Search results for: local machine learning

Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: blended learning, higher education, WhatsApp, programming, novices, lecturers

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Authors: Kang Zijian, Zhang Tingyu, Burra Venkata Durga Kumar

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This article investigates the challenges in memory migration during the live migration of virtual machines. We found three challenges probably existing in pre-copy technology. One of the main challenges is the challenge of downtime migration. Decrease the downtime could promise the normal work for a virtual machine. Although pre-copy technology is greatly decreasing the downtime, we still need to shut down the machine in order to finish the last round of data transfer. This paper provides an optimization scheme for the problems existing in pro-copy technology, mainly the optimization of the dirty page migration mechanism. The typical pre-copy technology copy n-1th’s dirty pages in nth turn. However, our idea is to create a double iteration method to solve this problem.

Keywords: virtual machine, pre-copy technology, memory migration process, downtime, dirty pages migration method

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Authors: M. Hisham, S. Cabemaiwai, S. Prasad, T. Dauvakatini, R. Ananthanarayanan

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A solenoid valve is an important part of many fluid systems. Its purpose is to regulate fluid flow in a machine. Due to the crucial role of the solenoid valve and its design intricacy, it is quite expensive to obtain in Fiji and is not manufactured locally. A concern raised by the local health industry is that the housing of the solenoid valve gets damaged when machines are continuously being used and this part of the valve is very costly to replace due to the lack of availability in Fiji and many other South Pacific region countries. This study explores the agile manufacturing of a solenoid coil housing using the Fused Deposition Modeling (FDM) process. An emergy study was carried out to analyze the feasibility and sustainability of producing the part locally after estimating a Unit Emergy Value (or emergy transformity) of 1.27E+05 sej/j for the electricity in Fiji. The total emergy of the process was calculated to be 3.05E+12 sej, of which a majority was sourced from imported services and materials. Renewable emergy sources contributed to just 16.04% of the total emergy. Therefore, the part is suitable to be manufactured in Fiji with a reasonable quality and a cost of $FJ 2.85. However, the loading on the local environment is found to be significant and therefore, alternative raw materials for the filament like recycled PET should be explored or alternative manufacturing processes may be analyzed before committing to fabricating the part using FDM in its analyzed state.

Keywords: emergy analysis, fused deposition modeling, solenoid valve housing, sustainable production

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Authors: Tommy Krieger, Klaus Gruendler

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We present a novel approach for measuring democracy, which enables a very detailed and sensitive index. This method is based on Support Vector Machines, a mathematical algorithm for pattern recognition. Our implementation evaluates 188 countries in the period between 1981 and 2011. The Support Vector Machines Democracy Index (SVMDI) is continuously on the 0-1-Interval and robust to variations in the numerical process parameters. The algorithm introduced here can be used for every concept of democracy without additional adjustments, and due to its flexibility it is also a valuable tool for comparison studies.

Keywords: democracy, democracy index, machine learning, support vector machines

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Authors: S. J. Hachar

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The goal of this paper is to provide educators an overview of international practices supporting young learners, arming us with adequate information to lead effective change. We will report on research and observations of Service Learning Projects conducted by one South Texas University. The intent of the paper is also to provide readers an overview of service learning in the preparation of teacher candidates pursuing a Bachelor of Science in Elementary Education. The objective of noting the efficiency and effectiveness of programs leading to literacy and oral fluency in a native language and second language will be discussed. This paper also highlights experiential learning for academic credit that combines community service with student learning. Six weeks of visits to a variety of community sites, making personal observations with faculty members, conducting extensive interviews with parents and key personnel at all sites will be discussed. The culminating Service Learning Expo will be reported as well.

Keywords: elementary education, junior achievement, service learning

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Authors: T. T. K. Nguyen, T. H. Doan

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The study investigates students’ perceptions and students’ use of vocabulary learning strategies (VLS) among non-English majors at Ho Chi Minh City University of Technology (HUTECH). Three main issues addressed are (1) to determine students’ perception in terms of their awareness and the level of the importance of vocabulary learning strategies; (2) students’ use in terms of frequency and preference; (3) the correlation between students’ perception in terms of the level of the importance of vocabulary learning strategies and their use in terms of frequency. The mixed method is applied in this investigation; additionally, questionnaires focus on social groups, memory groups, cognitive groups, and metacognitive groups with 350 sophomores from four different majors, and 10 sophomores are invited to structured interviews. The results showed that the vocabulary learning strategies of the current study were well aware. All those strategies were perceived as important in learning vocabulary, and four groups of vocabulary were used frequently. Students’ responses in terms of preference also confirmed students’ use in terms of frequency. On the other hand, students’ perception correlated with students’ use in only the cognitive group of vocabulary learning strategies, but not the three others.

Keywords: vocabulary learning strategies, students' perceptions, students' use, mixed methods, non-English majors

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Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

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There is evidence that any learning experience should happen in a safe learning environment as students then will interact, experiment, and construct new knowledge. However, little is known about the specific elements required to create a safe learning environment for the millennial generation, especially in optometry education. This study aimed to identify the specific elements that will contribute to a safe learning environment for the millennial generation of optometry students. Methods: An intrinsic qualitative case study was undertaken with undergraduate students from the Department of Optometry at the University of the Free State, South Africa. An open-ended questionnaire survey was completed after the application of nine different teaching-learning methods based on the experiential learning cycle. A total number of 307 questionnaires were analyzed. Two focus group interviews were also conducted to provide additional data to supplement the data and ensure the triangulation of data. Results: Important elements based on the opinions, feelings, and perceptions of student respondents were analyzed. Students feel safe in an environment with which they are familiar, and when they are familiar with each other, the educators, and the surroundings. Small-group learning also creates a safe and familiar environment. Both these elements create an environment where they feel safe to ask questions. Students value an environment where they are able to learn without influencing their marks or disadvantaging the patients. They enjoy learning from their peers, but also need personal contact with educators. Elements such as consistency and an achievable objective also were also analyzed. Conclusion: The findings suggest that to respond to the real need of this generation of students, insight must be gained in students’ perceptions to identify their needs and the learning environment to optimize learning pedagogies. With the implementation of these personalized elements, optometry students will be able to take responsibility and accountability for their learning.

Keywords: experiences and perceptions, safe learning environment, millennial generation, recommendation for optometry education

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Atiya Khan

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Recent research on the condition of school education in India has reaffirmed the importance of quality teacher professional development, especially in light of the rapid changes in teaching methods, learning theories, curriculum, and major shifts in information and technology that education systems are experiencing around the world. However, the quality of programs of teacher professional development in India is often uneven, in some cases non-existing. The educational authorities in India have long recognized this and have developed a range of programs to assist in-service teacher education. But, these programs have been mostly inadequate at improving the quality of teachers in India. Policy literature and reports indicate that the unevenness of these programs and more generally the lack of quality teacher professional development in India are due to factors such as a large number of teachers, budgetary constraints, top-down decision making, teacher overload, lack of infrastructure, and little or no follow-up. The disparity between the government stated goals for quality teacher professional development in India and its inability to meet the learning needs of teachers suggests that new interventions are needed. The realization that globalization has brought about an increase in the social, cultural, political and economic interconnectedness between countries has also given rise to transnational opportunities for education systems, such as India’s, aiming to build their capacity to support teacher professional development. Moreover, new developments in communication technologies seem to present a plausible means of achieving high-quality professional development for teachers through the creation of social learning spaces, such as transnational learning networks. This case study investigates the potential of one such transnational learning network to support the quality of teacher professional development in India, namely the Australia-Asia BRIDGE School Partnerships Project. It explores the participation of some fifteen teachers and their principals from BRIDGE participating schools in Delhi region of India; focusing on their professional development expectations from the BRIDGE program and account for their experiences in the program, in order to determine the program’s potential for the professional development of teachers in this study.

Keywords: case study, Australia-Asia BRIDGE Project, teacher professional development, transnational learning networks

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Authors: Noha Desouky Aly, Maged Makram Habib

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Given the imperative role educational institutions have in the creation of a motivational learning community that develops and engages their students, the influence of evoking the same environment for their teachers needs to be examined. Teachers and their role lie at the core of the efficiency of the learning experience. One exigent aspect in the process of providing professional development to teachers is to involve them in this process, and the best manner would be through creating a learning community in which they are directly engaged and responsible for their own learning. An educational institution that thinks first of its teachers learning and growth would achieve its goals in providing an effective education for its students. The purpose of this research paper is to examine the effect of engaging teachers in a learning community in which they are responsible for their own learning through conducting and providing the material required for the training on their self efficacy, engagement, and perceived autonomy. The sample includes twenty instructors at the German University in Cairo teaching Academic skills at the Department of English and Scientific Methods. The courses taught at the department include Academic skills, writing argumentative essays, critical thinking, communication and presentation skills, and research paper writing. Procedures for the duration of eight weeks will entail pre-post measures to include The Teachers Self Efficacy Scale and an interview. During the weekly departmental meeting, teachers are to share resources and experiences or research and present a topic of their choice that contributes to their professional development. Results are yet to be found.

Keywords: learning community, self- efficacy, teachers, learning experience

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Authors: Abdulrahman Yarali

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The advancement of technology never stops because the demands for improved internet and communication connectivity are increasing. Just as 5G networks are rolling out, the world has begun to talk about the sixth-generation networks (6G). The semantics of 6G are more or less the same as 5G networks because they strive to boost speeds, machine-to-machine (M2M) communication, and latency reduction. However, some of the distinctive focuses of 6G include the optimization of networks of machines through super speeds and innovative features. This paper discusses many aspects of the technologies, architectures, challenges, and opportunities of 6G wireless communication systems.

Keywords: 6G, characteristics, infrastructures, technologies, AI, ML, IoT, applications

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

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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

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Charles Kwaku Oppong

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This study examined the effects of the agricultural land grabbed for the Bui Dam project on the livelihoods assets of the affected people and its implication on food production. Both quantitative and qualitative data were collected through the use of focus group discussions, questionnaire administration, interview guide, and observations. It was found that the land grabbing incident in the study communities as a result of the Bui Dam construction has resulted in the improvements in the physical assets of the affected people. The findings also indicated that local food crop production and the quantity of fish catch have dwindled after the land grabs. Contrary to this, the local people’s access to the natural capital, particularly the local land for agricultural activities has been worsened. The study recommends alternative sustainable livelihood for the affected people by the local government.

Keywords: land grabbing, livelihood, asset, food production

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

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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

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Authors: Nouredine Benouzza, Ahmed Hamida Boudinar, Azeddine Bendiabdellah

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An algorithm for Eccentricity Fault Detection (EFD) applied to a squirrel cage induction machine is proposed in this paper. This algorithm employs the behavior of the stator current spectral analysis and the localization of the Rotor Slot Harmonic (RSH) frequency to detect eccentricity faults in three phase induction machine. The RHS frequency once obtained is used as a key parameter into a simple developed expression to directly compute the eccentricity fault frequencies in the induction machine. Experimental tests performed for both a healthy motor and a faulty motor with different eccentricity fault severities illustrate the effectiveness and merits of the proposed EFD algorithm.

Keywords: squirrel cage motor, diagnosis, eccentricity faults, current spectral analysis, rotor slot harmonic

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Authors: Rasheed Gbenga Jimoh, Akinbowale Nathaniel Babatunde

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The use of Automated Teller Machine (ATM) has become an important tool among commercial banks, customers of banks have come to depend on and trust the ATM conveniently meet their banking needs. Although the overwhelming advantages of ATM cannot be over-emphasized, its alarming fraud rate has become a bottleneck in it’s full adoption in Nigeria. This study examined the menace of ATM in the society another cost of running ATM services by banks in the country. The researcher developed a prototype of an enhanced Automated Teller Machine Authentication using Short Message Service (SMS) Verification. The developed prototype was tested by Ten (10) respondents who are users of ATM cards in the country and the data collected was analyzed using Statistical Package for Social Science (SPSS). Based on the results of the analysis, it is being envisaged that the developed prototype will go a long way in reducing the alarming rate of ATM fraud in Nigeria.

Keywords: ATM, ATM fraud, e-banking, prototyping

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Authors: Hema Vanita Kesevan

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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

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Authors: Sumaira Taj

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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

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Authors: Samad Sajjadi

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Machine translation is a new subject increasingly being used by academic writers, especially students and researchers whose native language is not English. There are numerous studies conducted on machine translation, but few investigations have assessed the accuracy of machine translation from Persian to English at lexical, semantic, and syntactic levels. Using Groves and Mundt’s (2015) Model of error taxonomy, the current study evaluated Persian-to-English translations produced by two famous online translators, Google Translate and Bing Translator. A total of 240 texts were randomly selected from different academic fields (law, literature, medicine, and mass media), and 60 texts were considered for each domain. All texts were rendered by the two translation systems and then by four human translators. All statistical analyses were applied using SPSS. The results indicated that Google translations were more accurate than the translations produced by the Bing Translator, especially in the domains of medicine (lexis: 186 vs. 225; semantic: 44 vs. 48; syntactic: 148 vs. 264 errors) and mass media (lexis: 118 vs. 149; semantic: 25 vs. 32; syntactic: 110 vs. 220 errors), respectively. Nonetheless, both machines are reasonably accurate in Persian-to-English translation of lexicons and syntactic structures, particularly from mass media and medical texts.

Keywords: machine translations, accuracy, human translation, efficiency

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

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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

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Authors: Benjaporn Yaemjamuang

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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

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Authors: Xin Wang, Chaoqun Ma, Zheng Yao

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Although green technology innovation faces new opportunities and challenges in the digital era, its theoretical research remains limited. Drawing on the attention-based view, this study employs the spatial Durbin model to investigate the impact of local government digital attention and digital industrial agglomeration on green technology innovation across 30 Chinese provinces from 2011 to 2021, as well as the spatial spillover effects present. The results suggest that both government digital attention and digital industrial agglomeration positively influence green technology innovation in local and neighboring provinces, with digital industrial agglomeration exhibiting a positive moderating effect on this direct local and indirect spatial spillover relationship. The findings of this study provide a new theoretical perspective for green technology innovation research and hold valuable implications for the advancement of the attention-based view and green technology innovation.

Keywords: local government digital attention, digital industrial agglomeration, green technology innovation, attention-based view

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Authors: Asim Qayyum, David Smith

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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

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Authors: Ntandoni Gloria Biyela

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During traditional times, there were no formal institutions of learning as they are today, where children attend classes to acquire or develop knowledge. This does not mean that there was no learning in indigenous African societies. Grandparents used to tell their grandchildren stories or teach them educational games around the fireplace, which this study refers to as a ‘traditional classroom’. A story recreated in symbolic or allegorical way, forms a base for a society’s beliefs, customs, accepted norms and language learning. Through folklore narratives, a society develops its own self awareness and education. So narrative characters, especially animals may be mythical products of the pre-literate folklore world and thus show the closeness that the Zulu society had with the wildlife. Oral cultures strive to create new facets of meaning by the use of animal metaphors to reflect the relationship of humans with the animal realm and to contribute to the language learning or literature in cross-cultural studies. Although animal metaphors are widespread in Zulu language because of the Zulu nation’s traditional closeness to wildlife, little field-research has been conducted on the social behavior of animals on the way in which their characteristics were transferred with precision to depictions of King Shaka’s behavior and activities during the amalgamation of Nguni clans into a Zulu kingdom. This study attempts to fill the gap by using first-hand interviews with local informants in areas traditionally linked to the king in KwaZulu-Natal province, South Africa. Departing from the conceptual metaphor theory, the study concentrates on King Shaka’s praise-poems in which the praise-poet describes his physical and dispositional characteristics through bold animal metaphors of the ‘Big Five’; namely, the lion, the leopard, the buffalo, the rhinoceros and the elephant, which are often referred to as Zulu royal favorites. These metaphors are still learnt by young and old in the 21st century because they reflect the responsibilities, status, and integrity of the king and the respect in which he is held by his people. They also project the crescendo growth of the Zulu nation, which, through the fulfillment of his ambitions, grew from a small clan to a mighty kingdom.

Keywords: animal, indigenous, learning, metaphor

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Authors: Akiko Kondo, Akio Kondo

Abstract:

We are facing serious problems related to a long-term depopulation and an aging society with a falling birth rate in Japan. In this situation, we are suffering from a shortfall in human resources as well as a shortage of workforce in rural regions. In addition, we are struggling with a protracted economic slump and excess concentration of population in the Tokyo Metropolitan area. It is an urgent national issue to consider how to live in this country and what kind of structure of society and administration policy is needed. It is necessary to clarify people’s desire for their way of living and social assistance to be provided. The aim of this study is to clarify the characteristics of regional issues and the degree of their seriousness in local municipalities of Japan. We conducted a questionnaire survey about regional agenda in all local municipalities in Japan. We obtained responses concerning the degree of seriousness of regional issues and degree of importance of policies. Based on the data gathered from the survey, it is apparent that many local municipalities are facing an aging population and declining population. We constructed a model to analyze factors for declining population. Using the model, it was clarified that a population’s age structure, job opportunities, and income level affect the decline of population. In addition, we showed the way of the evaluation of the state of a local municipality.

Keywords: evaluation, local municipality, regional analysis, regional issue

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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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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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Authors: T. Holecki, J. Wozniak-Holecka, K. Sobczyk

Abstract:

Development, implementation, and evaluation of the effects of health policy programs, resulting from the identified health needs and health status of residents, is the own task of all local government units in Poland. This is due to the obligation to provide access to healthcare services to all residents and the implementation of tasks in the field of health promotion based on specific legal acts. Until the end of 2016 local governments financed health policy programs only with their own funds. Currently, there are additional resources available from the public health insurance subsidising up to 80% of health policy programs costs in cities with a population under 5 thousand people and up to 40% in bigger cities. Changes in legal provisions do not translate automatically to increased involvement of local government units in the implementation of public health tasks. The main objective of the study was to assess the actual impact of the new legal regulation on financing local health policy programs on the engagement of local administration in this area of public health activity. To achieve this aim, we analyzed difference in the number of local governments developing and implementing health policy programs before and after the new law came into force. The aim of the study was also to estimate the level of expenditures incurred by self-government units and the National Health Fund to cover the costs of health policy programs. In the first stage of the project, legal acts concerning the subject of research and financial data published by the National Health Fund were analyzed. The material for the second, main stage of the study was the detailed financial data obtained from the National Health Fund and data obtained from local government units. The results present the situation in Poland in territorial terms, divided into 16 voivodships.

Keywords: health care system, health policy programs, local self-governments, public health

Procedia PDF Downloads 153