Search results for: smart training

Authors: Sedat Bilgili, Alper K. Demir

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The current Internet has become the dominant use with continuing growth in the home, medical, health, smart cities and industrial automation applications. Internet of Things (IoT) is an emerging technology to enable such applications in our lives. Moreover, Named Data Networking (NDN) is also emerging as a Future Internet architecture where it fits the communication needs of IoT networks. The aim of this study is to provide an NDN protocol stack implementation running on the Contiki operating system (OS). Contiki OS is an OS that is developed for constrained IoT devices. In this study, an NDN protocol stack that can work on top of IEEE 802.15.4 link and physical layers have been developed and presented.

Keywords: internet of things (IoT), named-data, named data networking (NDN), operating system

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Authors: Jocelyn Solomons, Kraak

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Rhythmic movement, also referred to as “dance”, involves the execution of different motor skills as well as the integration and sequencing of actions between limbs, timing and spatial precision. The aim of this study was therefore to investigate and compare the effect of a 16-week rhythmic movement intervention on flexibility, dynamic balance, agility, power and local muscular endurance of academy rugby players in the Western Cape, according to positional groups. Players (N ¼ 54) (age 18.66 0.81 years; height 1.76 0.69 cm; weight 76.77 10.69 kg), were randomly divided into a treatment-control [TCA] (n ¼ 28) and a control-treatment [CTB] (n ¼ 26) group. In this crossover experimental design, the interaction effect of the treatment order and the treatment time between the TCA and CTB group, was determined. Results indicated a statistically significant improvement (p < 0.05) in agility2 (p ¼ 0.06), power2 (p ¼ 0.05), local muscular endurance1 (p ¼ 0.01) & 3 (p ¼ 0.01) and dynamic balance (p < 0.01). Likewise, forwards and backs also showed statistically significant improvements (p < 0.05) per positional groups. Therefore, a rhythmic movement intervention has the potential to improve rugby-specific bio-motor skills and furthermore, improve positional specific skills should it be designed with positional groups in mind. Future studies should investigate, not only the effect of rhythmic movement on improving specific rugby bio-motor skills, but the potential of its application as an alternative training method during off- season (or detraining phases) or as a recovery method.

Keywords: agility, dance, dynamic balance, flexibility, local muscular endurance, power, training

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Authors: Abigaile Rose Mary R. Capay, Janne Ly Castillon-Gilpo, Sheila A. Javier

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The transition to online learning has been a challenging feat on the mental health of tertiary students. This study investigated whether learning mindfulness strategies online would help in improving students’ imagination, conscientiousness, extraversion, agreeableness and emotional stability, as measured by the International Personality Item Pool (IPIP) Big Five Factor Markers, as well as their dispositional mindfulness as measured by the Mindfulness Attention Awareness Scale (MAAS). Fifty-two college students participated in the experiment. The 23 participants assigned to the treatment condition received 6-weekly experiential sessions of online mindfulness training and were advised to follow a daily mindfulness practice, while the 29 participants from the control group only received a 1-hour lecture. Scores were collected at pretest and posttest. Findings show that there was a significant difference in the pretest and posttest scores of students assigned in the treatment group, likewise medium effect sizes in the variables: dispositional mindfulness (t (22) = 2.64, p = 0.015, d = .550), extraversion (t (22) = 2.76, p = 0.011, d = 0.575), emotional stability (t (22) = 2.99, p = 0.007, d = .624), conscientiousness (t (22) = 2.74, p = 0.012, d = .572) and imagination (t (22) = 4.08, p < .001), but not for agreeableness (t (22) = 2.01, p = 0.057, d = .419). No significant differences were observed on the scores of the control group. Educational institutions are recommended to consider teaching basic mindfulness strategies to tertiary students, as a valuable resource in improving their mental health as they navigate through adjustments in online learning.

Keywords: mindfulness, school-based interventions, MAAS, IPIP Big Five Markers, experiment

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Ramune Kasperaviciene, Jurgita Motiejuniene, Dalia Venckiene

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Familiarising students with strategies for transferring cultural meanings (intertextual units, culture-specific idioms, culture-specific items, etc.) should be part of a comprehensive translator training programme. The present paper focuses on strategies for transferring such meanings into other languages and explores possibilities for introducing these methods and practice to translation students. The authors (university translation teachers) analyse the means of transferring cultural meanings from English into Lithuanian in a specific travel book, attribute these means to theoretically grounded strategies, and make calculations related to the frequency of adoption of specific strategies; translation students are familiarised with concepts and methods related to transferring cultural meanings and asked to put their theoretical knowledge into practice, i.e. interpret and translate certain culture-specific items from the same source text, and ground their decisions on theory; the comparison of the strategies employed by the professional translator of the source text (as identified by the authors of this study) and by the students is made. As a result, both students and teachers gain valuable experience, and new practices of conducting translation classes for a specific purpose evolve. Conclusions highlight the differences and similarities of non-professional and professional choices, summarise the possibilities for introducing methods of transferring cultural meanings to students, and round up with specific considerations of the impact of theoretical knowledge and the degree of experience on decisions made in the translation process.

Keywords: cultural meanings, culture-specific items, strategies for transferring cultural meanings, translator training

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Authors: Karthiyayini J., Arpita Chowdary Vantipalli, Darshana Sailu Tanti, Malvika Ravi Kudari, Krtin Kannan

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This paper is propelled from the generally existing undertaking of the smart water quality management, which addresses an IoT (Internet of things) based brilliant water quality observing (SWQM) framework which we call it AquaSwach that guides in the ceaseless estimation of water conditions dependent on five actual boundaries i.e., temperature, pH, electric conductivity and turbidity properties and water virtue estimation each time you drink water. Six sensors relate to Arduino-Mega in a discrete way to detect the water parameters. Extracted data from the sensors are transmitted to a desktop application developed in the NET platform and compared with the WHO (World Health Organization) standard values.

Keywords: AquaSwach, IoT, WHO, water quality

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Authors: Justyna Mroczkowska

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Social worker's ability to provide culturally sensitive assistance in child protection is taken for granted; given limited training opportunities and lack of clear guidance, practitioners report working with migrant families more demanding in comparison to working with native families. In this study, the author developed and factor analyzed the Norwegian Cultural Self-Efficacy Scale to describe the level of cultural capability among Norwegian child protection professionals. The study aimed to determine the main influencing factors to cultural efficacy and examine the relationship between self-efficacy and perceived difficulty in working with migrant families. The scale was administered to child protection workers in Norway (N=251), and the reliability of the scale measured by Cronbach's alpha coefficient was .904. The confirmatory factor analysis of social work cultural self-efficacy found support for four separate but correlated subscales: Assessment, Communication, Support Request, and Teamwork. Regression analyses found the experience in working with migrant families, training and support from external agencies, and colleague support to be significant predictors of cultural self-efficacy. Self-efficacy in assessment skills and self-efficacy in communication skills were moderately related to the perceived difficulty to work with migrant families. The findings conclude with previous research and highlight the need for both professional development programs and institutional resources to be provided to support the practitioner's preparation for multicultural practice in child protection.

Keywords: child protection, cultural self-efficacy, cultural competency, migration, resources

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Authors: Cissy Li

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Mentorship is a commonly used strategy for career development that has obvious benefits for students in undergraduate pre-service teacher training programs. In contrast to teaching practicum, which generally involves pedagogical supervision and performance evaluation by teachers, mentorship is more focused on sharing experiences, supporting challenges, and nurturing skills in order to promote personal and professional growth. To empower pre-service teachers and prepare them for potential challenges in the context of local English language teaching (ELT), an alumni mentoring program was established in the framework of communities of practice (CoP), with the mentors being in-service graduates working in local schools and mentees being students on the teacher-training programme in a Hong Kong university. By triangulating audio transcripts of mentoring sessions delivered by three top mentors with data from questionnaire responses and mentor logs, this paper examines the mentoring styles of the three best mentors from the metadiscursive perspective. It was found that, in a community of practice, mentors who may seem to enjoy a relative more dominant position, in fact, had to strategically and pragmatically employ metadiscursive resources to manage relationships with the mentees and organize talks in the mentoring process. Other attributing factors for a successful mentoring session include mentor personality and prior mentorship experiences, nature of the activities in the session, and group dynamics. This paper concludes that it is the combination of all the factors that constitute a particular mentoring style. The findings have implications for mentoring programs in teacher preparation.

Keywords: mentoring, teacher education, mentoring style, metadiscourse

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Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu

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Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.

Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Celina Nowak

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The development of information and communication technologies (ICT) and a consequent growth of cyberspace have become a reality of modern societies. The newest addition to this complex structure has been Internet of Things which is due to the appearance of smart devices. IoT creates a new dimension of the network, as the communication is no longer the domain of just humans, but has also become possible between devices themselves. The possibility of communication between devices, devoid of human intervention and real-time supervision, generated new societal and legal challenges. Some of them may and certainly will eventually be connected to criminal law. Legislators both on national and international level have been struggling to cope with this technologically evolving environment in order to address new threats created by the ICT. There are legal instruments on cybercrime, however imperfect and not of universal scope, sometimes referring to specific types of prohibited behaviors undertaken by criminals, such as money laundering, sex offences. However, the criminal law seems largely not prepared to the challenges which may arise because of the development of IoT. This is largely due to the fact that criminal law, both on national and international level, is still based on the concept of perpetration of an offence by a human being. This is a traditional approach, historically and factually justified. Over time, some legal systems have developed or accepted the possibility of commission of an offence by a corporation, a legal person. This is in fact a legal fiction, as a legal person cannot commit an offence as such, it needs humans to actually behave in a certain way on its behalf. Yet, the legislators have come to understand that corporations have their own interests and may benefit from crime – and therefore need to be penalized. This realization however has not been welcome by all states and still give rise to doubts of ontological and theoretical nature in many legal systems. For this reason, in many legislations the liability of legal persons for commission of an offence has not been recognized as criminal responsibility. With the technological progress and the growing use of IoT the discussions referring to criminal responsibility of corporations seem rather inadequate. The world is now facing new challenges and new threats related to the ‘smart’ things. They will have to be eventually addressed by legislators if they want to, as they should, to keep up with the pace of technological and societal evolution. This will however require a reevaluation and possibly restructuring of the most fundamental notions of modern criminal law, such as perpetration, guilt, participation in crime. It remains unclear at this point what norms and legal concepts will be and may be established. The main goal of the research is to point out to the challenges ahead of the national and international legislators in the said context and to attempt to formulate some indications as to the directions of changes, having in mind serious threats related to privacy and security related to the use of IoT.

Keywords: criminal law, internet of things, privacy, security threats

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Authors: Khalifa Al Baloushi, Hongwei Zhang, Terrence Perera

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Over the last few decades, the government of the UAE has been taking actions to consolidate defense manufacturing entities with the view to build a coherent and modern defense manufacturing base. Whilst these actions have significantly improved the overall capabilities of defense manufacturing; further opportunities exist to radically transform the sector. A comprehensive literature review and data collected from a survey identified three potential areas of improvements, (a) integration of Industry 4.0 technologies and other smart technologies, (b) stronger engagement of small and Medium-sized defense manufacturing companies and (c) Enhancing the national defense policies by embedding best practices from other nations. This research paper presents the design and development of a conceptual framework for the UAE defense industrial ecosystem.

Keywords: industry 4.0, defense manufacturing, eco-systems, integration

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Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

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Authors: Juvanie C. Lapesigue

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Worldwide school closures result from a significant public health crisis that has affected the nation and the entire world. It has affected students, educators, educational organizations globally, and many other aspects of society. Academic institutions worldwide teach students using diverse approaches of various learning delivery modes. This paper investigates the competence and performance of physical education teachers using various learning delivery modes, including Distance learning, Blended Learning, and Homeschooling during online distance education. To identify the Gap between their age generation using various learning delivery that affects teachers' preparation for distance learning and evaluates how these modalities impact teachers’ competence and performance in the case of a pandemic. The respondents were the Senior High School teachers of the Department of Education who taught in Davao City before and during the pandemic. Purposive sampling was utilized on 61 Senior High School Teachers in Davao City Philippines. The result indicated that teaching performance based on pedagogy and assessment has significantly affected teaching performance in teaching physical education, particularly those Non-PE teachers teaching physical education subjects. It should be supplied with enhancement training workshops to help them be more successful in preparation in terms of teaching pedagogy and assessment in the following norm. Hence, a proposed unique training design for non-P.E. Teachers has been created to improve the teachers’ performance in terms of pedagogy and assessment in teaching P.E subjects in various learning delivery modes in the next normal.

Keywords: distance learning, learning delivery modes, P.E teachers, senior high school, teaching competence, teaching performance

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: A. R. Nezamabadi, M. Veiskarami

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This paper studies free vibration of simply supported functionally graded beams with piezoelectric layers based on the first order shear deformation theory. The Young's modulus of beam is assumed to be graded continuously across the beam thickness. The governing equation is established. Resulting equation is solved using the Euler's equation. The effects of the constituent volume fractions, the influences of applied voltage on the vibration frequency are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: mechanical buckling, functionally graded beam, first order shear deformation theory, free vibration

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Authors: Meenakshi Pappu

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The terms like liveability, Sustainable Development Goals and pandemic have been widely analysed in proving sustainable cities and community living in growing urban areas by 2030. The pandemic has made us all ruminate about how we look into different fast-growing cities which vary in geographical location, climatic zones, terrains, land use and varying cultural backgrounds & traditions belong to the mother soil. India has taken up huge steps to move towards achieving UN-SDGs. Smart city missions have played a vital role in moving towards SDG. Visakhapatnam city is the executive capital in the state of Andhra Pradesh. Located on the Eastern Ghats in South India, it is surrounded by a mountain range on three sides and the Indian Ocean on one side. This unique geographical location and fast urbanization in the last two decades, has put up immense pressure on the natural environment and recourses. It's observed that a lot of investigation to address the existing and proposed land-use, spatial, natural resources, air quality, environmental challenges, and a range of socio-economic, economic challenges were identified during the assessment phase. The citizen concerns with quality and quantity of access to water, sewerage, energy, transportation (public & private) and safety for the public were found out through surveying. Urban infrastructure plays a major part in city building. These cities are occupied by people who come for a better living. This paper aims to provide off-center way of approach to citizens-oriented community habits by addressing SDG 11: Sustainable cities & community by enkindling a characteristic framework of amalgamating 1.eco-design principal, 2. three factors of liveability and 3. a local traditional planning solution. Aiming towards a sustainable development utilized with the focus on the quality of the life and experience of the people who live in urban areas integrating life with soil & water. Building strong social agenda that includes affordable housing for all levels of households, secure and place for good quality public realm for the local people with activity in green corridor, open meeting space & adding recreational places for advantage..

Keywords: livability, eco-design, smart city mission, sustainable

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Authors: Cristina Maria Ribeiro Martins Pereira Caridade, Ana Rita Ferreira Morais

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The use of computational tools has become essential in the context of interactive learning, especially in engineering education. In the medical industry, teaching medical image processing techniques is a crucial part of training biomedical engineers, as it has integrated applications with healthcare facilities and hospitals. The aim of this article is to present a teaching-learning simulation tool developed in MATLAB using a graphical user interface for medical image fusion that explores different image fusion methodologies and processes in combination with image pre-processing techniques. The application uses different algorithms and medical fusion techniques in real time, allowing you to view original images and fusion images, compare processed and original images, adjust parameters, and save images. The tool proposed in an innovative teaching and learning environment consists of a dynamic and motivating teaching simulation for biomedical engineering students to acquire knowledge about medical image fusion techniques and necessary skills for the training of biomedical engineers. In conclusion, the developed simulation tool provides real-time visualization of the original and fusion images and the possibility to test, evaluate and progress the student’s knowledge about the fusion of medical images. It also facilitates the exploration of medical imaging applications, specifically image fusion, which is critical in the medical industry. Teachers and students can make adjustments and/or create new functions, making the simulation environment adaptable to new techniques and methodologies.

Keywords: image fusion, image processing, teaching-learning simulation tool, biomedical engineering education

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Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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Authors: Aminath Waseela, Vinesh Chandra, Shaun Nykvist,

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

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

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Authors: Ahmed F. Ghanem, Marwa I. Wahba, Asmaa N. El-Dein, Mohamed A. EL-Raey, Ghada E. A. Awad

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Numerous attempts are being performed in order to formulate suitable packaging materials for the meat products. However, to the best of our knowledge, the incorporation of the free hibiscus extract or its microcapsules in the pure polyvinyl alcohol (PVA) matrix as packaging materials for the meats is seldom reported. Therefore, this study aims at the protection of the aqueous crude extract of the hibiscus flowers utilizing the spry drying encapsulation technique. Results of the Fourier transform infrared (FTIR), the scanning electron microscope (SEM), and the particle size analyzer confirmed the successful formation of the assembled capsules via strong interactions, the spherical rough microparticles, and the particle size of ~ 235 nm, respectively. Also, the obtained microcapsules enjoy higher thermal stability than the free extract. Then, the obtained spray-dried particles were incorporated into the casting solution of the pure PVA film with a concentration of 10 wt. %. The segregated free-standing composite films were investigated, compared to the neat matrix, with several characterization techniques such as FTIR, SEM, thermal gravimetric analysis (TGA), mechanical tester, contact angle, water vapor permeability, and oxygen transmission. The results demonstrated variations in the physicochemical properties of the PVA film after the inclusion of the free and the extract microcapsules. Moreover, biological studies emphasized the biocidal potential of the hybrid films against the microorganisms contaminating the meat. Specifically, the microcapsules imparted not only antimicrobial but also antioxidant activities to the PVA matrix. Application of the prepared films on the real meat samples displayed a low bacterial growth with a slight increase in the pH over the storage time which continued up to 10 days at 4 oC, as further evidence to the meat safety. Moreover, the colors of the films did not significantly changed except after 21 days indicating the spoilage of the meat samples. No doubt, the dual-functional of the prepared composite films pave the way towards combined active and smart food packaging applications. This would play a vital role in the food hygiene, including also the quality control and the assurance.

Keywords: PVA, hibiscus, extraction, encapsulation, active packaging, smart and intelligent packaging, meat spoilage

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Authors: Matthew Fleet, Savannah Elliott

Abstract:

Background: This study investigates the use of teaching and learning to meet the needs of deaf children in the UK PE curriculum. Research has illustrated that deaf students in mainstream schools do not receive sufficient support from teachers in lessons. This research examines the impact of different types of hearing loss and its implications within Physical Education (PE) in secondary schools. Purpose: The purpose of this study is to highlight challenges PE teachers face and make recommendations for more inclusive learning environments for deaf students. The aims and objectives of this research are: to critically analyse the current situation for deaf students accessing the PE curriculum, by identifying barriers deaf students face; to identify the challenges for PE teachers in providing appropriate support for deaf students; to provide recommendations for deaf awareness training, to enhance PE teachers’ understanding and knowledge. Method: Semi-structured interviews collected data from both PE teachers and deaf students, to examine: the support available and coping mechanisms deaf students use when they do not receive support; strategies PE teachers use to provide support for deaf students; areas for improvement and potential strategies PE teachers can apply to their practice. Results & Conclusion: The findings from the study concluded that PE teachers were inconsistent in providing appropriate support for deaf students in PE lessons. Evidence illustrated that PE teachers had limited exposure to deaf awareness training. This impacted on their ability to support deaf students effectively. Communication was a frequent barrier for deaf students, affecting their ability to retain and learn information. Also, the use of assistive technology was found to be compromised in practical PE lessons.

Keywords: physical education, deaf, inclusion, education

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Authors: Chi Wu, Dean Wu, Wen-Te Liu, Cheng-Yu Tsai, Shin-Mei Hsu, Yin-Tzu Lin, Ru-Yin Yang

Abstract:

Background: The results of previous studies compared the benefits and risks of receiving insomnia medication. However, the effects between hypnotic drugs used and enhancement of sleep quality were still unclear. Objective: The aim of this study is to establish a prediction model for hypnotic drugs' dosage used for insomnia subjects and associated the relationship between sleep stage ratio change and drug types. Methodologies: According to American Academy of Sleep Medicine (AASM) guideline, sleep stages were classified and transformed to hypnogram via the polysomnography (PSG) in a hospital in New Taipei City (Taiwan). The subjects with diagnosis for insomnia without receiving hypnotic drugs treatment were be set as the comparison group. Conversely, hypnotic drugs dosage within the past three months was obtained from the clinical registration for each subject. Furthermore, the collecting subjects were divided into two groups for training and testing. After training convolution neuron network (CNN) to predict types of hypnotics used and dosages are taken, the test group was used to evaluate the accuracy of classification. Results: We recruited 76 subjects in this study, who had been done PSG for transforming hypnogram from their sleep stages. The accuracy of dosages obtained from confusion matrix on the test group by CNN is 81.94%, and accuracy of hypnotic drug types used is 74.22%. Moreover, the subjects with high ratio of wake stage were correctly classified as requiring medical treatment. Conclusion: CNN with hypnogram was potentially used for adjusting the dosage of hypnotic drugs and providing subjects to pre-screening the types of hypnotic drugs taken.

Keywords: convolution neuron network, hypnotic drugs, insomnia, polysomnography

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Authors: Rafal Stegierski, Krzysztof Dmitruk

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The paper focuses on robotic tele-presence system build around humanoid robot operated with controller-less Wizard of Oz technique. Proposed solution gives possibility to quick start acting as a operator with short, if any, initial training.

Keywords: robotics, motion capture, Wizard of Oz, humanoid robots, human robot interaction

Procedia PDF Downloads 469

Authors: Deependra Prasad Sarraf, Gajendra Prasad Rauniar, Robin Maskey, Rajiv Maharjan, Ashish Shrestha, Ramayan Prasad Kushwaha

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Objectives: To assess the perception of faculties towards online teaching-learning activities conducted during the COVID-19 pandemic and to identify barriers and facilitators to conducting online teaching-learning activities in our context. Methods: A cross-sectional study was conducted among faculties at B. P. Koirala Institute of Health Sciences using a 26-item semi-structured questionnaire. A Google Form was prepared, and its link was sent to the faculties via email. Descriptive statistics were calculated, and findings were presented as tables and graphs. Results: Out of 158 faculties, the majority were male (66.46%), medical faculties (85.44%), and assistant professors (46.84%). Only 16 (10.13%) faculties had received formal training regarding preparing and/or delivering online teaching learning activities. Out of 158, 133 (84.18%) faculties faced technical and internet issues. The most common advantage and disadvantage of online teaching learning activities perceived by the faculties were ‘not limited to time or place’ (94.30%) and ‘lack of interaction with the students’ (82.28%), respectively. Majority (94.3%) of them had a positive perception towards online teaching-learning activities conducted during COVID-19 pandemic. Slow internet connection (91.77%) and frequent electricity interruption (82.91%) were the most common perceived barriers to online teaching-learning. Conclusions: Most of the faculties had a positive perception towards online teaching-learning activities. Academic leaders and stakeholders should provide uninterrupted internet and electricity connectivity, training on online teaching-learning platform, and timely technical support.

Keywords: COVID-19 pandemic, faculties, medical education, perception

Procedia PDF Downloads 157

Authors: Stefana Francisca Lupu, Jasmin Chantah, Mara Krone, Ingo Roden, Stephan Bongard, Gunter Kreutz

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Long-term music interventions could enhance both musical and nonmusical skills. The present study was designed to explore cognitive, socio-emotional, and musical development in a longitudinal setting. Third-graders (N = 184: 87 male, 97 female; mean age = 8.61 years; 115 native German and 69 migrant children) were randomly assigned to two intervention groups (music and maths) and a control group over a period of one school-year. At baseline, children in these groups were similar in basic cognitive skills, with a trend of advantage in the control group. Dependent measures included the culture fair intelligence test CFT 20-R; the questionnaire of emotional and social school experience for grade 3 and 4 (FEESS 3-4), the test of resources in childhood and adolescence (FRKJ 8-16), the test of language proficiency for German native and non-native primary school children (SFD 3), the reading comprehension test (ELFE 1-6), the German math test (DEMAT 3+) and the intermediate measures of music audiation (IMMA). Data were collected two times at the beginning (T1) and at the end of the school year (T2). A third measurement (T3) followed after a six months retention period. Data from baseline and post-intervention measurements are currently being analyzed. Preliminary results of all three measurements will be presented at the conference.

Keywords: musical training, primary-school German and migrant children, socio-emotional skills, transfer

Procedia PDF Downloads 230

Authors: Daud Muhammad

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Introduction: Ankle radiographs are frequently requested in Emergency Departments (ED) for patients presenting with traumatic ankle pain. The Ottawa Ankle Rules (OAR) serve as a clinical guideline to determine the necessity of these radiographs, aiming to reduce unnecessary imaging. This audit was conducted to evaluate the adequacy of clinical information provided in radiograph requests in relation to the OAR. Methods: A retrospective analysis was performed on 50 consecutive ankle radiograph requests under ED clinicians' names for patients aged above 5 years, specifically excluding follow-up radiographs for known fractures. The study assessed whether the provided clinical information met the criteria outlined by the OAR. Results: The audit revealed that none of the 50 radiograph requests contained sufficient information to satisfy the Ottawa Ankle Rules. Furthermore, 10 out of the 50 radiographs (20%) identified fractures. Discussion: The findings indicate a significant lack of adherence to the OAR, suggesting potential overuse of radiography and unnecessary patient exposure to radiation. This non-compliance may also contribute to increased healthcare costs and resource utilization, as well as possible delays in diagnosis and treatment. Recommendations: To address these issues, the following recommendations are proposed: (1) Education and Training: Enhance awareness and training among ED clinicians regarding the OAR. (2) Standardised Request Forms: Implement changes to imaging request forms to mandate relevant information according to the OAR. (3) Scan Vetting: Promote awareness among radiographers to discuss the appropriateness of scan requests with clinicians. (4) Regular re-audits should be conducted to monitor improvements in compliance.

Keywords: Ottawa ankle rules, ankle radiographs, emergency department, traumatic pain

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Authors: David A. Wallace, Salakjit J. Nilboworn

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Secure and reliable transmission and distribution of electrical power is crucial in today’s ever-increasing demand for electricity. Traditional methods of protecting the electrical grid have relied on relaying systems receiving voltage and current inputs from inductive instruments transformers (IT). This method has provided robust and stable performance throughout the years. Today with the advent of new non-conventional transformers (NCIT) and sensors, the electrical landscape is changing. These new systems have to ability to provide the same electrical performance as traditional instrument transformers with the added features of data acquisition, communication, smaller footprint, lower cost and resistance to GMD/GIC events.

Keywords: non-conventional instrument transformers, digital substations, smart grids, micro-grids

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Authors: Saeed Asiri

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The Novel Automated System (NAS) has the control system of the level of chlorine and acid (i.e. pH level) through a feedback in three forms of synchronous alerts. The feedback is in the form of an alert voice, a visible color, and a message on a digital screen. In addition, NAS contains a slide-in container in which chemicals are used to treat the problems of chlorine and acid levels independently. Moreover, NAS has a net in front of it to clean the pool on the surface of the water from leaves and wastes and so on which is controlled through a remote control. The material used is a lightweight aluminum with mechanical and electric parts integrated with each other. In fact, NAS is qualified to serve as an assistant security guard for swimming pools because it has the characteristics that make it unique and smart.

Keywords: novel automated system, pool safety, maintenance, pH level, digital screen

Procedia PDF Downloads 50