Search results for: Early Childhood Learning

Authors: Rahimah Abdulrahman, A. Eardle, Wilfred Alan, Abdel Hamid Soliman

Abstract:

With the rapid development in technology, and advances in learning technologies, m-learning has begun to occupy a great part of our lives. The pace of the life getting together with the need for learning started mobile learning (m-learning) concept. In 2008, Saudi Arabia requested a national plan for the adoption of information technology (IT) across the country. Part of the recommendations of this plan concerns the implementation of mobile learning (m-learning) as well as their prospective applications to higher education within the Kingdom of Saudi Arabia. The overall aim of the research is to explore the main issues that impact the deployment of m-learning in nursing institutes in Saudi Arabia, at the Armed Force Hospitals (AFH), Alhada. This is in order to be able to develop a generic model to enable and assist the educational policy makers and implementers of m-learning, to comprehend and treat those issues effectively. Specifically, the research will explore the concept of m-learning; identify and analyse the main organisational; technological and cultural issue, that relate to the adoption of m-learning; develop a model of m-learning; investigate the perception of the students of the Nursing Institutes to the use of m-learning technologies for their nursing diploma programmes based on their experiences; conduct a validation of the m-learning model with the use of the nursing Institute of the AFH, Alhada in Saudi Arabia, and evaluate the research project as a learning experience and as a contribution to the body of knowledge. Activity Theory (AT) will be adopted for the study due to the fact that it provides a conceptual framework that engenders an understanding of the structure, development and the context of computer-supported activities. The study will be adopt a set of data collection methods which engage nursing students in a quantitative survey, while nurse teachers are engaged through in depth qualitative studies to get first-hand information about the organisational, technological and cultural issues that impact on the deployment of m-learning. The original contribution will be a model for developing m-learning material for classroom-based learning in the nursing institute that can have a general application.

Keywords: activity theory (at), mobile learning (m-learning), nursing institute, Saudi Arabia (sa)

Procedia PDF Downloads 340

Authors: Salvador Antelmo Casanova Valencia

Abstract:

This study documents the use of the Minecraft Education Edition application to explore immersive game-based learning environments. We analyze the contributions of fourth-year university students who are pursuing a degree in Administrative Computing at the Universidad Michoacana de San Nicolas de Hidalgo. In this study, descriptive data and statistical inference are detailed using a quasi-experimental design using the Wilcoxon test. The instruments will provide data validation. Game-based learning in immersive environments necessarily implies greater student participation and commitment, resulting in the study, motivation, and significant improvements, promoting cooperation and autonomous learning.

Keywords: game-based learning, gamification, higher education, Minecraft

Procedia PDF Downloads 149

Authors: Subramaniam Chandran, A. Geetha

Abstract:

This paper addresses three issues: how to prepare the instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in a preparatory program for bachelor’s degree. This program is designed for the disadvantaged learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India, nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where the conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

Procedia PDF Downloads 407

Authors: Panagiotis Kosmas, Panayiotis Zaphiris

Abstract:

Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: embodied cognition, embodied learning, education, technology, schools

Procedia PDF Downloads 128

Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

Abstract:

Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

Procedia PDF Downloads 45

Authors: Erick C. Valverde, Wansu Lim

Abstract:

Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 104

Authors: Derek Brandon G. Yu, Clyde Vincent O. Pilapil, Christine F. Peña

Abstract:

College students of Cebu province have been indoors since March 2020, and a challenge encountered is the sudden shift from face to face to online learning and with the lack of empirical data on online learning on Higher Education Institutions (HEIs) in the Philippines. Sentiments on face to face and online learning will be collected from University of San Carlos (USC), School of Arts and Sciences (SAS) students regarding Mathematics in the Modern World (MMW), a General Education (GE) course. Natural Language Processing with machine learning algorithms will be used to classify the sentiments of the students. Results of the research study are the themes identified through topic modelling and the overall sentiments of the students in USC SAS

Keywords: natural language processing, online learning, sentiment analysis, topic modelling

Procedia PDF Downloads 224

Authors: Eun Jae Ko, In Young Sung, Eui Soo Joeng

Abstract:

Cognitive impairment is commonly encountered problem in children with various clinical diseases, including Down syndrome, autism spectrum disorder, brain injury, and others. Cognitive impairment limits participation in education and society, and this further hinders development in cognition. However, young children with cognitive impairment tend not to respond well to traditional cognitive treatments, therefore alternative treatment choices are need. As a cognitive training program, touch screen technology can easily be applied to very young children by involving visual and auditory support. Injini was developed as tablet computer based cognitive rehabilitation program for young children or individuals with severe cognitive impairment, which targeted on cognitive ages of 18 to 36 months. The aim of this study was to evaluate the efficacy of a tablet computer based cognitive rehabilitation program (Injini) for children with cognitive impairment. 38 children between cognitive ages of 18 to 36 months confirmed by cognitive evaluations were recruited and randomly assigned to the intervention group (n=20) and the control group (n=18). The intervention group received tablet computer based cognitive rehabilitation program (Injini) for 30 minutes per session, twice a week, over a period of 12 weeks, in addition to the traditional rehabilitation program. The control group received traditional rehabilitation program only. Mental score of Bayley Scales of Infant Development II (BSID II), Pediatric Evaluation of Disability Inventory (PEDI), Laboratory Temperament Assessment Battery (Lab-TAB), Early Childhood Behavior Questionnaire (ECBQ), and Goal Attainment Scale (GAS) were evaluated before and after 12 weeks of therapeutic intervention. When comparing the baseline characteristics, there was no significant difference between the two groups in the measurements of cognitive function. After 12 weeks of treatment, both group showed improvements in all measurements. However, in comparison of improvements after treatment, the intervention group showed more improvements in the mental score of BSID II, social function domain of PEDI, observation domain of Lab-TAB, and GAS, as compared to the control group. Application of the tablet computer based cognitive rehabilitation program (Injini) would be beneficial for improvement of cognitive function in young children with cognitive impairment.

Keywords: cognitive therapy, computer-assisted therapy, early intervention, tablets

Procedia PDF Downloads 270

Authors: PB Venkataraman

Abstract:

Most of the real-life problems are ill-structured. They do not have a single solution but many competing solutions. The solution paths are non-linear and ambiguous, and the problem definition itself is many times a challenge. Students of professional education learn to solve such problems through internships. The current pandemic situation has constrained on-site internship opportunities; thus the students have no option but to pursue this learning online. This research assessed the learning gain of four undergraduate students in engineering as they undertook an online internship in an organisation over a period of eight weeks. A clinical interview at the end of the internship provided the primary data to assess the team’s problem-solving skills using a tested rubric. In addition to this, change in their learning attitudes were assessed through a pre-post study using a repurposed CLASS instrument for Electrical Engineering. Analysis of CLASS data indicated a shift in the sophistication of their learning attitude. A learning engagement survey adopting a 6-point Likert scale showed active participation and motivation in learning. We hope this new research will stimulate educators to exploit online internships even beyond the time of pandemic as more and more business operations are transforming into virtual.

Keywords: ill-structured problems, learning attitudes, internship, assessment, student engagement

Procedia PDF Downloads 192

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 41

Authors: Pieter Conradie, M. Marina Moller

Abstract:

Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

Procedia PDF Downloads 402

Authors: Luciana Marrone

Abstract:

Natural dyes are a great resource for today's artists and designers providing endless possibilities for design and sustainability. This research and development project focuses on the idea of making these dyeing or painting methodologies reach the widest possible range of students. The main objective is to inform and train, free of charge, teachers and students from different academic institutions, at different levels, kindergarten, primary, secondary, tertiary and university. In this research and dissemination project, in the first instance, institutions from Argentina, Chile, Uruguay, Mexico, Spain, Italy, Colombia, Paraguay, Venezuela, Brazil and Australia joined the project, reaching the grassroots of education from the very beginning. Natural dyes will become part of everyday life for more people, achieving their own colors for art, textiles or any other application. The knowledge of the techniques and resources of the student a fundamental tool, sustainable and opens endless possibilities even in places or homes with few economic resources, thus achieving that natural dyes are not only part of the world of designers but also that they are incorporated from the basics and can thus become a resource applicable in different areas even in places with few economic or development possibilities.

Keywords: art, education, natural dyes, sustainability, textile design.

Procedia PDF Downloads 73

Authors: Heny Hartono, Cecilia Titiek Murniati

Abstract:

The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

Procedia PDF Downloads 86

Authors: Jianhua Wang, Ying Zhou, Xi Zhang

Abstract:

To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

Procedia PDF Downloads 186

Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

Abstract:

Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

Procedia PDF Downloads 222

Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

Abstract:

The study investigated learning challenges experienced by students in universities situated in developing sub-Saharan African countries using selected universities in South Africa and Nigeria. Questionnaires were administered to 2,335 randomly selected students from selected universities in South Africa and Nigeria. The outcome of the study shows that six common learning challenges are visible in developing sub-Sahara African universities. The causes of these learning challenges cut across the failure in responsibilities of the various stakeholders in the field of education and the effects are monumental both to the students and society. This paper suggests recommendations to university administrators, education policy makers and implementers on the need to take education more seriously, to review and implement appropriate policies, and to ensure provision of quality education through the supply of adequate amenities and other motivating factors.

Keywords: learning, challenges, learning challenges, access with success, participatory access

Procedia PDF Downloads 280

Authors: Eyasu Gemech, Kassa Michael, Mulugeta Atnafu

Abstract:

A non-equivalent group's quasi-experiment research was conducted at Wolkite University to investigate MATLAB supported learning and students' conceptual understanding in learning Applied Mathematics II using four different comparative instructional approaches: MATLAB supported traditional lecture method, MATLAB supported collaborative method, only collaborative method, and only traditional lecture method. Four intact classes of mechanical engineering groups 1 and 2, garment engineering and textile engineering students were randomly selected out of eight departments. The first three departments were considered as treatment groups and the fourth one 'Textile engineering' was assigned as a comparison group. The departments had 30, 29, 35 and 32 students respectively. The results of the study show that there is a significant mean difference in students' conceptual understanding between groups of students learning through MATLAB supported collaborative method and the other learning approaches. Students who were learned through MATLAB technology-supported learning in combination with collaborative method were found to understand concepts of functions of two variables better than students learning through the other methods of learning. These, hence, are informative of the potential approaches universities would follow for a better students’ understanding of concepts.

Keywords: MATLAB supported collaborative method, MATLAB supported learning, collaborative method, conceptual understanding, functions of two variables

Procedia PDF Downloads 258

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 264

Authors: Haitham Taha

Abstract:

The cognitive flexibility of 27 asthmatic children with learning difficulties was tested by using the Wisconsin card sorting test (WCST) and compared to the performances of 30 non-asthmatic children who have persistence learning difficulties also. The results revealed that the asthmatic group had poor performance through all the WCST psychometric parameters and especially the preservative errors one. The results were discussed in light of the postulation that poor executive functions and specifically poor cognitive flexibility are in the basis of the learning difficulties of asthmatic children with learning difficulties. Neurophysiologic framework was suggested for explaining the etiology of poor executive functions and cognitive flexibility among children with moderate into severe asthma.

Keywords: asthma, learning disabilities, executive functions, cognitive flexibility, WCST

Procedia PDF Downloads 483

Authors: Claudia Carbajal, Jija Dutt, Smriti Pahwa, Sumukhi Vaid, Karishma Vats

Abstract:

ASER Centre, the research and assessment arm of Pratham Education Foundation sees measurement as the first stage of action. ASER uses primary research to push and give empirical foundations to policy discussions at a multitude of levels. At a household level, common citizens use a simple assessment (a floor-level test) to measure learning across rural India. This paper presents the evidence on the applicability of an ASER approach to the health sector. A citizen-led assessment was designed and executed that collected information from young mothers with children up to a year of age. The pilot assessments were rolled-out in two different models: Paid surveyors and student volunteers. The survey covered three geographic areas: 1,239 children in the Jaipur District of Rajasthan, 2,086 in the Rae Bareli District of Uttar Pradesh, and 593 children in the Bhuj Block in Gujarat. The survey tool was designed to study knowledge of health-related issues, daily practices followed by young mothers and access to relevant services and programs. It provides insights on behaviors related to infant and young child feeding practices, child and maternal nutrition and supplementation, water and sanitation, and health services. Moreover, the survey studies the reasons behind behaviors giving policy-makers actionable pathways to improve implementation of social sector programs. Although data on health outcomes are available, this approach could provide a rapid annual assessment of health issues with indicators that are easy to understand and act upon so that measurements do not become an exclusive domain of experts. The results give many insights into early childhood health behaviors and challenges. Around 98% of children are breastfed, and approximately half are not exclusively breastfed (for the first 6 months). Government established diet diversity guidelines are met for less than 1 out of 10 children. Although most households are satisfied with the quality of drinking water, most tested households had contaminated water.

Keywords: citizen-led assessment, rapid health assessment, Infant and Young Children Feeding, water and sanitation, maternal nutrition, supplementation

Procedia PDF Downloads 154

Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

Abstract:

Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

Procedia PDF Downloads 231

Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

Abstract:

Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: emotion, emotion-enhanced memory, learning technique, STEM

Procedia PDF Downloads 77

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

Procedia PDF Downloads 153

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 113

Authors: Hamza Zidoum

Abstract:

This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 361

Authors: Behrooz Nikahval, Mohammad Saeed Ahrari-Khafi, Sakineh Behroozpoor, Saeed Nazifi

Abstract:

Osteoarthritis (OA) is a progressive and degenerative condition of the articular cartilage and other joints’ structures. It is essential to diagnose this condition as early as possible. The present research was performed to measure the Osteoprotegrin (OPG) and Tumor Necrosis Factor α (TNF-α) in synovial fluid and blood serum of dogs with surgically transected cruciate ligament as a model of OA, to evaluate if measuring of these parameters can be used as a way of early diagnosis of OA. In the present study, four mature, clinically healthy dogs were selected to investigate the effect of experimental OA, on OPG and TNF-α as a way of early detection of OA. OPG and TNF-α were measured in synovial fluid and blood serum on days 0, 14, 28, 90 and 180 after surgical transaction of cranial cruciate ligament in one stifle joint. Statistical analysis of the results showed that there was a significant increase in TNF-α in both synovial fluid and blood serum. OPG showed a decrease two weeks after OA induction. However, it fluctuated afterward. In conclusion, TNF-α could be used in both synovial fluid and blood serum as a way of early detection of OA; however, further research still needs to be conducted on OPG values in OA detection.

Keywords: osteoarthritis, osteoprotegrin, tumor necrosis factor α, synovial fluid, serum, dog

Procedia PDF Downloads 306

Authors: Fahimeh Ghorbani, Alam Saleh

Abstract:

Ideology, politics and art have always been omnipresent patterns of Islam since its early age. The Islamic empire, expanded from China to Andalusia, has instrumentalized art and architecture to enhance political legitimacy of different dynasties or states throughout its history. Quranic verses utilized to convey ideological messages in the major mosques and mausoleums. Iranians had already been employing art and architecture to propagate their political legitimacy prior to Islam. The land of Iran and its art with strong civilizational pre-Islamic history has been profoundly politicized since the rise of Islam in the region. Early Islamic period in Iran has witnessed introduction of a new architectural language, new formulas for spatial configuration in built spaces, as well as new system of architectural decoration. Studying Iran’s Early Islamic architecture helps in better understanding the process of socio-political identity making of Iranian-Islamic culture, and thus art and architecture. This period also set the stage for formation of glorious architectural movements through Persianate world in later periods. During the Early Islamic period in Iran, the innovative combination of Islamic ideology and Iranian Architecture created formidable ideological tools in politicizing art in the region and beyond. As such, this paper aims to investigate the political history and architectural legacy from late Sassanid to Early Islamic period, delves into the ways in which Early Islamic architecture played role in transforming Persian concepts of kingship, administration, and social organization. In so doing, the study focuses on the Perso-Islamic architectural synthesis under the Samanids and Seljuk dynasty as case studies. The paper also explores how the newly introduced Islamic architecture has been employed to address the question of political legitimacy and to propagate states’ political agenda in early Islamic Iran (650-1250). As for the existing literature, despite its uniqueness and significance, Early Islamic architecture of Iran has received little scholarly attention. However, there exists a sizeable body of scholarship on socio-historic condition of the land of Iran during Early Islamic period which provide a solid base for the project. Methodologically speaking, the authors look into the subject through various lenses. They will conduct historic and archival research in libraries, private collections, and archives in Iran and the related neighbouring countries in Persian, Arabic and English. The methods of visual and formal analysis are applied to examine architectural features of the period. There are also a high number of intriguing, yet poorly examined, published and unpublished documents, old plans, drawings and photos of monuments preserved in Cultural Heritage of Iran Organization which will be consulted.

Keywords: Iran, Islamic architecture, early Islamic Iran, early Islamic architecture, politicized art, political legitimacy, propaganda, aesthetics

Procedia PDF Downloads 106

Authors: Geraldine Landon, Enora Clero, Jean-Rene Jourdain

Abstract:

In 2005, the Institut de Radioprotection et de Sûreté Nucléaire (IRSN, France) launched a research program named EPICE (acronym for 'Evaluation of Pathologies potentially Induced by CaEsium') to collect scientific information on non-cancer effects possibly induced by chronic exposures to low doses of ionizing radiation with the view of addressing a question raised by several French NGOs related to health consequences of the Chernobyl nuclear accident in children. The implementation of the program was preceded by a pilot phase to ensure that the project would be feasible and determine the conditions for implementing an epidemiological study on a population of several thousand children. The EPICE program focused on childhood cardiac arrhythmias started in May 2009 for 4 years, in partnership with the Russian Bryansk Diagnostic Center. The purpose of this cross-sectional study was to determine the prevalence of cardiac arrhythmias in the Bryansk oblast (depending on the contamination of the territory and the caesium-137 whole-body burden) and to assess whether caesium-137 was or not a factor associated with the onset of cardiac arrhythmias. To address these questions, a study bringing together 18 152 children aged 2 to 18 years was initiated; each child received three medical examinations (ECG, echocardiography, and caesium-137 whole-body activity measurement) and some of them were given with a 24-hour Holter monitoring and blood tests. The findings of the study, currently submitted to an international journal justifying that no results can be given at this step, allow us to answer clearly to the issue of radiation-induced childhood arrhythmia, a subject that has been debated for many years. Our results will be certainly helpful for health professionals responsible for the monitoring of population exposed to the releases from the Fukushima Dai-ichi nuclear power plant and also useful for future comparative study in children exposed to ionizing radiation in other contexts, such as cancer radiation therapies.

Keywords: Caesium-137, cardiac arrhythmia, Chernobyl, children

Procedia PDF Downloads 235

Authors: Ercan Eker, Muhammer Karaman, Akif Aslan, Hakan Tanrikuluoglu

Abstract:

Deficiency of institutional memory and knowledge management can result in information security breaches, loss of prestige and trustworthiness and the worst the loss of know-how and institutional knowledge. Traditional learning management within organizations is generally handled by personal efforts. That kind of struggle mostly depends on personal desire, motivation and institutional belonging. Even if an organization has highly motivated employees at a certain time, the institutional knowledge and memory life cycle will generally remain limited to these employees’ spending time in this organization. Having a learning management system in an organization can sustain the institutional memory, knowledge and know-how in the organization. Learning management systems are much more needed especially in public organizations where the job rotation is frequently seen and managers are appointed periodically. However, a learning management system should not be seen as an organizations’ website. It is a more comprehensive, interactive and user-friendly knowledge management tool for organizations. In this study, the importance of using learning management systems in the process of emerging tacit knowledge is underlined.

Keywords: knowledge management, learning management systems, tacit knowledge, institutional memory

Procedia PDF Downloads 362

Authors: Salwa Aftab, Sehrish Riaz

Abstract:

The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

Procedia PDF Downloads 380