Search results for: activity learning

Authors: M. Van Zyl, M. H. A. Combrinck, E. J. Spamer

Abstract:

Due to the need for higher education in South Africa, the country experiences a rapid growth in open distance learning, especially in rural areas. It is difficult for people to enrol fulltime at contact universities, owing to work and financial constraints. The Unit for Open Distance Learning (UODL) at the North-West University (NWU), Potchefstroom campus, South Africa was established in 2013 with its main function to deliver open distance learning programmes to 30 000 students from the Faculties of Education Sciences, Theology and Health Sciences. With the use of interactive whiteboards (IWBs), the NWU and UODL are now able to deliver lectures to students concurrently at 60 regional open learning centres across Southern Africa as well as to an unlimited number of individuals with Internet access worldwide. Although IWBs are not new, our initiative is to use them more extensively in order to create more contact between lecturers and students. To be able to ensure and enhance quality education it is vital to determine students’ perceptions on the delivery of programmes by means of IWBs. Therefore, the aim of the study is to explore students’ perceptions for the use of IWBs in the delivery of programmes in terms of Moore’s Theory of Transactional Distance.

Keywords: interactive white board, open distance learning, technology, transactional learning

Procedia PDF Downloads 443

Authors: Ana Tsokilauri

Abstract:

The uppermost factor in the regulation of lignin-cellulose activity of decaying white rot or free rot are the substances serving as carbon and nitrogen nutrition of microorganisms and are considered as the most important factor of generative activity of white rot. The research object was Basidiomycete Fungi, peculiar and common in Georgia, and the separation of 10 of them as pure crops. The unidentified pure crops have tasted in order to be determined the potential of synthesis of lignin-degrading enzymes and the substrate of optimal lignocellulose growth. One of the most important aspects of the research conducted on Basidiomycetes was the use of specific lignocellulosic residues for selecting Fungi as a substrate of their growth. In order to increase lignocellulose with the help of substrate, crops were selected from the screening stage that showed good laccase activity. (Dusheti 1; Dusheti 10; Fshavi 5; Fshavi1; Fshavi 8; Fshavi 32; Manglisi 26; Sabaduri20; Dusheti 7; Sabaduri 1 ), Among the selected cultures, the crops with good laccase activity against the following substances, in particular: Dusheti 1- in this case, the rate of enzymatic activity on bran substrate was -105,6 u/ml, mandarin-96,4 u/ml. In case of corn - 102,9 u/ml. In case of Dusheti 7- the indicators were as follows: bananas-121,7 u/ml, mandarin-125,4 u/ml, corn - 117,1 u/ml. In the case of Sanaduri 32, the laccase activity was as follows: pomegranate- 101,2 u/ml. As a result of conducted experiments, the synthesis and activity rates of enzymes depending on plant substrates varied within a fairly wide range, which is still being under research.

Keywords: Lignocellulosic substrate, Basidiomycetes, white-rot basidiomycetes, Laccase

Procedia PDF Downloads 180

Authors: Omaimah Algohary

Abstract:

Kaolin is one of the principle intestinal adsorbents, has traditionally been used internally in the treatment of various enteric disorders, colitis, enteritis, dysentery, and diarrhea associated with food and alkaloidal poisoning and in traveler’s diarrhea. It binds to and traps bacteria and its toxins and gases in the gut. It also binds to water in the gut, which helps to make the stools firmer, hence giving symptomatic relief. Metronidazole is a synthetic antibacterial agent that is used primarily in the treatment of various anaerobic infections such as intra-abdominal infections, antiprotozoal, and as amebicidal. The need for safe, therapeutically effective antidiarrheal combination continuously lead to effective treatment. Metronidazol used for treatment of anaerobic bacteria and kaolin , when administered simultaneously, Metronidazole–Kaolin interactions have been reported by FDA but not studied. This project is the first to study the effect of Metronidazole–Kaolin interactions on the antimicrobial activity of metronidazole. Agar diffusion method performed to test the antimicrobial activity of metronidazole–kaolin antidiarrheal combination from aqueous solutions at an in-vivo simulated pHs conditions that obtained at 37+0.5 °C on Helicobacter pylori as anaerobic bacteria and E.coli as aerobic bacteria and used as a control for the technique. The antimicrobial activity of metronidazole combination as 1:1 and 1:2 with kaolin was abolished in acidic media as no zones of inhibition shown compared to only metronidazole that used as a control. In alkaline media metronidazole combination as 1:1 and 1:2 with kaolin showed diminutive activity compared to the control. These results proved that the kaolin adsorb metronidazole and abolish its antimicrobial activity and such combination should be avoided.

Keywords: kaolin, metronidazole, interaction, Helicobacter pylori. E. coli, antimicrobial activity

Procedia PDF Downloads 371

Authors: Ananya Gangavarapu

Abstract:

Convolutional Neural Networks (CNN) based models are providing diagnostic capabilities on par with the medical specialists in many specialty areas. However, collecting the medical data for training purposes is very challenging because of the increased regulations around data collections and privacy concerns around personal health data. The gathering of the data becomes even more difficult if the capture devices are edge-based mobile devices (like smartphones) with feeble wireless connectivity in rural/remote areas. In this paper, I would like to highlight Federated Learning approach to mitigate data privacy and security issues.

Keywords: deep learning in healthcare, data privacy, federated learning, training in distributed environment

Procedia PDF Downloads 124

Authors: Tri Pratiwi, Sufyarma Marsidin, Hermawati Syarif, Yahya

Abstract:

The 21st-century skills being highly promoted today are Creativity and Innovation, Critical Thinking and Problem Solving, Communication and Collaboration. Communication Skill is one of the essential skills that should be mastered by the students. To master Communication Skills, students must first master their Language Skills. Language Skills is one of the main supporting factors in improving Communication Skills of a person because by learning Language Skills students are considered capable of communicating well and correctly so that the message or how to deliver the message to the listener can be conveyed clearly and easily understood. However, it cannot be denied that English output or learning outcomes which are less optimal is the problem which is frequently found in the implementation of the learning process. This research aimed to improve students’ language skills by developing learning model in English subject for VIII graders of SMP N 1 Uram Jaya through Directed-Project Based Learning (DPjBL) implementation. This study is designed in Research and Development (R & D) using ADDIE model development. The researcher collected data through observation, questionnaire, interview, test, and documentation which were then analyzed qualitatively and quantitatively. The results showed that DPjBL is effective to use, it is seen from the difference in value between the pretest and posttest of the control class and the experimental class. From the results of a questionnaire filled in general, the students and teachers agreed to DPjBL learning model. This learning model can increase the students' English achievement.

Keywords: language skills, learning model, Directed-Project Based Learning (DPjBL), English achievement

Procedia PDF Downloads 153

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 220

Authors: Heidarali Malmir

Abstract:

The effects of acid rain (AR), smog’s cars (SC), and combined AR+SC on the antioxidants enzymes, lipid-soluble antioxidants, and water-soluble antioxidants were studied in the two cultivars of rice. The results showed that simulated AR significantly increased the total glutathione (TGSH), thiobarbituric acid (TBA), and α-tocopherol, accompanied by decreases in dry weight and leaves area in the two cultivars, and this change was more obvious in Shirudi cultivar than in Aus cultivar (p≤0.05). Under SC stress cultivar shirudi had higher H+-ATPase, glutathione peroxidase (GSH-px), and catalase (CAT) activities than cultivar Aus. The results of superoxide dismutase (SOD) activity, TGSH, and α-tocopherol levels affected by AR treatments were very different to those of SOD activity, TGSH, and α-tocopherol levels, as shown in SC treatment. It seems that SOD activity coupled with the water-soluble antioxidants and α-tocopherol levels correlated with the lipid-soluble antioxidants. It is suggested that α-tocopherol increases H+-ATPase activity.

Keywords: H+-ATPase, membrane permeability, lipid soluble antioxidants, water soluble antioxidants, associated enzyme

Procedia PDF Downloads 63

Authors: Toktam Khatibi

Abstract:

Self-supervised learning (SSL) includes machine learning models that are trained on one aspect and/or one part of the input to learn other aspects and/or part of it. SSL models are divided into two different categories, including pre-text task-based models and contrastive learning ones. Pre-text tasks are some auxiliary tasks learning pseudo-labels, and the trained models are further fine-tuned for downstream tasks. However, one important disadvantage of SSL using pre-text task solving is defining an appropriate pre-text task for each image dataset with a variety of image modalities. Therefore, it is required to design an appropriate pretext task automatically for each dataset and each downstream task. To the best of our knowledge, the automatic designing of pretext tasks for image analysis has not been considered yet. In this paper, we present a framework based on In-context learning that describes each task based on its input and output data using a pre-trained image transformer. Our proposed method combines the input image and its learned description for optimizing the pre-text task design and its hyper-parameters using Meta-learning models. The representations learned from the pre-text tasks are fine-tuned for solving the downstream tasks. We demonstrate that our proposed framework outperforms the compared ones on unseen tasks and image modalities in addition to its superior performance for previously known tasks and datasets.

Keywords: in-context learning (ICL), meta learning, self-supervised learning (SSL), vision-language domain, transformers

Procedia PDF Downloads 60

Authors: Fatiha Guessabi

Abstract:

Students of the Tahri Muhammed University of Bechar shifted to the virtual platform using E-learning platforms when the lockdown started due to the Coronavirus. This paper aims to explore the advantages and inconveniences of online learning and teaching in EFL classes at Tahri Mohammed University. For this investigation, a questionnaire was addressed to EFL students and an interview was arranged with EFL teachers. Data analysis was obtained from 09 teachers and 70 students. After the investigation, the results show that some of the most applied educational technologies and applications are used to turn online EFL classes effectively exciting. Thus, EFL classes became more interactive. Although learners give positive viewpoints about online learning/teaching, they prefer to learn in the classroom.

Keywords: advantages, disadvantages, COVID19, EFL, online learning/teaching, university of Bechar

Procedia PDF Downloads 150

Authors: Habibollah Mashhady, Behruz Lotfi, Mohammad Doosti, Moslem Fatollahi

Abstract:

An exploration of the related literature reveals that all instruction methods aim at training autonomous learners. After the turn of second language pedagogy toward learner-oriented strategies, learners’ needs were more focused. Yet; the historical, social and political aspects of learning were still neglected. The present study investigates the notion of autonomous learning and explains its various facets from a pedagogical point of view. Furthermore; different elements, fields and scopes of autonomous learning will be explored. After exploring different aspects of autonomy, it is postulated that liberatory autonomy is highlighted since it not only covers social autonomy but also reveals learners’ capabilities and human potentials. It is also recommended that learners consider different elements of autonomy such as motivation, knowledge, confidence, and skills.

Keywords: critical pedagogy, social autonomy, academic learning, cultural notions

Procedia PDF Downloads 447

Authors: Simon Ibor Akpama

Abstract:

The study investigated the extent to which innovative teaching-learning techniques can influence and attenuate learning difficulties among adult learners participating in different literacy education programmes in Calabar Metropolis, Cross River State, Nigeria. A quasi-experimental design was adopted to collect data from a sample size of 150 participants of the programme. The sample was drawn using the simple random sampling method. As an experimental study, the 150 participants were divided into two equal groups –the first was the experimental group while the second was the control. A pre-test was administered to the two groups which were later exposed to a post-test after treatment. Two instruments were used for data collection. The first was the guide for the Literacy Learning Difficulties Inventory (LLDI). Three hypotheses were postulated and tested as .05 level of significance using Analysis of Covariance (ANOVA) test statistics. Results of the analysis firstly showed that the two groups (treatment and control) did not differ in the pre-test regarding their literacy learning difficulties. Secondly, the result showed that for each hypothesis, innovative teaching-learning techniques significantly influenced adult learners’ (participants) literacy learning difficulties. Based on these findings, the study recommends the use of innovative teaching-learning techniques in adult literacy education centres to mitigate the learning difficulties of adult learners in literacy education programmes in Calabar Metropolis.

Keywords: teaching, learning, techniques, innovative, difficulties, programme

Procedia PDF Downloads 109

Authors: Vesa Salminen, Esa Santakallio, Heikki Ruohomaa

Abstract:

Introduction: The city of Riihimäki has decided robotics on well-being, service and industry as the main focus area on their ecosystem strategy. Robotics is going to be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, also education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The objective of this activity has been to develop education continuity from diaper age to doctorate. The main target of the development activity is to create a unique robotics study entity that enables ongoing robotics studies from preprimary education to university. The aim is also to attract students internationally and supply a skilled workforce to the private sector, capable of the challenges of the future. Methodology: Education instances (high school, second grade, Universities on all levels) in a large area of Tavastia Province have gradually directed their education programs to support this goal. On the other hand, applied research projects have been created to make proof of concept- phases on areal real environment field labs to test technology opportunities and digitalization to change business processes by applying robotic solutions. Customer-oriented applied research projects offer for students in robotics education learning environments to learn new knowledge and content. That is also a learning environment for education programs to adapt and co-evolution. New content and problem-based learning are used in future education modules. Major findings: Joint robotics education entity is being developed in cooperation with the city of Riihimäki (primary education), Syria Education (secondary education) and HAMK (bachelor and master education). The education modules have been developed to enable smooth transitioning from one institute to another. This article is introduced a case study of the change of education of wellbeing education because of digitalization and robotics. Riihimäki's Elderly citizen's service house, Riihikoti, has been working as a field lab for proof-of-concept phases on testing technology opportunities. According to successful case studies also education programs on various levels of education have been changing. Riihikoti has been developed as a physical learning environment for home care and robotics, investigating and developing a variety of digital devices and service opportunities and experimenting and learn the use of equipment. The environment enables the co-development of digital service capabilities in the authentic environment for all interested groups in transdisciplinary cooperation.

Keywords: ecosystem strategy, digitalization and robotics, education continuity, learning environment, transdisciplinary co-operation

Procedia PDF Downloads 159

Authors: Sarit Rashkovits, Anat Drach- Zahavy

Abstract:

The research considers the unresolved question regarding the link between nursing team accountability and team learning and the resulted team performance in nursing teams. Empirical findings reveal disappointing evidence regarding improvement in healthcare safety and quality. Therefore, there is a need in advancing managerial knowledge regarding the factors that enhance constant healthcare teams' proactive improvement efforts, meaning team learning. We first aim to identify the organizational resources that are needed for team learning in nursing teams; second, to test the moderating role of nursing teams' learning resources in the team accountability-team learning link; and third, to test the moderated mediation model suggesting that nursing teams' accountability affects team performance by enhancing team learning when relevant resources are available to the team. We point on the intervening role of three team learning resources, namely time availability, team autonomy and performance data on the relation between team accountability and team learning and test the proposed moderated mediation model on 44 nursing teams (462 nurses and 44 nursing managers). The results showed that, as was expected, there was a positive significant link between team accountability and team learning and the subsequent team performance when time availability and team autonomy were high rather than low. Nevertheless, the positive team accountability- team learning link was significant when team performance feedback was low rather than high. Accordingly, there was a positive mediated effect of team accountability on team performance via team learning when either time availability or team autonomy were high and the availability of team performance data was low. Nevertheless, this mediated effect was negative when time availability and team autonomy were low and the availability of team performance data was high. We conclude that nurturing team accountability is not enough for achieving nursing teams' learning and the subsequent improved team performance. Rather there is need to provide nursing teams with adequate time, autonomy, and be cautious with performance feedback, as the latter may motivate nursing teams to repeat routine work strategies rather than explore improved ones.

Keywords: nursing teams' accountability, nursing teams' learning, performance feedback, teams' autonomy

Procedia PDF Downloads 247

Authors: Kanokrat Kunasaraphan

Abstract:

The purpose of the study was to identify whether English language learning strategies commonly used by the first year students at International College, Suan Sunandha Rajabhat University include six direct and indirect strategies. The study served to explore whether there was a difference in these students’ use of six direct and indirect English learning strategies between the different levels of their English proficiency. The questionnaire used as a research instrument was comprised of two parts: General information of participants and the Strategy Inventory for Language Learning (SILL). The researcher employed descriptive statistics and one-way ANOVA (F-test) to analyze the data. The results of the analysis revealed that English learning strategies commonly used by the first year students include six direct and indirect strategies, including differences in strategy use of the students with different levels of English proficiency. Recommendations for future research include the study of language learning strategy use with other research methods focusing on other languages, specific language skills, and/or the relationship of language learning strategy use and other factors in other programs and/or institutions.

Keywords: English learning strategies, direct strategies, indirect strategies, proficiency level

Procedia PDF Downloads 291

Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

Abstract:

Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

Procedia PDF Downloads 172

Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

Abstract:

This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

Procedia PDF Downloads 239

Authors: Phongkon Weerpiput

Abstract:

This research study aimed to compare learning achievement between Jigsaw I and jigsaw IV techniques. The target group was 70 Thai major sophomores enrolled in a course entitled Foreign Language in Thai at the Faculty of Education, Suan Sunandha Rajabhat University. The research methodology was quasi-experimental design. A control group was given the Jigsaw I technique while an experimental group experienced the Jigsaw IV technique. The treatment content focused on Khmer loanwords in Thai language executed for a period of 3 hours per week for total of 3 weeks. The instruments included learning management plans and multiple-choice test items. The result yields no significant difference at level .05 between learning achievement of both techniques.

Keywords: Jigsaw I technique, Jigsaw IV technique, learning achievement, major sophomores

Procedia PDF Downloads 267

Authors: Amira Kalifa, Faïek Errouissi

Abstract:

The seasonal changes and the daily activity of Stomoxys calcitrans (Diptera: Muscidae) were examined, using Vavoua traps, in a dairy cattle farm in Zaouiet Sousse, the Sahel area of Tunisia during May 2014 to October 2014. Over this period, a total of 4366 hematophagous diptera were captured and Stomoxys calcitrans was the most commonly trapped species (96.52%). Analysis of the seasonal activity, showed that S.calcitrans is bivoltine, with two peaks: a significant peak is recorded in May-June, during the dry season, and a second peak at the end of October, which is quite weak. This seasonal pattern would depend on climatic factors, particularly the temperature of the manure and that of the air. The activity pattern of Stomoxys calcitrans was diurnal with seasonal variations. The daily rhythm shows a peak between 11:00 am to 15:00 pm in May and between 11:00 am to 17:00 pm in June. These vector flies are important pests of livestock in Tunisia, where they are known as a mechanical vector of several pathogens and have a considerable economic and health impact on livestock. A better knowledge of their ecology is a prerequisite for more efficient control measures.

Keywords: cattle farm, daily rhythm, Stomoxys calcitrans, seasonal activity

Procedia PDF Downloads 255

Authors: Oluwatofunmi Otobo

Abstract:

This paper presents a review of the challenges of e-learning and e-learning technologies in tertiary institutions. This review is based on the researchers observations of the challenges of making use of ICT for learning in Nigeria using Adeyemi College of Education as a case study; this is in comparison to tertiary institutions in the UK, US and other more developed countries. In Nigeria and probably Africa as a whole, power is the major challenge. Its inconsistency and fluctuations pose the greatest challenge to making use of online education inside and outside the classroom. Internet and its supporting infrastructures in many places in Nigeria are slow and unreliable. This, in turn, could frustrate any attempt at making use of online education and e-learning technologies. Lack of basic knowledge of computer, its technologies and facilities could also prove to be a challenge as many young people up until now are yet to be computer literate. Personal interest on both the parts of lecturers and students is also a challenge. Many people are not interested in learning how to make use of technologies. This makes them resistant to changing from the ancient methods of doing things. These and others were reviewed by this paper, suggestions, and recommendations were proffered.

Keywords: education, e-learning, Nigeria, tertiary institutions

Procedia PDF Downloads 180

Authors: I. Hua Chu, Hsiang-Chi Yu, Hsuan Su

Abstract:

Purpose: To examine the associations between self-determined motivation and physical activity in patients with coronary heart disease (CHD) in a longitudinal study. Methods: Patients with CHD were recruited for this study. Their motivations for exercise were measured by the Behavioral Regulation in Exercise Questionnaire-2 (BREQ-2). Physical activity was assessed using the 7-day physical activity recall questionnaire. Duration and energy expenditure of moderate to vigorous physical activity (MVPA) were used in data analysis. All outcome measures were assessed at baseline and 12 months follow up. Data were analyzed using Pearson correlation analysis and regression analysis. Results: The results of the 45 participants (mean age 60.24 yr; 90.2% male) revealed that there were significant negative correlations between amotivation at baseline and duration (r=-.295, p=.049) and energy expenditure (r=-.300, p=.045) of MVPA at 12 months. In contrast, there were significant positive correlations between calculated relative autonomy index (RAI) at baseline and duration (r=.377, p=.011) and energy expenditure (r=.382, p=.010) of MVPA at 12 months. There was no significant correlation between other subscales of the BREQ-2 and duration or energy expenditure of MVPA. Regression analyses revealed that RAI was a significant predictor of duration (p=.011) and energy expenditure (p=.010) of MVPA at 12 months follow-up. Conclusions: These results suggest that the relative degree of self-determined motivation could predict long-term MVPA behaviors in CHD patients. Physical activity interventions are recommended to target enhancing one’s identified and intrinsic motivation to increase the likelihood of physical activity participation in this population.

Keywords: self-determined motivation, physical activity, coronary heart disease, relative autonomy index (RAI)

Procedia PDF Downloads 416

Authors: Syed Ahmed Hasnain

Abstract:

Instructors’ perception of blended learning plays an important role in the field of education. The literature review shows that there is a gap in research. Instructor perception of the blended learning approach has an impact on the motivation of the instructor to use technology in the classroom. The role of the student's perspective on the instructor’s perception is also important. Research also shows that instructor perceptions can be changed based on their past and present experiences with technology and blended learning. This paper draws the attention of the readers to the need for further research and contributions to studying instructor perceptions globally. Instructor perception affects the implementation of technology in the classroom, instructor-student relationship, and the class environment. Various publications, literature reviews, and articles are studied to show the importance of instructor perceptions. A lot of work has been published on student perceptions of the blended learning approach but there is a gap in research on instructor perceptions. The paper also makes recommendations for further research in the area of instructor perceptions of the blended learning approach. Institutions, administrators, senior management, and instructors can benefit from this paper.

Keywords: blended learning, education, literature review, instructor perceptions

Procedia PDF Downloads 89

Authors: Martín Pratto Burgos

Abstract:

The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

Procedia PDF Downloads 69

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

Abstract:

Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

Procedia PDF Downloads 159

Authors: Ogbonnaya Nwokoro, Florence O. Anya

Abstract:

Nutritional factors relating to the production of linamarase from Lactobacillus delbrueckii NRRL B–763 were investigated. The microorganism was cultivated in a medium containing 1% linamarin. Enzyme was produced using a variety of carbon substrates but the highest enzyme activity was detected in the presence of salicin (522 U/ml) after 48 h while the lowest yield was observed with CM cellulose (38 U/ml) after 72 h. Enzyme was not produced in the presence of cellobiose. Among a variety of nitrogen substrates tested, peptone supported maximum enzyme production (412 U/ml) after 48 h. Lowest enzyme production was observed with urea (40 U/ml). Organic nitrogen substrates generally supported higher enzyme productivity than inorganic nitrogen substrates. Enzyme activity was observed in the presence of Mn2+ (% relative activity = 216) while Hg2+ was inhibitory (% relative activity = 28). Locally-formulated media were comparable to MRS broth in supporting linamarase production by the bacterium. Higher enzyme activity was produced in media with surfactant than in media without surfactant. The enzyme may be useful in enhanced degradation of cassava cyanide.

Keywords: linamarase, locally formulated media, carbon substrates, nitrogen substrates, metal ions

Procedia PDF Downloads 418

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

Abstract:

Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

Procedia PDF Downloads 244

Authors: Laref Nora, Guessas Bettache

Abstract:

Lactic acid bacteria (LAB) have a major potential to be used in biopreservation methods because they are safe to consume (GRAS: generally regarded as safe) and they naturally occurring microflora of many foods. The preservative action of LAB is due to several antimicrobial metabolites, including lactic acid, acetic acid, hydrogen peroxide, bacteriocins, carbon dioxide, diacetyl, and reuterin. Several studies have focused on the antifungal activity compounds from natural sources for biopreservation in alternatives to chemical use. LAB has an antifungal activity which may inhibit food spoilage fungi. Lactobacillus strains isolated from silage prepared in our laboratory by fermentation of grass in anaerobic condition were screened for antifungal activity with overlay assay against Aspergillus spp. The antifungal compounds were originated from organic acids; inhibitory activity did not change after treatment with proteolytic enzymes. Lactobacillus strains were able also to inhibit Trichoderma spp, Penicillium spp, Fusarium roseum, and Stemphylim spp by confrontation assay. The inhibitory activity could be detected against the mould Aspergillus spp in the apricot juice but not in a bakery product. These antifungal compounds have the potential to be used as food biopreservation to inhibit conidia germination, and mycelia growth of spoilage fungi depending on food type, pH of food especially in heat, and cold processed foods.

Keywords: lactic acid bacteria, Lactobacillus, Aspergillus, antifungal activity

Procedia PDF Downloads 311

Authors: Hussah M. AlShayea

Abstract:

This study aimed to identify the potential of cloud computing, "Google Drive" in overcoming the problems of collective learning from the viewpoint of Princess Noura University students. The study included (92) students from the College of Education. To achieve the goal of the study, several steps have been taken. First, the most important problems of collective learning were identified from the viewpoint of the students. After that, a survey identifying the potential of cloud computing "Google Drive" in overcoming the problems of collective learning was distributed among the students. The study results showed that the students believe that the use of Google Drive contributed to overcoming these problems. In the light of those results, the researcher presented a set of recommendations and proposals, including: encouraging teachers and learners to employ cloud computing to overcome the problems and constraints of collective learning.

Keywords: cloud computing, collective learning, Google drive, Princess Noura University

Procedia PDF Downloads 473

Authors: Kennedy Efosa Ehimwenma, Sujatha Krishnamoorthy, Safiya Al‑Sharji

Abstract:

The probability computation of events is in the interval of [0, 1], which are values that are determined by the number of outcomes of events in a sample space S. The probability Pr(A) that an event A will never occur is 0. The probability Pr(B) that event B will certainly occur is 1. This makes both events A and B a certainty. Furthermore, the sum of probabilities Pr(E₁) + Pr(E₂) + … + Pr(Eₙ) of a finite set of events in a given sample space S equals 1. Conversely, the difference of the sum of two probabilities that will certainly occur is 0. This paper first discusses Bayes, the complement of probability, and the difference of probability for occurrences of learning-events before applying them in the prediction of learning objects in student learning. Given the sum of 1; to make a recommendation for student learning, this paper proposes that the difference of argMaxPr(S) and the probability of student-performance quantifies the weight of learning objects for students. Using a dataset of skill-set, the computational procedure demonstrates i) the probability of skill-set events that have occurred that would lead to higher-level learning; ii) the probability of the events that have not occurred that requires subject-matter relearning; iii) accuracy of the decision tree in the prediction of student performance into class labels and iv) information entropy about skill-set data and its implication on student cognitive performance and recommendation of learning.

Keywords: complement of probability, Bayes’ rule, prediction, pre-assessments, computational education, information theory

Procedia PDF Downloads 142

Authors: Raziel Felix-Aguelo

Abstract:

Language competencies refer to the knowledge and abilities to use English in four inter-related skills: Speaking, listening, reading, and writing. Cooperative learning is a type of instruction where learners are grouped together to work on an assignment, project, or task. To become competent in second language, one needs to actively use English in each of four modalities. Learning English is challenging to second language learners. Sometimes, some students feel demotivated and scared to use English during class discussions and recitations. This paper explores the students’ attitude and perception towards cooperative learning in enhancing their language competencies. The primary method for this research is case study. Thirty-two grade 9 students within a single selected class are used as sample. The instruments used in data collection were questionnaire and semi-structured interviews. The finding shows that collaborative learning activities enhance the four skills of the students. The participants consider this approach motivational as they engage and interact with others. This indicates that students develop their language competencies as they rely to one another in doing meaningful language activities.

Keywords: language competencies, collaborative learning, motivation, language activities

Procedia PDF Downloads 325

Authors: Rini Jarial, Puranjan Mishra, Lakhveer Singh, Sveta Thakur, A. W. Zularisam, Mimi Sakinah

Abstract:

The aim of the present study was to assess the biological properties of Camellia sinensis and to identify its functional compounds. The methanolic leaves-extract (MLE) of commercial green tea (Camellia sinensis) was assessed for anti-bacterial activities by measuring inhibition zones against a panel of pathogenic bacterial strains using agar diffusion method. The flavonoid (5.0 to 8.0 mg/ml) and protein content (10 to 15 mg/ml) of the MLE were recorded. MLE at a concentration of 25 μg/ml showed marked anti-bacterial activity against all bacterial strains (11-30 mm zone of inhibition) and was maximum against Staphylococcus aureus (30 mm). The MLE of Camellia sinensis had the best MIC values of 2.25 and 0.56 mg/ml against S. aureus and Enterobacter sp., respectively. The MLE also possessed good anti-lipolytic activity (65%) against a Porcine pancreatic lipase (PPL) and cholesterol oxidase inhibition (79%). The present study provided strong experimental evidences that the MLE of Camellia sinensis is not only a potent source of natural anti-oxidants and anti-bacterial activity but also possesses efficient cholesterol degradation and anti-lipolytic activities that might be beneficial in the body weight management.

Keywords: anti-oxidant, anti-bacterial activity, anti-lipolytic activity, Camellia sinensis, phyto-chemicals

Procedia PDF Downloads 272