists to information-seeking, entertainment, self-presentation, and socialization for traveling. These roles of social media would evoke the traveling intention to a specific destination at a certain time, which further influences the tourist flow. When the tourist flow concentrate, the overtourism would be aggravated. This study contributes to the destination managers to deep-understand the cause-effect relationship between social media and overtourism in order to address this problem.

Keywords: social media, overtourism, tourist flow, SEM, Maslow’s hierarchy of needs, Hangzhou

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Authors: Malik Ghulam Behlol, Alison Fox, Faiza Masood, Sabiha Arshad

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This paper explores the barriers to the application of learning-supportive assessment at teaching practicum while investigating the role of university teachers (UT), cooperative teachers (CT), prospective teachers ( PT) and heads of the practicum schools (HPS) in the selected universities of Pakistan and the UK. It is a qualitative case study and data were collected through the lesson observation of UT in the pre-service teacher education setting and PT in practicum schools. Interviews with UT, HPS, and Focus Group Discussions with PT were conducted too. The study has concluded that as compared to the UK counterpart, PT in Pakistan faces significant barriers in applying learning-supportive assessment in the school practicum settings because of large class sizes, lack of institutionalised collaboration between universities and schools, poor modelling of the lesson, ineffective feedback practices, lower order thinking assignments, and limited opportunities to use technology in school settings.

Keywords: assessment, pre-service teacher education, theory-practice gap, teacher education

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Authors: Tina Stavredes

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Increasingly borderless learning opportunities including online learning are expanding. Singapore University of Social Science (SUSS) conducted research in February of 2017 to determine the level of consumer interest in undertaking a completely online distance learning degree program across three countries in the Asian Pacific region. The target audience was potential bachelor degree and post-degree students from Malaysia, Indonesia, and Vietnam. The results gathered were used to assess the market size and ascertain the business potential of online degree programs in Malaysia, Indonesia and Vietnam. Secondly, the results were used to determine the most receptive markets to prioritise entry and identify the most receptive student segments. In order to achieve the key outcomes, the key points of understanding were as follows: -Motivations for higher education & factors that influence the choice of institution, -Interest in online learning, -Interest in online learning from a Singapore university relative to other foreign institutions, -Key drivers and barriers of interest in online learning. An online survey was conducted from from 7th Feb 2017 to 27th Feb 2017 amongst n=600 respondents aged 21yo-45yo, who have a basic command of English, A-level qualifications and above, and who have an intent to further their education in the next 12 months. Key findings from the study regarding enrolling in an online program include the need for a marriage between intrinsic and extrinsic motivation factors and the flexibility and support offered in an online program. Overall, there was a high interest for online learning. Survey participants stated they are intrinsically motivated to learn because of their interest in the program of study and the need for extrinsic rewards including opportunities for employment or salary increment in their current job. Seven out of ten survey participants reported they are motivated to further their education and expand their knowledge to become more employable. Eight in ten claims that the feasibility of furthering their education depends on cost and maintaining a work-life balance. The top 2 programs of interest are business and information and communication technology. They describe their choice of university as a marriage of both motivational and feasibility factors including cost, choice, quality of support facilities, and the reputation of the institution. Survey participants reported flexibility as important and stated that appropriate support assures and grows their intent to enrol in an online program. Respondents also reported the importance of being able to work while studying as the main perceived advantage of online learning. Factors related to the choice of an online university emphasized the quality of support services. Despite concerns, overall there was a high interest for online learning. One in two expressed strong intent to enrol in an online programme of study. However, unfamiliarity with online learning is a concern including the concern with the lack of face-to-face interactions. Overall, the findings demonstrated an interest in online learning. A main driver was the ability to earn a recognised degree while still being able to be with the family and the ability to achieve a ‘better’ early career growth.

Keywords: distance education, student motivations, online learning, online student needs

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Leigh Ann Wilson, Melanie Borrego

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The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

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Authors: M. Roberts Masillamani

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There is a phenomenal difference, as regard to the teaching methodology adopted at the urban and the rural area colleges. However, bright and talented student may be from rural back ground even. But there is huge dearth of the digitization in the rural areas and lesser developed countries. Today’s students need new skills to compete and successful in the future. Education should be combination of practical, intellectual, and social skills. What does this mean for rural classrooms and how can it be achieved. Rural colleges are not able to hire the best resources, since the best teacher’s aim is to move towards the city. If city is provided everywhere, then there will be no rural area. This is possible by forming university clusters (UC). The University cluster is a group of renowned and accredited universities coming together to bridge this dearth. The UC will deliver the live lectures and allow the students’ from remote areas to actively participate in the classroom. This paper tries to present a plan of action of providing a better live classroom teaching and learning system from the city to the rural and the lesser developed countries. This paper titled “University Clusters using ICT for teaching and learning” provides a true concept of opening live digital classroom windows for rural colleges, where resources are not available, thus reducing the digital divide. This is different from pod casting a lecture or distance learning and eLearning. The live lecture can be streamed through digital equipment to another classroom. The rural students can collaborate with their peers and critiques, be assessed, collect information, acquire different techniques in assessment and learning process. This system will benefit rural students and teachers and develop socio economic status. This will also will increase the degree of confidence of the Rural students and teachers. Thus bringing about the concept of ‘Train the Trainee’ in reality. An educational university cloud for each cluster will be built remote infrastructure facilities (RIF) for the above program. The users may be informed, about the available lecture schedules, through the RIF service. RIF with an educational cloud can be set by the universities under one cluster. This paper talks a little more about University clusters and the methodology to be adopted as well as some extended features like, tutorial classes, library grids, remote laboratory login, research and development.

Keywords: lesser developed countries, digital divide, digital learning, education, e-learning, ICT, library grids, live classroom windows, RIF, rural, university clusters and urban

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Authors: Bruno Cossu, Elio Carlo

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The invention (patent pending) relates to the field of devices aimed to harness wave energy (WEC) especially for artificial upwelling, forced downwelling, production of compressed air. In its basic form, the pump consists of a hydro-pneumatic machine, driven by wave energy, characterised by the fact that it has no moving mechanical parts, and is made up of only two structural components: an hollow body, which is open at the bottom to the sea and partially immersed in sea water, and a tube, both joined together to form a single body. The shape of the hollow body is like a mushroom whose cap and stem are hollow; the stem is open at both ends and the lower part of its surface is crossed by holes; the tube is external and coaxial to the stem and is joined to it so as to form a single body. This shape of the hollow body and the type of connection to the tube allows the pump to operate simultaneously as an air compressor (OWC) on the cap side, and as an airlift on the stem side. The pump can be implemented in four versions, each of which provides different variants and methods of implementation: 1) firstly, for the artificial upwelling of cold, deep ocean water; 2) secondly, for the lifting and transfer of these waters to the place of use (above all, fish farming plants), even if kilometres away; 3) thirdly, for the forced downwelling of surface sea water; 4) fourthly, for the forced downwelling of surface water, its oxygenation, and the simultaneous production of compressed air. The transfer of the deep water or the downwelling of the raised surface water (as for pump versions indicated in points 2 and 3 above), is obtained by making the water raised by the airlift flow into the upper inlet of another pipe, internal or adjoined to the airlift; the downwelling of raised surface water, oxygenation, and the simultaneous production of compressed air (as for the pump version indicated in point 4), is obtained by installing a venturi tube on the upper end of the pipe, whose restricted section is connected to the external atmosphere, so that it also operates like a hydraulic air compressor (trompe). Furthermore, by combining one or more pumps for the upwelling of cold, deep water, with one or more pumps for the downwelling of the warm surface water, the system can be used in an Ocean Thermal Energy Conversion plant to supply the cold and the warm water required for the operation of the same, thus allowing to use, without increased costs, in addition to the mechanical energy of the waves, for the purposes indicated in points 1 to 4, the thermal one of the marine water treated in the process.

Keywords: air lifted upwelling, fish farming plant, hydraulic air compressor, wave energy converter

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Authors: Bruno Gontijo Batista

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This paper analyzes how the Socially Aware Design (SAwD) and the Value-oriented and Culturally Informed Approach (VCIA) design model can be used to develop an edutainment game for children with Attention Deficit Hyperactivity Disorder (ADHD). The SAwD approach seeks a design that considers new dimensions in human-computer interaction, such as culture, aesthetics, emotional and social aspects of the user's everyday experience. From this perspective, the game development was VCIA model-based, including the users in the design process through participatory methodologies, considering their behavioral patterns, culture, and values. This is because values, beliefs, and behavioral patterns influence how technology is understood and used and the way it impacts people's lives. This model can be applied at different stages of design, which goes from explaining the problem and organizing the requirements to the evaluation of the prototype and the final solution. Thus, this paper aims to understand how this model can be used in the development of an edutainment game for children with ADHD. In the area of education and learning, children with ADHD have difficulties both in behavior and in school performance, as they are easily distracted, which is reflected both in classes and on tests. Therefore, they must perform tasks that are exciting or interesting for them, once the pleasure center in the brain is activated, it reinforces the center of attention, leaving the child more relaxed and focused. In this context, serious games have been used as part of the treatment of ADHD in children aiming to improve focus and attention, stimulate concentration, as well as be a tool for improving learning in areas such as math and reading, combining education and entertainment (edutainment). Thereby, as a result of the research, it was developed, in a participatory way, applying the VCIA model, an edutainment game prototype, for a mobile platform, for children between 8 and 12 years old.

Keywords: ADHD, edutainment, SAwD, VCIA

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Authors: Saziye Darendeli

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Motivation has a significant impact on a second/foreign language learning process, so it plays a vital role while achieving the learning goal. As it is defined by Simon (1967, p. 29), motivation is “a goal terminating mechanism, permitting goals to be processed serially.”AccordingtoSimon, if a learning goal is activated and enough attention is given, the learner starts learning. In connection with this view, the more attention is given on a subject, and the more activation takes place on it, the quicker learning will occur. Moreover, today almost every teacher is familiar with the term “distance education” regardless of their student's age group. As it is stated by Visser (2002), when compared to the traditional classrooms, in distance education, the rate and success of language learningdecreasesandone of the most essential reasons is that motivating students in distance education contexts, in which interaction is lower, is much more challenging than face-to-face training especially with young learners(Lim& Kim, 2003). Besides, there are limited numbers of studies conducted on motivational strategies for young learners in distance education contexts since we have been experiencing full time the online schooling process recently, yet online teaching seems to be permanent in our lives with the new technological era. Therefore, there appears to be a need for various strategies to motivate young learners in distance education, and the current study aims to find out the strategies that young learners’ teachers use to increase their students’ motivation level in distance education. To achieve this aim, a qualitative research approach and a phenomenological method with an interpretive design will be used. The participants, who are teachers of young learners, will be interviewed using a structured interview format consisting of 7 questions. As the participants are young learners’teacherswhohavebeenexperiencingteaching online, exploring thestrategiesthattheyusetoincreasetheirstudents’ motivationlevelwillprovidesomesuggestionsaboutthemotivationalstrategiesforfuture online classes. Also, in this paper, I will move beyond the traditional classrooms that have face-to-face lessons and discuss the effective motivational strategies for young learners in distance education.

Keywords: motivation, distance education, young learners, strategies

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Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

Procedia PDF Downloads 234