Search results for: learning networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9350

Search results for: learning networks

8390 FPGA Implementation of Adaptive Clock Recovery for TDMoIP Systems

Authors: Semih Demir, Anil Celebi

Abstract:

Circuit switched networks widely used until the end of the 20th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization

Procedia PDF Downloads 278
8389 MOOCs (E-Learning) Project Personnel Competency Analysis

Authors: Shang-Hua Wu, Rong-Chi Chang, Horng–Twu Liaw

Abstract:

Nowadays, competencies of e-learning project personnel are very important in assisting them in offering courses, serving students in an effective way, leveraging advantages, strengthen their relationships with potential students, etc. among e-learning platforms, MOOCs has recently attracted increasing focuses in distance education since it can be conducted for a large numbers of virtual learners. Nonetheless, since MOOCs is a relatively new e-learning platform, top concerns have been paid to what competencies are important for e-learning personnel to consider. Taking this need, this research aimed to carry out an in-depth exploration of competency requirements of MOOCs (e-learning) project personnel in Taiwan vocational schools. Data were collected through thorough literature reviews and discussions and competency analysis was carried out using Delphi technique questionnaires. The results show that that MOOCs (e-learning) project personnel’ professional competency lie in three main dimensions, among which ‘demand analysis competency’ (i.e., containing 10 major competences and 48 subordinate capabilities) is the most important competency, followed by ‘project management competency’ (i.e., comprising 6 major competences and 31 secondary capabilities), and finally ‘digital content production competency’ (i.e., including 12 major competences and 79 secondary capabilities). As such, in Taiwan context with different organizational scales and market sizes, the e-learning competency items and unique experience/ achievements throughout the promotion process obtained in this research will provide useful references for academic institutions in promoting e-learning.

Keywords: competency analysis, Delphi technique questionnaire, e-learning, massive open online courses

Procedia PDF Downloads 285
8388 Development of Electroencephalograph Collection System in Language-Learning Self-Study System That Can Detect Learning State of the Learner

Authors: Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

Abstract:

This research aims to develop a self-study system equipped with an artificial teacher who gives advice to students by detecting the learners and to evaluate language learning in a unified framework. 'Detecting the learners' means that the system understands the learners' learning conditions, such as each learner’s degree of understanding, the difference in each learner’s thinking process, the degree of concentration or boredom in learning, and problem solving for each learner, which can be interpreted from learning behavior. In this paper, we propose a system to efficiently collect brain waves from learners by focusing on only the brain waves among the biological information for 'detecting the learners'. The conventional Electroencephalograph (EEG) measurement method during learning using a simple EEG has the following disadvantages. (1) The start and end of EEG measurement must be done manually by the experiment participant or staff. (2) Even when the EEG signal is weak, it may not be noticed, and the data may not be obtained. (3) Since the acquired EEG data is stored in each PC, there is a possibility that the time of data acquisition will be different in each PC. This time, we developed a system to collect brain wave data on the server side. This system overcame the above disadvantages.

Keywords: artificial teacher, e-learning, self-study system, simple EEG

Procedia PDF Downloads 145
8387 Remote Learning During Pandemic: Malaysian Classroom

Authors: Hema Vanita Kesevan

Abstract:

The global spread of Covid-19 virus in early 2020 has led to major changes in many walks of life, including the education system. Traditional face to face lessons that were carried out for years has been replaced by online learning. Although online learning has been used before the pandemic, it has not been the only source of teaching and learning. This drastic change has brought significant impact to the process of teaching and learning in many classrooms around the world. Likewise, in country like Malaysia that that has been promoting online learning but has not utilize it fully due to many restrictions in terms of technology, accessibility, and online literacy, the sudden change to full online platform learning in all educational sector has definitely caused Issues in terms of its adaptation and usage. Although many studies have been conducted to explore the efficiency and impact of online learning during the pandemic, studies focusing on the same are limited in Malaysian classroom context, especially in English language classrooms. Thus, this study seeks to explore on the efficacy and effectiveness of online learning tools in ESL classroom contexts during the pandemic. The aim of this study is to understand the educator's and student's perceptions on the implementation of online learning tools in the teaching and learning process and the types of online learning tools that were used to assist the teaching and learning process during the pandemic. Particularly, this study focused to explore the types of online learning tools used in Malaysian schools and university during the online teaching and learning process and further explores how the various types of tools used impacted the students' participation in the lessons conducted. The participants of this study are secondary school students, teachers, and university students. Data will be collected in terms of survey questionnaire and interviews. The survey data intends to obtain information on the types of online learning used in ESL teaching and learning practices during the pandemic, how the various types of online tools influence students' participation during lessons. The interview data from the teachers serves to provide information about the selection of online learning tools, challenges of using it to conduct online lessons, and other arising issues. A mixed method design will be used to analysed the data obtained. The questionnaire will be analysed quantitatively using descriptive analysis meanwhile, the interview data will be analysed qualitatively.

Keywords: Covid 19, online learning tools, ESL classroom, effectiveness, efficacy

Procedia PDF Downloads 236
8386 Artificial Neural Networks with Decision Trees for Diagnosis Issues

Authors: Y. Kourd, D. Lefebvre, N. Guersi

Abstract:

This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

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8385 Effectiveness of Blended Learning in Public School During Covid-19: A Way Forward

Authors: Sumaira Taj

Abstract:

Blended learning is emerged as a prerequisite approach for teaching in all schools after the outbreak of the COVID-19 pandemic. However, how much public elementary and secondary schools in Pakistan are ready for adapting this approach and what should be done to prepare schools and students for blended learning are the questions that this paper attempts to answer. Mixed-method research methodology was used to collect data from 40 teachers, 500 students, and 10 mothers. Descriptive statistics was used to analyze quantitative data. As for as readiness is concerned, schools lack resources for blended/ virtual/ online classes from infra-structure to skills, parents’ literacy level hindered students’ learning process and teachers’ skills presented challenges in a smooth and swift shift of the schools from face-to-face learning to blended learning. It is recommended to establish a conducive environment in schools by providing all required resources and skills. Special trainings should be organized for low literacy level parents. Multiple ways should be adopted to benefit all students.

Keywords: blended learning, challenges in online classes, education in covid-19, public schools in pakistan

Procedia PDF Downloads 166
8384 Research on Integrating Adult Learning and Practice into Long-Term Care Education

Authors: Liu Yi Hui, Chun-Liang Lai, Jhang Yu Cih, He You Jing, Chiu Fan-Yun, Lin Yu Fang

Abstract:

For universities offering long-term care education, the inclusion of adulting learning and practices in professional courses as appropriate based on holistic design and evaluation could improve talent empowerment by leveraging social capital. Moreover, it could make the courses and materials used in long-term care education responsive to real-life needs. A mixed research method was used in the research design. A quantitative study was also conducted using a questionnaire survey, and the data were analyzed by SPSS 22.0 Chinese version. The qualitative data included students’ learning files (learning reflection notes, course reports, and experience records).

Keywords: adult learning, community empowerment, social capital, mixed research

Procedia PDF Downloads 154
8383 An Investigation of Project-Based Learning: A Case Study of Tourism Students

Authors: Benjaporn Yaemjamuang

Abstract:

The purposes of this study were to investigate the success of project-based learning and to evaluate the performance and level of satisfaction of tourism students who participated in the study. This paper drew upon a data collection from a senior tourism students survey conducted in Rajamangala University during summer 2013. The purposive sampling was utilized to obtain the sample which included 45 tourism students. The pretest and posttest method was utilized. The findings revealed that the majority of respondents had gained higher knowledge after the posttest significantly. The respondents’ knowledge increased about 53.33 percent from pretest to posttest. Also, the findings revealed the top three highest level of satisfaction as follows: 1) the role of teacher and students, 2) the research activities of the project-based learning, 3) the learning methods of the project-based learning. Moreover, the mean score of all categories was 3.98 with a standard deviation of 0.88 which indicated that the average level of satisfaction was high.

Keywords: performance, project-based learning, satisfaction, tourism

Procedia PDF Downloads 291
8382 Sustainable Design of Coastal Bridge Networks in the Presence of Multiple Flood and Earthquake Risks

Authors: Riyadh Alsultani, Ali Majdi

Abstract:

It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

Procedia PDF Downloads 94
8381 Using Technology to Enhance the Student Assessment Experience

Authors: Asim Qayyum, David Smith

Abstract:

The use of information tools is a common activity for students of any educational stage when they encounter online learning activities. Finding the relevant information for particular learning tasks is the topic of this paper as it investigates the use of information tools for a group of student participants. The paper describes and discusses the results with particular implications for use in higher education, and the findings suggest that improvement in assessment design and subsequent student learning may be achieved by structuring the purposefulness of information tools usage and online reading behaviors of university students.

Keywords: information tools, assessment, online learning, student assessment experience

Procedia PDF Downloads 560
8380 Nurturing of Children with Results from Their Nature (DNA) Using DNA-MILE

Authors: Tan Lay Cheng (Cheryl), Low Huiqi

Abstract:

Background: All children learn at different pace. Individualized learning is an approach that tailors to the individual learning needs of each child. When implementing this approach, educators have to base their lessons on the understanding that all students learn differently and that what works for one student may not work for another. In the current early childhood environment, individualized learning is for children with diverse needs. However, a typical developing child is also able to benefit from individualized learning. This research abstract explores the concept of utilizing DNA-MILE, a patented (in Singapore) DNA-based assessment tool that can be used to measure a variety of factors that can impact learning. The assessment report includes the dominant intelligence of the user or, in this case, the child. From the result, a personalized learning plan that is tailored to each individual student's needs. Methods: A study will be conducted to investigate the effectiveness of DNA-MILE in supporting individualized learning. The study will involve a group of 20 preschoolers who were randomly assigned to either a DNA-MILE-assessed group (experimental group) or a control group. 10 children in each group. The experimental group will receive DNA Mile assessments and personalized learning plans, while the control group will not. The children in the experimental group will be taught using the dominant intelligence (as shown in the DNA-MILE report) to enhance their learning in other domains. The children in the control group will be taught using the curriculum and lesson plan set by their teacher for the whole class. Parents’ and teachers’ interviews will be conducted to provide information about the children before the study and after the study. Results: The results of the study will show the difference in the outcome of the learning, which received DNA Mile assessments and personalized learning plans, significantly outperformed the control group on a variety of measures, including standardized tests, grades, and motivation. Conclusion: The results of this study suggest that DNA Mile can be an effective tool for supporting individualized learning. By providing personalized learning plans, DNA Mile can help to improve learning outcomes for all students.

Keywords: individualized, DNA-MILE, learning, preschool, DNA, multiple intelligence

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8379 The Perceptions, Experiences, and Views of E-Tutors on Active Learning in the ODeL Context

Authors: Bunki Enid Pitsoane

Abstract:

This study was influenced by the radical change in the tutorial system of UNISA, immigrating from face to face to E-tutoring. The study was undertaken to investigate the perceptions, experiences, and views of E-tutors in relation to active learning. The study is aimed at capturing the views and experiences of E-tutors as they are deemed to implement active learning within their E-tutoring. The problem was traced from Developmental and behaviorist’s theorists perspective and factors related to perception, experience, and views of E-tutors on active learning. The research is aligned with the views of constructivism which put more emphasis on situated learning, chaos, and digital factors. The basis of the theory is that learning is developmental, situational and context-sensitive and also digital. The theorists further purports that the tutor’s conception of teaching and learning influence their tutoring style. In order to support or reject the findings of the literature study, qualitative research in the form of interviews and document analysis were conducted. The sample of the study constituted of 10 E-tutors who are involved in tutoring modules from the College of Education. The identified E-tutors were randomly selected based on their availability. The data concerning E-tutors perception and experience was analysed and interpreted. The results of the empirical study indicated that some tutors are struggling to implement active learning because they are digital immigrants or they lack in digital knowledge which affect productivity in their teaching.

Keywords: E-Tutoring, active learning, perceptions, views

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8378 Prediction of the Crustal Deformation of Volcán - Nevado Del RUíz in the Year 2020 Using Tropomi Tropospheric Information, Dinsar Technique, and Neural Networks

Authors: Juan Sebastián Hernández

Abstract:

The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

Procedia PDF Downloads 103
8377 The Role of Interactive White Boards towards Achieving Transactional Learning in the Context of Open Distance 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 454
8376 Normalized P-Laplacian: From Stochastic Game to Image Processing

Authors: Abderrahim Elmoataz

Abstract:

More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

Procedia PDF Downloads 512
8375 The Development of Directed-Project Based Learning as Language Learning Model to Improve Students' English Achievement

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 165
8374 In-Context Meta Learning for Automatic Designing Pretext Tasks for Self-Supervised Image Analysis

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 80
8373 Pros and Cons of Teaching/Learning Online during COVID-19: English Department at Tahri Muhammed University of Bechar as a Case Study

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

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8372 Self-Reliant and Auto-Directed Learning: Modes, Elements, Fields and Scopes

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

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8371 Innovative Teaching Learning Techniques and Learning Difficulties of Adult Learners in Literacy Education Programmes in Calabar Metropolis, Cross River State, Nigeria

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

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8370 Enhancing Nursing Teams' Learning: The Role of Team Accountability and Team Resources

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

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8369 English Learning Strategy and Proficiency Level of the First Year Students, International College, Suan Sunandha Rajabhat University

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

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8368 Magnetic Navigation in Underwater Networks

Authors: Kumar Divyendra

Abstract:

Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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8367 Marketing in Post-Pandemic Environment

Authors: Mohammad Mehdizadeh

Abstract:

COVID-19 forced marketers to change their marketing strategies, focusing less on reactive approaches and more on proactive approaches, primarily social media. The next few years will be dominated by employee engagement and customer experience, leading to businesses focusing more on "long-term customer relationships." A large number of marketing strategies need to be employed in an ever-evolving online environment, which is both filled with opportunities and dangers, as well as being an intimidating platform to use, incorporating new and exciting opportunities for businesses and organizations as it constantly evolves. In this article, we examine the effect of social networks on marketing in post-pandemic environments. A descriptive survey is used as the research method. The results show that social networks have a positive and significant impact on marketing in a post-pandemic environment. Among the social networks studied, Instagram, Facebook, and Twitter have the most positive effect on marketing advancement.

Keywords: COVID-19, customers, marketing, post-pandemic

Procedia PDF Downloads 86
8366 Blockchain for IoT Security and Privacy in Healthcare Sector

Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

Abstract:

The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

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8365 Comparative Study of Learning Achievement via Jigsaw I and IV Techniques

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

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8364 Challenges of Online Education and Emerging E-Learning Technologies in Nigerian Tertiary Institutions Using Adeyemi College of Education as a Case Study

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

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8363 Literature Review of Instructor Perceptions of the Blended Learning Approach

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

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8362 An Attentional Bi-Stream Sequence Learner (AttBiSeL) for Credit Card Fraud Detection

Authors: Amir Shahab Shahabi, Mohsen Hasirian

Abstract:

Modern societies, marked by expansive Internet connectivity and the rise of e-commerce, are now integrated with digital platforms at an unprecedented level. The efficiency, speed, and accessibility of e-commerce have garnered a substantial consumer base. Against this backdrop, electronic banking has undergone rapid proliferation within the realm of online activities. However, this growth has inadvertently given rise to an environment conducive to illicit activities, notably electronic payment fraud, posing a formidable challenge to the domain of electronic banking. A pivotal role in upholding the integrity of electronic commerce and business transactions is played by electronic fraud detection, particularly in the context of credit cards which underscores the imperative of comprehensive research in this field. To this end, our study introduces an Attentional Bi-Stream Sequence Learner (AttBiSeL) framework that leverages attention mechanisms and recurrent networks. By incorporating bidirectional recurrent layers, specifically bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers, the proposed model adeptly extracts past and future transaction sequences while accounting for the temporal flow of information in both directions. Moreover, the integration of an attention mechanism accentuates specific transactions to varying degrees, as manifested in the output of the recurrent networks. The effectiveness of the proposed approach in automatic credit card fraud classification is evaluated on the European Cardholders' Fraud Dataset. Empirical results validate that the hybrid architectural paradigm presented in this study yields enhanced accuracy compared to previous studies.

Keywords: credit card fraud, deep learning, attention mechanism, recurrent neural networks

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8361 The Potential of Cloud Computing in Overcoming the Problems of Collective Learning

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 492