Search results for: English as a foreign language (EFL) learning

Authors: Dua Hişam, Serhat İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

Procedia PDF Downloads 51

Authors: Rubaiyat Jahan

Abstract:

This paper reports some findings of a study on the issues related to teacher autonomy in the Bangladeshi school contexts, and data of this research was collected from fourteen practicing English teachers of Bangladesh through semi structured interviews. The theoretical underpinning of teacher autonomy, on an apparent note, focuses on the behavioral aspects of teacher autonomy hence emphasizing mostly on the teachers’ capacity for self-directed acts of teaching and self-directed acts of professional development. Yet, a contemporary literature survey of teacher autonomy seems to be concerned more on the political interpretations of teacher autonomy. Thus, autonomous teachers are expected to generate their personal theories of teaching from their practices. The idea of personal theories of practice upholds the view that along with the teaching, teachers need to engage themselves in various classroom based research with a view to theorising from their practices. The findings of this research indicate enormous evidence of behavioral aspects of teacher autonomy. As the data of this research suggests, the participant teachers’ understanding of classroom situations, their reflections on the situational realities and opting for classroom decisions on the basis of those realizations are some good examples of teacher autonomy. Also, a few teachers’ stated teaching practices seem to reflect, though in a subtle way, their effort of outlining context embedded personal theories of teaching. This paper has got one significant pedagogical implication for the teacher education. Any teacher education must promote the conditions and capabilities for the present and prospective teachers for the role of theorisers in addition to develop their professional, procedural, and personal knowledge base.

Keywords: personal theories of practice, self-directed acts of professional development, self-directed acts of teaching, teacher autonomy

Procedia PDF Downloads 320

Authors: Ngong Eugene Ekia

Abstract:

Education is the foundation for the success of any society as its impact transcends across all sectors, including economics, politics, and social welfare. It is through education that individuals acquire the necessary knowledge and skills to succeed in life and contribute meaningfully to society. However, the world is changing rapidly, and it is vital for education systems to adapt to these changes to remain relevant. In this paper, we will discuss the current trends and challenges in education and management and propose solutions that can enable individuals to thrive in an ever-evolving world.

Keywords: access to education, effective teaching and learning, strong management practices, and empowering and personal development

Procedia PDF Downloads 114

Authors: A. Dinelka Panagoda, Bathiya Bandara, Chamod Wijetunga, Chathura Malinda, Lakmal Rupasinghe, Chethana Liyanapathirana

Abstract:

This research takes us forward with the concepts of Federated Learning and Software-Defined Networking (SDN) to introduce an efficient malware detection technique and provide a mitigation mechanism to give birth to a resilient and automated healthcare sector network system by also adding the feature of extended privacy preservation. Due to the daily transformation of new malware attacks on hospital Integrated Clinical Environment (ICEs), the healthcare industry is at an undefinable peak of never knowing its continuity direction. The state of blindness by the array of indispensable opportunities that new medical device inventions and their connected coordination offer daily, a factor that should be focused driven is not yet entirely understood by most healthcare operators and patients. This solution has the involvement of four clients in the form of hospital networks to build up the federated learning experimentation architectural structure with different geographical participation to reach the most reasonable accuracy rate with privacy preservation. While the logistic regression with cross-entropy conveys the detection, SDN comes in handy in the second half of the research to stack up the initial development phases of the system with malware mitigation based on policy implementation. The overall evaluation sums up with a system that proves the accuracy with the added privacy. It is no longer needed to continue with traditional centralized systems that offer almost everything but not privacy.

Keywords: software-defined network, federated learning, privacy, integrated clinical environment, decentralized learning, malware detection, malware mitigation

Procedia PDF Downloads 156

Authors: Deepa Kapoor, Rajshree Singh

Abstract:

This paper appreciates the emergence and growing importance as a new production factor makes the development of technologies, methodologies and strategies for measurement, creation, and diffusion into one of the main priorities of the organizations in the knowledge society. There are many models for creation and management of knowledge and diverse and varied perspectives for study, analysis, and understanding. In this article, we will conduct a theoretical approach to the type of models for the creation and management of knowledge; we will discuss some of them and see some of the difficulties and the key factors that determine the success of the processes for the creation and management of knowledge.

Keywords: knowledge creation, knowledge management, organizational development, organization learning

Procedia PDF Downloads 321

Authors: C. Fortin, D. Tokmeninova, O. Ushakova

Abstract:

Among 500 Russian universities Skolkovo Institute of Science and Technology (Skoltech) is one of the youngest (established in 2011), quite small and vastly international, comprising 20 percent of international students and 70 percent of faculty with significant academic experience at top-100 universities (QS, THE). The institute has emerged from close collaboration with MIT and leading Russian universities. Skoltech is an entirely English speaking environment. Skoltech curriculum plans of ten Master programs are based on the CDIO learning outcomes model. However, despite the Institute’s unique focus on industrial innovations and startups, one of the main challenges has become an evident large proportion of nearly half of MSc graduates entering PhD programs at Skoltech or other universities rather than industry or entrepreneurship. In order to increase the share of students joining the industrial sector after graduation, Skoltech started implementing a number of unique practices with a focus on employers’ expectations incorporated into the curriculum redesign. In this sense, extended knowledge exchange with industrial partners via collaboration in learning activities, industrial projects and assessments became essential for students’ headway into industrial and entrepreneurship pathways. Current academic curriculum includes the following types of components based on extended knowledge exchange with industrial partners: innovation workshop, industrial immersion, special industrial tracks, MSc defenses. Innovation workshop is a 4 week full time diving into the Skoltech vibrant ecosystem designed to foster innovators, focuses on teamwork, group projects, and sparks entrepreneurial instincts from the very first days of study. From 2019 the number of mentors from industry and startups significantly increased to guide students across these sectors’ demands. Industrial immersion is an exclusive part of Skoltech curriculum where students after the first year of study spend 8 weeks in an industrial company carrying out an individual or team project and are guided jointly by both Skoltech and company supervisors. The aim of the industrial immersion is to familiarize students with relevant needs of Russian industry and to prepare graduates for job placement. During the immersion a company plays the role of a challenge provider for students. Skoltech has started a special industrial track comprising deep collaboration with IPG Photonics – a leading R&D company and manufacturer of high-performance fiber lasers and amplifiers for diverse applications. The track is aimed to train a new cohort of engineers and includes a variety of activities for students within the “Photonics” MSc program. It is expected to be a successful story and used as an example for similar initiatives with other Russian high-tech companies. One of the pathways of extended knowledge exchange with industrial partners is an active involvement of potential employers in MSc Defense Committees to review and assess MSc thesis projects and to participate in defense procedures. The paper will evaluate the effect and results of the above undertaken measures.

Keywords: Curriculum redesign, knowledge exchange model, learning outcomes framework, stakeholder engagement

Procedia PDF Downloads 64

Authors: Carlos Theran, Yohn Parra Bautista, Victor Adankai, Richard Alo, Jimwi Liu, Clement G. Yedjou

Abstract:

Alzheimer's disease (AD) is a neurodegenerative disorder primarily characterized by deteriorating cognitive functions. AD has gained relevant attention in the last decade. An estimated 24 million people worldwide suffered from this disease by 2011. In 2016 an estimated 40 million were diagnosed with AD, and for 2050 is expected to reach 131 million people affected by AD. Therefore, detecting and confirming AD at its different stages is a priority for medical practices to provide adequate and accurate treatments. Recently, Machine Learning (ML) models have been used to study AD's stages handling missing values in multiclass, focusing on the delineation of Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI), and normal cognitive (CN). But, to our best knowledge, robust performance information of these models and the missing data analysis has not been presented in the literature. In this paper, we propose studying the performance of five different machine learning models for AD's stages multiclass prediction in terms of accuracy, precision, and F1-score. Also, the analysis of three imputation methods to handle the missing value problem is presented. A framework that integrates ML model for AD's stages multiclass prediction is proposed, performing an average accuracy of 84%.

Keywords: alzheimer's disease, missing value, machine learning, performance evaluation

Procedia PDF Downloads 215

Authors: Linnea Stenliden

Abstract:

The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

Procedia PDF Downloads 349

Authors: Mamani Acurio Alex, Aguilar Alonso Igor

Abstract:

The lack of interest and the lack of motivation are related. The lack of both in school generates serious problems such as school dropout or a low level of learning. Augmented reality has been very useful in different areas, and in this research, it was implemented in the area of education. Information necessary for the correct development of this mobile application with augmented reality was searched using six different research repositories. It was concluded that the application must be immersive, attractive, and fun for students, and the necessary technologies for its construction were defined.

Keywords: augmented reality, Vuforia, school interest, learning

Procedia PDF Downloads 72

Authors: Aiydh Aljeddani, Fran Martin

Abstract:

Sustainable human development is an essential component of a sustainable economic, social and environmental development. Addressing sustainable learning only through the addition of new teaching methods, or embedding certain approaches, is not sufficient on its own to support the goals of sustainable human development. This research project seeks to explore how the process of redesigning the current principles of curriculum based on the concept of sustainable learning could contribute to preparing a citizen who could later contribute towards sustainable human development. Multiple qualitative methodologies were employed in order to achieve the aim of this study. The main research methods were teachers’ field notes, artefacts, informal interviews (unstructured interview), a passive participant observation, a mini nominal group technique (NGT), a weekly diary, and weekly meeting. The study revealed that the integration of a curriculum for sustainable development, in addition to the use of innovative teaching approaches, highly valued by students and teachers in social studies’ sessions. This was due to the fact that it created a positive atmosphere for interaction and aroused both teachers and students’ interest. The content of the new curriculum also contributed to increasing students’ sense of shared responsibility through involving them in thinking about solutions for some global issues. This was carried out through addressing these issues through the concept of sustainable development and the theory of Thinking Activity in a Social Context (TASC). Students had interacted with sustainable development sessions intellectually and they also practically applied it through designing projects and cut-outs. Ongoing meetings and workshops to develop work between both the researcher and the teachers, and by the teachers themselves, played a vital role in implementing the new curriculum. The participation of teachers in the development of the project through working papers, exchanging experiences and introducing amendments to the students' environment was also critical in the process of implementing the new curriculum. Finally, the concept of sustainable learning can contribute to the learning outcomes much better than the current curriculum and it can better develop the learning objectives in educational institutions.

Keywords: redesigning, social studies and citizenship education curriculum, sustainable learning, thinking activity in a social context

Procedia PDF Downloads 211

Authors: Nicholas V. Scott, Jack McCarthy

Abstract:

Military, law enforcement, and counter terrorism organizations are often tasked with target detection and image characterization of scenes containing explosive materials in various types of environments where light scattering intensity is high. Mitigation of this photonic noise using classical digital filtration and signal processing can be difficult. This is partially due to the lack of robust image processing methods for photonic noise removal, which strongly influence high resolution target detection and machine learning-based pattern recognition. Such analysis is crucial to the delivery of reliable intelligence. Polarization filters are a possible method for ambient glare reduction by allowing only certain modes of the electromagnetic field to be captured, providing strong scene contrast. An experiment was carried out utilizing a polarization lens attached to a hyperspectral imagery camera for the purpose of exploring the degree to which an imaged polarized scene of potassium, phosphorus, and nitrogen mixture allows for improved target detection and image segmentation. Preliminary imagery results based on the application of machine learning algorithms, including competitive leaky learning and distance metric analysis, to polarized hyperspectral imagery, suggest that polarization filters provide a slight advantage in image segmentation. The results of this work have implications for understanding the presence of explosive material in dry, desert areas where reflective glare is a significant impediment to scene characterization.

Keywords: explosive material, hyperspectral imagery, image segmentation, machine learning, polarization

Procedia PDF Downloads 124

Authors: Paulomi Polly Burey, Mark Lynch

Abstract:

It has been shown that laboratory activities can help cement understanding of theoretical concepts, but it is difficult to deliver such an activity to an online cohort and issues such as occupational health and safety in the students’ learning environment need to be considered. Chemistry, in particular, is one of the sciences where practical experience is beneficial for learning, however typical university experiments may not be suitable for the learning environment of a distance learner. Food provides an ideal medium for demonstrating chemical concepts, and along with a few simple physical and virtual tools provided by educators, analytical chemistry can be experienced by distance learners. Food chemistry experiments were designed to be carried out in a home-based environment that 1) Had sufficient scientific rigour and skill-building to reinforce theoretical concepts; 2) Were safe for use at home by university students and 3) Had the potential to enhance student learning by linking simple hands-on laboratory activities with high-level virtual science. Two main components of the resources were developed, a home laboratory experiment component, and a virtual laboratory component. For the home laboratory component, students were provided with laboratory kits, as well as a list of supplementary inexpensive chemical items that they could purchase from hardware stores and supermarkets. The experiments used were typical proximate analyses of food, as well as experiments focused on techniques such as spectrophotometry and chromatography. Written instructions for each experiment coupled with video laboratory demonstrations were used to train students on appropriate laboratory technique. Data that students collected in their home laboratory environment was collated across the class through shared documents, so that the group could carry out statistical analysis and experience a full laboratory experience from their own home. For the virtual laboratory component, students were able to view a laboratory safety induction and advised on good characteristics of a home laboratory space prior to carrying out their experiments. Following on from this activity, students observed laboratory demonstrations of the experimental series they would carry out in their learning environment. Finally, students were embedded in a virtual laboratory environment to experience complex chemical analyses with equipment that would be too costly and sensitive to be housed in their learning environment. To investigate the impact of the intervention, students were surveyed before and after the laboratory series to evaluate engagement and satisfaction with the course. Students were also assessed on their understanding of theoretical chemical concepts before and after the laboratory series to determine the impact on their learning. At the end of the intervention, focus groups were run to determine which aspects helped and hindered learning. It was found that the physical experiments helped students to understand laboratory technique, as well as methodology interpretation, particularly if they had not been in such a laboratory environment before. The virtual learning environment aided learning as it could be utilized for longer than a typical physical laboratory class, thus allowing further time on understanding techniques.

Keywords: chemistry, food science, future pedagogy, STEM education

Procedia PDF Downloads 150

Authors: Edith Esparza-Young, Ángel M. Matos, Yaritza Gonzalez, Kirthana Sugunathevan

Abstract:

Introduction: This research describes the existing medical school program which supports a multicultural setting and bilingualism. The rise of Spanish speakers in the United States has led to the recruitment of bilingual medical students who can serve the evolving demographics. This paper includes anecdotal evidence, narratives and the latest research on the outcomes of supporting a multilingual academic experience in medical school and beyond. People in the United States will continue to need health care from physicians who have experience with multicultural competence. Physicians who are bilingual and possess effective communication skills will be in high demand. Methodologies: This research is descriptive. Through this descriptive research, the researcher will describe the qualities and characteristics of the existing medical school programs, curriculum, and student services. Additionally, the researcher will shed light on the existing curriculum in the medical school and also describe specific programs which help to serve as safety nets to support diverse populations. The method included observations of the existing program and the implementation of the medical school program, specifically the Accelerated Review Program, the Language Education and Professional Communication Program, student organizations and the Global Health Institute. Concluding Statement: This research identified and described characteristics of the medical school’s program. The research explained and described the current and present phenomenon of this medical program, which has focused on increasing the graduation of bilingual and minority physicians. The findings are based on observations of the curriculum, programs and student organizations which evolves and remains innovative to stay current with student enrollment.

Keywords: bilingual, English, medicine, doctor

Procedia PDF Downloads 123

Authors: Ya-Ting Carolyn Yang, Ping-Han Cheng, Shi-Hui Gilbert Chang, Terry Yuan-Fang Chen, Chih-Chieh Li

Abstract:

Nanotechnology is widely applied in various areas so professionals in the related fields have to know more than nano knowledge. In the study, we focus on adopting ICT-assisted PBL in college general education to foster professionals who possess multiple abilities. The research adopted a pretest and posttest quasi-experimental design. The control group received traditional instruction, and the experimental group received ICT-assisted PBL instruction. Descriptive statistics will be used to describe the means, standard deviations, and adjusted means for the tests between the two groups. Next, analysis of covariance (ANCOVA) will be used to compare the final results of the two research groups after 6 weeks of instruction. Statistics gathered in the end of the research can be used to make contrasts. Therefore, we will see how different teaching strategies can improve students’ understanding about nanotechnology and learning skills.

Keywords: nanotechnology, science education, project-based learning, information and communication technology

Procedia PDF Downloads 355

Authors: Robert Jesiolowski, Monique Jesiolowski

Abstract:

Today more than ever before, we have access to new technologies which provide unforeseen opportunities for educators to pursue in online education. It starts with an idea, but that needs to be coupled with the right team of experts willing to take big risks and put in the hard work to build something different. An instructional design team was empowered to reimagine an Introduction to Sociology university course as a Game-Based Learning (GBL) experience utilizing cutting edge Virtual Reality (VR) technology. The result was a collaborative process that resulted in a type of learning based in Game theory, Method of Loci, and VR Immersion Simulations to promote deeper retention of core concepts. The team deconstructed the way that university courses operated, in order to rebuild the educational process in a whole learner-centric manner. In addition to a review of the build process, this paper will explore the results of in-course surveys completed by student participants.

Keywords: higher education, innovation, virtual reality, game-based learning, loci method

Procedia PDF Downloads 65

Authors: Karl Eddie T. Malabanan

Abstract:

Due to the quick transmission and public health risk of coronavirus disease, schools and universities have shifted to distant learning. Teachers everywhere were forced to shift gears instantly in order to react to the needs of students and families using synchronous and asynchronous virtual teaching. This study aims to explore the lived experiences of physical education teachers who are currently experiencing remote learning in teaching during the time of the COVID-19 pandemic. Specifically, the challenges that the physical education teachers encounter during remote learning and teaching. The participants include 12 physical education teachers who have taught in higher education institutions for at least five years. The researcher utilized qualitative research; specifically, the researcher used Consensual Qualitative Research (CQR). The results of this study showed that there are five categories for the Lived Experiences of Physical Education Teachers with thirty-one subcategories. This study revealed that physical education teachers experienced very challenging situations during the time of the pandemic. It also found that students had challenges in the abrupt transition from traditional to virtual learning classes, but it also showed that students are tenacious and willing to face any adversity. The researcher also finds that teachers are mentally drained during this time. Furthermore, one of the main focuses for the teachers should be on improving their well-being. And lastly, to cope with the challenges, teachers employ socializing to relieve tension and anxiety.

Keywords: lived experiences, consensual qualitative research, pandemic, education

Procedia PDF Downloads 76

Authors: He Lingsong, Wang Junfeng, Tan Qiong, Xu Jiang

Abstract:

The paper describes efforts on reconstruction methods of engineering testing and measurement technology course by applying new techniques and applications. Firstly, flipped classroom was introduced. In-class time was used for in-depth discussions and interactions while theory concept teaching was done by self-study course outside of class. Secondly, two hands-on practices of technique applications, including the program design of MATLAB Signal Analysis and the measurement application of Arduino sensor, have been covered in class. Class was transformed from an instructor-centered teaching process into an active student-centered learning process, consisting of the pre-class massive open online course (MOOC), in-class discussion and after-class practice. The third is to change sole written homework to the research-oriented application practice assignments, so as to enhance the breadth and depth of the course.

Keywords: testing and measurement, flipped classroom, MOOC, research-oriented learning, practice-oriented learning

Procedia PDF Downloads 124

Authors: Edgardo V. Gubatanga Jr., Mark Joshua Salvacion

Abstract:

Most aerial LiDAR systems have accompanying aerial cameras in order to capture not only the terrain of the surveyed area but also its true-color appearance. However, the presence of atmospheric clouds, poor lighting conditions, and aerial camera problems during an aerial survey may cause absence of aerial photographs. These leave areas having terrain information but lacking aerial photographs. Intensity images can be derived from LiDAR data but they are only grayscale images. A deep learning model is developed to create a complex function in a form of a deep neural network relating the pixel values of LiDAR-derived intensity images and true-color images. This complex function can then be used to predict the true-color images of a certain area using intensity images from LiDAR data. The predicted true-color images do not necessarily need to be accurate compared to the real world. They are only intended to look realistic so that they can be used as base maps.

Keywords: aerial LiDAR, colorization, deep learning, intensity images

Procedia PDF Downloads 143

Authors: James Purnama, Riri Fitri Sari

Abstract:

We investigate the machine learning algorithm selection problem in the term of a depth image based eye gaze estimation, with respect to its essential difficulty in reducing the number of required training samples and duration time of training. Statistics based prediction accuracy are increasingly used to assess and evaluate prediction or estimation in gaze estimation. This article evaluates Root Mean Squared Error (RMSE) and R-Squared statistical analysis to assess machine learning methods on depth camera data for gaze estimation. There are 4 machines learning methods have been evaluated: Random Forest Regression, Regression Tree, Support Vector Machine (SVM), and Linear Regression. The experiment results show that the Random Forest Regression has the lowest RMSE and the highest R-Squared, which means that it is the best among other methods.

Keywords: gaze estimation, gaze tracking, eye tracking, kinect, regression model, orange python

Procedia PDF Downloads 521

Authors: Ann Devitt, Mairead Brady, Markus Lamest, Stephen Gomez

Abstract:

This study set out to explore the use of an online collaborative serious game for student learning in a postgraduate introductory marketing module. The simulation game aimed to bridge the theory-practice divide in marketing by allowing students to apply theory in a safe, simulated marketplace. This study addresses the following research questions: Does an online marketing simulation game engage students higher order cognitive skills? Does collaborative activity required develop students’ “soft” skills, such as communication and negotiation? What specific affordances of the online simulation promote learning? This qualitative case study took place in 2014 with 40 postgraduate students on a Business Masters Programme. The two-week intensive module combined lectures with collaborative activity on a marketing simulation game, MMX from Pearsons. The game requires student teams to compete against other teams in a marketplace and design a marketing plan to maximize key performance indicators. The data for this study comprise essays written by students after the module reflecting on their learning on the module. A thematic analysis was conducted of the essays using the following a priori theme sets: 6 levels of the cognitive domain of Blooms taxonomy; 5 principles of Cooperative Learning; affordances of simulation environments including experiential learning; motivation and engagement; goal orientation. Preliminary findings would strongly suggest that the game facilitated students identifying the value of theory in practice, in particular for future employment; enhanced their understanding of group dynamics and their role within that; and impacted very strongly, both positively and negatively on motivation. In particular the game mechanics of MMX, which hinges on the correct identification of a target consumer group, was identified as a key determinant of extrinsic and intrinsic motivation for learners. The findings also suggest that the situation of the simulation game within a broader module which required post-game reflection was valuable in identifying key learning of marketing concepts in both the positive and the negative experiences of the game.

Keywords: simulation, marketing, serious game, cooperative learning, bloom's taxonomy

Procedia PDF Downloads 537

Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

Abstract:

This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

Procedia PDF Downloads 44

Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

Procedia PDF Downloads 175

Authors: Henriette van Rensburg, Betty Adcock

Abstract:

Concern about the lack of knowledge of quality teaching and teacher retention in rural and remote areas of Australia, has caused academics to improve pre-service teachers’ understanding of this problem. The participants in this study were forty students enrolled in an undergraduate educational course (EDO3341 Teaching in rural and remote communities) at the University of Southern Queensland in Toowoomba in 2012. This study involved an innovative case-based teaching approach in order to broaden their generally under-informed understanding of teaching in a rural and remote area. Three themes have been identified through analysing students’ critical reflections: learning expertise, case-based learning support and authentic learning. The outcomes identified the changes in pre-service teachers’ understanding after they have deepened their knowledge of the realities of teaching in rural and remote areas.

Keywords: rural and remote education, case based teaching, innovative education approach, higher education

Procedia PDF Downloads 471

Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

Abstract:

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing

Procedia PDF Downloads 106

Authors: Rosa M. Gambier, Jennifer L. Carlson

Abstract:

In order to revitalize the science curriculum for botany courses for non-science majors, we have introduced the use of the medicinal plants into a first-year botany course. We have connected the use of scientific method, scientific inquiry and active learning in the classroom with the study of Western Traditional Medical Botany. The students have researched models of Botanical medicine and have designed a sustainable medicinal plants garden using native medicinal plants from the northeast. Through the semester, the students have researched their chosen species, planted seeds in the college greenhouse, collected germination ratios, growth ratios and have successfully produced a beginners medicinal plant garden. Phase II of the project will be to tie in SCCCs community outreach goals by involving the public in the expanded development of the garden as a way of sharing learning about medicinal plants and traditional medicine outside the classroom.

Keywords: medicinal plant garden, botany curriculum, active learning, community outreach

Procedia PDF Downloads 282

Authors: Shalini Attri

Abstract:

Silence has been 'scriptured' in women within dominating social structures, as the modes of speaking and behaving which deny women free investiture to language. A woman becomes the product of ideological constructions as language substantiates andro-centric bias. Constrained from writing/speaking in the public sphere, women have traditionally been confined to expressing themselves in writing private poetry, letters or diaries. The helplessness of a woman is revealed in the ways in which she is expected to speak a language, which, in fact, is man-made. There are visible binaries of coloniser- colonised; Western-Eastern; White-Black, Nature-Culture, even Male-Female that contribute significantly to our understanding of the concept of representation and its resultant politics. Normally, an author is labeled as feminist, humanist, or propagandist and this process of labeling correspond to a sense of politics besides his inclination to a particular field. One cannot even think of contemporary literature without this representational politics. Thus, each and every bit of analysis of a work of literature demands a political angle to be dealt with. Besides literature, the historical facts and manuscripts are also subject to this politics. The image of woman as someone either dependent on man or is exploited by him only provides half the picture of this representational politics. The present paper is an attempt to study Panchali’s (Draupadi of Mahabharata) voiceless articulation and her representation as a strong woman in Chitra Divakurani’s The Palace of Illusions.

Keywords: politics, representation, silence, social structures

Procedia PDF Downloads 247

Authors: Mehrnoosh Mirzaei

Abstract:

Children are among the most vulnerable at the occurrence of natural disasters such as earthquakes. Most of the management and measures which are considered for both before and during an earthquake are neither suitable nor efficient for this age group and cannot be applied. On the other hand, due to their age, it is hard to educate and train children to learn and understand the concept of earthquake risk mitigation as matters like earthquake prevention and safe places during an earthquake are not easily perceived. To our knowledge, children’s awareness of such concepts via their own world with the help of games is the best training method in this case. In this article, the researcher has tried to consider the child an active element before and during the earthquake. With training, provided by adults before the incidence of an earthquake, the child has the ability to learn disaster risk reduction (DRR). The focus of this research is on learning risk reduction behavior and regarding children as an individual element. The information of this article has been gathered from library resources, observations and the drawings of 10 children aged 5 whose subject was their conceptual definition of an earthquake who were asked to illustrate their conceptual definition of an earthquake; the results of 20 questionnaires filled in by preschoolers along with information gathered by interviewing them. The design of the suitable educational game, appropriate for the needs of this age group, has been made based on the theory of design with help of the user and the priority of children’s learning needs. The final result is a package of a game which is comprised of a learning table and matching cards showing sign marks for safe and unsafe places which introduce the safe behaviors and safe locations before and during the earthquake. These educational games can be used both in group contexts in kindergartens and on an individual basis at home, and they help in earthquake risk reduction.

Keywords: disaster education, earthquake sign marks, learning table, matching card, risk reduction behavior

Procedia PDF Downloads 237

Authors: Chaithanya Pothuganti

Abstract:

Open and semi-open spaces in educational buildings like corridors, mid landings, seating spaces, lobby, courtyards are traditionally have been the places of social communion and interaction which helps in promoting the knowledge, performance, activeness, and motivation in students. Factors like availability of land, commercialization, of educational facilities, especially in e-techno and smart schools, led to closed classrooms to accommodate students thereby lack quality open and semi-open spaces. This insufficient attention towards open space design which is a means of informal learning misses an opportunity to encourage the student’s skill development, behavior and learning skills. The core objective of this paper is to find the level of impact on student learning behavior and to identify the suitable proportions and configuration of spaces that shape the schools. In order to achieve this, different types of open spaces in schools and their impact on student’s performance in various existing models are analysed using case studies to draw some design principles. The study is limited to indoor open spaces like corridors, break out spaces and courtyards. The expected outcome of the paper is to suggest better design considerations for the development of semi-open and open spaces which functions as an element for informal learnings. Its focus is to provide further thinking on designing and development of open spaces in educational buildings.

Keywords: configuration of spaces and proportions, informal learning, open spaces, schools, student’s behavior

Procedia PDF Downloads 295

Authors: M. Rodionov, Z. Dedovets

Abstract:

This article discusses ways to implement a differentiated approach to developing academic motivation for mathematical studies which relies on defining the primary structural characteristics of motivation. The following characteristics are considered: features of realization of cognitive activity, meaning-making characteristics, level of generalization and consistency of knowledge acquired by personal experience. The assessment of the present level of individual student understanding of each component of academic motivation is the basis for defining the relevant educational strategy for its further development.

Keywords: learning activity, mathematics, motivation, student

Procedia PDF Downloads 405

Authors: Shaila Rana, Wasim Alhamdani

Abstract:

Effective cybersecurity learning relies on an engaging, interactive, and entertaining activity that fosters positive learning outcomes. VR cybersecurity training may promote these aforementioned variables. However, a methodological approach and framework have not yet been created to allow trainers and educators to employ VR cybersecurity training methods to promote positive learning outcomes to the author’s best knowledge. Thus, this paper aims to create an approach that cybersecurity trainers can follow to create a VR cybersecurity training module. This methodology utilizes concepts from other cybersecurity training frameworks, such as NICE and CyTrONE. Other cybersecurity training frameworks do not incorporate the use of VR. VR training proposes unique challenges that cannot be addressed in current cybersecurity training frameworks. Subsequently, this ontology utilizes concepts unique to developing VR training to create a relevant methodology for creating VR cybersecurity training modules. The outcome of this research is to create a methodology that is relevant and useful for designing VR cybersecurity training modules.

Keywords: virtual reality cybersecurity training, VR cybersecurity training, traditional cybersecurity training, ontology

Procedia PDF Downloads 264