Search results for: adversarial machine learning

Authors: Ali Shah

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This paper outlines the case study experience of using a variety of online strategies in an Australian music academy context during covid times. The study aimed at exploring how online applications help students to learn music, specifically playing musical instruments, composing songs, and performing virtually. To explore this, music teachers’ perceptions and experiences regarding online learning, the teaching strategies they implemented, and the challenges they faced were examined. For the purpose of this study, a qualitative research structure was adopted through the use of three data collection tools. These methods included pre- and post-research individual interviews of teachers and students, analysis of their lesson plans, virtual classroom observations of the teachers followed by the researcher’sown reflections, post-observation discussions, and teachers’ reflective journals. The findings revealed that teachers had a theoretical understanding of virtual learning and recent musical application such as Flowkey, Skoove, and Piano marvel, which are benefits of e-learning. While teachers faced challenges in implementing strategies to teach keyboard/piano online, overall, both students and teachers felt the positive impact of online applications and strategies on their learning and felt that modern technology made it possible for anyone to take music lessons at home.

Keywords: music, keyboard, piano, online learning, virtual learning

Procedia PDF Downloads 73

Authors: Y. Alrubyli

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Unmanned Arial Vehicles (UAVs), and more specifically, quadcopters need to be stable during their flights. Altitude stability is usually achieved by using a PID controller that is built into the flight controller software. Furthermore, the PID controller has gains that need to be tuned to reach optimal altitude stabilization during the quadcopter’s flight. For that, control system engineers need to tune those gains by using extensive modeling of the environment, which might change from one environment and condition to another. As quadcopters penetrate more sectors, from the military to the consumer sectors, they have been put into complex and challenging environments more than ever before. Hence, intelligent self-stabilizing quadcopters are needed to maneuver through those complex environments and situations. Here we show that by using online reinforcement learning with minimal background knowledge, the altitude stability of the quadcopter can be achieved using a model-free approach. We found that by using background knowledge instead of letting the online reinforcement learning algorithm wander for a while to tune the PID gains, altitude stabilization can be achieved faster. In addition, using this approach will accelerate development by avoiding extensive simulations before applying the PID gains to the real-world quadcopter. Our results demonstrate the possibility of using the trial and error approach of reinforcement learning combined with background knowledge to achieve faster quadcopter altitude stabilization in different environments and conditions.

Keywords: reinforcement learning, Q-leanring, online learning, PID tuning, unmanned aerial vehicle, quadcopter

Procedia PDF Downloads 170

Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju

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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.

Keywords: school climate, parental involvement, ODL, learning gains, mathematics

Procedia PDF Downloads 519

Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

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Authors: Zolzaya Badmaavanchig, Shoko Miyamoto

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In recent years, universal design for learning (hereinafter referred to as "UDL"), which aims to establish an inclusive education system and to make all children, regardless of their disabilities, experts in learning, has been attracting attention, and there have been some attempts to incorporate it into regular classrooms where children with developmental disabilities and those who show such tendencies are enrolled. The purpose of this study was to examine the effectiveness and challenges of implementing UDL in Japanese elementary schools based on the previous literature. As a method, we first searched for articles on UDL for learning and UDL in the classroom from 2010 to 2022. In addition, we selected practice studies that targeted children with special educational support needs and the classroom as a whole. In response to the extracted literature, this bridge examined the following five perspectives: (1) subjects and grades in which UDL was practiced, (2) methods to grasp the actual conditions of the children, (3) consideration for children with special needs during class, (4) form of class, and (5) effects of the practice. Based on the results, we would like to present issues related to future UDL efforts in Japanese elementary schools.

Keywords: universal design for learning, regular elementary school class, children with special education needs, special educational support

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Authors: Haruya Tamaki, Tsugunosuke Sakai, Ryuichi Yoshida, Ryohei Egusa, Shigenori Inagaki, Etsuji Yamaguchi, Fusako Kusunoki, Miki Namatame, Masanori Sugimoto, Hiroshi Mizoguchi

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Art appreciation is important as part of children education. Art appreciation can enrich sensibility and creativity. To enrich sensibility and creativity, the children have to learning knowledge of picture such as social and historical backgrounds and author intention. High learning effect can acquire by actively learning. In short, it is important that encourage learning of the knowledge about pictures actively. It is necessary that children feel like interest to encourage learning of the knowledge about pictures actively. In a general art museum, comments on pictures are done through writing. Thus, we expect that this method cannot arouse the interest of the children in pictures, because children feel like boring. In brief, learning about the picture information is difficult. Therefore, we are developing an art-appreciation support system that will encourage learning of the knowledge about pictures actively by children feel like interest. This system uses that Interacting with Pictures to learning of the knowledge about pictures. To Interacting with Pictures, children have to utterance by themselves. We expect that will encourage learning of the knowledge about pictures actively by Interacting with Pictures. To more actively learning, children can choose who talking with by information that location and movement of the children. This system must be able to acquire real-time knowledge of the location, movement, and voice of the children. We utilize the Microsoft’s Kinect v2 sensor and its library, namely, Kinect for Windows SDK and Speech Platform SDK v11 for this purpose. By using these sensor and library, we can determine the location, movement, and voice of the children. As the first step of this system, we developed ukiyo-e game that use ukiyo-e to appreciation object. Ukiyo-e is a traditional Japanese graphic art that has influenced the western society. Therefore, we believe that the ukiyo-e game will be appreciated. In this study, we applied talking to pictures to learn information about the pictures because we believe that learning information about the pictures by talking to the pictures is more interesting than commenting on the pictures using only texts. However, we cannot confirm if talking to the pictures is more interesting than commenting using texts only. Thus, we evaluated through EDA measurement whether the user develops an interest in the pictures while talking to them using voice recognition or by commenting on the pictures using texts only. Hence, we evaluated that children have interest to picture while talking to them using voice recognition through EDA measurement. In addition, we quantitatively evaluate that enjoyed this game or not and learning information about the pictures for primary schoolchildren. In this paper, we summarize these two evaluation results.

Keywords: actively learning, art appreciation, EDA, Kinect V2

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Authors: Najith Duminda Galmangoda Guruge, Nadeeka Rathnayake, Vinodani Wimalasena, Dinesha Wijesooriya

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Investing in Early Learning can improve children’ interests for education and makes them ready for school. Children in economically disadvantaged communities may have reduced readiness for schools. Health Promotion approach enables communities including disadvantaged to control over their health. Mothers of children under the age five in ‘Alapathwewa’ community (n=40) were selected as the sample with the aim to promote early learning of children to improve their school readiness. Mothers in ‘Morakeewa’ community (n=40) were the control. Interventions were for a period of 2 years and children of these mothers were followed up to school entry. Importance of early learning and possibility of providing quality learning environments for children at a low cost was discussed with mothers in an experimental setting by facilitators. Mothers were enabled to make age-appropriate baby rooms which provide learning opportunities. Collective community playhouses and play areas were developed by mothers to provide opportunities for children to interact and learn with each other. Mothers started discussing with each other and sharing experiences. The progress was monitored by mothers at regular intervals. Data regarding school competencies of children were obtained from school teachers. School teachers measured thirteen competencies of children on a scale of ‘very good, good, moderate and weak’. All children in the experimental group were in ‘very good’ level in two competencies, ‘communicate friendly with others’ and ‘express ideas well’. Children in the experimental group reported a significantly higher achievement of all thirteen competencies (p < .05) than children in control. Providing quality early learning environments for children even in economically disadvantaged settings makes them ready for schools. Through a Health Promotion approach, early learning experiences for children can be provided at a low cost.

Keywords: disadvantaged, early learning, economically, health promotion

Procedia PDF Downloads 257

Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

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MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize the human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: computer vision, MediaPipe, adaptive boosting, fast dynamic time warping

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Authors: Lakdar Sadi-Haddad

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The past few years study of very high speed electrical drives have seen a resurgence of interest. An inventory of the number of scientific papers and patents dealing with the subject makes it relevant. In fact democratization of magnetic bearing technology is at the origin of recent developments in high speed applications. These machines have as main advantage a much higher power density than the state of the art. Nevertheless particular attention should be paid to the design of the inverter as well as control and command. Surface mounted permanent magnet synchronous machine is the most appropriate technology to address high speed issues. However, it has the drawback of using a carbon sleeve to contain magnets that could tear because of the centrifugal forces generated in rotor periphery. Carbon fiber is well known for its mechanical properties but it has poor heat conduction. It results in a very bad evacuation of eddy current losses induce in the magnets by time and space stator harmonics. The three-phase inverter is the main harmonic source causing eddy currents in the magnets. In high speed applications such harmonics are harmful because on the one hand the characteristic impedance is very low and on the other hand the ratio between the switching frequency and that of the fundamental is much lower than that of the state of the art. To minimize the impact of these harmonics a first lever is to use strategy of modulation producing low harmonic distortion while the second is to introduce a sinus filter between the inverter and the machine to smooth voltage and current waveforms applied to the machine. Nevertheless, in very high speed machine the interaction of the processes mentioned above may introduce particular harmonics that can irreversibly damage the system: harmonics at the resonant frequency, harmonics at the shaft mode frequency, subharmonics etc. Some studies address these issues but treat these phenomena with separate solutions (specific strategy of modulation, active damping methods ...). The purpose of this paper is to present a complete new active harmonic compensation algorithm based on an improvement of the standard vector control as a global solution to all these issues. This presentation will be based on a complete theoretical analysis of the processes leading to the generation of such undesired harmonics. Then a state of the art of available solutions will be provided before developing the content of a new active harmonic compensation algorithm. The study will be completed by a validation study using simulations and practical case on a high speed machine.

Keywords: active harmonic compensation, eddy current losses, high speed machine

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Authors: Jessica Chakowa

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Learning a foreign language requires practice that needs to be undertaken beyond the classroom. Nowadays, learners can find a lot of resources online, but it can be challenging for them to find suitable material, receive timely and effective feedback on their progress, and, more importantly practice the target language with native speakers. This paper focuses on the development of interactive activities combined with online tutoring sessions to consolidate and enhance the learning experience of beginner students of French at * University. This project is based on collaboration with four pre-service teachers from a French university. It calls for authentic language learning material, real-life situations, cultural awareness, and aims for the sustainability of learning and teaching. The paper will first present the design of the project as part of a holistic approach. It will then provide some examples of activities before commenting on the learners and the teachers’ experiences based on quantitative and qualitative data obtained through activity reports, surveys and focus groups. The main findings of the study lie in the tension between the willingness to achieve pedagogical goals and to be involved in authentic interactions, highlighting the complementary between the role of the learner and the role of teacher. The paper will conclude on benefits, challenges and recommendations when implementing such educational projects.

Keywords: authenticity, language teaching and learning, online interaction, sustainability

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Authors: J. Lu, H. Li, F. Cole

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This paper proposes a high-frequency rotary transformer (HFRT) for a separately excited synchronous machine (SESM) used in a flywheel energy storage system. The SESM can eliminate and reduce rare earth permanent magnet (REPM) usage and provide a better performance in renewable energy systems. However, the major drawback of such SESM is the necessity of brushes and slip rings to supply the field current, which increases the maintenance cost and operation reliability. To overcome these problems, an HFRT integrated with SiC semiconductor devices can replace brushes and slip rings in the SESM. The proposed HFRT features a high-frequency magnetic ferrite for both the stationary part as the transformer primary and the rotating part as the transformer secondary, as well as an air gap, allowing safe operation at high rotational speeds. Hence, this rotary transformer can enable the adoption of a wound rotor synchronous machine (WRSM). The HFRT, working at over 100kHz operating frequency, exhibits excellent performance of power efficiency and significant size reduction. The experimental validations to support the theoretical findings have been provided.

Keywords: brushes and slip rings, flywheel energy storage, high frequency rotary transformer, separately excited synchronous machine

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Authors: Ani Demetrashvili

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As online learning continues to reshape the landscape of education, questions arise regarding its efficacy for diverse learning styles, particularly for visual learners. This abstract delves into the impact of online learning on visual learners, exploring how digital mediums influence their educational experience and how educational platforms can be optimized to cater to their needs. Visual learners comprise a significant portion of the student population, characterized by their preference for visual aids such as diagrams, charts, and videos to comprehend and retain information. Traditional classroom settings often struggle to accommodate these learners adequately, relying heavily on auditory and written forms of instruction. The advent of online learning presents both opportunities and challenges in addressing the needs of visual learners. Online learning platforms offer a plethora of multimedia resources, including interactive simulations, virtual labs, and video lectures, which align closely with the preferences of visual learners. These platforms have the potential to enhance engagement, comprehension, and retention by presenting information in visually stimulating formats. However, the effectiveness of online learning for visual learners hinges on various factors, including the design of learning materials, user interface, and instructional strategies. Research into the impact of online learning on visual learners encompasses a multidisciplinary approach, drawing from fields such as cognitive psychology, education, and human-computer interaction. Studies employ qualitative and quantitative methods to assess visual learners' preferences, cognitive processes, and learning outcomes in online environments. Surveys, interviews, and observational studies provide insights into learners' preferences for specific types of multimedia content and interactive features. Cognitive tasks, such as memory recall and concept mapping, shed light on the cognitive mechanisms underlying learning in digital settings. Eye-tracking studies offer valuable data on attentional patterns and information processing during online learning activities. The findings from research on the impact of online learning on visual learners have significant implications for educational practice and technology design. Educators and instructional designers can use insights from this research to create more engaging and effective learning materials for visual learners. Strategies such as incorporating visual cues, providing interactive activities, and scaffolding complex concepts with multimedia resources can enhance the learning experience for visual learners in online environments. Moreover, online learning platforms can leverage the findings to improve their user interface and features, making them more accessible and inclusive for visual learners. Customization options, adaptive learning algorithms, and personalized recommendations based on learners' preferences and performance can enhance the usability and effectiveness of online platforms for visual learners.

Keywords: online learning, visual learners, digital education, technology in learning

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Authors: Jacob Medupe

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Life as we know it has changed since the global outbreak of Coronavirus Disease 2019 (COVID-19) and business as usual will not continue. The human impact of the COVID-19 crisis is already immeasurable. Moreover, COVID-19 has already negatively impacted economies, livelihoods and disrupted food systems around the world. The disruptive nature of the Corona virus has affected every sphere of life including the culture and teaching and learning. Right now the majority of education research is based around classroom management techniques that are no longer necessary with digital delivery. Instead there is a great need for new data about how to make the best use of the one-on-one attention that is now becoming possible (Diamandis & Kotler, 2014). The COVID-19 pandemic has necessitated an environment where the South African learners are focused to adhere to social distancing in order to minimise the wild spread of the Corona virus. This arrangement forces the student to utilise the online classroom technologies to continue with the lessons. The historical reality is that the country has not made much strides on the closing of the digital divide and this is particularly a common status quo in the deep rural areas. This will prove to be a toll order for most of the learners affected by the Corona Virus to be able to have a seamless access to the online learning facilities. The paper will seek to look deeply into this reality and how the Corona virus has brought us to the reality that South Africa remains a deeply unequal society in every sphere of life. The study will also explore the state of readiness for education system around the online classroom environment.

Keywords: virtual learning, virtual classroom, COVID-19, Corona virus, internet connectivity, blended learning, online learning, distance education, e-learning, self-regulated Learning, pedagogy, digital literacy

Procedia PDF Downloads 126

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Bok Check Meng, Goh Ying Soon

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Giving additional learning materials such as Chinese fantasy novel to non-native learners can be strenuous. Instructors have to understand the underpinning theories about cognitive theory for new word instruction. This paper discusses the underpinning theories. Relevant literature reviews are given. There are basically five major areas of cognitive related theories mentioned in this article. These include motivational learning theory, Affective theory of learning, Cognitive psychology theory, Vocabulary acquisition theory and Bloom’s cognitive levels theory. A theoretical framework has been constructed. Thus, this will give a hand in ensuring non-native learners might gain positive outcomes in the instruction process. Instructors who are interested in teaching new word from Chinese fantasy novel in specific to support additional learning might be able to get insights from this article.

Keywords: Chinese fantasy novel, new word teaching, non-native learners, cognitive theory, bloom

Procedia PDF Downloads 734

Authors: Xi Vivien Wu, Emily Neo Kim Ang, Yi Jung Tung, Wenru Wang

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Background and Objective: The increase in life expectancy and emphasis on self-reliance for the older adults are global phenomena. As such, lifelong learning in the community is considered a viable means of promoting successful and active aging. This systematic review aims to examine various lifelong learning programs for community-dwelling older adults and to synthesize the contents and outcomes of these lifelong learning programs. Methods: A systematic search was conducted in July to December 2016. Two reviewers were engaged in the process to ensure creditability of the selection process. Narrative description and analysis were applied with the support of a tabulation of key data including study design, interventions, and outcomes. Results: Eleven articles, which consisted of five randomized controlled trials and six quasi-experimental studies, were included in this review. Interventions included e-health literacy programs with the aid of computers and the Internet (n=4), computer and Internet training (n=3), physical fitness programs (n=2), music program (n=1), and intergenerational program (n=1). All studies used objective measurement tools to evaluate the outcomes of the study. Conclusion: The systematic review indicated lifelong learning programs resulted in positive outcomes in terms of physical health, mental health, social behavior, social support, self-efficacy and confidence in computer usage, and increased e-health literacy efficacy. However, the lifelong learning programs face challenges such as funding shortages, program cuts, and increasing costs. A comprehensive lifelong learning program could be developed to enhance the well-being of the older adults at a more holistic level. Empirical research can be done to explore the effectiveness of this comprehensive lifelong learning program.

Keywords: community-dwelling older adults, e-health literacy program, lifelong learning program, the wellbeing of the older adults

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Authors: Hamid Chaikhy, Mouna Essaadi, Aziz El Afia

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This paper presents an experimental implementation of a new direct torque control strategy of induction machine called twelve sectors direct torque control strategy (12_DTC) using DSPACE TMS 320F2812.The aim of this work is to give an experimental performance analysis of 12_DTC in term of torque, currents distortions and stator flux, to validate simulation results obtained in previous works.

Keywords: 12_DTC, DSPACE TMS 320F2812 torque, stator flux, currents distortions, experimental performance analysis

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Authors: Jane O`Halloran

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This research aims to identify the issues and challenges of teaching English as a Foreign Language to Japanese university students who have special learning needs. This study sought to investigate factors influencing the academic performance of students with special or additional needs in an inclusive education context. This study will focus on a consideration of the methods available to support those with hearing impairments. While the study population is limited, it is important to give classes to be inclusive places where all students receive equal access to content. Hearing impairments provide an obvious challenge to language learning and, therefore, second-language learning. However, strategies and technologies exist to support the instructor without specialist training. This paper aims to identify these and present them to other teachers of English as a second language who wish to provide the best possible learning experience for every student. Two case studies will be introduced to compare and contrast the experience of in-class teaching and the online option and to share the positives and negatives of the two approaches. While the study focuses on the situation in a university in Japan, the lessons learned by the author may have universal value to any classroom with a student with a hearing disability.

Keywords: inclusive learning, special needs, hearing impairments, teaching strategies

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Authors: Nalini Chitanand

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Given the dynamic nature of the higher education landscape, induction programmes for new academics has become the norm nowadays to support academics negotiate these rough terrain. This study investigates an induction programme for new academics in a higher education institution to establish what difference it has made to participants. The findings revealed that the benefits ranged from creating safe spaces for collaboration and networking to fostering reflective practice and contributing to the scholarship of teaching and learning. The study also revealed that some of the intentions of the programme may not have been achieved, for example transformative learning. This led to questioning whether this intention is an appropriate one given the short duration of the programme and the long, drawn out process of transformation. It may be concluded that the academic induction programme in this study serves to sow the seeds for transformative learning through fostering critically reflective practice. Recommendations for further study could include long term impact of the programme on student learning and success, these being the core business of higher education. It is also recommended that in addition to an induction programme, the university invests in a mentoring programme for new staff and extend the support for academics in order to sustain critical reflection and which may contribute to transformative educational practice.

Keywords: induction programme, reflective practice, scholarship of teaching, transformative learning

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Authors: Aliyah Dosani, Kerri Alderson

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Two different simulations using standardized patients were developed to reinforce content and foster undergraduate nursing students’ practice and development of interpersonal skills in difficult clinical situations in the classroom. The live actor simulations focused on fostering interpersonal skills, traditionally considered by students to be simple and easy. However, seemingly straightforward interactions can be very stressful, particularly in women’s complex social/emotional situations. Supporting patients in these contexts is fraught with complexity and high emotion, requiring skillful support, assessment and intervention by a registered nurse. In this presentation, the personal and professional perspectives of the development, incorporation, and execution of the live actor simulations will be discussed, as well as the inclusion of student perceptions, and the learning gained by the involved faculty.

Keywords: adult learning, interpersonal skill development, simulation learning, teaching and learning

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Authors: Ju-Young Choi, Ki-Il Song, Kyoung-Yul Kim

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During Tunnel Boring Machine (TBM) tunnel excavation, backfill grout should be injected after the installation of segment lining to ensure the stability of the tunnel and to minimize ground deformation. If grouting is not sufficient to fill the gap between the segments and rock mass, hydraulic pressures occur in the void, which can negatively influence the stability of the tunnel. Recently the tendency to use TBM tunnelling method to replace the drill and blast(NATM) method is increasing. However, there are only a few studies of evaluation of backfill grout. This study evaluates the TBM tunnel backfill state using Impact-Echo(IE). 3-layers, segment-grout-rock mass, are simulated by FLAC 2D, FDM-based software. The signals obtained from numerical analysis and IE test are analyzed by Short-Time Fourier Transform(STFT) in time domain, frequency domain, and time-frequency domain. The result of this study can be used to evaluate the quality of backfill grouting in tail void.

Keywords: tunnel boring machine, backfill grout, impact-echo method, time-frequency domain analysis, finite difference method

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Authors: Ismail Halijah, Abdullah Rusli

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Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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Authors: Niphattha Hannapha

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This paper examines how the classroom environment influences slow learners’ learning achievement; it focuses on how seating patterns affect students’ behaviours and which patterns best contribute to students’ learning performance. The researcher studied how slow learners’ characteristics and seating patterns influenced their behaviours and performance at Ban Hin Lad School. As a nonparticipant observation, the target groups included 15 slow learners from Prathomsueksa (Grades) 4 and 5. Students’ behaviours were recorded during their learning activities in order to minimize their reading and written expression disorder in Thai language tutorials. The result showed four seating patterns and two behaviors which obstructed students’ learning. The average of both behaviours mostly occurred when students were seated with patterns 1 (the seat facing the door, with the corridor alongside) and 3 (the seat alongside the door, facing the aisle) respectively. Seating patterns 1 and 3 demonstrated visibility (the front and side) of a walking path with two-way movement. However, seating patterns 2 (seating with the door alongside and the aisle at the back) and 4 (sitting with the door at the back and the aisle alongside) demonstrated visibility (the side) of a walking path with one-way movement. In Summary, environmental design is important to enhance concentration in slow learners who have reading and writing disabilities. This study suggests that students should be seated where they can have the least visibility of movement to help them increase continuous learning. That means they can have a better chance of developing reading and writing abilities in comparison with other patterns of seating.

Keywords: slow learning, interior design, interior environment, classroom

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Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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The primary aim of the present study is to undertake an extensive comparative examination of distance learning and blended learning modalities, with a particular focus on assessing their efficacy during the period of confinement imposed by the COVID-19 pandemic. This investigation is grounded in the firsthand experiences of educators at the high school and secondary levels across both private and public educational institutions. To gather the necessary data, we designed and distributed a meticulously crafted survey to these educators, soliciting detailed accounts of their professional experiences throughout this challenging period. The survey's objectives include elucidating the specific difficulties faced by teachers, as well as highlighting the innovative pedagogical strategies they developed in response to these challenges. By synthesizing the insights gained from this survey, we aim to foster an exchange of experiences among educators and to generate informed recommendations that will guide future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: distributed control, game theory, multi-agent learning, reinforcement learning

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Authors: Jaimala Ghambir, Tilak Thakur, Puneet Chawla

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As per the statistical data, the Doubly-fed Induction Generator (DFIG) based wind turbine with variable speed and variable pitch control is the most common wind turbine in the growing wind market. This machine is usually used on the grid connected wind energy conversion system to satisfy grid code requirements such as grid stability, fault ride through (FRT), power quality improvement, grid synchronization and power control etc. Though the requirements are not fulfilled directly by the machine, the control strategy is used in both the stator as well as rotor side along with power electronic converters to fulfil the requirements stated above. To satisfy the grid code requirements of wind turbine, usually grid side converter is playing a major role. So in order to improve the operation capacity of wind turbine under critical situation, the intensive study of both machine side converter control and grid side converter control is necessary In this paper DFIG is modeled using power components as variables and the performance of the DFIG system is analysed under grid voltage fluctuations. The voltage fluctuations are made by lowering and raising the voltage values in the utility grid intentionally for the purpose of simulation keeping in view of different grid disturbances.

Keywords: DFIG, dynamic modeling, DPC, sag, swell, voltage fluctuations, FRT

Procedia PDF Downloads 461

Authors: Oluwaponmile D. Alao

Abstract:

In this paper, two models have been developed to ascertain the best network needed for diagnosis of breast cancer. Breast cancer has been a disease that required the attention of the medical practitioner. Experience has shown that misdiagnose of the disease has been a major challenge in the medical field. Therefore, designing a system with adequate performance for will help in making diagnosis of the disease faster and accurate. In this paper, two models: backpropagation neural network and support vector machine has been developed. The performance obtained is also compared with other previously obtained algorithms to ascertain the best algorithms.

Keywords: breast cancer, data mining, neural network, support vector machine

Procedia PDF Downloads 345

Authors: Mohamed Dhouibi, Bogdan Stirbu, Chabotier André, Marc Pirlot

Abstract:

Internal barrel wear is a major factor affecting the performance of small caliber guns in their different life phases. Wear analysis is, therefore, a very important process for understanding how wear occurs, where it takes place, and how it spreads with the aim on improving the accuracy and effectiveness of small caliber weapons. This paper discusses the measurement and analysis of combustion chamber wear for a small-caliber gun using a Coordinate Measuring Machine (CMM). Initially, two different NATO small caliber guns: 5.56x45mm and 7.62x51mm, are considered. A Micura Zeiss Coordinate Measuring Machine (CMM) equipped with the VAST XTR gold high-end sensor is used to measure the inner profile of the two guns every 300-shot cycle. The CMM parameters, such us (i) the measuring force, (ii) the measured points, (iii) the time of masking, and (iv) the scanning velocity, are investigated. In order to ensure minimum measurement error, a statistical analysis is adopted to select the reliable CMM parameters combination. Next, two measurement strategies are developed to capture the shape and the volume of each gun chamber. Thus, a task-specific measurement uncertainty (TSMU) analysis is carried out for each measurement plan. Different approaches of TSMU evaluation have been proposed in the literature. This paper discusses two different techniques. The first is the substitution method described in ISO 15530 part 3. This approach is based on the use of calibrated workpieces with similar shape and size as the measured part. The second is the Monte Carlo simulation method presented in ISO 15530 part 4. Uncertainty evaluation software (UES), also known as the Virtual Coordinate Measuring Machine (VCMM), is utilized in this technique to perform a point-by-point simulation of the measurements. To conclude, a comparison between both approaches is performed. Finally, the results of the measurements are verified through calibrated gauges of several dimensions specially designed for the two barrels. On this basis, an experimental database is developed for further analysis aiming to quantify the relationship between the volume of wear and the muzzle velocity of small caliber guns.

Keywords: coordinate measuring machine, measurement uncertainty, erosion and wear volume, small caliber guns

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Authors: Dorottya Horváth, Tímea Harmath-Tánczos

Abstract:

Attention deficit hyperactivity disorder (ADHD) and learning disabilities are common neurocognitive disorders that can have a significant impact on a child's academic performance. ADHD is characterized by inattention, hyperactivity, and impulsivity, while learning disabilities are characterized by difficulty with specific academic skills, such as reading, writing, or math. The aim of this study was to investigate the working memory, executive, and attention functions of neurotypical children and children with ADHD and learning disabilities in order to fill the gaps in the Hungarian mean test scores of these cognitive functions in children with neurocognitive disorders. Another aim was to specify the neuropsychological differential diagnostic toolkit in terms of the relationships and peculiarities between these cognitive functions. The research question addressed in this study was: How do the working memory, executive, and attention functions of neurotypical children compare to those of children with ADHD and learning disabilities? A self-administered test battery was used as a research tool. Working memory was measured with the Non-Word Repetition Test, the Listening Span Test, the Digit Span Test, and the Reverse Digit Span Test; executive function with the Letter Fluency, Semantic Fluency, and Verb Fluency Tests; and attentional concentration with the d2-R Test. The data for this study was collected from 115 children aged 9-14 years. The children were divided into three groups: neurotypical children (n = 44), children with ADHD without learning disabilities (n = 23), and children with ADHD with learning disabilities (n = 48). The data was analyzed using a variety of statistical methods, including t-tests, ANOVAs, and correlational analyses. The results showed that the performance of children with neurocognitive involvement in working memory, executive functions, and attention was significantly lower than the performance of neurotypical children. However, the results of children with ADHD and ADHD with learning disabilities did not show a significant difference. The findings of this study are important because they provide new insights into the cognitive profiles of children with ADHD and learning disabilities and suggest that working memory, executive functions, and attention are all impaired in children with neurocognitive involvement, regardless of whether they have ADHD or learning disabilities. This information can be used to develop more effective diagnostic and treatment strategies for these disorders.

Keywords: ADHD, attention functions, executive functions, learning disabilities, working memory

Procedia PDF Downloads 92

Authors: René A. Sørensen, Søren Skovsen, Peter Christiansen, Henrik Karstoft

Abstract:

Autonomous agricultural machines act in stochastic surroundings and therefore, must be able to perceive the surroundings in real time. This perception can be achieved using image sensors combined with advanced machine learning, in particular Deep Learning. Deep convolutional neural networks excel in labeling and perceiving color images and since the cost of high-quality RGB-cameras is low, the hardware cost of good perception depends heavily on memory and computation power. This paper investigates the possibility of designing lightweight convolutional neural networks for semantic segmentation (pixel wise classification) with reduced hardware requirements, to allow for embedded usage in autonomous agricultural machines. Using compression techniques, a lightweight convolutional neural network is designed to perform real-time semantic segmentation on an embedded platform. The network is trained on two large datasets, ImageNet and Pascal Context, to recognize up to 400 individual classes. The 400 classes are remapped into agricultural superclasses (e.g. human, animal, sky, road, field, shelterbelt and obstacle) and the ability to provide accurate real-time perception of agricultural surroundings is studied. The network is applied to the case of autonomous grass mowing using the NVIDIA Tegra X1 embedded platform. Feeding case-specific images to the network results in a fully segmented map of the superclasses in the image. As the network is still being designed and optimized, only a qualitative analysis of the method is complete at the abstract submission deadline. Proceeding this deadline, the finalized design is quantitatively evaluated on 20 annotated grass mowing images. Lightweight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show competitive performance with regards to accuracy and speed. It is feasible to provide cost-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: autonomous agricultural machines, deep learning, safety, visual perception

Procedia PDF Downloads 394