Dysgraphia is a disorder of expression with the writing of letters, words, and numbers. Dysgraphia is one of the learning disabilities attributed to the educational sector, which has a strong impact on the academic, motor, and emotional aspects of the individual. The purpose of this study is to identify dysgraphia in children by creating an engaging robot-mediated activity, to collect a new dataset of Latin digits written exclusively by children aged 6 to 12 years. An interactive scenario that explains and demonstrates the steps involved in handwriting digits is created using the verbal and non-verbal behaviors of the social humanoid robot Nao. Therefore, we have collected a dataset that contains 11,347 characters written by 174 participants with and without dysgraphia. And through the advent of deep learning technologies and their success in various fields, we have developed an approach based on these methods. The proposed approach was tested on the generated database. We performed a classification with a convolutional neural network (CNN) to identify dysgraphia in children. The results show that the performance of our model is promising, reaching an accuracy of 91%.
DESIGNING A WORKING MEMORY CAPACITY TEST FOR COGNITIVE-FRIENDLY TANGIBLE MULT...ijma
A working memory capacity (WMC) test called “objects-span tri-tasks” is designed for preschoolers
undergoing treatment using a new genre of multimedia, tangible multimedia, created by the authors. It tests
the dual-functions of the preschoolers’ working memory (WM), namely storage and manipulation capacity,
essential in supporting academic skills. The third task in the test is the overt setting of task engaging the
long-term memory that supports the operation of WM. Tangible multimedia potentially enhances the WMC
of preschoolers to a considerable extent because firstly, it uses tangible objects that are cognitively
appropriate to the “preoperational” stage of preschoolers, and secondly, it simultaneously stimulates three
main sensory channels, prescribed as equally crucial in knowledge acquisition in human memory theories.
A pragmatic significance of the research is that it deepens the scope of multimedia research by looking into
the aspect of cognitive structure which is rarely conducted in the multimedia realm. It also demonstrates an
important step forward in multimedia research by relating WMC to the newly explored tangible
multimedia, which could determine the real capability and value of such system. This paper starts off by
discussing the underlying theories that contribute to the formation of the system and test, followed by its
procedure, and a brief report of a case study
DESIGNING A WORKING MEMORY CAPACITY TEST FOR COGNITIVE-FRIENDLY TANGIBLE MULT...ijma
This document describes the design of a working memory capacity test called "objects-span tri-tasks" for preschoolers using a new genre of multimedia called tangible multimedia. Tangible multimedia augments traditional digital multimedia with physical tangible objects. The test assesses both the storage and manipulation functions of working memory, which are important for academic skills. It includes three tasks - the third engages long-term memory to support working memory operations. Tangible multimedia may enhance preschoolers' working memory capacity by using cognitively appropriate tangible objects and stimulating three sensory channels simultaneously as prescribed by human memory theories. The test and tangible multimedia are grounded in theories of working memory including the unified theory presented, which integrates aspects of Atkinson and
This Children are future of a society within a country. They should be provided with all round educational development since educating children has many advantages. If they are educated, they can face any problem and this makes them strong and happy. In other words the growth of a country is dependent on its learned population. Children with special education needs have problems to develop cognitive abilities like thinking, learning and obtain new knowledge and concept. It may also be required to improve their conduct, communication skills and interactions with their environment. It is required to develop customizable and compliant applications designed to support them in adapting with respect to the current situations they face and thus take actions appropriately. Such applications would provide them the assistance to allow them frame their learning essentials and help to process to the diverse sensory and cognitive impairments including the mobility issues. This research will be based on artificial intelligence concept and will be self-adaptable. Besides, in many cases they have the opportunity to perform activities that previously were not accessible to them, because of the interface and contents of the activities have been adapted specifically to them. The study also suggests that the repertoire of types of activities provided is suitable for learning purposes with students with impairments. Finally, the use of electronic devices and multimedia contents increases their interest in learning and attention.
AN INTELLIGENT SELF-ADAPTABLE APPLICATION TO SUPPORT CHILDREN EDUCATION AND L...ijcsit
ABSTRACT
This Children are future of a society within a country. They should be provided with all round educational development since educating children has many advantages. If they are educated, they can face any problem and this makes them strong and happy. In other words the growth of a country is dependent on its learned population. Children with special education needs have problems to develop cognitive abilities like thinking, learning and obtain new knowledge and concept. It may also be required to improve their conduct, communication skills and interactions with their environment. It is required to develop customizable and compliant applications designed to support them in adapting with respect to the current situations they face and thus take actions appropriately. Such applications would provide them the assistance to allow them frame their learning essentials and help to process to the diverse sensory and cognitive impairments including the mobility issues. This research will be based on artificial intelligence concept and will be self-adaptable. Besides, in many cases they have the opportunity to perform activities that previously were not accessible to them, because of the interface and contents of the activities have been adapted specifically to them. The study also suggests that the repertoire of types of activities provided is suitable for learning purposes with students with impairments. Finally, the use of electronic devices and multimedia contents increases their interest in learning and attention.
Child Education Through Animation: An Experimental Study ijcga
Teachers have tried to teach their students by introducing text books along with verbal instructions in
traditional education system. However, teaching and learning methods could be changed for developing
Information and Communication Technology (ICT). It's time to adapt students with interactive learning
system so that they can improve their learning, catching, and memorizing capabilities. It is indispensable to
create high quality and realistic leaning environment for students. Visual learning can be easier to
understand and deal with their learning. We developed visual learning materials (an overview of solar
system) in the form of video for students of primary level using different multimedia application tools. The
objective of this paper is to examine the impact of student’s abilities to acquire new knowledge or skills
through visual learning materials and blended leaning that is integration of visual learning materials with
teacher’s instructions. We visited a primary school in Dhaka city for this study and conducted teaching
with three different groups of students (i) teacher taught students by traditional system on same materials
and marked level of student’s ability to adapt by a set of questions (ii) another group was taught with only
visual learning material and assessment was done with 15 questionnaires, (iii) the third group was taught
with the video of solar system combined with teacher’s instructions and assessed with the same
questionnaires. This integration of visual materials (solar system) with verbal instructions is a blended
approach of learning. The interactive blended approach greatly promoted students ability of acquisition of
knowledge and skills. Students response and perception were very positive towards the blended technique
than the other two methods. This interactive blending leaning system may be an appropriate method
especially for school children.
This document discusses using virtual manipulatives to teach fractions to students with learning disabilities. It begins by noting that students with learning disabilities often struggle with fractions and their conceptual understanding. Recent research supports using interactive visual models or virtual manipulatives to teach fractions as they allow for adjustable instruction, scaffolding of content, and increased practice opportunities. The document then discusses trends in using technology to teach math to students with disabilities. It provides examples of virtual manipulative tools and their features. Benefits of using virtual manipulatives include helping students follow visual images, providing individualized accommodations, and allowing active student engagement. Potential challenges include technical difficulties and ensuring students understand the connection between the virtual manipulatives and mathematical concepts.
This document discusses the use of educational robotics as assistive tools for learning mathematics and science. It provides an overview of the advantages of using robots in education, such as developing cognitive and social skills. However, challenges also exist, such as teachers not being prepared to implement new technologies. The document also examines different robotics platforms and programming software used in education. Overall, educational robotics have been shown to improve student learning and motivation, especially for subjects like math, but support materials and training for teachers is needed for successful integration.
Knowledge, social media and technologies for a learning societywanzahirah
The document summarizes several papers presented in a special issue of the journal Transactions of the SDPS on the topics of knowledge, social media, and technologies for learning. The papers explore how new technologies and social media are changing learning and discuss approaches like using smartphones and scaffolding tools to enhance the learning process. They also address challenges in recommending learning resources and the role of collective intelligence in driving innovation. The goal of the special issue is to look at the future of education from a transdisciplinary perspective.
DESIGNING A WORKING MEMORY CAPACITY TEST FOR COGNITIVE-FRIENDLY TANGIBLE MULT...ijma
A working memory capacity (WMC) test called “objects-span tri-tasks” is designed for preschoolers
undergoing treatment using a new genre of multimedia, tangible multimedia, created by the authors. It tests
the dual-functions of the preschoolers’ working memory (WM), namely storage and manipulation capacity,
essential in supporting academic skills. The third task in the test is the overt setting of task engaging the
long-term memory that supports the operation of WM. Tangible multimedia potentially enhances the WMC
of preschoolers to a considerable extent because firstly, it uses tangible objects that are cognitively
appropriate to the “preoperational” stage of preschoolers, and secondly, it simultaneously stimulates three
main sensory channels, prescribed as equally crucial in knowledge acquisition in human memory theories.
A pragmatic significance of the research is that it deepens the scope of multimedia research by looking into
the aspect of cognitive structure which is rarely conducted in the multimedia realm. It also demonstrates an
important step forward in multimedia research by relating WMC to the newly explored tangible
multimedia, which could determine the real capability and value of such system. This paper starts off by
discussing the underlying theories that contribute to the formation of the system and test, followed by its
procedure, and a brief report of a case study
DESIGNING A WORKING MEMORY CAPACITY TEST FOR COGNITIVE-FRIENDLY TANGIBLE MULT...ijma
This document describes the design of a working memory capacity test called "objects-span tri-tasks" for preschoolers using a new genre of multimedia called tangible multimedia. Tangible multimedia augments traditional digital multimedia with physical tangible objects. The test assesses both the storage and manipulation functions of working memory, which are important for academic skills. It includes three tasks - the third engages long-term memory to support working memory operations. Tangible multimedia may enhance preschoolers' working memory capacity by using cognitively appropriate tangible objects and stimulating three sensory channels simultaneously as prescribed by human memory theories. The test and tangible multimedia are grounded in theories of working memory including the unified theory presented, which integrates aspects of Atkinson and
This Children are future of a society within a country. They should be provided with all round educational development since educating children has many advantages. If they are educated, they can face any problem and this makes them strong and happy. In other words the growth of a country is dependent on its learned population. Children with special education needs have problems to develop cognitive abilities like thinking, learning and obtain new knowledge and concept. It may also be required to improve their conduct, communication skills and interactions with their environment. It is required to develop customizable and compliant applications designed to support them in adapting with respect to the current situations they face and thus take actions appropriately. Such applications would provide them the assistance to allow them frame their learning essentials and help to process to the diverse sensory and cognitive impairments including the mobility issues. This research will be based on artificial intelligence concept and will be self-adaptable. Besides, in many cases they have the opportunity to perform activities that previously were not accessible to them, because of the interface and contents of the activities have been adapted specifically to them. The study also suggests that the repertoire of types of activities provided is suitable for learning purposes with students with impairments. Finally, the use of electronic devices and multimedia contents increases their interest in learning and attention.
AN INTELLIGENT SELF-ADAPTABLE APPLICATION TO SUPPORT CHILDREN EDUCATION AND L...ijcsit
ABSTRACT
This Children are future of a society within a country. They should be provided with all round educational development since educating children has many advantages. If they are educated, they can face any problem and this makes them strong and happy. In other words the growth of a country is dependent on its learned population. Children with special education needs have problems to develop cognitive abilities like thinking, learning and obtain new knowledge and concept. It may also be required to improve their conduct, communication skills and interactions with their environment. It is required to develop customizable and compliant applications designed to support them in adapting with respect to the current situations they face and thus take actions appropriately. Such applications would provide them the assistance to allow them frame their learning essentials and help to process to the diverse sensory and cognitive impairments including the mobility issues. This research will be based on artificial intelligence concept and will be self-adaptable. Besides, in many cases they have the opportunity to perform activities that previously were not accessible to them, because of the interface and contents of the activities have been adapted specifically to them. The study also suggests that the repertoire of types of activities provided is suitable for learning purposes with students with impairments. Finally, the use of electronic devices and multimedia contents increases their interest in learning and attention.
Child Education Through Animation: An Experimental Study ijcga
Teachers have tried to teach their students by introducing text books along with verbal instructions in
traditional education system. However, teaching and learning methods could be changed for developing
Information and Communication Technology (ICT). It's time to adapt students with interactive learning
system so that they can improve their learning, catching, and memorizing capabilities. It is indispensable to
create high quality and realistic leaning environment for students. Visual learning can be easier to
understand and deal with their learning. We developed visual learning materials (an overview of solar
system) in the form of video for students of primary level using different multimedia application tools. The
objective of this paper is to examine the impact of student’s abilities to acquire new knowledge or skills
through visual learning materials and blended leaning that is integration of visual learning materials with
teacher’s instructions. We visited a primary school in Dhaka city for this study and conducted teaching
with three different groups of students (i) teacher taught students by traditional system on same materials
and marked level of student’s ability to adapt by a set of questions (ii) another group was taught with only
visual learning material and assessment was done with 15 questionnaires, (iii) the third group was taught
with the video of solar system combined with teacher’s instructions and assessed with the same
questionnaires. This integration of visual materials (solar system) with verbal instructions is a blended
approach of learning. The interactive blended approach greatly promoted students ability of acquisition of
knowledge and skills. Students response and perception were very positive towards the blended technique
than the other two methods. This interactive blending leaning system may be an appropriate method
especially for school children.
This document discusses using virtual manipulatives to teach fractions to students with learning disabilities. It begins by noting that students with learning disabilities often struggle with fractions and their conceptual understanding. Recent research supports using interactive visual models or virtual manipulatives to teach fractions as they allow for adjustable instruction, scaffolding of content, and increased practice opportunities. The document then discusses trends in using technology to teach math to students with disabilities. It provides examples of virtual manipulative tools and their features. Benefits of using virtual manipulatives include helping students follow visual images, providing individualized accommodations, and allowing active student engagement. Potential challenges include technical difficulties and ensuring students understand the connection between the virtual manipulatives and mathematical concepts.
This document discusses the use of educational robotics as assistive tools for learning mathematics and science. It provides an overview of the advantages of using robots in education, such as developing cognitive and social skills. However, challenges also exist, such as teachers not being prepared to implement new technologies. The document also examines different robotics platforms and programming software used in education. Overall, educational robotics have been shown to improve student learning and motivation, especially for subjects like math, but support materials and training for teachers is needed for successful integration.
Knowledge, social media and technologies for a learning societywanzahirah
The document summarizes several papers presented in a special issue of the journal Transactions of the SDPS on the topics of knowledge, social media, and technologies for learning. The papers explore how new technologies and social media are changing learning and discuss approaches like using smartphones and scaffolding tools to enhance the learning process. They also address challenges in recommending learning resources and the role of collective intelligence in driving innovation. The goal of the special issue is to look at the future of education from a transdisciplinary perspective.
SAMPLE GED 501 RESEARCH PAPERTechnology Based Education How.docxagnesdcarey33086
1) The document discusses how Vygotsky's sociocultural theory of development can guide the use of technology in teaching immigrant and English language learners. 2) It notes that the number of English language learners in US classrooms is rapidly increasing as the number of immigrant students grows. 3) Vygotsky's theory emphasizes that social interaction and culture play important roles in cognitive development, and that instruction should be tailored to students' zones of proximal development to help them progress to more advanced levels.
Impact of play based learning on the development.pdfvideosplay360
Play-based learning is a pedagogical approach that emphasises the use of play in promoting multipleareas of children’s development and learning. Free play and guided play are two types of play-basedlearning which guide early learning. The children acquire concepts, skills, and attitudes that lay thefoundation for lifelong learning through play pedagogies.
This document provides background information on a study being conducted to improve students' cognitive abilities using interactive virtual art. It discusses Malaysia's initiatives to integrate technology into education to prepare students for 21st century skills. Studies have shown benefits of arts education for student achievement and well-being. The study aims to identify students' current art achievement levels, determine the effectiveness of interactive learning for teaching visual art, and identify ways to improve art learning. It puts forth a hypothesis that student achievement will be significantly different after using interactive software and defines key terms like cognitive and interactive.
This document provides background information on a study being conducted to improve students' cognitive abilities using interactive virtual art. It discusses Malaysia's initiatives to integrate technology into education to prepare students for 21st century skills. Studies have shown benefits of arts education for student achievement and skills such as communication. The study aims to identify students' current art achievement levels, determine the effectiveness of interactive learning for teaching visual art, and ways to improve art learning. It puts forth a hypothesis that interactive software will result in a significant difference in student achievement. Key terms related to cognition and interactivity are also operationally defined.
Educational robotics has several potential benefits but also faces challenges in implementation. It can develop students' cognitive and social skills, and motivate learning. However, teachers need time and appropriate curricula to successfully integrate the technology. Research found that educational robotics benefited both genders and improved students' problem-solving and higher-order thinking skills through constructivist learning approaches. User-friendly robots and introductory curricula can make educational robotics more accessible and enjoyable for both students and teachers.
Present day showing techniques request imaginative and powerful utilization of innovation at most extreme level. Consolidating a virtual group outside classroom instructing has turned out to be inescapable in computerized age training. This exploration was planned to discover how this can be utilized as a part of terms of intuitive instructing and how it can encourage understudies to recuperate the absences of learning in classroom. A web group of a college called Learning Feedback System (LFS) has been utilized here as the strategy to break down five example cases. Impacts of
A critical level of connection in LFS showed that it decreased the correspondence hole between understudies and educators that obviously prompting appropriate learning.
This document presents a model for understanding how digital technologies can best support personalized learning in schools. The model conceptualizes four learning spaces that influence students' education: the personal learning space, teaching space, school space, and living space. These spaces are interrelated and influenced by technologies. The model was validated using data from research projects, which found that technologies can provide feedback, motivation, and opportunities for collaboration. However, teachers and students may have differing comfort levels with technologies and understandings of personalized learning. Recommendations include better aligning perceptions across learning spaces to effectively use digital tools for personalization.
Development of interactive instructional model using augmented reality based ...IJITE
The research aims to develop an interactive instructional model usingaugmented reality based on
edutainment to enhance emotional quotientand evaluate the model. Two phases of the research will be
carried out: a development and an evaluation of the model. Samples are experts in the field of IT, child
psychology, and 7th grade curriculum management. Ten experts are selected by purposive sampling
method. The obtained data are analyzed using mean and standard deviation.
The research result demonstrates the following findings:
1) The results of this research show that Model consists of 3 elements: IIAR, EduLA, and EQ. EQ is a
means to assess EQ based on Time Series Experimental Design using 2 kinds of tools; i.e. EQ Assessment
by programs in tablet computers, and EQ Assessment by behavioral observation.
(2The ten experts have evaluated the model and commented that the developed model showed high
suitability.
This document discusses classifying user preferences of web learning systems using a neural network with genetic algorithm optimization. It begins with an abstract describing using cognitive attributes from user questionnaires to train classifiers to identify areas for improving a web learning system's layout. A multilayer perceptron neural network was proposed to classify user preferences, and genetic algorithm was used to optimize the neural network parameters to improve performance. 182 students were given questionnaires assessing their cognitive responses to known and unknown subjects on a learning website to collect training data for the proposed genetically optimized neural network classifier.
This paper summarizes studies from 2003-2013 on how information and communication technologies (ICTs) can support skills in kindergarteners, including early literacy, mathematics, cognitive, social-emotional, and creativity skills. It examines the effectiveness of ICT for special education and gifted children. There are eight sections that overview how ICTs can specifically support early literacy, mathematics, cognitive skills, etc. The paper also discusses teachers' positive attitudes towards ICTs and the need for training to enhance their skills and confidence in using technologies.
A “BIRD’S EYE VIEW” ON COMMUNICATION ACTS IN A CLASSROOM OF LOW LITERACY ADULTSIJITE
This paper starts by discussing the relevance of dialogues in Adult Education and Training courses with
low levels of literacy. In this group, the educational challenges are complex, and innovating the knowledge
creation process involves a better understanding of the teaching/learning process. With these case study,
we pretend to understand which Communicative Acts are effective in adult learning process, mainly in
adults with low literacy. Based on a mixed methods, applied to a convenience sample, we used an
ethnographic approach, and the Grounded Theory Methodology. Using the Contextual Design approach,
we developed several models of the context (work models) and got a bird's-eye view of the way the
communicational acts and the dynamic acts flow in the classroom. The results showed that it was
important to integrate the learners' emotions in an existing framework, the SEDA Framework. We found
also essential to expand the Communicative Acts coding, with a new set of 17 codes organized in 3
categories in order to understand better the flow of communication in the classroom.
This document summarizes experiences implementing a robotics education program called RoboESL at a junior high school in Athens, Greece over two school years. It describes:
1) How students worked in groups to solve problems using LEGO Mindstorms robots, applying a constructivist learning model.
2) The six step problem-based learning framework used, involving defining a problem, planning solutions, implementing strategies, and evaluating outcomes.
3) Details of the two implementations, including adjustments made the second time to address student fatigue.
DEVELOPMENT OF INTERACTIVE INSTRUCTIONAL MODEL USING AUGMENTED REALITY BASED ...IJITE
The research aims to develop an interactive instructional model usingaugmented reality based on
edutainment to enhance emotional quotientand evaluate the model. Two phases of the research will be
carried out: a development and an evaluation of the model. Samples are experts in the field of IT, child
psychology, and 7th grade curriculum management. Ten experts are selected by purposive sampling
method. The obtained data are analyzed using mean and standard deviation.
The research result demonstrates the following findings:
1) The results of this research show that Model consists of 3 elements: IIAR, EduLA, and EQ. EQ is a
means to assess EQ based on Time Series Experimental Design using 2 kinds of tools; i.e. EQ Assessment
by programs in tablet computers, and EQ Assessment by behavioral observation.
2 ( The ten experts have evaluated the model and commented that the developed model showed high
suitability.
DEVELOPMENT OF INTERACTIVE INSTRUCTIONAL MODEL USING AUGMENTED REALITY BASED ...IJITE
The document describes the development of an interactive instructional model using augmented reality and edutainment to enhance emotional quotient. It includes:
1) The development of a model consisting of three elements: interactive instructional augmented reality, edutainment learning activities, and emotional quotient assessment.
2) An evaluation of the model by 10 experts found it to have high suitability, with the interactive instructional augmented reality steps and edutainment learning activity steps rated as having the highest suitability.
3) The experts' evaluation demonstrated that the model's components, steps, and activities were highly suitable for effectively using augmented reality and edutainment to enhance students' emotional quotient.
International Journal of Multimedia & Its Applications (IJMA)ijma
The International Journal of Multimedia & Its Applications (IJMA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Multimedia & its applications. The journal focuses on all technical and practical aspects of Multimedia and its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding recent developments this arena, and establishing new collaborations in these areas.
International Journal of Multimedia & Its Applications (IJMA)ijma
Call for Papers
*****************
International Journal of Multimedia & Its Applications (IJMA)
Contact Us : ijmajournal@airccse.org or ijma@aircconline.com
Submission Deadline : February 18, 2023
website link : https://airccse.org/journal/ijma.html
Virtual Assistants and Its ImplementationOmar Cóndor
This document discusses the implementation of virtual assistants in education. It describes how virtual assistants, which are AI-based software that can interact with users, answer questions, and perform tasks, are beginning to be used as educational tools in classrooms. The document outlines several virtual assistants like Alexa, Siri, Google Assistant, and Cortana, and discusses how they are able to motivate students through interaction, help teach languages, and act as virtual tutors. However, it notes that more research is still needed on their educational applications and impacts on learning outcomes.
Tangible user interface design for learners with different multiple intellige...IJECEIAES
The creation of learning activities responsive to learners with different basic skills has been limited due to a classroom environment and applied technologies. The goals of this research were to develop Tang-MI, a game with a tangible user interface supporting primary school learners’ analytical skills based on the theory of multiple intelligences (MI), and to present design guidelines for a tangible user interface suitable for learners in different MI groups. In this research, the Tangible user interface for multiple intelligence (Tang-MI) was tested with thirty students initially evaluated for their multiple intelligences. The learners’ usage behavior was observed and recorded while the students performed the assigned tasks. The behavioral data were analyzed and grouped into behaviors occurring before performing the tasks, during the tasks, and after completing the tasks. Based on the learners’ usage behavior, the tangible user interface design guidelines for learners in different MI groups were proposed concerning physical equipment design, question design, interactive program design, audio design, and animated visual feedback design. These guidelines would help educators build learning games that respond to the learners’ intelligence styles and enhance students’ motivation to learn.
Autism spectrum disorder is a developmental disability that can cause significant social, communication and behavioural challenges. Parents of children on the spectrum find it difficult for their kids to communicate with them and other people, which makes it challenging for social interactions. Researchers have introduced different solutions such as Therapy Robot that Teaches Social Skills to Children with Autism. Additionally, Virtual reality was used to teach emotional and social skills to children with autism spectrum disorder. However, these solutions focus only on the person on the spectrum, neglecting the fact that the social challenges that people on the spectrum face are partly due to the lack of understanding on the neurotypicals' end. In this study, the solution introduced focuses on the neurotypical perspective; An advanced and interactive intelligent technology that can educate neurotypical people on how to communicate with people on the spectrum in different scenarios and environments. It also allows the learner to see the consequences of the different interactions from the point of view of a person on the spectrum, be aware of their actions, and fully engage in the scenarios through Virtual Reality (VR). Virtual Reality is a technology that simulates experiences that can be similar to the real world. The project aim was achieved by implementing a storyline game that is VR-based.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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SAMPLE GED 501 RESEARCH PAPERTechnology Based Education How.docxagnesdcarey33086
1) The document discusses how Vygotsky's sociocultural theory of development can guide the use of technology in teaching immigrant and English language learners. 2) It notes that the number of English language learners in US classrooms is rapidly increasing as the number of immigrant students grows. 3) Vygotsky's theory emphasizes that social interaction and culture play important roles in cognitive development, and that instruction should be tailored to students' zones of proximal development to help them progress to more advanced levels.
Impact of play based learning on the development.pdfvideosplay360
Play-based learning is a pedagogical approach that emphasises the use of play in promoting multipleareas of children’s development and learning. Free play and guided play are two types of play-basedlearning which guide early learning. The children acquire concepts, skills, and attitudes that lay thefoundation for lifelong learning through play pedagogies.
This document provides background information on a study being conducted to improve students' cognitive abilities using interactive virtual art. It discusses Malaysia's initiatives to integrate technology into education to prepare students for 21st century skills. Studies have shown benefits of arts education for student achievement and well-being. The study aims to identify students' current art achievement levels, determine the effectiveness of interactive learning for teaching visual art, and identify ways to improve art learning. It puts forth a hypothesis that student achievement will be significantly different after using interactive software and defines key terms like cognitive and interactive.
This document provides background information on a study being conducted to improve students' cognitive abilities using interactive virtual art. It discusses Malaysia's initiatives to integrate technology into education to prepare students for 21st century skills. Studies have shown benefits of arts education for student achievement and skills such as communication. The study aims to identify students' current art achievement levels, determine the effectiveness of interactive learning for teaching visual art, and ways to improve art learning. It puts forth a hypothesis that interactive software will result in a significant difference in student achievement. Key terms related to cognition and interactivity are also operationally defined.
Educational robotics has several potential benefits but also faces challenges in implementation. It can develop students' cognitive and social skills, and motivate learning. However, teachers need time and appropriate curricula to successfully integrate the technology. Research found that educational robotics benefited both genders and improved students' problem-solving and higher-order thinking skills through constructivist learning approaches. User-friendly robots and introductory curricula can make educational robotics more accessible and enjoyable for both students and teachers.
Present day showing techniques request imaginative and powerful utilization of innovation at most extreme level. Consolidating a virtual group outside classroom instructing has turned out to be inescapable in computerized age training. This exploration was planned to discover how this can be utilized as a part of terms of intuitive instructing and how it can encourage understudies to recuperate the absences of learning in classroom. A web group of a college called Learning Feedback System (LFS) has been utilized here as the strategy to break down five example cases. Impacts of
A critical level of connection in LFS showed that it decreased the correspondence hole between understudies and educators that obviously prompting appropriate learning.
This document presents a model for understanding how digital technologies can best support personalized learning in schools. The model conceptualizes four learning spaces that influence students' education: the personal learning space, teaching space, school space, and living space. These spaces are interrelated and influenced by technologies. The model was validated using data from research projects, which found that technologies can provide feedback, motivation, and opportunities for collaboration. However, teachers and students may have differing comfort levels with technologies and understandings of personalized learning. Recommendations include better aligning perceptions across learning spaces to effectively use digital tools for personalization.
Development of interactive instructional model using augmented reality based ...IJITE
The research aims to develop an interactive instructional model usingaugmented reality based on
edutainment to enhance emotional quotientand evaluate the model. Two phases of the research will be
carried out: a development and an evaluation of the model. Samples are experts in the field of IT, child
psychology, and 7th grade curriculum management. Ten experts are selected by purposive sampling
method. The obtained data are analyzed using mean and standard deviation.
The research result demonstrates the following findings:
1) The results of this research show that Model consists of 3 elements: IIAR, EduLA, and EQ. EQ is a
means to assess EQ based on Time Series Experimental Design using 2 kinds of tools; i.e. EQ Assessment
by programs in tablet computers, and EQ Assessment by behavioral observation.
(2The ten experts have evaluated the model and commented that the developed model showed high
suitability.
This document discusses classifying user preferences of web learning systems using a neural network with genetic algorithm optimization. It begins with an abstract describing using cognitive attributes from user questionnaires to train classifiers to identify areas for improving a web learning system's layout. A multilayer perceptron neural network was proposed to classify user preferences, and genetic algorithm was used to optimize the neural network parameters to improve performance. 182 students were given questionnaires assessing their cognitive responses to known and unknown subjects on a learning website to collect training data for the proposed genetically optimized neural network classifier.
This paper summarizes studies from 2003-2013 on how information and communication technologies (ICTs) can support skills in kindergarteners, including early literacy, mathematics, cognitive, social-emotional, and creativity skills. It examines the effectiveness of ICT for special education and gifted children. There are eight sections that overview how ICTs can specifically support early literacy, mathematics, cognitive skills, etc. The paper also discusses teachers' positive attitudes towards ICTs and the need for training to enhance their skills and confidence in using technologies.
A “BIRD’S EYE VIEW” ON COMMUNICATION ACTS IN A CLASSROOM OF LOW LITERACY ADULTSIJITE
This paper starts by discussing the relevance of dialogues in Adult Education and Training courses with
low levels of literacy. In this group, the educational challenges are complex, and innovating the knowledge
creation process involves a better understanding of the teaching/learning process. With these case study,
we pretend to understand which Communicative Acts are effective in adult learning process, mainly in
adults with low literacy. Based on a mixed methods, applied to a convenience sample, we used an
ethnographic approach, and the Grounded Theory Methodology. Using the Contextual Design approach,
we developed several models of the context (work models) and got a bird's-eye view of the way the
communicational acts and the dynamic acts flow in the classroom. The results showed that it was
important to integrate the learners' emotions in an existing framework, the SEDA Framework. We found
also essential to expand the Communicative Acts coding, with a new set of 17 codes organized in 3
categories in order to understand better the flow of communication in the classroom.
This document summarizes experiences implementing a robotics education program called RoboESL at a junior high school in Athens, Greece over two school years. It describes:
1) How students worked in groups to solve problems using LEGO Mindstorms robots, applying a constructivist learning model.
2) The six step problem-based learning framework used, involving defining a problem, planning solutions, implementing strategies, and evaluating outcomes.
3) Details of the two implementations, including adjustments made the second time to address student fatigue.
DEVELOPMENT OF INTERACTIVE INSTRUCTIONAL MODEL USING AUGMENTED REALITY BASED ...IJITE
The research aims to develop an interactive instructional model usingaugmented reality based on
edutainment to enhance emotional quotientand evaluate the model. Two phases of the research will be
carried out: a development and an evaluation of the model. Samples are experts in the field of IT, child
psychology, and 7th grade curriculum management. Ten experts are selected by purposive sampling
method. The obtained data are analyzed using mean and standard deviation.
The research result demonstrates the following findings:
1) The results of this research show that Model consists of 3 elements: IIAR, EduLA, and EQ. EQ is a
means to assess EQ based on Time Series Experimental Design using 2 kinds of tools; i.e. EQ Assessment
by programs in tablet computers, and EQ Assessment by behavioral observation.
2 ( The ten experts have evaluated the model and commented that the developed model showed high
suitability.
DEVELOPMENT OF INTERACTIVE INSTRUCTIONAL MODEL USING AUGMENTED REALITY BASED ...IJITE
The document describes the development of an interactive instructional model using augmented reality and edutainment to enhance emotional quotient. It includes:
1) The development of a model consisting of three elements: interactive instructional augmented reality, edutainment learning activities, and emotional quotient assessment.
2) An evaluation of the model by 10 experts found it to have high suitability, with the interactive instructional augmented reality steps and edutainment learning activity steps rated as having the highest suitability.
3) The experts' evaluation demonstrated that the model's components, steps, and activities were highly suitable for effectively using augmented reality and edutainment to enhance students' emotional quotient.
International Journal of Multimedia & Its Applications (IJMA)ijma
The International Journal of Multimedia & Its Applications (IJMA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Multimedia & its applications. The journal focuses on all technical and practical aspects of Multimedia and its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding recent developments this arena, and establishing new collaborations in these areas.
International Journal of Multimedia & Its Applications (IJMA)ijma
Call for Papers
*****************
International Journal of Multimedia & Its Applications (IJMA)
Contact Us : ijmajournal@airccse.org or ijma@aircconline.com
Submission Deadline : February 18, 2023
website link : https://airccse.org/journal/ijma.html
Virtual Assistants and Its ImplementationOmar Cóndor
This document discusses the implementation of virtual assistants in education. It describes how virtual assistants, which are AI-based software that can interact with users, answer questions, and perform tasks, are beginning to be used as educational tools in classrooms. The document outlines several virtual assistants like Alexa, Siri, Google Assistant, and Cortana, and discusses how they are able to motivate students through interaction, help teach languages, and act as virtual tutors. However, it notes that more research is still needed on their educational applications and impacts on learning outcomes.
Tangible user interface design for learners with different multiple intellige...IJECEIAES
The creation of learning activities responsive to learners with different basic skills has been limited due to a classroom environment and applied technologies. The goals of this research were to develop Tang-MI, a game with a tangible user interface supporting primary school learners’ analytical skills based on the theory of multiple intelligences (MI), and to present design guidelines for a tangible user interface suitable for learners in different MI groups. In this research, the Tangible user interface for multiple intelligence (Tang-MI) was tested with thirty students initially evaluated for their multiple intelligences. The learners’ usage behavior was observed and recorded while the students performed the assigned tasks. The behavioral data were analyzed and grouped into behaviors occurring before performing the tasks, during the tasks, and after completing the tasks. Based on the learners’ usage behavior, the tangible user interface design guidelines for learners in different MI groups were proposed concerning physical equipment design, question design, interactive program design, audio design, and animated visual feedback design. These guidelines would help educators build learning games that respond to the learners’ intelligence styles and enhance students’ motivation to learn.
Autism spectrum disorder is a developmental disability that can cause significant social, communication and behavioural challenges. Parents of children on the spectrum find it difficult for their kids to communicate with them and other people, which makes it challenging for social interactions. Researchers have introduced different solutions such as Therapy Robot that Teaches Social Skills to Children with Autism. Additionally, Virtual reality was used to teach emotional and social skills to children with autism spectrum disorder. However, these solutions focus only on the person on the spectrum, neglecting the fact that the social challenges that people on the spectrum face are partly due to the lack of understanding on the neurotypicals' end. In this study, the solution introduced focuses on the neurotypical perspective; An advanced and interactive intelligent technology that can educate neurotypical people on how to communicate with people on the spectrum in different scenarios and environments. It also allows the learner to see the consequences of the different interactions from the point of view of a person on the spectrum, be aware of their actions, and fully engage in the scenarios through Virtual Reality (VR). Virtual Reality is a technology that simulates experiences that can be similar to the real world. The project aim was achieved by implementing a storyline game that is VR-based.
Similar to Dysgraphia detection based on convolutional neural networks and child-robot interaction (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
Dysgraphia detection based on convolutional neural networks and child-robot interaction
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 13, No. 3, June 2023, pp. 2999~3009
ISSN: 2088-8708, DOI: 10.11591/ijece.v13i3.pp2999-3009 2999
Journal homepage: http://ijece.iaescore.com
Dysgraphia detection based on convolutional neural networks
and child-robot interaction
Soukaina Gouraguine, Mustapha Riad, Mohammed Qbadou, Khalifa Mansouri
M2S2I Laboratory, ENSET Mohammedia, Hassan II University of Casablanca, Mohammedia, Morocco
Article Info ABSTRACT
Article history:
Received Aug 7, 2022
Revised Aug 31, 2022
Accepted Sep 2, 2022
Dysgraphia is a disorder of expression with the writing of letters, words, and
numbers. Dysgraphia is one of the learning disabilities attributed to the
educational sector, which has a strong impact on the academic, motor, and
emotional aspects of the individual. The purpose of this study is to identify
dysgraphia in children by creating an engaging robot-mediated activity, to
collect a new dataset of Latin digits written exclusively by children aged 6 to
12 years. An interactive scenario that explains and demonstrates the steps
involved in handwriting digits is created using the verbal and non-verbal
behaviors of the social humanoid robot Nao. Therefore, we have collected a
dataset that contains 11,347 characters written by 174 participants with and
without dysgraphia. And through the advent of deep learning technologies and
their success in various fields, we have developed an approach based on these
methods. The proposed approach was tested on the generated database. We
performed a classification with a convolutional neural network (CNN) to
identify dysgraphia in children. The results show that the performance of our
model is promising, reaching an accuracy of 91%.
Keywords:
Convolutional neural network
Dysgraphia
Handwriting digits
Interactive scenario
Social humanoid robot Nao
This is an open access article under the CC BY-SA license.
Corresponding Author:
Soukaina Gouraguine
M2S2I Laboratory, ENSET Mohammedia, Hassan II University of Casablanca
Mohammedia, Morocco
Email: soukainagoura@gmail.com
1. INTRODUCTION
Learning disabilities are a major problem for many students who suffer from them [1]. They face real
challenges that are not limited to academic aspects, but also extend to behavioral and social aspects [2]. Recent
studies in the field of learning disabilities have confirmed that the percentage of children with learning disabilities
is continually increasing [3], which obliges the researchers to concentrate their research in this area to conceive
methods of detection and early diagnosis, also develop appropriate programs of treatment to decrease and
attenuate the severity of the student's difficulty of learning and raise them to the level of ordinary students [2], [4].
Among the difficulties encountered by the students during their first steps in school is difficulty with
handwriting. However, the handwriting process constitutes an important competence and a fundamental
starting point in the learning process, rather, it is the common denominator between learning other academic
subjects such as reading, writing, and arithmetic [5]. It is the basis of teaching, learning, logical reasoning, and
solid observation [6]. The ability to write is the result of both mental and physical development related to the
capacity to adapt and transmit signals between the nervous system and the motor systems of the body (muscles)
[7]. The inability to write is the main contributor to school failure [8], and this is where the danger lies, insofar
as the problem of dysgraphia is a hidden difficulty that affects a part of normal children, which leads them to
some psychological troubles [9].
Research highlights the crucial relevance of identifying and remedying these writing challenges as soon
as feasible [7], because it can affect the whole life cycle of the student, damaging their academic achievement and
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self-esteem in a variety of educational activities [10]. Motor competencies affect the severity of dysgraphia and
contribute principally to the development of dysgraphia in the earliest stages of a child's development [11]. A
common assessment defined as the brief evaluation scale for children's handwriting (BHK) serves to identify
writing difficulties. It represents the reference test for assessing the quality and speed of children's handwriting.
This detection, conducted by therapists, is time-consuming due to its high cost and subjectivity. Therefore, several
researchers have attempted to find solutions and numerical approaches to identify and characterize handwriting
difficulties [12]. Similarly, the development of writing skills requires regular practice and a profound learning
process. Given the significance of time in the processes of teaching and learning, the acquisition and accurate
treatment ofthe redaction abilities require the interventionof mechanisms that ensure time and permit constructive
communication, breaking the frontiers of the students' fear and timidity towards the teacher.
Some scientific studies revealed that social robots (SR), can play an important role in the educational
process [13]. They were considered intelligent tutoring systems, which have the potential to become a
component of the educational infrastructure, such as paper, tablets, and, whiteboards, releasing time for the
teacher to focus on the core aspects of education such as providing a comprehensive and productive learning
experience [14]. In addition, SR has gained popularity during the previous years and is expected to be used in
a variety of social applications. They have produced therapy interventions for autistic children [15], [16],
exercise trainers, and provided specialized education and assistance to the elderly [17].
However, several machine learning algorithms have been used to investigate the topic of identifying
dysgraphia, for example, support vector machines (SVM) [18], and the k-nearest neighbors (KNN) [11].
Research affirms that a convolutional neural network (CNN) is a category of neural network that has been
proven to be very efficient in performing tasks like image classification and recognition [19]. The CNNs
became a standard in text recognition [20], producing exceptional results. Moreover, CNN models are
perceived to be the best-performing algorithms achieving excellent outcomes on the modified national institute
of standards and technology (MNIST) dataset [21], which represents the most commonly used benchmark for
the recognition of single handwritten digits, and EMNIST [22], as well as Latin and Chinese letters [10].
Furthermore, in order to improve the classification process of dysgraphia in children we intend to apply the
convolutional neural network-based deep learning methods and human-robot interactions [23]. In this regard,
the following are the primary contributions of our research: i) the creation of an engaging activity based on
robot-child interaction; ii) a new fully annotated dataset containing images captured in real-time conditions of
several handwritings of digits and containing 11,347 images, coming from the top camera of our Nao robot;
and iii) a validation step based on deep learning.
2. RELATED WORK
In this section, we briefly examine the existing research related to our present work on the analysis of
handwriting legibility and the machine learning approaches used to identify dysgraphia in children. Thus, the
social assistance robotics to which our research contributes most directly to establishing child-robot interaction.
2.1. Assistive robotics in education
The integration and inclusion of children with special needs in educational environments are made
possible by the immense creative potential of assistive technology and robots [24]. Then to achieve the
fundamental requirement for inclusive and sustainable education [25], where children with disabilities are to
be successfully included in the educational environments, it is required to develop and create new and
innovative opportunities that allow all children and young people the opportunity to learn despite their special
needs [26]. Accordingly, social robotics can be an effective tool in the educational sector to establish a more
efficient and inclusive learning experience for children to help them develop socially and academically while
performing child-robot interactions in real time. Social robots constitute a potential resource in inclusive
education due to their simplicity of interaction with humans and because they stimulate cooperation and
collaboration in different ways, which facilitates the rapid assimilation of information by the recipient. This
increases their ability to communicate and social competencies or to provoke unexpected situations and break
communication barriers such as shyness and fear. Because robots are incapable to identify misunderstandings,
they can encourage dysgraphic children to enhance their communication skills [27]. Thus, robots have been
used as teachers or social agents to support children's learning in a diverse context, most frequently related to
language and writing skills, although the social robot may be employed not only as a communicator or teacher,
but also as a mediator to engage with others, increasing the child's abilities, and competencies.
2.2. Machine learning approaches used to identify dysgraphia
Handwriting recognition is a process of identifying letters, digits, and symbols of a written language
by hand presented to the system through an image or video format. It is just a classification assignment in
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mathematical terms. A video or picture as input data must be classified by the resulting system into one of the
predefined classes. Machine learning has proven a very important tool for the analysis of handwriting and many
investigations have generated models to address this. The MNIST dataset has been classified using a variety
of machine learning approaches, from the multilayer perceptron (MLP) [28] to versions of SVM [18] that are
more complicated. However, the MNIST dataset, Latin letters, and Chinese characters show that the CNN
models perform well by providing exceptional results [22]. This research uses advanced deep learning
approaches to recognize the handwriting of learners representing dysgraphia in order to classify them. Deep
learning represents a high-level abstraction algorithm that enables the modeling of data from large, trained
datasets. While there are a large number of models in the literature for recognizing numbers, letters, words, or
written sentences in different languages, such as Arabic, English, Chinese, and Hebrew [29], very few studies
have assessed handwriting legibility and intelligibility for the purpose of detecting dysgraphia in children [30].
In certain studies, the classification of dysgraphic and non-dysgraphic children in Hebrew script was
done by using an SVM classifier on a collection of manually collected handwriting features [29]. The SVM
model is also used to determine if the child has an English writing disability or not, based on the specified input
characteristics in the search [31] such as letter slant, letter size, spacing, and pressure, the model is mainly
suitable for children aged 5 to 12 years. In other studies [32], 98% of the 56 dysgraphic students in their dataset
were accurately identified using the Random Forest supervised machine learning technique, which is often
employed in classification challenges. Their approach was based on the BHK test (Latin alphabet) [33]. The
following study [34] introduced a numerical approach to identifying and characterizing handwriting difficulties
via a recurrent neural network (RNN) model. An RNN is a kind of neural network widely used in the field of
deep learning. Using the BHK test successfully diagnoses more than 90% of dysgraphic children.
In our work, we intend to create a child-robot interaction-based screening test to efficiently detect
dysgraphia in a school classroom context by adopting a new approach based on the use of CNN to a new set
of data collected through the interaction between learners and the robot. We designed a prototype image,
respecting a predefined pattern and focusing on digits that are already learned in the early school years. In
addition, we constructed a customized training system that would produce specific numbers specifically
selected to meet the child's training requirements. The section that follows describes our motivations as well
as the machine learning methods we employed to construct and build our diagnostic models.
3. METHOD
3.1. Overall process
We have presented the general process describing our work in Figure 1. The important step at the
beginning of the pipeline consists of initiating the process of data collection. Then, we used the classification
algorithm CNN on the gathered dataset to identify dysgraphia in the children.
- Interactive scenario with the robot: this step aims to establish the learner-robot interaction in order to collect
the data. This interaction was carried out by using the humanoid robot Nao (V6) which has been
programmed with Choregraphe [35] to perform the desired actions and appropriate interventions to
complete the teaching-learning process, such as initiating exchange and discussion about the presentation,
hand-waving, speaking, and moving.
- Data collection: among the objectives of the study was the constitution of a database of digits handwritten
by children in order to explore the writing affected by dysgraphia.
- Data preprocessing: this technique consists of data mining and transformation of the raw data into a useful
and efficient format, which enables the next step of feature extraction, where relevant information is
extracted that helps in classification. Feature extraction is a difficult, generally time-consuming process that
cannot process the raw visual data. The manually extracted features are used to classify the image into a
specific class.
- CNN Classification: once the dataset is well defined, CNN can be used for image classification. CNNs are
now able to achieve excellent results in the case of handwriting recognition[36].
- Result evaluation: the proposed approach provides excellent accuracy results. More details are given in the
results section.
Figure 1. The overall process for the deep learning detection of the dysgraphia
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3.2. The informational scenario mediated by the robot
3.2.1. Nao robot
In the educational sector, the humanoid robot Nao is considered the main mediating robot used as an
assisted teaching instrument. The integration and implementation of this robotic tool in education, especially
in early education, has shown positive results. As a programmable robot, Nao may be used to support a vast
number of interactive activities targeting various audiences and goals. This research uses the Nao robot, shown
in Figure 2, as a tool to incorporate both verbal and non-verbal communication into the child-robot interaction
with its user. This autonomous and programmable robot developed by Aldebaran robotics in 2006, is small
(58 cm) and completely equipped with cameras and several sensors, enabling the robot to interact with its
environment in a variety of ways. Nao can speak several languages, tell stories, play music, recognize human
faces, and has other advanced features and functionalities [37].
Figure 2. Nao robot used for our research
3.2.2. Experimental environment and participants
An appropriate structure was prepared to perform the experiment. A classroom organization system
has been adopted, consisting of tools and equipment that make the classroom the ideal learning environment.
The room is equipped with tables, a projection screen, and a video camera to record the progress of the session.
In addition, there is the robot and the children, each child is equipped with a tablet and a pen or paper and a
pen. Near the classroom, there is the Wizard of Oz, who has the ability to control the behavior of the robot as
needed and as the situation demands. The configuration of the experimental environment is shown in Figure 3.
Figure 3. The setting of the experimentation
The unseen human operator in the next room was responsible for controlling the behavior of the Nao
robot, applying the Wizard of Oz approach [38], in terms of managing the robot-mediated activity and initiating
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the various Nao robot movement sequences, including sequences of improvised verbal and non-verbal
behavior. The Nao robot was positioned in front of the presentation backboard and located at a distance of
approximately 1.50 m so that the students could see it clearly, and to make the robot's gestural explanations
easier to see on a visual level. In addition, Nao is placed on the floor because the scenario also includes walking
movements, the robot must move around the board and towards the students in order to cover the classroom so
as to promote engagement and the illusion of agentivity among them.
3.2.3. Sequence diagram of the establishment of the student-robot interaction
An interactive scenario involving robot behaviors both verbal and nonverbal was conceived to collect
the new dataset. A procedure was adopted to perform the task and to make the data collection process simple
and easy, respecting the teaching standards. To do this, the course elements presented by the Nao robot were
selected based on the educational program taught to students at an early grade level. The scenario was created
in a variety of versions and iteratively tested with researchers and professionals in the area of education because
the content of the lesson model presented by the robot had to be accurate and convincing to ensure good quality
content. First, using a unified modeling language (UML) sequence diagram, a child-robot interaction model is
created, as in Figure 4, to represent the general scenario adopted to describe the relevant information and
actions that are executed during the student-robot interaction, focusing on the sequence of actions to be
performed.
Figure 4. Sequence diagram of the global interactive scenario
The sub-mentioned sequence diagram models the overall interaction of the activity from its initial
stages between the child, the robot, and the WoZ in the temporal progression and during the interaction task in
the context of dysgraphia detection. A scenario presented in Figure 5 describes an example of a perfect, and
real, conversation between the child and the Nao robot initiated by the WoZ. The scenario is composed of three
sequences described as follows.
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- Introduction: The Nao robot introduces itself as an assistant supporting teacher and provides a general
overview of the session's objectives by explaining the process followed to successfully master the
handwriting of digits.
- Course presentation: The Nao robot starts by teaching learners the basic concepts of how to write a number,
including the following steps: teach children to count from zero to nine, pronounce each digit aloud by
pointing fingers, present each digit in order, demonstrate to children how to write the numbers correctly, and
reinforce the importance of the sequence of digits.
- Data gathering: The Nao robot contributes to enhancing the learners' abilities by engaging their sense of
practice and training on the handwriting of digits. The process concludes by collecting the learners'
handwriting attempts on their reference papers.
Figure 5. Outline of an educational interactive scenario for the presentation of the digits handwriting for data
collection
3.2.4. Dataset
The collected data set of 174 learners was used for the analysis and prediction of dysgraphia among
the learners. The reference paper used is intended to prepare a uniform writing structure for children and at the
same time, it was used to analyze legibility and spatial awareness. In addition, other parameters such as skills
related to the structure and expression of numbers, visuomotor integration, visuospatial relationship, and even
the time data of the learners were analyzed. The resulting dataset contains 11,347 images equally divided
between twenty classes, digits with dysgraphia and digits without dysgraphia. These images are distributed in
three folders: testing, learning, and validation. Some of the 11,347 images contained in the database are shown
in Figure 6, a selection of the handwritings affected by dysgraphia have presented in Figure 6(a), while the
handwritings of normal children have been displayed in Figure 6(b).
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(a) (b)
Figure 6. The handwriting of learners; (a) with dysgraphia and (b) without dysgraphia
3.2.5. CNN classification
As previously mentioned, in this research, we performed classification with CNN to identify
dysgraphia in children. For image classification tasks, CNNs are currently the most sophisticated model
architecture. CNNs employ a succession of filters to extract and learn higher-level characteristics from an
image's initial raw pixel data, which the model may subsequently use for categorization. In the area of
recognizing handwritten digits, CNN is one of the most used algorithms, it plays two main roles in image
processing, the role of a feature extractor with a convolution process that treats the data, and the role of a classifier
that contains several layers to classify the images. Figure 7 illustrates the complete architecture of a CNN.
Figure 7. The complete architecture of the CNN
4. RESULTS AND DISCUSSION
4.1. Training and validation curves
After implementing our CNN classification algorithm, we compared their accuracy and execution
time using experimental graphs for a better understanding. We allocated 8,525 images for training,
2,483 images for validation, and 2,822 for testing. We also set the epoch size to 50 initially for analysis. The
graph of the training and validation accuracy with the best epoch designation is shown in Figure 8(a). When
the epoch size is 42, the training and validation curves start to flatten, and the accuracy is 91% and higher.
Figure 8(b) shows the training performance as a function of the epoch. As we can see, the learning loss plot
decreases until the epoch size is 2. However, after the epoch size is 40, the validation loss plot starts to increase,
which means that the training is overfitted.
4.2. Confusion matrix
In order to explore the performance of the developed CNN on each output class, and to see where the
model gets confused, i.e., which classes the model predicts correctly and which classes the model predicts
incorrectly, the confusion matrix was calculated; it is presented in Figure 9. We can see that our CNN works
extremely well on all digits with few errors given the size of the validation set (2,062 images). However, it
seems that our CNN has some small problems with the number 1, which is misclassified as 7. Sometimes it is
very difficult to catch the difference between 1 and 7 when the curves are smooth, and when the middle line
for seven or the bottom line for 1 are absent.
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(a) (b)
Figure 8. Training and validation: (a) accuracy and (b) loss in our CNN model
Figure 9. Normalized confusion matrix for children's handwriting digit classification results based on the CNN
4.3. Performance measures
A confusion matrix is a table that is frequently used to evaluate the result of a machine-learning model
based on a training dataset where the true values are known. In addition, some performance measures are
applied to analyze the classifier's performance, such as precision, recall, and F-factor. Table 1 shows the
classification report for our neural network model. Although the accuracy could reach 91% in our CNN model,
we were still able to use the classification report to analyze our results and reinforce our dataset.
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Table 1. Classification report
Classes Precision Recall F1-score Support
eight_correct 0.9821 1.0000 0.9910 220
eight_incorrect 0.6383 0.7143 0.6742 42
five_correct 0.9815 0.9422 0.9615 225
five_incorrect 0.4750 0.7308 0.5758 26
four_correct 0.9965 1.0000 0.9982 285
four_incorrect 0.9167 0.3235 0.4783 34
nine_correct 1.0000 1.0000 1.0000 270
nine_incorrect 0.8929 0.7143 0.7937 35
one_correct 0.6909 0.9955 0.8156 220
one_incorrect 0.7273 0.8000 0.7619 50
seven_correct 1.0000 0.5617 0.7193 235
seven_incorrect 0.4571 0.8205 0.5872 39
six_correct 0.9787 1.0000 0.9892 230
six_incorrect 0.7838 0.8788 0.8286 33
three_correct 0.9711 1.0000 0.9853 235
three_incorrect 0.8636 0.5278 0.6552 36
two_correct 0.9831 0.9667 0.9748 300
two_incorrect 0.8125 0.3611 0.5000 36
zero_correct 0.9919 1.0000 0.9959 245
zero_incorrect 0.7419 0.8846 0.8070 26
Accuracy 0.9139 2822
macro avg 0.8442 0.8111 0.8046 2822
weighted avg 0.9321 0.9139 0.9111 2822
In our case, the one_correct class has high recall but low precision. This illustrates the fact that the
number of test data is not one_correct but the model recognizes it as one_correct is large. For the seven_correct
class, it has high precision but low recall. This presents that many numbers are seven_correct but the model
recognizes it as a different number. The rest of the classes have high recall and high precision, which means
that all results come back correctly in this class. According to this observation, most of the one_correct classes
were recognized correctly but some seven_correct classes were recognized as one_correct. Thus, we could
improve our dataset by increasing the number of seven_correct classes to enhance the identification
performance of the seven_correct class. To indicate, the incorrect word means that the class corresponds to the
handwriting of the digits referring to a child with dysgraphia, while the correct word corresponds to the class
of normal handwriting for a child without dysgraphia.
5. CONCLUSION
This research introduces the humanoid robot Nao that establishes a child-robot interaction with both
dysgraphic and non-dysgraphic students at the primary school level. The motivation behind this research is to
differentiate between students with and without dysgraphia in an educational environment using an assistant
robot. This research was performed by using CNN on the collected dataset. The three principal research
objectives are satisfied: first, an interactive, stimulating, functional, and explicative scenario of the humanoid
robot Nao that allows demonstration to the learners of the method of handwriting the digits, second, the capture
of the students' handwriting using the camera of the robot Nao permitted us to create a new dataset, and finally,
the realized model produced precious results. We have demonstrated that our model can identify dysgraphia
from the learners' handwriting with an accuracy of 91%, a precision of 93%, a recall of 91%, and an F1 score
of 91%. Results indicate that the suggested approach is quite efficient in terms of accuracy. The CNN proves
to be a more robust classifier, providing valuable results.
The focus of our future research will be focused on students with special needs so that they can have
an inclusive education that allows them to challenge their disabilities and advance toward academic excellence.
Therefore, we wish to perform an adjacent, supervised classification allowing our assistant robot Nao to
classify students affected by dysgraphia according to the severity of their affectation and according to their
type of dysgraphia in order to help them fight and surmount their handicap.
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BIOGRAPHIES OF AUTHORS
Soukaina Gouraguine was born in Casablanca, Morocco. She is a Ph.D. student
and part of the team: Distributed Computing Systems in the research laboratory: Signals,
Distributed Systems and Artificial Intelligence at the ENSET Institute of Mohammedia. Her
doctoral work explores the creation and integration of intelligent robotic agents for assistance
in innovative educational systems, especially for users (students and teachers) with special
needs. She holds a master's degree in Engineering Informatics and Internet from the University
Hassan II Casablanca in 2019. She can be contacted at soukainagoura@mail.com.
Mustapha Riad was born in Tinghir, Morocco. He is a Ph.D. student and part of
the team: Distributed Computing Systems in the research laboratory: Signals, Distributed
Systems and Artificial Intelligence at the ENSET Institute of Mohammedia. He received his
master’s degree in Information Systems Engineering (ISI) from the Cadi Ayyad University
Marrakech in 2019. Her doctoral work explores contribution to the development of intelligent
education systems and adaptive learning through the personalization and adaptation of
educational content, for the learner. He can be contacted at My.mustapha.riad@gmail.com.
Mohammed Qbadou was born in Kalaa Sraghna, Morocco. He obtained a
master's degree in Mechanical Engineering from ENSET of Mohammedia in 1992, the DEA
in energetics and physics in 1993, and the first Ph.D. in robotics especially in the modeling
and control of flexible manipulator robots at the Mohammed V University of Rabat in 1998,
the HDR in computer science in 2017 and the second Ph.D. in computer science in 2021 at the
Hassan II University of Casablanca. Since 1998, he has been a research professor in computer
science at ENSET of Mohammedia. His research focuses on semantic web, big data analytics,
artificial intelligence, inclusive smart education systems, and assistive robotics. He has
accumulated 30 years of experience in teaching mechanical engineering, robotics, and
computer science. In scientific research, he has produced over 100 indexed publications. He
can be contacted at qbmedn7@gmail.com.
Khalifa Mansouri was born in AZILAL, Morocco. At the present, he works as a
researcher and computer science teacher at the ENSET Institute of the University Hassan II of
Casablanca. His research interests include real-time systems, information systems, e-learning
systems, and industrial systems (modeling, optimization, and numerical computing). Degrees
from ENSET of Mohammedia in 1991, CEA in 1992, and a Ph.D. in calculation and
optimization of structures at Mohammed V University in Rabat in 1994, HDR in 2010, and a
Ph.D. in computer science from the University of Hassan II in Casablanca in 2016. He can be
contacted at khmansouri@hotmail.com.