Search results for: personalized learning paths
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7755

Search results for: personalized learning paths

4665 A Non-Destructive Estimation Method for Internal Time in Perilla Leaf Using Hyperspectral Data

Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

Abstract:

Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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4664 Integrating Cooperative Education Experience into Engineering Curriculum: An Approach

Authors: Robin Lok-Wang Ma

Abstract:

The Center/Unit for Industry Engagement and Collaboration, as well as Internship, play a significant role at university. In general, the Center serves as the official interface between the industry and the School or Department to cultivate students’ early exposure to professional experience. The missions of the Center are not limited to provide a communication channel and collaborative platform for the industries and the university but also to assist students to build up their career paths early while still in the university. In recent years, a cooperative education experience (commonly known as a co-op) has been strongly advocated for students to make the school-to-work transition. The nature of the co-op program is not only consistent with the internships/final year design projects, but it is also more industrial-oriented with academic support from faculty at the university. The purpose of this paper is to describe an approach to how cooperative education experience can be integrated into Engineering Curriculum. It provides a mutual understanding and exchange of ideas for the approach between the university and the industry. A suggested format in terms of timeline, duration, selection of candidates, students, and companies’ expectations for the co-op program is described. Also, feedbacks from employers/industries show that a longer-term co-op program is well suited for students compared with a short-term internship. To this end, it provides a new insight into collaboration and/or partnership between the university and the industries to prepare professional work-ready graduates.

Keywords: cooperative education, industry, engagement, collaboration

Procedia PDF Downloads 95
4663 Bio-Grouting Applications in Caprock Sealing for Geological CO2 Storage

Authors: Guijie Sang, Geo Davis, Momchil Terziev

Abstract:

Geological CO2 storage has been regarded as a promising strategy to mitigate the emission of greenhouse gas generated from traditional power stations and energy-intensive industry. Caprocks with very low permeability and ultra-fine pores create viscous and capillary barriers to guarantee CO2 sealing efficiency. However, caprock fractures, either naturally existing or artificially induced due to injection, could provide preferential paths for CO₂ escaping. Seeking an efficient technique to seal and strengthen caprock fractures is crucial. We apply microbial-induced-calcite-precipitation (MICP) technique for sealing and strengthening caprock fractures in the laboratory scale. The MICP bio-grouting technique has several advantages over conventional cement grouting methods, including its low viscosity, micron-size microbes (accessible to fine apertures), and low carbon footprint, among others. Different injection strategies are tested to achieve relatively homogenous calcite precipitation along the fractures, which is monitored dynamically based on laser ultrasonic technique. The MICP process in caprock fractures, which integrates the coupled flow and bio-chemical precipitation, is also modeled and validated through the experiment. The study could provide an effective bio-mediated grouting strategy for caprock sealing and thus ensuring a long-term safe geological CO2 storage.

Keywords: caprock sealing, geological CO2 storage, grouting strategy, microbial induced calcite precipitation

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4662 Impact Location From Instrumented Mouthguard Kinematic Data In Rugby

Authors: Jazim Sohail, Filipe Teixeira-Dias

Abstract:

Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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4661 Determination of the Gain in Learning the Free-Fall Motion of Bodies by Applying the Resource of Previous Concepts

Authors: Ricardo Merlo

Abstract:

In this paper, we analyzed the different didactic proposals for teaching about the free fall motion of bodies available online. An important aspect was the interpretation of the direction and sense of the acceleration of gravity and of the falling velocity of a body, which is why we found different applications of the Cartesian reference system used and also different graphical presentations of the velocity as a function of time and of the distance traveled vertically by the body in the period of time that it was dropped from a height h0. In this framework, a survey of previous concepts was applied to a voluntary group of first-year university students of an Engineering degree before and after the development of the class of the subject in question. Then, Hake's index (0.52) was determined, which resulted in an average learning gain from the meaningful use of the reference system and the respective graphs of v=ƒ (t) and h=ƒ (t).

Keywords: didactic gain, free–fall, physics teaching, previous knowledge

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4660 A Case Study on the Development and Application of Media Literacy Education Program Based on Circular Learning

Authors: Kim Hyekyoung, Au Yunkyung

Abstract:

As media plays an increasingly important role in our lives, the age at which media usage begins is getting younger worldwide. Particularly, young children are exposed to media at an early age, making early childhood media literacy education an essential task. However, most existing early childhood media literacy education programs focus solely on teaching children how to use media, and practical implementation and application are challenging. Therefore, this study aims to develop a play-based early childhood media literacy education program utilizing topic-based media content and explore the potential application and impact of this program on young children's media literacy learning. Based on theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perceptions of media literacy education for preschool children, this study developed a media literacy education program for preschool children, considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication). To verify the effectiveness of the program, 20 preschool children aged 5 from C City M Kindergarten were chosen as participants, and the program was implemented from March 28th to July 4th, 2022, once a week for a total of 7 sessions. The program was developed based on Gallenstain's (2003) iterative learning model (participation-exploration-explanation-extension-evaluation). To explore the quantitative changes before and after the program, a repeated measures analysis of variance was conducted, and qualitative analysis was employed to examine the observed process changes. It was found that after the application of the education program, media literacy levels such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication significantly improved. The recursive learning-based early childhood media literacy education program developed in this study can be effectively applied to young children's media literacy education and help enhance their media literacy levels. In terms of observed process changes, it was confirmed that children learned about various topics, expressed their thoughts, and improved their ability to communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can contribute to empowering young children to safely and effectively utilize media in their media environment. The results of this study, exploring the potential application and impact of the recursive learning-based early childhood media literacy education program on young children's media literacy learning, demonstrated positive changes in young children's media literacy levels. These results go beyond teaching children how to use media and can help foster their ability to safely and effectively utilize media in their media environment. Additionally, to enhance young children's media literacy levels and create a safe media environment, diverse content and methodologies are needed, and the continuous development and evaluation of education programs should be conducted.

Keywords: young children, media literacy, recursive learning, education program

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4659 Assessment of DNA Sequence Encoding Techniques for Machine Learning Algorithms Using a Universal Bacterial Marker

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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4658 Teachers’ Stress as a Moderator of the Impact of POMPedaSens on Preschool Children’s Social-Emotional Learning

Authors: Maryam Zarra-Nezhad, Ali Moazami-Goodarzi, Joona Muotka, Nina Sajaniemi

Abstract:

This study examines the extent to which the impact of a universal intervention program, i.e., POMPedaSens, on children’s early social-emotional learning (SEL) is different depending on early childhood education (ECE) teaches stress at work. The POMPedaSens program aims to promote children’s (5–6-year-olds) SEL by supporting ECE teachers’ engagement and emotional availability. The intervention effectiveness has been monitored using an 8-month randomized controlled trial design with an intervention (IG; 26 teachers and 195 children) and a waiting control group (CG; 36 teachers and 198 children) that provided the data before and after the program implementation. The ECE teachers in the IG are trained to implement the intervention program in their early childhood education and care groups. Latent change score analysis suggests that the program increases children’s prosocial behavior in the IG when teachers show a low level of stress. No significant results were found for the IG regarding a change in antisocial behavior. However, when teachers showed a high level of stress, an increase in prosocial behavior and a decrease in antisocial behavior were only found for children in the CG. The results suggest a promising application of the POMPedaSens program for promoting prosocial behavior in early childhood when teachers have low stress. The intervention will likely need a longer time to display the moderating effect of ECE teachers’ well-being on children’s antisocial behavior change.

Keywords: early childhood, social-emotional learning, universal intervention program, professional development, teachers' stress

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4657 Crystallized Colored Towels Obtained by Special Coloration of Yarns

Authors: Hasan Eskin, Gizem Özmen, A. Nazmi Çeler

Abstract:

When we examine the home textile development process, it follows a parallel line with the other textile products especially in the garment fabrics in terms of raw materials, production technologies and pattern characteristics. As a result, the expectations of people regarding textile, comfort, pattern (texture) and color properties are increasing. One of the places where comfort is most sought after is bath, pool, sea and baths. In addition to the material and technique that make up the physical structure in woven fabrics, color has an impressive importance with its strong effects. Color is the most prominent element in the fabric, and the color and texture are visually reinforcing. Evaluation of color in fabric is a personal phenomenon. Factors that determine color determination in fabric are the amount of color used, color ratio and its relationship with other colors. In this project; Considering the effect of color dimensions on human, we are talking about the crystallized colored towel that we developed in terms of comfort and texture properties. The basis of the effect created in the towel; It is formed by bending the yarn from its own special blend and the harmonious appearance of the natural crystallized rainbow colors with the pattern effect it determines on the warp yarns by using the weft yarns in the weaving. In addition, by using different weaving techniques and colors, alternatives can be created and personalized patterns can be created. One side of the towel determines the properties related to color, while the pile part determines the comfort characteristics with its soft touch and water absorbency.

Keywords: color effect, comfort, towel, weaving technique

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4656 Machine Learning for Exoplanetary Habitability Assessment

Authors: King Kumire, Amos Kubeka

Abstract:

The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: machine-learning, habitability, exoplanets, supercomputing

Procedia PDF Downloads 89
4655 Machine Learning for Exoplanetary Habitability Assessment

Authors: King Kumire, Amos Kubeka

Abstract:

The synergy of machine learning and astronomical technology advancement is giving rise to the new space age, which is pronounced by better habitability assessments. To initiate this discussion, it should be recorded for definition purposes that the symbiotic relationship between astronomy and improved computing has been code-named the Cis-Astro gateway concept. The cosmological fate of this phrase has been unashamedly plagiarized from the cis-lunar gateway template and its associated LaGrange points which act as an orbital bridge to the moon from our planet Earth. However, for this study, the scientific audience is invited to bridge toward the discovery of new habitable planets. It is imperative to state that cosmic probes of this magnitude can be utilized as the starting nodes of the astrobiological search for galactic life. This research can also assist by acting as the navigation system for future space telescope launches through the delimitation of target exoplanets. The findings and the associated platforms can be harnessed as building blocks for the modeling of climate change on planet earth. The notion that if the human genus exhausts the resources of the planet earth or there is a bug of some sort that makes the earth inhabitable for humans explains the need to find an alternative planet to inhabit. The scientific community, through interdisciplinary discussions of the International Astronautical Federation so far, has the common position that engineers can reduce space mission costs by constructing a stable cis-lunar orbit infrastructure for refilling and carrying out other associated in-orbit servicing activities. Similarly, the Cis-Astro gateway can be envisaged as a budget optimization technique that models extra-solar bodies and can facilitate the scoping of future mission rendezvous. It should be registered as well that this broad and voluminous catalog of exoplanets shall be narrowed along the way using machine learning filters. The gist of this topic revolves around the indirect economic rationale of establishing a habitability scoping platform.

Keywords: exoplanets, habitability, machine-learning, supercomputing

Procedia PDF Downloads 117
4654 Transgressing Boundaries for Encouraging Critical Thinking: Reflections on the Integration of Active Pedagogy and Transnational Exchange into Social Work Education

Authors: Rosemary R. Carlton, Roxane Caron

Abstract:

Almost three decades ago, bell hooks (1994) identified the classroom as “the most radical space of possibility in the academy”. A feminist scholar, educator, and activist, hooks urged educators to transgress the boundaries of what might be customary or considered acceptable in teaching, thus encouraging the pursuit of new ways of knowing and different strategies for sharing knowledge. This paper reflects upon a particular response to hooks’ still relevant call for transgression in teaching. Specifically, this paper reports on the design, implementation, and preliminary analysis of a social work course integrating active pedagogy and transnational exchange to encourage students’ critical thinking and autonomous learning in their development as social workers in a global context. The bachelor’s level course, Pratiques spécifiques: Projet international, was developed collaboratively across three francophone institutions of higher learning in Belgium, Canada, and France: the Haute École de Namur-Liège-Luxembourg (Hénallux); the Université de Montréal; and, the Institut d’enseignement supérieur et professionnel, l’IRTS Paris Île-de-France. The driving aims of the course are to promote autonomous learning and critical thinking through a lens of transnational understandings of social problems -competencies indispensable to students’ development as social workers. The course is offered to two paired cohorts, one addressing the subject of “migrations” (Canada/France) and the other the subject of “sexual exploitation” (Canada/Belgium). Through the adaptation of a critical pedagogy of problem-based learning, students are called upon to actively engage in acquiring and applying knowledge to respond to “real life” social issues relating to migration or sexual exploitation. At the conclusion of the course, each cohort of students is brought together for a week-long intensive period of transnational exchange either at the Université de Montréal in Canada or at Hénallux in Belgium. Extending the bounds of the classroom across international borders allows students novel opportunities to deepen and expand their understandings of issues relating to predefined social issues and to critically examine associated social work practices. The paper opens with a presentation of the social work course. Specifically, the authors will outline their adaptation of a pedagogy of problem-based learning integrating transnational exchange in the design and implementation of the course. Returning to hooks’ notion of transgression in teaching, the paper offers a preliminary analysis of how and with what effect the course provides opportunities to transgress hierarchical student-teacher relationships; transgress conventional modes of learning to explore diverse sources of knowledge and transgress the walls of the university to engage with and learn from local and global partners. The paper concludes with a consideration of the potential influence of such transgressions in teaching for students’ development of critical thinking in their practice of social work in global context.

Keywords: active learning, critical pedagogy, social work intervention, transnational learning

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4653 The Impact of an Interactive E-Book on Mathematics Reading and Spatial Ability in Middle School Students

Authors: Abebayehu Yohannes, Hsiu-Ling Chen, Chiu-Chen Chang

Abstract:

Mathematics reading and spatial ability are important learning components in mathematics education. However, many students struggle to understand real-world problems and lack the spatial ability to form internal imagery. To cope with this problem, in this study, an interactive e-book was developed. The result indicated that both groups had a significant increase in the mathematics reading ability test, and a significant difference was observed in the overall mathematics reading score in favor of the experimental group. In addition, the interactive e-book learning mode had significant impacts on students’ spatial ability. It was also found that the richness of content with visual and interactive elements provided in the interactive e-book enhanced students’ satisfaction with the teaching material.

Keywords: interactive e-books, spatial ability, mathematics reading, satisfaction, three view

Procedia PDF Downloads 192
4652 Safety Validation of Black-Box Autonomous Systems: A Multi-Fidelity Reinforcement Learning Approach

Authors: Jared Beard, Ali Baheri

Abstract:

As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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4651 Family Income and Parental Behavior: Maternal Personality as a Moderator

Authors: Robert H. Bradley, Robert F. Corwyn

Abstract:

There is abundant research showing that socio-economic status is implicated in parenting. However, additional factors such as family context, parent personality, parenting history and child behavior also help determine how parents enact the role of caregiver. Each of these factors not only helps determine how a parent will act in a given situation, but each can serve to moderate the influence of the other factors. Personality has long been studied as a factor that influences parental behavior, but it has almost never been considered as a moderator of family contextual factors. For this study, relations between three maternal personality characteristics (agreeableness, extraversion, neuroticism) and four aspects of parenting (harshness, sensitivity, stimulation, learning materials) were examined when children were 6 months, 36 months, and 54 months old and again at 5th grade. Relations between these three aspects of personality and the overall home environment were also examined. A key concern was whether maternal personality characteristics moderated relations between household income and the four aspects of parenting and between household income and the overall home environment. The data for this study were taken from the NICHD Study of Early Child Care and Youth Development (NICHD SECCYD). The total sample consisted of 1364 families living in ten different sites in the United States. However, the samples analyzed included only those with complete data on all four parenting outcomes (i.e., sensitivity, harshness, stimulation, and provision of learning materials), income, maternal education and all three measures of personality (i.e., agreeableness, neuroticism, extraversion) at each age examined. Results from hierarchical regression analysis showed that mothers high in agreeableness were more likely to demonstrate sensitivity and stimulation as well as provide more learning materials to their children but were less likely to manifest harshness. Maternal agreeableness also consistently moderated the effects of low income on parental behavior. Mothers high in extraversion were more likely to provide stimulation and learning materials, with extraversion serving as a moderator of low income on both. By contrast, mothers high in neuroticism were less likely to demonstrate positive aspects of parenting and more likely to manifest negative aspects (e.g., harshness). Neuroticism also served to moderate the influence of low income on parenting, especially for stimulation and learning materials. The most consistent effects of parent personality were on the overall home environment, with significant main and interaction effects observed in 11 of the 12 models tested. These findings suggest that it may behoove professional who work with parents living in adverse circumstances to consider parental personality in helping to better target prevention or intervention efforts aimed at supporting parental efforts to act in ways that benefit children.

Keywords: home environment, household income, learning materials, personality, sensitivity, stimulation

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4650 A Study of Variables Affecting on a Quality Assessment of Mathematics Subject in Thailand by Using Value Added Analysis on TIMSS 2011

Authors: Ruangdech Sirikit

Abstract:

The purposes of this research were to study the variables affecting the quality assessment of mathematics subject in Thailand by using value-added analysis on TIMSS 2011. The data used in this research is the secondary data from the 2011 Trends in International Mathematics and Science Study (TIMSS), collected from 6,124 students in 172 schools from Thailand, studying only mathematics subjects. The data were based on 14 assessment tests of knowledge in mathematics. There were 3 steps of data analysis: 1) To analyze descriptive statistics 2) To estimate competency of students from the assessment of their mathematics proficiency by using MULTILOG program; 3) analyze value added in the model of quality assessment using Value-Added Model with Hierarchical Linear Modeling (HLM) and 2 levels of analysis. The research results were as follows: 1. Student level variables that had significant effects on the competency of students at .01 levels were Parental care, Resources at home, Enjoyment of learning mathematics and Extrinsic motivation in learning mathematics. Variable that had significant effects on the competency of students at .05 levels were Education of parents and self-confident in learning mathematics. 2. School level variable that had significant effects on competency of students at .01 levels was Extra large school. Variable that had significant effects on competency of students at .05 levels was medium school.

Keywords: quality assessment, value-added model, TIMSS, mathematics, Thailand

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4649 Develop a Conceptual Data Model of Geotechnical Risk Assessment in Underground Coal Mining Using a Cloud-Based Machine Learning Platform

Authors: Reza Mohammadzadeh

Abstract:

The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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4648 Road Condition Monitoring Using Built-in Vehicle Technology Data, Drones, and Deep Learning

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

Abstract:

Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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4647 Efficacy of Problem Solving Approach on the Achievement of Students in Mathematics

Authors: Akintunde O. Osibamowo, Abdulrasaq O. Olusanya

Abstract:

The present study was designed to examine the effect of problem-solving approach as a medium of instruction in teaching and learning of mathematics to improve the achievement of the student. One Hundred (100) students were randomly chosen from five (5) Junior Secondary School in Ijebu-Ode Local Government Area of Ogun State, Nigeria. The data was collected through Mathematics Achievement Test (MAT) on the two groups (experimental and control group). The study confirmed that there is a significant different in the achievement of students exposed to problem-solving approach than those not exposed. The result also indicated that male students, however, had a greater mean-score than the female with no significant difference in their achievement. The result of the study supports the use of problem-solving approach in the teaching and learning of mathematics in secondary schools.

Keywords: problem, achievement, teaching phases, experimental control

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4646 Online Delivery Approaches of Post Secondary Virtual Inclusive Media Education

Authors: Margot Whitfield, Andrea Ducent, Marie Catherine Rombaut, Katia Iassinovskaia, Deborah Fels

Abstract:

Learning how to create inclusive media, such as closed captioning (CC) and audio description (AD), in North America is restricted to the private sector, proprietary company-based training. We are delivering (through synchronous and asynchronous online learning) the first Canadian post-secondary, practice-based continuing education course package in inclusive media for broadcast production and processes. Despite the prevalence of CC and AD taught within the field of translation studies in Europe, North America has no comparable field of study. This novel approach to audio visual translation (AVT) education develops evidence-based methodology innovations, stemming from user study research with blind/low vision and Deaf/hard of hearing audiences for television and theatre, undertaken at Ryerson University. Knowledge outcomes from the courses include a) Understanding how CC/AD fit within disability/regulatory frameworks in Canada. b) Knowledge of how CC/AD could be employed in the initial stages of production development within broadcasting. c) Writing and/or speaking techniques designed for media. d) Hands-on practice in captioning re-speaking techniques and open source technologies, or in AD techniques. e) Understanding of audio production technologies and editing techniques. The case study of the curriculum development and deployment, involving first-time online course delivery from academic and practitioner-based instructors in introductory Captioning and Audio Description courses (CDIM 101 and 102), will compare two different instructors' approaches to learning design, including the ratio of synchronous and asynchronous classroom time and technological engagement tools on meeting software platform such as breakout rooms and polling. Student reception of these two different approaches will be analysed using qualitative thematic and quantitative survey analysis. Thus far, anecdotal conversations with students suggests that they prefer synchronous compared with asynchronous learning within our hands-on online course delivery method.

Keywords: inclusive media theory, broadcasting practices, AVT post secondary education, respeaking, audio description, learning design, virtual education

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4645 The Impact of the Flipped Classroom Instructional Model on MPharm Students in Two Pharmacy Schools in the UK

Authors: Mona Almanasef, Angel Chater, Jane Portlock

Abstract:

Introduction: A 'flipped classroom' uses technology to shift the traditional lecture outside the scheduled class time and uses the face-to-face time to engage students in interactive activities. Aim of the Study: Assess the feasibility, acceptability, and effectiveness of using the 'flipped classroom' teaching format with MPharm students in two pharmacy schools in the UK: UCL School of Pharmacy and the School of Pharmacy and Biomedical Sciences at University of Portsmouth. Methods: An experimental mixed methods design was employed, with final year MPharm students in two phases; 1) a qualitative study using focus groups, 2) a quasi-experiment measuring knowledge acquisition and satisfaction by delivering a session on rheumatoid arthritis, in two teaching formats: the flipped classroom and the traditional lecture. Results: The flipped classroom approach was preferred over the traditional lecture for delivering a pharmacy practice topic, and it was comparable or better than the traditional lecture with respect to knowledge acquisition. In addition, this teaching approach was found to overcome the perceived challenges of the traditional lecture method such as fast pace instructions, student disengagement and boredom due to lack of activities and/or social anxiety. However, high workload and difficult or new concepts could be barriers to pre-class preparation, and therefore successful flipped classroom. The flipped classroom encouraged learning scaffolding where students could benefit from application of knowledge, and interaction with peers and the lecturer, which might, in turn, facilitate learning consolidation and deep understanding. This research indicated that the flipped classroom was beneficial for all learning styles. Conclusion: Implementing the flipped classroom at both pharmacy institutions was successful and well received by final year MPharm students. Given the attention now being put on the Teaching Excellence Framework (TEF), understanding effective methods of teaching to enhance student achievement and satisfaction is now more valuable than ever.

Keywords: blended learning, flipped classroom, inverted classroom, pharmacy education

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4644 Critical Understanding on Equity and Access in Higher Education Engaging with Adult Learners and International Student in the Context of Globalisation

Authors: Jin-Hee Kim

Abstract:

The way that globalization distinguishes itself from the previous changes is scope and intensity of changes, which together affect many parts of a nation’s system. In this way, globalization has its relation with the concept of ‘internationalization’ in that a nation state formulates a set of strategies in many areas of its governance to actively react to it. In short, globalization is a ‘catalyst,’ and internationalization is a ‘response’. In this regard, the field of higher education is one of the representative cases that globalization has several consequences that change the terrain of national policy-making. Started and been dominated mainly by the Western world, it has now been expanded to the ‘late movers,’ such as Asia-Pacific countries. The case of internationalization of Korean higher education is, therefore, located in a unique place in this arena. Yet Korea still is one of the major countries of sending its students to the so-called, ‘first world.’ On the other hand, it has started its effort to recruit international students from the world to its higher education system. After new Millennium, particularly, internationalization of higher education has been launched in its full-scale and gradually been one of the important global policy agenda, striving in both ways by opening its turf to foreign educational service providers and recruiting prospective students from other countries. Particularly the latter, recruiting international students, has been highlighted under the government project named ‘Study Korea,’ launched in 2004. Not only global, but also local issues and motivations were based to launch this nationwide project. Bringing international students means various desirable economic outcomes such as reducing educational deficit as well as utilizing them in Korean industry after the completion of their study, to name a few. In addition, in a similar vein, Korea's higher education institutes have started to have a new comers of adult learners. When it comes to the questions regarding the quality and access of this new learning agency, the answer is quite tricky. This study will investigate the different dimension of education provision and learning process to empower diverse group regardless of nationality, race, class and gender in Korea. Listening to the voices of international students and adult learning as non-traditional participants in a changing Korean higher educational space not only benefit students themselves, but Korean stakeholders who should try to accommodate more comprehensive and fair educational provisions for more and more diversifying groups of learners.

Keywords: education equity, access, globalisation, international students, adult learning, learning support

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4643 Black-Box-Base Generic Perturbation Generation Method under Salient Graphs

Authors: Dingyang Hu, Dan Liu

Abstract:

DNN (Deep Neural Network) deep learning models are widely used in classification, prediction, and other task scenarios. To address the difficulties of generic adversarial perturbation generation for deep learning models under black-box conditions, a generic adversarial ingestion generation method based on a saliency map (CJsp) is proposed to obtain salient image regions by counting the factors that influence the input features of an image on the output results. This method can be understood as a saliency map attack algorithm to obtain false classification results by reducing the weights of salient feature points. Experiments also demonstrate that this method can obtain a high success rate of migration attacks and is a batch adversarial sample generation method.

Keywords: adversarial sample, gradient, probability, black box

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4642 A Developmental Study of the Flipped Classroom Approach on Students’ Learning in English Language Modules in British University in Egypt

Authors: A. T. Zaki

Abstract:

The flipped classroom approach as a mode of blended learning was formally introduced to students of the English language modules at the British University in Egypt (BUE) at the start of the academic year 2015/2016. This paper aims to study the impact of the flipped classroom approach after three semesters of implementation. It will restrict itself to the examination of students’ achievement rates, student satisfaction, and how different student cohorts have benefited differently from the flipped practice. The paper concludes with recommendations of how the experience can be further developed.

Keywords: achievement rates, developmental experience, Egypt, flipped classroom, higher education, student cohorts, student satisfaction

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4641 The Use of Self-Determination Theory to Assess the Opportunities and Challenges for Blended E-Learning in Egypt: An Analysis of the Motivations of Logistics Lecturers

Authors: Aisha Tarek Noour, Nick Hubbard

Abstract:

Blended e-Learning (BL) is proving to be an effective pedagogical tool in many areas of business and management education, but there remains a number of barriers to overcome before its implementation. This paper seeks to analyse the views of lecturers towards BL according to Self-Determination Theory (SDT), and identifies the opportunities and challenges for using BL in Logistics Education in an Egyptian higher education establishment. SDT is approached from a different perspective and the relationship between intrinsic motivation (IM), extrinsic motivation (EM), and amotivation (AM) is analysed and related to the opportunities and challenges of the BL method. The case study methodology comprises of a series of interviews with lecturers employed at three Colleges of International Transport and Logistics (CITLs) at the Arab Academy for Science, Technology, Maritime and Transport (AAST&MT) in Egypt. A structured face-to-face interview was undertaken with 61 interviewees across all faculty positions: Deans, Associate Professors, Assistant Professor, Department Heads, Part-time instructors, Teaching Assistants, and Graduate Teaching Assistants. The findings were based on "content analysis" of the interview transcripts and use of the NVivo10 software program. The research contributes to the application of SDT within the field of BL through an analysis of the views of lecturers towards the opportunities and challenges that BL offers to logistics educators in Egypt.

Keywords: intrinsic motivation, extrinsic motivation, amotivation, autonomy, competence, relatedness, self-determination theory and blended e-learning

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4640 Analyzing Healthy Eating Among Adolescent Teens Using the Socioecological Model

Authors: Kaavya Chandrasekar

Abstract:

Healthy eating is essential to maintain good health and stable mental status regardless of age. WHO describes that a healthy diet consists of incorporating more fruits and vegetables and reducing the consumption of sugary and salty foods into a regularly scheduled healthy diet. Although this attitude is rather uncommon among all age groups, it is notably uncommon among the teens being a very vulnerable state in a man’s life. Faulty dietary habits, in the long run, interfere with health, leading to obesity, cardiovascular diseases, and mental instability. This study collates a discussion on the barriers prevailing among adolescents, to inculcate healthy eating practices by means of the socioecological model. The studies consisted of teens aged 13 to 19 years from schools and colleges of both sexes. The socio-ecological model emphasizes the interplay and interconnectedness of elements at all levels of health behavior, acknowledging that the majority of public health issues are just too complicated to be solved from a single-level perspective. As a result, it necessitates that people are not considered in isolation from bigger social groups. According to the studies retrieved from ten articles studies conducted globally, more than five articles suggest that socioeconomic class, lack of adult supervision and easy access to fast food stores and schools affect their decision of healthy eating. Awareness via personalized intervention has been tried and found successful. Future research is still needed to address various dimensions of the issue.

Keywords: socio ecological model, healthy eating, adolescents, fast food consumption, interventions.

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4639 Decay Analysis of 118Xe* Nucleus Formed in 28Si Induced Reaction

Authors: Manoj K. Sharma, Neha Grover

Abstract:

Dynamical cluster decay model (DCM) is applied to study the decay mechanism of 118Xe* nucleus in reference to recent data on 28Si + 90Zr → 118Xe* reaction, as an extension of our previous work on the dynamics of 112Xe* nucleus. It is relevant to mention here that DCM is based on collective clusterization approach, where emission probability of different decay paths such as evaporation residue (ER), intermediate mass fragments (IMF) and fission etc. is worked out on parallel scale. Calculations have been done over a wide range of center of mass energies with Ec.m. = 65 - 92 MeV. The evaporation residue (ER) cross-sections of 118Xe* compound nucleus are fitted in reference to available data, using spherical and quadrupole (β2) deformed choice of decaying fragments within the optimum orientations approach. It may be noted that our calculated cross-sections find decent agreement with experimental data and hence provide an opportunity to analyze the exclusive role of deformations in view of fragmentation behavior of 118Xe* nucleus. The possible contribution of IMF fragments is worked out and an extensive effort is being made to analyze the role of excitation energy, angular momentum, diffuseness parameter and level density parameter to have better understanding of the decay patterns governed in the dynamics of 28Si + 90Zr → 118Xe* reaction.

Keywords: cross-sections, deformations, fragmentation, angular momentum

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4638 Blockchain-Based Assignment Management System

Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf,.doc,.ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: education technology, learning management system, decentralized applications, blockchain

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4637 Melanoma and Non-Melanoma, Skin Lesion Classification, Using a Deep Learning Model

Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

Abstract:

Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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4636 QTAIM View of Metal-Metal Bonding in Trinuclear Mixed-Metal Bridged Ligand Clusters Containing Ruthenium and Osmium

Authors: Nadia Ezzat Al-Kirbasee, Ahlam Hussein Hassan, Shatha Raheem Helal Alhimidi, Doaa Ezzat Al-Kirbasee, Muhsen Abood Muhsen Al-Ibadi

Abstract:

Through DFT/QTAIM calculations, we have provided new insights into the nature of the M-M, M-H, M-O, and M-C bonds of the (Cp*Ru)n(Cp*Os)3−n(μ3-O)2(μ-H)(Cp* = η5-C5Me5, n= 3,2,1,0). The topological analysis of the electron density reveals important details of the chemical bonding interactions in the clusters. Calculations confirm the absence of bond critical points (BCP) and the corresponding bond paths (BP) between Ru-Ru, Ru-Os, and Os-Os. The position of bridging hydrides and Oxo atoms coordinated to Ru-Ru, Ru-Os, and Os-Os determines the distribution of the electron densities and which strongly affects the formation of the bonds between these transition metal atoms. On the other hand, the results confirm that the four clusters contain a 6c–12e and 4c–2e bonding interaction delocalized over M3(μ-H)(μ-O)2 and M3(μ-H), respectively, as revealed by the non-negligible delocalization indexes calculations. The small values for electron density ρ(b) above zero, together with the small values, again above zero, for laplacian ∇2ρ(b) and the small negative values for total energy density H(b) are shown by the Ru-H, Os-H, Ru-O, and Os-O bonds in the four clusters are typical of open shell interactions. Also, the topological data for the bonds between Ru and Os atoms with the C atoms of the pentamethylcyclopentadienyl (Cp*) ring ligands are basically similar and show properties very consistent with open shell interactions in the QTAIM classification.

Keywords: metal-metal and metal-ligand interactions, organometallic complexes, topological analysis, DFT and QTAIM analyses

Procedia PDF Downloads 93