Search results for: embedded machine learning

Authors: Kamal Heidari

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Covid-19 has borne drastic effects on different areas of society, including the education area, in that it brought virtual education to the center of attention, as an alternative to in-person education. In virtual education, the importance of flipped learning doubles, as students are supposed to take the main responsibility of teaching/learning process; and teachers play merely a facilitative/monitoring role. Given the students’ responsibility in virtual flipped learning, students’ motivation plays a pivotal role in the effectiveness of this learning method. The L2 Motivational Self-System (L2MSS) model is a currently proposed model elaborating on students’ motivation based on three sub-components: ideal L2 self, ought-to L2 self, and L2 learning experience. Drawing on an exploratory sequential mixed-methods research design, this study probed the effect of virtual flipped learning (via SHAD platform) on 112 gifted and non-gifted students’ motivation based on the L2 MSS. This study uncovered that notwithstanding the point that virtual flipped learning improved both gifted and non-gifted students’ motivation, it differentially affected their motivation. In other words, gifted students mostly referred to ideal L2 self, while non-gifted ones referred to ought-to L2 self and L2 learning experience aspects of motivation.

Keywords: virtual flipped learning, giftedness, motivation, L2MSS

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Authors: Yen-Hui Lu

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In the past two decades, in order to increase university visibility and internationalization, English as a medium of instruction (EMI) has become one of the main language policies in higher education institutions where English is not a dominant language. However, given the complex, discipline-embedded nature of academic communication, academic literacy does not come with students’ everyday language experience, and it is a challenge for all students. Particularly, to engage students in the effective learning process of discipline concepts in the EMI classrooms, teachers need to provide explicit academic language instruction to assist students in deep understanding of discipline concepts. To bridge the gap between academic language development and discipline learning in the EMI classrooms, the researcher incorporates academic language strategies and key elements of project-based learning (PBL) into an Academic Language Strategy driven PBL (ALS-PBL) model. With clear steps and strategies, the model helps EMI teachers to scaffold students’ academic language development in the EMI classrooms. ALS-PBL model includes three major stages: preparation, implementation, and assessment. First, in the preparation stage, ALS-PBL teachers need to identify learning goals for both content and language learning and to design PBL topics for investigation. Second, during the implementation stage, ALS-PBL teachers use the model as a guideline to create a lesson structure and class routine. There are five important elements in the implementation stage: (1) academic language preparation, (2) connecting background knowledge, (3) comprehensible input, (4) academic language reinforcement, and (5) sustained inquiry and project presentation. Finally, ALS-PBL teachers use formative assessments such as student learning logs, teachers’ feedback, and peer evaluation to collect detailed information that demonstrates students’ academic language development in the learning process. In this study, ALS-PBL model was implemented in an interdisciplinary course entitled “Science is Everywhere”, which was co-taught by five professors from different discipline backgrounds, English education, civil engineering, business administration, international business, and chemical engineering. The purpose of the course was to cultivate students’ interdisciplinary knowledge as well as English competency in disciplinary areas. This study used a case-study design to systematically investigate students’ learning experiences in the class using ALS-PBL model. The participants of the study were 22 college students with different majors. This course was one of the elective EMI courses in this focal university. The students enrolled in this EMI course to fulfill the school language policy, which requires the students to complete two EMI courses before their graduation. For the credibility, this study used multiple methods to collect data, including classroom observation, teachers’ feedback, peer assessment, student learning log, and student focus-group interviews. Research findings show four major successful aspects of implementing ALS-PBL model in the EMI classroom: (1) clear focus on both content and language learning, (2) meaningful practice in authentic communication, (3) reflective learning in academic language strategies, and (4) collaborative support in content knowledge.This study will be of value to teachers involved in delivering English as well as content lessons to language learners by providing a theoretically-sound practical model for application in the classroom.

Keywords: academic language development, content and language integrated learning, english as a medium of instruction, project-based learning

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Authors: Kinda Alsamara

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Foreign language education is a complex endeavor that often presents educators with a range of challenges and difficulties. This study shed light on the specific challenges encountered in the context of teaching Arabic as a foreign language at the Australian National University (ANU). Drawing from real-world experiences and insights, we explore the multifaceted nature of these challenges and discuss strategies that educators have employed to address them. The challenges in teaching the Arabic language encompass various dimensions, including linguistic intricacies, cultural nuances, and diverse learner backgrounds. The complex Arabic script, grammatical structures, and pronunciation patterns pose unique obstacles for learners. Moreover, the cultural context embedded within the language demands a nuanced understanding of cultural norms and practices. The diverse backgrounds of learners further contribute to the challenge of tailoring instruction to meet individual needs and proficiency levels. This study also underscores the importance of technology in tackling these challenges. Technological tools and platforms offer innovative solutions to enhance language acquisition and engagement. Online resources, interactive applications, and multimedia content can provide learners with immersive experiences, aiding in overcoming barriers posed by traditional teaching methods. Furthermore, this study addresses the role of instructors in mitigating challenges. Educators often find themselves adapting teaching approaches to accommodate different learning styles, abilities, and motivations. Establishing a supportive learning environment and fostering a sense of community can contribute significantly to overcoming challenges related to learner diversity. In conclusion, this study provides a comprehensive overview of the challenges faced in teaching Arabic as a foreign language at ANU. By recognizing these challenges and embracing technological and pedagogical advancements, educators can create more effective and engaging learning experiences for students pursuing Arabic language proficiency.

Keywords: Arabic, Arabic online, blended learning, teaching and learning, Arabic language, educational aids, technology

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Evgeny Pyshkin, Maxim Mozgovoy, Vladislav Volkov

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The paper follows a discourse on computer-assisted language learning. We examine problems of foreign language teaching and learning and introduce a metamodel that can be used to define learning models of language grammar structures in order to support teacher/student interaction. Special attention is paid to the concept of a virtual language lab. Our approach to language education assumes to encourage learners to experiment with a language and to learn by discovering patterns of grammatically correct structures created and managed by a language expert.

Keywords: computer-assisted instruction, language learning, natural language grammar models, HCI

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Authors: Vijayan Narayananayar

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Identifying learning gaps is crucial in ensuring learners have the necessary knowledge and skills to succeed. The Learning and Teaching (L&T) approach requires tutors to identify gaps in knowledge and improvise learning activities to close them. One approach to identifying learning gaps is through diagnostic assessment, which uses well-structured questions and answer options. The paper focuses on the use of diagnostic assessment as a learning and teaching approach in a foundational module at a polytechnic. The study used diagnostic assessment over two semesters, including the COVID and post-COVID semesters, to identify gaps in learning. The design of the diagnostic activity, pedagogical intervention, and survey responses completed by learners were analyzed. Results showed that diagnostic assessment can be an effective tool for identifying learning gaps and designing interventions to address them. Additionally, the use of diagnostic assessment provides an opportunity for tutors to engage with learners on a one-to-one basis, tailoring teaching to individual needs. The paper also discusses the design of diagnostic questions and answer options, including characteristics that need to be considered in achieving the target of identifying learning gaps. The implications of using diagnostic assessment as a learning and teaching approach include bridging the gap between theory and practice, and ensuring learners are equipped with skills necessary for their future careers. This paper can be useful in helping educators and practitioners to incorporate diagnostic assessment into their L&T approach.

Keywords: assessment, learning & teaching, diagnostic assessment, analytics

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Authors: Annette McArthur

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The traditional model of teaching and learning, where ICT sits as a separate entity is not a model for a 21st century school. It is imperative that teaching and learning embraces technological advancements. The challenge in schools lies in shifting the mindset of teachers so they see ICT as integral to their teaching, learning and curriculum rather than a separate E-Learning curriculum stream. This research project investigates how the effective, planned, intentional integration of ICT into a STEM curriculum, can enable the shift in the teacher mindset. The project incorporated: • Developing a professional coaching relationship with key STEM teachers. • Facilitating staff professional development involving student centered project based learning pedagogy in the context of a STEM curriculum. • Facilitating staff professional development involving digital literacy. • Establishing a professional community where collaboration; sharing and reflection were part of the culture of the STEM community. • Facilitating classroom support for the effective delivery innovative STEM curriculum. • Developing STEM learning spaces where technologies were used to empower and engage learners to participate in student-centered, project-based learning.

Keywords: e-learning, ICT, project based learning, STEM

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Authors: Chechen Liao, Chin Yi Yang

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Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: learning performance, programming learning, TDD, training method

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Authors: Nurul Yusnita

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Many studies have been developed to help the students to get good achievement in English learning. They can be from the teaching method or psychological ones. One of the psychological studies in educational research is learning style. In some ways, learning style can affect the achievement of the students. This study aimed to examine 4 (four) learning styles and their relations to English achievement among the students learning English in Language Training Center of Universitas Muhammadiyah Yogyakarta (LTC UMY). The method of this study was descriptive analytical. The sample consisted of 39 Accounting students in LTC UMY. The data was collected through questionnaires with Likert-scale. The achievement was obtained from the grade of the students. To analyze the questionnaires and to see the relation between the learning styles and the student achievement, SPSS statistical software of correlational analysis was used. The result showed that both visual and auditory had the same percentage of 35.9% (14 students). 3 students (7.7%) had kinaesthetic learning style and 8 students (20.5%) had visual and auditory ones. Meanwhile, there were 5 students (12.8%) who had visual learning style could increase their grades. Only 1 student (2.5%) who had visual and auditory could improve his grade. Besides grade increase, there were also grade decrease. Students with visual, auditory, visual and auditory, and kinaesthetic learning styles were 3 students (7.7%), 5 students (12%), 4 students (10.2%) and 1 student (2.5%) respectively. In conclusion, there was no significant relationship between learning style and English achievement. Most of the good achievers were the students with visual and auditory learning styles and most of them preferred visual method. The implication is the teachers and material designers could improve their method through visual things to achieve effective English teaching learning.

Keywords: accounting students, English achievement, language training centre, learning styles

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Yen-Mei Lee

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Mobile learning (m-learning) has been applied in the education field not only because it is an alternative to web-based learning but also it possesses the ‘anytime, anywhere’ learning features. However, most studies focus on the technology-related issue, such as usability and functionality instead of addressing m-learning from the motivational perspective. Accordingly, the main purpose of the current paper is to integrate critical factors from different motivational theories and related findings to have a better understand the catalysts of an individual’s learning motivation toward m-learning. The main research question for this study is stated as follows: based on different motivational perspectives, what factors of applying mobile devices as medium can facilitate people’s learning motivations? Self-Determination Theory (SDT), Uses and Gratification Theory (UGT), Malone and Lepper’s taxonomy of intrinsic motivation theory, and different types of motivation concepts were discussed in the current paper. In line with the review of relevant studies, three motivating factors with five essential elements are proposed. The first key factor is autonomy. Learning on one’s own path and applying personalized format are two critical elements involved in the factor of autonomy. The second key factor is to apply a build-in instant feedback system during m-learning. The third factor is creating an interaction system, including communication and collaboration spaces. These three factors can enhance people’s learning motivations when applying mobile devices as medium toward learning. To sum up, in the currently proposed paper, with different motivational perspectives to discuss the m-learning is different from previous studies which are simply focused on the technical or functional design. Supported by different motivation theories, researchers can clearly understand how the mobile devices influence people’s leaning motivation. Moreover, instructional designers and educators can base on the proposed factors to build up their unique and efficient m-learning environments.

Keywords: autonomy, learning motivation, mobile learning (m-learning), motivational perspective

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Authors: Kornchanok Chidchaisuwan

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This project is a study of learning activities through experience to enhance career skills and technical abilities on the creative strategies for advertising course of undergraduate students. This instructional model consisted of study learning approaches: 1) Simulation-based learning: used to create virtual learning activities plans for work like working at advertising companies. 2) Project-based learning: Actual work based on the processed creating and focus on producing creative works to present on new media channels. The results of learning management found that there were effects on the students in various areas, including 1) The learners have experienced in the step by step of advertising work process. 2) The learner has the skills to work from the actual work (Learning by Doing), allowing the ability to create, present, and produce the campaign accomplished achievements and published on online media at a better level.

Keywords: technical, advertising, presentation, career skills, experience, simulation based learning

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Authors: Jatuphum Ketchatturat

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The objective of this research was to study the learning and innovation skills of undergraduate students after Research-Based Learning had been applied. Eighty research participants were selected from undergraduate students enrolled in Educational Research Program using the Purposive Sampling Method. Research Methodology was Descriptive Research, the research took one semester to complete. The research instruments consisted of (1) Research Skill Assessment Form, (2) Research Quality Assessment Form, (3) Scale of learning and innovation skills 25 items. The quantitative data were analysed using descriptive statistics including, frequency, percentage, average and standard deviation. The qualitative data were analyzed using content analysis. The research results were (1) The students were able to conduct research that focused on educational research, which has a fair to the excellent level of standards of a research learning outcome, research skills, and research quality. The student’s learning and innovation skills have relating to research skills and research quality. (2) The findings found that the students have been developed to be learning and innovation skills such as systematic thinking, analytical thinking, critical thinking, creative problem solving, collaborative, research-creation, communication, and knowledge and experience sharing to friends, community and society.

Keywords: learning and innovation skills, research based learning, research skills, undergraduate students

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Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

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Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

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Authors: Ferenc Kovács, Gábor Hosszú

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The paper presents an advanced control system for tennis ball throwing machines to improve their accuracy according to the ball impact points. A further advantage of the system is the much easier calibration process involving the intelligent solution of the automatic adjustment of the stroking parameters according to the ball elasticity, the self-calibration, the use of the safety margin at very flat strokes and the possibility to placing the machine to any position of the half court. The system applies mathematical methods to determine the exact ball trajectories and special approximating processes to access all points on the aimed half court.

Keywords: control system, robot programming, robot control, sports equipment, throwing machine

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Authors: Muhammad Afzal Malik

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Traditional Learning & Distance based learning are the two systems prevailing in Pakistan. These systems affect the level of education standard. The purpose of this study was to compare the traditional classroom learning and distance learning in Pakistan: (a) To explore the effectiveness of the traditional to Distance learning in Pakistan; (b) To identify the factors that affect traditional and distance learning. This review found that, on average, students in traditional classroom conditions performed better than those receiving education in and distance learning. The difference between student outcomes for traditional Classroom and distance learning classes —measured as the difference between treatment and control means, divided by the pooled standard deviation— was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. This research was conducted to highlight the impact of distance learning education system on education standard. The education standards were institutional support, course development, learning process, student support, faculty support, evaluation and assessment. A well developed questionnaire was administered and distributed among 26 faculty members of GCET, H-9 and Virtual University of Pakistan from each. Data was analyzed through correlation and regression analysis. Results confirmed that there is a significant relationship and impact of DLE system on education standards. This will also provide baseline for future research. It will add value to the existing body of knowledge.

Keywords: distance learning education, higher education, education standards, student performance

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Authors: M. Abdelmalek

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In this work, we study the hypersurfaces of constant weighted mean curvature embedded in weighted manifolds. We give a condition about these hypersurfaces to be minimal. This condition is given by the ellipticity of the weighted Newton transformations. We especially prove that two compact hypersurfaces of constant weighted mean curvature embedded in space forms and with the intersection in at least a point of the boundary must be transverse. The method is based on the calculus of the matrix of the second fundamental form in a boundary point and then the matrix associated with the Newton transformations. By equality, we find the weighted elementary symmetric function on the boundary of the hypersurface. We give in the end some examples and applications. Especially in Euclidean space, we use the above result to prove the Alexandrov spherical caps conjecture for the weighted case.

Keywords: weighted mean curvature, weighted manifolds, ellipticity, Newton transformations

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: Szu-Kai Hsu, Po-Ching Lin

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As more and more multi-core processors emerge, traditional sequential programming paradigm no longer suffice. Yet only few modern dynamic programming languages can leverage such advantage. Ruby, for example, despite its wide adoption, only includes threads as a simple parallel primitive. The global virtual machine lock of official Ruby runtime makes it impossible to exploit full parallelism. Though various alternative Ruby implementations do eliminate the global virtual machine lock, they only provide developers dated locking mechanism for data synchronization. However, traditional locking mechanism error-prone by nature. Software Transactional Memory is one of the promising alternatives among others. This paper introduces a new virtual machine: GobiesVM to provide a native software transactional memory based solution for dynamic programming languages to exploit parallelism. We also proposed a simplified variation of Transactional Locking II algorithm. The empirical results of our experiments show that support of STM at virtual machine level enables developers to write straightforward code without compromising parallelism or sacrificing thread safety. Existing source code only requires minimal or even none modi cation, which allows developers to easily switch their legacy codebase to a parallel environment. The performance evaluations of GobiesVM also indicate the difference between sequential and parallel execution is significant.

Keywords: global interpreter lock, ruby, software transactional memory, virtual machine

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

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Authors: Fahri Benli, Sitalakshmi Venkartraman, Ye Wei, Fiona Wahr

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A flipped classroom which is a form of blended learning shifts the focus from a teacher-centered approach to a learner-centered approach. However, not all learners are ready to take the active role of knowledge and skill acquisition through a flipped classroom and they continue to delve in a passive mode of learning. This challenges educators in designing, scaffolding and facilitating in-class activities for students to have active learning experiences in a flipped classroom environment. Experiential learning theories have been employed by educators in the past in physical classrooms based on the principle that knowledge could be actively developed through direct experience. However, with more of online teaching witnessed recently, there are inherent limitations in designing and simulating an experiential learning activity for an online environment. In this paper, we explore enhancing experiential learning using smart digital tools that could be employed in a flipped classroom within a higher education setting. We present the use of smart collaborative tools online to enhance the experiential learning activity to teach higher-order cognitive concepts of business process modelling as a case study.

Keywords: experiential learning, flipped classroom, smart software tools, online learning higher-order learning attributes

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Authors: Heba Mustafa Abdullah

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The research aimed at examining the effect of a using a quest based learning strategy on developing EFL Pre-Master Students. The study adopted the quasi-experimental design. The sample of the research consists of a group of 30 students enrolled in Pre-Master program, Curriculum and EFL Instruction Department, Faculty of Graduate Studies in Education Tools of the study included a EFL research skills checklist and EFL research skills test. Results revealed that there were statistically significant differences at 0.01 levels with regard to some research skills. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating e-learning technologies in general and Quest based learning strategy in particular with respect to EFL research skills.

Keywords: English as foreign language, e-Learning, research skills, quest based learning

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Authors: S. S. Bendib, L. W. Mouss, S. Kalla

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This paper proposes a self-organization-based approach for real-time systems design. The addressed issue is the mapping of an application onto an architecture of heterogeneous processors while optimizing both makespan and reliability. Since this problem is NP-hard, a heuristic algorithm is used to obtain efficiently approximate solutions. The proposed approach takes into consideration the quality as well as the diversity of solutions. Indeed, an alternate treatment of the two objectives allows to produce solutions of good quality while a self-organization approach based on the neighborhood structure is used to reorganize solutions and consequently to enhance their diversity. Produced solutions make different compromises between the makespan and the reliability giving the user the possibility to select the solution suited to his (her) needs.

Keywords: embedded real-time systems design, makespan, reliability, self-organization, compromises

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: John Q. Todd

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Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

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Authors: Gunmala Suri

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The purpose of this study was to investigate the relationship between various dimensions of Knowledge Management and Learning Organizations. On the basis of the dimensions of Learning Organization, Hypothesis were formulated. Knowledge Management (KM) is taken as the independent variable and Learning Organization (LO) as a dependent variable. KM had 5 dimensions and LO had 7. For this study, a total of 92 participants took part and answered the questionnaire. The respondents were selected using Judgemental and Snowball sampling. The respondents were from SMEs in and around Chandigarh. SPSS was used to for the data analysis purposes. The results showed that the dimensions of KM had a positive influence on the dimensions of LO. The hypothesis were accepted.

Keywords: knowledge management leadership, knowledge management, learning organization, knowledge management culture

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Authors: Erteki̇n Kotbaş

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Teaching English as a Foreign Language (EFL) is on the front burner of many countries in the world, in particular for English language teaching departments that train EFL teachers. Under the head of motivational theories in foreign language education, there are numerous researches in literature. However; researches comprising English language self-efficacy and teachers’ learning goal orientation which has a positive impact on learning teachings skills are scarce. Examination of these English language self-efficacy beliefs and learning goal orientations of pre-service EFL teachers may broaden the horizons, considering the importance of self-efficacy and goal orientation on learning and teaching activities. At this juncture, present study aims to investigate the strong relationship between English language self efficacy and teachers’ learning goal orientation from Turkish context in addition to teacher students’ grade factor.

Keywords: English language, learning goal orientation, self efficacy, pre-service teachers

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Heba Mustafa Abdullah

Abstract:

The research aimed at examining the effect of using a suggested blended learning (BL) strategy on developing EFL pre- intermediate students. The study adopted the quasi-experimental design. The sample of the research consisted of a group of 26 EFL pre- intermediate students. Tools of the study included a listening comprehension checklist and a pre-post listening comprehension test. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating BL strategy with respect to language learning process in general and oral language learning in particular.

Keywords: blended learning, english as a foreign language, listening comprehension, oral language instruction

Procedia PDF Downloads 545

Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

Abstract:

Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: e-learning, information and communication technology (ICT), teaching, virtual learning environment

Procedia PDF Downloads 269