Search results for: cellular learning automata
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7660

Search results for: cellular learning automata

7270 A Review on Enhancing Heat Transfer Processes by Open-Cell Metal Foams and Industrial Applications

Authors: S. Cheragh Dar, M. Saljooghi, A. Babrgir

Abstract:

In the last couple of decades researchers' attitudes were focused on developing and enhancing heat transfer processes by using new components or cellular solids that divide into stochastic structures and periodic structures. Open-cell metal foams are part of stochastic structures families that they can be considered as an avant-garde technology and they have unique properties, this porous media can have tremendous achievements in thermal processes. This paper argues and surveys postulating possible in industrial thermal issues which include: compact electronic cooling, heat exchanger, aerospace, fines, turbo machinery, automobiles, crygen tanks, biomechanics, high temperature filters and etc. Recently, by surveying exponential rate of publications in thermal open-cell metal foams, all can be demonstrated in a holistic view which can lead researchers to a new level of understanding in different industrial thermal sections.

Keywords: heat transfer, industrial thermal, cellular solids, open cell metal foam

Procedia PDF Downloads 277
7269 Experiential Learning: A Case Study for Teaching Operating System Using C and Unix

Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni, Raghavendra Nakod

Abstract:

In most of the universities and colleges Operating System (OS) course is treated as theoretical and usually taught in a classroom using conventional teaching methods. In this paper we are presenting a new approach of teaching OS through experiential learning, the course is designed to suit the requirement of undergraduate engineering program of Instrumentation Technology. This new approach has benefited us to improve our student’s programming skills, presentation skills and understanding of the operating system concepts.

Keywords: pedagogy, interactive learning, experiential learning, OS, C, UNIX

Procedia PDF Downloads 586
7268 The Impact of E-Learning on the Performance of History Learners in Eswatini General Certificate of Secondary Education

Authors: Joseph Osodo, Motsa Thobekani Phila

Abstract:

The study investigated the impact of e-learning on the performance of history learners in Eswatini general certificate of secondary education in the Manzini region of Eswatini. The study was guided by the theory of connectivism. The study had three objectives which were to find out the significance of e-learning during the COVID-19 era in learning History subject; challenges faced by history teachers’ and learners’ in e-learning; and how the challenges were mitigated. The study used a qualitative research approach and descriptive research design. Purposive sampling was used to select eight History teachers and eight History learners from four secondary schools in the Manzini region. Data were collected using face to face interviews. The collected data were analyzed and presented in thematically. The findings showed that history teachers had good knowledge on what e-learning was, while students had little understanding of e-learning. Some of the forms of e-learning that were used during the pandemic in teaching history in secondary schools included TV, radio, computer, projectors, and social media especially WhatsApp. E-learning enabled the continuity of teaching and learning of history subject. The use of e-learning through the social media was more convenient to the teacher and the learners. It was concluded that in some secondary school in the Manzini region, history teacher and learners encountered challenges such as lack of finances to purchase e-learning gadgets and data bundles, lack of skills as well as access to the Internet. It was recommended that History teachers should create more time to offer additional learning support to students whose performance was affected by the COVID-19 pandemic effects.

Keywords: e-learning, performance, COVID-19, history, connectivism

Procedia PDF Downloads 54
7267 Using Facebook as an Alternative Learning Tools in Malaysian Higher Learning Institutions: A Structural Equation Modelling Approach

Authors: Ahasanul Haque, Abdullah Sarwar, Khaliq Ahmed

Abstract:

Networking is important among students to achieve better understanding. Social networking plays an important role in the education. Realizing its huge potential, various organizations, including institutions of higher learning have moved to the area of social networks to interact with their students especially through Facebook. Therefore, measuring the effectiveness of Facebook as a learning tool has become an area of interest to academicians and researchers. Therefore, this study tried to integrate and propose new theoretical and empirical evidences by linking the western idea of adopting Facebook as an alternative learning platform from a Malaysian perspective. This study, thus, aimed to fill a gap by being among the pioneering research that tries to study the effectiveness of adopting Facebook as a learning platform across other cultural settings, namely Malaysia. Structural equation modelling was employed for data analysis and hypothesis testing. This study findings have provided some insights that would likely affect students’ awareness towards using Facebook as an alternative learning platform in the Malaysian higher learning institutions. At the end, future direction is proposed.

Keywords: Learning Management Tool, social networking, education, Malaysia

Procedia PDF Downloads 407
7266 A Context Aware Mobile Learning System with a Cognitive Recommendation Engine

Authors: Jalal Maqbool, Gyu Myoung Lee

Abstract:

Using smart devices for context aware mobile learning is becoming increasingly popular. This has led to mobile learning technology becoming an indispensable part of today’s learning environment and platforms. However, some fundamental issues remain - namely, mobile learning still lacks the ability to truly understand human reaction and user behaviour. This is due to the fact that current mobile learning systems are passive and not aware of learners’ changing contextual situations. They rely on static information about mobile learners. In addition, current mobile learning platforms lack the capability to incorporate dynamic contextual situations into learners’ preferences. Thus, this thesis aims to address these issues highlighted by designing a context aware framework which is able to sense learner’s contextual situations, handle data dynamically, and which can use contextual information to suggest bespoke learning content according to a learner’s preferences. This is to be underpinned by a robust recommendation system, which has the capability to perform these functions, thus providing learners with a truly context-aware mobile learning experience, delivering learning contents using smart devices and adapting to learning preferences as and when it is required. In addition, part of designing an algorithm for the recommendation engine has to be based on learner and application needs, personal characteristics and circumstances, as well as being able to comprehend human cognitive processes which would enable the technology to interact effectively and deliver mobile learning content which is relevant, according to the learner’s contextual situations. The concept of this proposed project is to provide a new method of smart learning, based on a capable recommendation engine for providing an intuitive mobile learning model based on learner actions.

Keywords: aware, context, learning, mobile

Procedia PDF Downloads 231
7265 A Less Complexity Deep Learning Method for Drones Detection

Authors: Mohamad Kassab, Amal El Fallah Seghrouchni, Frederic Barbaresco, Raed Abu Zitar

Abstract:

Detecting objects such as drones is a challenging task as their relative size and maneuvering capabilities deceive machine learning models and cause them to misclassify drones as birds or other objects. In this work, we investigate applying several deep learning techniques to benchmark real data sets of flying drones. A deep learning paradigm is proposed for the purpose of mitigating the complexity of those systems. The proposed paradigm consists of a hybrid between the AdderNet deep learning paradigm and the Single Shot Detector (SSD) paradigm. The goal was to minimize multiplication operations numbers in the filtering layers within the proposed system and, hence, reduce complexity. Some standard machine learning technique, such as SVM, is also tested and compared to other deep learning systems. The data sets used for training and testing were either complete or filtered in order to remove the images with mall objects. The types of data were RGB or IR data. Comparisons were made between all these types, and conclusions were presented.

Keywords: drones detection, deep learning, birds versus drones, precision of detection, AdderNet

Procedia PDF Downloads 155
7264 Deep learning with Noisy Labels : Learning True Labels as Discrete Latent Variable

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

Abstract:

In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

Procedia PDF Downloads 100
7263 Introducing Transcending Pedagogies

Authors: Wajeehah Aayeshah, Joy Higgs

Abstract:

The term “transcending pedagogies” has been created to refer to teaching and learning strategies that transcend the mode of student enrolment, the needs of different students, and different learning spaces. The value of such pedagogies in the current arena when learning spaces, technologies and preferences are more volatile than ever before, is a key focus of this paper. The paper will examine current and emerging pedagogies that transcend the learning spaces and enrollment modes of on campus, distance, virtual and workplace learning contexts. A further point of interest is how academics in professional and higher education settings interpret and implement pedagogies in the current global conversation space and re-creation of higher education. This study questioned how the notion and practice of transcending pedagogies enables us to re-imagine and reshape university curricula. It explored the nature of teaching and learning spaces and those professional and higher education (current and emerging) pedagogies that can be implemented across these spaces. We set out to identify how transcending pedagogies can assist students in learning to deal with complexity, uncertainty and change in the practice worlds and better appeal to students who are making decisions on where to enrol. The data for this study was collected through in-depth interviews and focus groups with academics and policy makers within academia.

Keywords: Transcending Pedagogies, teaching and learning strategies, learning spaces, pedagogies

Procedia PDF Downloads 523
7262 Investigating The Use Of Socially Assistive Robots To Support Learner Engagement For Students With Learning Disabilities In One-to-one Instructional Settings

Authors: Jennifer Fane, Mike Gray, Melissa Sager

Abstract:

Children with diagnosed or suspected learning disabilities frequently experience significant skill gaps in foundational learning areas such as reading, writing, and math. Remedial one-to-one instruction is a highly effective means of supporting children with learning differences in building these foundational skills and closing the learning gap between them and their same-age peers. However, due to the learning challenges children with learning disabilities face, and ensuing challenges with self-confidence, many children with learning differences struggle with motivation and self-regulation within remedial one-to-one learning environments - despite the benefits of these sessions. Socially Assistive Robots (SARs) are an innovative educational technology tool that has been trialled in a range of educational settings to support diverse learning needs. Yet, little is known about the impact of SARs on the learning of children with learning differences in a one-to-one remedial instructional setting. This study sought to explore the impact of SARs on the engagement of children (n=9) with learning differences attending one-to-one remedial instruction sessions at a non-profit remedial education provider. The study used a mixed-methods design to explore learner engagement during learning tasks both with and without the use of a SAR to investigate how the use of SARs impacts student learning. The study took place over five weeks, with each session within the study followed the same procedure with the SAR acting as a teaching assistant when in use. Data from the study included analysis of time-sample video segments of the instructional sessions, instructor recorded information about the student’s progress towards their session learning goal and student self-reported mood and energy levels before and after the session. Analysis of the findings indicates that the use of SARs resulted in fewer instances of off-task behaviour and less need for instructor re-direction during learning tasks, allowing students to work in more sustained ways towards their learning goals. This initial research indicates that the use of SARs does have a material and measurable impact on learner engagement for children with learning differences and that further exploration of the impact of SARs during one-to-one remedial instruction is warranted.

Keywords: engagement, learning differences, learning disabilities, instruction, social robotics.

Procedia PDF Downloads 194
7261 An Approximation Technique to Automate Tron

Authors: P. Jayashree, S. Rajkumar

Abstract:

With the trend of virtual and augmented reality environments booming to provide a life like experience, gaming is a major tool in supporting such learning environments. In this work, a variant of Voronoi heuristics, employing supervised learning for the TRON game is proposed. The paper discusses the features that would be really useful when a machine learning bot is to be used as an opponent against a human player. Various game scenarios, nature of the bot and the experimental results are provided for the proposed variant to prove that the approach is better than those that are currently followed.

Keywords: artificial Intelligence, automation, machine learning, TRON game, Voronoi heuristics

Procedia PDF Downloads 440
7260 Game-Theory-Based on Downlink Spectrum Allocation in Two-Tier Networks

Authors: Yu Zhang, Ye Tian, Fang Ye Yixuan Kang

Abstract:

The capacity of conventional cellular networks has reached its upper bound and it can be well handled by introducing femtocells with low-cost and easy-to-deploy. Spectrum interference issue becomes more critical in peace with the value-added multimedia services growing up increasingly in two-tier cellular networks. Spectrum allocation is one of effective methods in interference mitigation technology. This paper proposes a game-theory-based on OFDMA downlink spectrum allocation aiming at reducing co-channel interference in two-tier femtocell networks. The framework is formulated as a non-cooperative game, wherein the femto base stations are players and frequency channels available are strategies. The scheme takes full account of competitive behavior and fairness among stations. In addition, the utility function reflects the interference from the standpoint of channels essentially. This work focuses on co-channel interference and puts forward a negative logarithm interference function on distance weight ratio aiming at suppressing co-channel interference in the same layer network. This scenario is more suitable for actual network deployment and the system possesses high robustness. According to the proposed mechanism, interference exists only when players employ the same channel for data communication. This paper focuses on implementing spectrum allocation in a distributed fashion. Numerical results show that signal to interference and noise ratio can be obviously improved through the spectrum allocation scheme and the users quality of service in downlink can be satisfied. Besides, the average spectrum efficiency in cellular network can be significantly promoted as simulations results shown.

Keywords: femtocell networks, game theory, interference mitigation, spectrum allocation

Procedia PDF Downloads 134
7259 The Impact of Content Familiarity of Receptive Skills on Language Learning

Authors: Sara Fallahi

Abstract:

This paper reviews the importance of content familiarity of receptive skills and offers solutions to the issue of content unfamiliarity in language learning materials. Presently, language learning materials are mainly comprised of global issues and target language speakers’ culture(s) in receptive skills. This might leadlearners to focus on content rather than the language. As a solution, materials on receptive skills can be developed with a focus on learners’culture and social concerns, especially in the beginner levels of learning. Language learners often learn their target language through the receptive skills of listening and reading before language production ensues through speaking and writing. Students’ journey from receptive skills to productive skills is mainly concentrated on by teachers. There are barriers to language learning, such as time and energy, that can hinder learners’ understanding and ability to build the required background knowledge of the content. This is generated due to learners’ unfamiliarity with the skill’s content. Therefore, materials that improve content familiarity will help learners improve their language comprehension, learning, and usage. This presentation will conclude with practical solutions to help teachers and learners more authentically integrate language and culture to elevate language learning.

Keywords: language learning, listening content, reading content, content familiarity, ESL books, language learning books, cultural familiarity

Procedia PDF Downloads 89
7258 An Exploratory Study of the Student’s Learning Experience by Applying Different Tools for e-Learning and e-Teaching

Authors: Angel Daniel Muñoz Guzmán

Abstract:

E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: student, experience, e-learning, e-teaching, e-tools, technology, education

Procedia PDF Downloads 89
7257 An Experience Report on Course Teaching in Information Systems

Authors: Carlos Oliveira

Abstract:

This paper is a criticism of the traditional model of teaching and presents alternative teaching methods, different from the traditional lecture. These methods are accompanied by reports of experience of their application in a class. It was concluded that in the lecture, the student has a low learning rate and that other methods should be used to make the most engaging learning environment for the student, contributing (or facilitating) his learning process. However, the teacher should not use a single method, but rather a range of different methods to ensure the learning experience does not become repetitive and fatiguing for the student.

Keywords: educational practices, experience report, IT in education, teaching methods

Procedia PDF Downloads 375
7256 An Experimental Study of Online Peer-to-Peer Language Learning

Authors: Abrar Al-Hasan

Abstract:

Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

Procedia PDF Downloads 365
7255 Investigating the Experiences of Higher Education Academics on the Blended Approach Used during the Induction Course

Authors: Ann-May Marais

Abstract:

South African higher education institutions are following the global adoption of a blended approach to teaching and learning. Blended learning is viewed as a transformative teaching-learning approach, as it provides students with the optimum experience by mixing the best of face-to-face and online learning. Although academics realise the benefits of blended learning, they find it challenging and time-consuming to implement blended strategies. Professional development is a critical component of the adoption of higher education teaching-learning approaches. The Institutional course for higher education academics offered at a South African University was designed in a blended model, implemented and evaluated. This paper reports on a study that investigated the experiences of academics on the blended approach used during the induction course. A qualitative design-based research methodology was employed, and data was collected using participant feedback and document analysis. The data gathered from each of the four ICNL offerings were used to inform the design of the next course. Findings indicated that lecturers realised that blended learning could cater to student diversity, different learning styles, engagement, and innovation. Furthermore, it emerged that the course has to cater for diversity in technology proficiency and readiness of participants. Participants also require ongoing support in technology usage and discipline-specific blended learning workshops. This paper contends that the modelling of a blended approach to professional development can be an effective way to motivate academics to apply blended learning in their teaching-learning experiences.

Keywords: blended learning, professional development, induction course, integration of technology

Procedia PDF Downloads 143
7254 Research on Community-Based Engineering Learning and Undergraduate Students’ Creativity in China: The Moderate Effect of Engineering Identity

Authors: Liang Wang, Wei Zhang

Abstract:

There have been some existing researches on design-based engineering learning (DBEL) and project-based or problem-based engineering learning (PBEL). Those findings have greatly promoted the reform of engineering education in China. However, the engineering with a big E means that more and more engineering activities are designed and operated by communities of practice (CoPs), namely community-based engineering learning. However, whether community-based engineering learning can promote students' innovation has not been verified in published articles. This study fills this gap by investigating the relationship between community-based learning approach and students’ creativity, using engineering identity as an intermediary variable. The goal of this study is to discover the core features of community-based engineering learning, and make the features more beneficial for students’ creativity. The study created and adapted open survey items from previously published studies and a scale on learning community, students’ creativity and engineering identity. Firstly, qualitative content analysis methods by MAXQDA were used to analyze 32 open-ended questionnaires. Then the authors collected data (n=322) from undergraduate students in engineering competition teams and engineering laboratories in Zhejiang University, and structural equation modelling (SEM) was used to understand the relationship between different factors. The study finds: (a) community-based engineering learning has four main elements like real-task context, self-inquiry learning, deeply-consulted cooperation and circularly-iterated design, (b) community-based engineering learning can significantly enhance the engineering undergraduate students’ creativity, and (c) engineering identity partially moderated the relationship between community-based engineering learning and undergraduate students' creativity. The findings further illustrate the value of community-based engineering learning for undergraduate students. In the future research, the authors should further clarify the core mechanism of community-based engineering learning, and pay attention to the cultivation of undergraduate students’ engineer identity in learning community.

Keywords: community-based engineering learning, students' creativity, engineering identity, moderate effect

Procedia PDF Downloads 118
7253 A Peer-Produced Community of Learning: The Case of Second-Year Algerian Masters Students at a Distance

Authors: Nihad Alem

Abstract:

Nowadays, distance learning (DL) is widely perceived as a reformed type of education that takes advantage of technology to give more appealing opportunities especially for learners whose life conditions impede their attendance to regular classrooms however, creating interactional environment for students to expand their learning community and alleviate the feeling of loneliness and isolation should receive more attention when designing a distance learning course. This research aims to explore whether the audio/video peer learning can offer pedagogical add-ons to the Algerian distance learners and what are the pros and cons of its application as an educational experience in a synchronous environment mediated by Skype. Data were collected using video recordings of six sessions, reflective logs, and in-depth semi-structured interviews and will be analyzed by qualitatively identifying and measuring the three constitutional elements of the educational experience of peer learning namely the social presence, the cognitive presence, and the facilitation presence using a modified community of inquiry coding template. The findings from this study will provide recommendations for effective peer learning educational experience using the facilitation presence concept.

Keywords: audio/visual peer learning, community of inquiry, distance learning, facilitation presence

Procedia PDF Downloads 120
7252 Breast Cancer Cellular Immunotherapies

Authors: Zahra Shokrolahi, Mohammad Reza Atashzar

Abstract:

The goals of treating patients with breast cancer are to cure the disease, prolong survival, and improve quality of life. Immune cells in the tumor microenvironment have an important role in regulating tumor progression. The term of cellular immunotherapy refers to the administration of living cells to a patient; this type of immunotherapy can be active, such as a dendritic cell (DC) vaccine, in that the cells can stimulate an anti-tumour response in the patient, or the therapy can be passive, whereby the cells have intrinsic anti-tumour activity; this is known as adoptive cell transfer (ACT) and includes the use of autologous or allogeneic lymphocytes that may, or may not, be modified. The most important breast cancer cellular immunotherapies involving the use of T cells and natural killer (NK) cells in adoptive cell transfer, as well as dendritic cells vaccines. T cell-based therapies including tumour-infiltrating lymphocytes (TILs), engineered TCR-T cells, chimeric antigen receptor (CAR T cell), Gamma-delta (γδ) T cells, natural killer T (NKT) cells. NK cell-based therapies including lymphokine-activated killers (LAK), cytokine-induced killer (CIK) cells, CAR-NK cells. Adoptive cell therapy has some advantages and disadvantages some. TILs cell strictly directed against tumor-specific antigens but are inactive against tumor changes due to immunoediting. CIK cell have MHC-independent cytotoxic effect and also need concurrent high dose IL-2 administration. CAR T cell are MHC-independent; overcome tumor MHC molecule downregulation; potent in recognizing any cell surface antigen (protein, carbohydrate or glycolipid); applicable to a broad range of patients and T cell populations; production of large numbers of tumor-specific cells in a moderately short period of time. Meanwhile CAR T cells capable of targeting only cell surface antigens; lethal toxicity due to cytokine storm reported. Here we present the most popular cancer cellular immunotherapy approaches and discuss their clinical relevance referring to data acquired from clinical trials .To date, clinical experience and efficacy suggest that combining more than one immunotherapy interventions, in conjunction with other treatment options like chemotherapy, radiotherapy and targeted or epigenetic therapy, should guide the way to cancer cure.

Keywords: breast cancer , cell therapy , CAR T cell , CIK cells

Procedia PDF Downloads 106
7251 Web Application for Evaluating Tests in Distance Learning Systems

Authors: Bogdan Walek, Vladimir Bradac, Radim Farana

Abstract:

Distance learning systems offer useful methods of learning and usually contain final course test or another form of test. The paper proposes web application for evaluating tests using expert system in distance learning systems. Proposed web application is appropriate for didactic tests or tests with results for subsequent studying follow-up courses. Web application works with test questions and uses expert system and LFLC tool for test evaluation. After test evaluation the results are visualized and shown to student.

Keywords: distance learning, test, uncertainty, fuzzy, expert system, student

Procedia PDF Downloads 464
7250 Hydrogel Based on Cellulose Acetate Used as Scaffold for Cell Growth

Authors: A. Maria G. Melero, A. M. Senna, J. A. Domingues, M. A. Hausen, E. Aparecida R. Duek, V. R. Botaro

Abstract:

A hydrogel from cellulose acetate cross linked with ethylenediaminetetraacetic dianhydride (HAC-EDTA) was synthesized by our research group, and submitted to characterization and biological tests. Cytocompatibility analysis was performed by confocal microscopy using human adipocyte derived stem cells (ASCs). The FTIR analysis showed characteristic bands of cellulose acetate and hydroxyl groups and the tensile tests evidence that HAC-EDTA present a Young’s modulus of 643.7 MPa. The confocal analysis revealed that there was cell growth at the surface of HAC-EDTA. After one day of culture the cells presented spherical morphology, which may be caused by stress of the sequestration of Ca2+ and Mg2+ ions at the cell medium by HAC-EDTA, as demonstrated by ICP-MS. However, after seven days and 14 days of culture, the cells present fibroblastoid morphology, phenotype expected by this cellular type. The results give efforts to indicate this new material as a potential biomaterial for tissue engineering, in the future in vivo approach.

Keywords: cellulose acetate, hydrogel, biomaterial, cellular growth

Procedia PDF Downloads 175
7249 Investigation the Impact of Flipped Learning on Developing Meta-Cognitive Ability in Chemistry Courses of Science Education Students

Authors: R. Herscu-Kluska

Abstract:

The rise of the flipped or inverted classroom meet the conceptual needs of our time. The evidence of increased student satisfaction and course grades improvement promoted the flipped learning approach. Due to the successful outcomes of the inverted classroom, the flipped learning became a pedagogy and educational rising strategy among all education sciences. The aim of this study is to analyze the effect of flipped classroom on higher order learning in chemistry courses since it has been suggested that in higher education courses, class time should focus on knowledge application. The results of this study indicate improving meta-cognitive thinking and learning skills. The students showed better ability to cope with higher order learning assignments during the actual class time, using inverted classroom strategy. These results suggest that flipped learning can be used as an effective pedagogy and educational strategy for developing higher order thinking skills, proved to contribute to building lifelong learning.

Keywords: chemistry education, flipped classroom, flipped learning, inverted classroom, science education

Procedia PDF Downloads 320
7248 Metanotes and Foreign Language Learning: A Case of Iranian EFL Learners

Authors: Nahıd Naderı Anarı, Mojdeh Shafıee

Abstract:

Languaging has been identified as a contributor to language learning. Compared to oral languaging, written languaging seems to have been less explored. In order to fill this gap, this paper examined the effect of ‘metanotes’, namely metatalk in a written modality to identify whether written languaging actually facilitates language learning. Participants were instructed to take metanotes as they performed a translation task. The effect of metanotes was then analyzed by comparing the results of these participants’ pretest and posttest with those of participants who performed the same task without taking metanotes. The statistical tests showed no evidence of the expected role of metanotes in foreign language learning.

Keywords: EFL learners, foreign language learning, language teaching, metanotes

Procedia PDF Downloads 425
7247 A Comprehensive Study of Spread Models of Wildland Fires

Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

Procedia PDF Downloads 61
7246 Scaling Siamese Neural Network for Cross-Domain Few Shot Learning in Medical Imaging

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Cross-domain learning in the medical field is a research challenge as many conditions, like in oncology imaging, use different imaging modalities. Moreover, in most of the medical learning applications, the sample training size is relatively small. Although few-shot learning (FSL) through the use of a Siamese neural network was able to be trained on a small sample with remarkable accuracy, FSL fails to be effective for use in multiple domains as their convolution weights are set for task-specific applications. In this paper, we are addressing this problem by enabling FSL to possess the ability to shift across domains by designing a two-layer FSL network that can learn individually from each domain and produce a shared features map with extra modulation to be used at the second layer that can recognize important targets from mix domains. Our initial experimentations based on mixed medical datasets like the Medical-MNIST reveal promising results. We aim to continue this research to perform full-scale analytics for testing our cross-domain FSL learning.

Keywords: Siamese neural network, few-shot learning, meta-learning, metric-based learning, thick data transformation and analytics

Procedia PDF Downloads 32
7245 International Service Learning 3.0: Using Technology to Improve Outcomes and Sustainability

Authors: Anthony Vandarakis

Abstract:

Today’s International Service Learning practices require an update: modern technologies, fresh educational frameworks, and a new operating system to accountably prosper. This paper describes a model of International Service Learning (ISL), which combines current technological hardware, electronic platforms, and asynchronous communications that are grounded in inclusive pedagogy. This model builds on the work around collaborative field trip learning, extending the reach to international partnerships across continents. Mobile technology, 21st century skills and summit-basecamp modeling intersect to support novel forms of learning that tread lightly on fragile natural ecosystems, affirm local reciprocal partnership in projects, and protect traveling participants from common yet avoidable cultural pitfalls.

Keywords: International Service Learning, ISL, field experiences, mobile technology, out there in here, summit basecamp pedagogy

Procedia PDF Downloads 157
7244 Fostering Students’ Active Learning in Speaking Class through Project-Based Learning

Authors: Rukminingsih Rukmi

Abstract:

This paper addresses the issue of L2 teaching speaking to ESL students by fostering their active learning through project-based learning. Project-based learning was employed in classrooms where teachers support students by giving sufficient guidance and feedback. The students drive the inquiry, engage in research and discovery, and collaborate effectively with teammates to deliver the final work product. The teacher provides the initial direction and acts as a facilitator along the way. This learning approach is considered helpful for fostering students’ active learning. that the steps in implementing of project-based learning that fosters students’ critical thinking in TEFL class are in the following: (1) Discussing the materials about Speaking Class, (2) Working with the group to construct scenario of ways on speaking practice, (3) Practicing the scenario, (4) Recording the speaking practice into video, and (5) Evaluating the video product. This research is aimed to develop a strategy of teaching speaking by implementing project-based learning to improve speaking skill in the second Semester of English Department of STKIP PGRI Jombang. To achieve the purpose, the researcher conducted action research. The data of the study were gathered through the following instruments: test, observation checklists, and questionnaires. The result was indicated by the increase of students’ average speaking scores from 65 in the preliminary study, 73 in the first cycle, and 82 in the second cycle. Besides, the results of the study showed that project-based learning considered to be appropriate strategy to give students the same amount of chance in practicing their speaking skill and to pay attention in creating a learning situation.

Keywords: active learning, project-based learning, speaking ability, L2 teaching speaking

Procedia PDF Downloads 378
7243 A Framework for SQL Learning: Linking Learning Taxonomy, Cognitive Model and Cross Cutting Factors

Authors: Huda Al Shuaily, Karen Renaud

Abstract:

Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

Procedia PDF Downloads 241
7242 Problems of Learning English Vowels Pronunciation in Nigeria

Authors: Wasila Lawan Gadanya

Abstract:

This paper examines the problems of learning English vowel pronunciation. The objective is to identify some of the factors that affect the learning of English vowel sounds and their proper realization in words. The theoretical framework adopted is based on both error analysis and contrastive analysis. The data collection instruments used in the study are questionnaire and word list for the respondents (students) and observation of some of their lecturers. All the data collected were analyzed using simple percentage. The findings show that it is not a single factor that affects the learning of English vowel pronunciation rather many factors concurrently do so. Among the factors examined, it has been found that lack of correlation between English orthography and its pronunciation, not mother-tongue (which most people consider as a factor affecting learning of the pronunciation of a second language), has the greatest influence on students’ learning and realization of English vowel sounds since the respondents in this study are from different ethnic groups of Nigeria and thus speak different languages but having the same or almost the same problem when pronouncing the English vowel sounds.

Keywords: English vowels, learning, Nigeria, pronunciation

Procedia PDF Downloads 416
7241 Personalize E-Learning System Based on Clustering and Sequence Pattern Mining Approach

Authors: H. S. Saini, K. Vijayalakshmi, Rishi Sayal

Abstract:

Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems.

Keywords: e-learning, cluster, personalization, sequence, pattern

Procedia PDF Downloads 406