Search results for: web-based learning systems

Authors: Rachel S. E. Lim, Winnie L. C. Tan

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Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

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Authors: Afsha Shaikh, Mohammed Azizur Rahman, Ibrahim Hassan, Mayur Pal

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Student engagement in learning is instantly affected by the sources of learning methods available for them, such as videos showing the applications of the concept or showing a practical demonstration. Specific to the engineering discipline, there exist enormous challenging concepts that can be simplified when they are connected to real-world scenarios. For this study, the concept of heat exchangers was used as it is a part of multidisciplinary engineering fields. To make the learning experience enjoyable and impactful, 3-D printed heat exchanger models were created for students to use while working on in-class activities and assignments. Students were encouraged to use the 3-D printed heat exchanger models to enhance their understanding of theoretical concepts associated with its applications. To assess the effectiveness of the method, feedback was received by students pursuing undergraduate engineering via an anonymous electronic survey. To make the feedback more realistic, unbiased, and genuine, students spent nearly two to three weeks using the models in their in-class assignments. The impact of these tools on their learning was assessed through their performance in their ungraded assignments as well as their interactive discussions with peers. ‘Having to apply the theory learned in class whilst discussing with peers on a class assignment creates a relaxed and stress-free learning environment in classrooms’; this feedback was received by more than half the students who took the survey and found 3-D models of heat exchanger very easy to use. Amongst many ways to enhance learning and make students more engaged through interactive models, this study sheds light on the importance of physical tools that help create a lasting mental representation in the minds of students. Moreover, in this technologically enhanced era, the concept of augmented reality was considered in this research. E-drawings application was recommended to enhance the vision of engineering students so they can see multiple views of the detailed 3-D models and cut through its different sides and angles to visualize it properly. E-drawings could be the next tool to implement in classrooms to enhance students’ understanding of engineering concepts.

Keywords: student engagement, life-long-learning, visual demonstration, 3-D printed models, engineering education

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Authors: Hussein Moselhy, Islam Salam

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There have been some challenges and problems which hinder the implementation of the e-marketing systems such as the high cost of information systems infrastructure and maintenance as well as their unavailability within the institution. Also, there is no system which supports all programming languages and different platforms. Another problem is the lack of integration between these systems on one hand and the operating systems and different web browsers on the other hand. No system for customer relationship management is established which recognizes their desires and puts them in consideration while performing e-marketing functions is available. Therefore, the service-oriented architecture emerged as one of the most important techniques and methodologies to build systems that integrate with various operating systems and different platforms and other technologies. This technology allows realizing the data exchange among different applications. The service-oriented architecture represents distributed computing concepts to demonstrate its success in achieving the requirements of systems through web services. It also reflects the appropriate design for the services to use different web services in supporting the requirements of business processes and software users. In a service-oriented environment, web services are deployed on the web in the form of independent services to be accessed without knowledge of the nature of the programs and systems with in. This Paper presents a proposal for a new model which contributes to the application of methods and means of e-marketing with the integration of marketing mix elements to improve marketing efficiency (E-MSOA). And apply it in the educational city of one of the Egyptian sector.

Keywords: service-oriented architecture, electronic commerce, virtual retailing, unified modeling language

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Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

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Authors: Jiang Fan

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With growth of PV market in tropical region, it is necessary to investigate the performance of different types of PV technology under the tropical weather conditions. Singapore Polytechnic was funded by Economic Development Board (EDB) to set up a solar PV test-bed for the research on performance of different types of PV modules in the country. The PV test-bed installed the nine different types of PV systems that are integrated to power utility grid for monitoring and analyzing their operating performances. This paper presents the 12 months operational data of nine different PV systems and analyses on performances of installed PV systems using energy yield and performance ratio. The nine types of PV systems under test have shown their energy yields ranging from 2.67 to 3.36 kWh/kWp and their performance ratios (PRs) ranging from 70% to 88%.

Keywords: monocrystalline, multicrystalline, amorphous silicon, cadmium telluride, thin film PV

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Authors: Alain Gholam

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Visual thinking routines are principles based on several theories, approaches, and strategies. Such routines promote thinking skills, call for collaboration and sharing of ideas, and above all, make thinking and learning visible. Visual thinking routines were implemented in the teaching methodology graduate course at the American University in Dubai. The study used mixed methods. It was guided by the following two research questions: 1). To what extent do visual thinking inspire learning in the classroom, and make time for students’ questions, contributions, and thinking? 2). How do visual thinking routines inspire learning in the classroom and make time for students’ questions, contributions, and thinking? Eight student teachers enrolled in the teaching methodology course at the American University in Dubai (Spring 2017) participated in the following study. First, they completed a survey that measured to what degree they believed visual thinking routines inspired learning in the classroom and made time for students’ questions, contributions, and thinking. In order to build on the results from the quantitative phase, the student teachers were next involved in a qualitative data collection phase, where they had to answer the question: How do visual thinking routines inspire learning in the classroom and make time for students’ questions, contributions, and thinking? Results revealed that the implementation of visual thinking routines in the classroom strongly inspire learning in the classroom and make time for students’ questions, contributions, and thinking. In addition, student teachers explained how visual thinking routines allow for organization, variety, thinking, and documentation. As with all original, new, and unique resources, visual thinking routines are not free of challenges. To make the most of this useful and valued resource, educators, need to comprehend, model and spread an awareness of the effective ways of using such routines in the classroom. It is crucial that such routines become part of the curriculum to allow for and document students’ questions, contributions, and thinking.

Keywords: classroom display, student engagement, thinking classroom, visual thinking routines

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Authors: S. Malisuwan, J. Sivaraks, N. Madan, N. Suriyakrai

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The ever going evolution of advanced wireless technologies makes it financially impossible for military operations to completely manufacture their own equipment. Therefore, Commercial-Off-The-Shelf (COTS) and Modified-Off-The-Shelf (MOTS) are being considered in military mission with low-cost modifications. In this paper, we focus on the LTE multicast systems for military communication systems under tactical environments with jamming condition. We examine the influence of the colored noise jamming on the performance of the LTE multicast systems in terms of the average throughput. The simulation results demonstrate the degradation of the average throughput for different dynamic ranges of the colored noise jamming versus average SNR.

Keywords: performance, LTE, multicast, jamming, throughput

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Authors: S. B. Tende, H. L. Abubakar

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It is acknowledged that small and medium enterprises (SMEs) may encounter different ethical issues and pressures that could affect the way in which they strategize or make decisions concerning the outcome of their business. Therefore, this research aimed at assessing entrepreneurial ethics in the business of SMEs in Nigeria. Secondary data were adopted as source of corpus for the analysis. The findings conclude that a sound entrepreneurial ethics system has a significant effect on the level of performance of SMEs in Nigeria. The Nigerian Government needs to provide both guiding and physical structures; as well as learning systems that could inculcate these entrepreneurial ethics.

Keywords: culture, entrepreneurial ethics, performance, SME

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Authors: Jiri Barta

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At the present time, awareness, education, computer simulation and information systems protection are very serious and relevant topics. The article deals with perspectives and possibilities of implementation of emergence or natural hazard threats into the system which is developed for communication among members of crisis management staffs. The Czech Hydro-Meteorological Institute with its System of Integrated Warning Service resents the largest usable base of information. National information systems are connected to foreign systems, especially to flooding emergency systems of neighboring countries, systems of European Union and international organizations where the Czech Republic is a member. Use of outputs of particular information systems and computer simulations on a single communication interface of information system for communication among members of crisis management staff and setting the site interoperability in the net will lead to time savings in decision-making processes in solving extraordinary events and crisis situations. Faster managing of an extraordinary event or a crisis situation will bring positive effects and minimize the impact of negative effects on the environment.

Keywords: computer simulation, communication, continuity, critical infrastructure, information systems, safety

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long

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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.

Keywords: agricultural object detection, deep learning, machine vision, YOLO family

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Authors: Shafaq Rubab

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The primary reason for dropping out of school is associated with students’ lack of motivation in class, especially in mathematics. Digital game-based learning is an approach that is being actively explored; there are very few learning games based on proven instructional design models or frameworks due to which the effectiveness of the learning games suffers. The purpose of this research was twofold: first, developing an appropriate instructional design model and second, evaluating the impact of the instructional design model on students’ motivation. This research contributes significantly to the existing literature in terms of student motivation and the impact of instructional design model in digital game-based learning. The sample size for this study consists of two hundred out-of-school students between the age of 6 and 12 years. The research methodology used for this research was a quasi-experimental approach and data was analyzed by using the instructional material motivational survey questionnaire which is adapted from the Keller Arcs model. Control and experimental groups consisting of two hundred students were analyzed by utilizing instructional material motivational survey (IMMS), and comparison of result from both groups showed the difference in the level of motivation of the students. The result of the research showed that the motivational level of student in the experimental group who were taught by the game was higher than the student in control group (taught by conventional methodology). The mean score of the experimental group against all subscales (attention, relevance, confidence, and satisfaction) of IMMS survey was higher; however, no statistical significance was found between the motivational scores of control and experimental group. The positive impact of game-based learning on students’ level of motivation, as measured in this study, strengthens the case for the use of pedagogically sound instructional design models in the design of interactive learning applications. In addition, the present study suggests learning from interactive, immersive applications as an alternative solution for children, especially in Third World countries, who, for various reasons, do not attend school. The mean score of experimental group against all subscales of IMMS survey was higher; however, no statistical significance was found between motivational scores of control and experimental group.

Keywords: digital game-based learning, students’ motivation, and instructional designing, instructional material motivational survey

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Authors: Paola Bordon, Breno Braga

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This paper investigates whether firms use university prestige to statistically discriminate among college graduates. The test is based on the employer learning literature which suggests that if firms use a characteristic for statistical discrimination, this variable should become less important for earnings as a worker gains labor market experience. In this framework, we use a regression discontinuity design to estimate a 19% wage premium for recent graduates of two of the most selective universities in Chile. However, we find that this premium decreases by 3 percentage points per year of labor market experience. These results suggest that employers use college selectivity as a signal of workers' quality when they leave school. However, as workers reveal their productivity throughout their careers, they become rewarded based on their true quality rather than the prestige of their college.

Keywords: employer learning, statistical discrimination, college returns, college selectivity

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Authors: Brahmia Nadjet

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The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Abul Bashar

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The recent surge in the adoption of cloud computing systems by various organizations has brought forth the challenge of evaluating their performance. One of the major issues faced by the cloud service providers and customers is to assess the ability of cloud computing systems to provide the desired services in accordance to the QoS and SLA constraints. To this end, an opportunity exists to develop means to ensure that the desired performance levels of such systems are met under simulated environments. This will eventually minimize the service disruptions and performance degradation issues during the commissioning and operational phase of cloud computing infrastructure. However, it is observed that several simulators and modelers are available for simulating the cloud computing systems. Therefore, this paper presents a critical evaluation of the state-of-the-art modeling and simulation frameworks applicable to cloud computing systems. It compares the prominent simulation frameworks in terms of the API features, programming flexibility, operating system requirements, supported services, licensing needs and popularity. Subsequently, it provides recommendations regarding the choice of the most appropriate framework for researchers, administrators and managers of cloud computing systems.

Keywords: cloud computing, modeling framework, performance evaluation, simulation tools

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Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

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Neurological findings provide foundational results for many different disciplines. In this article we want to discuss these with a special focus on mathematics education. The intention is to make neuroscience research useful for the description of cognitive mathematical learning processes. A key issue of mathematics education is that students often behave as if their mathematical knowledge is constructed in isolated compartments with respect to the specific context of the original learning situation; supporting students to link these compartments to form a coherent mathematical society of mind is a fundamental task not only for mathematics teachers. This aspect goes hand in hand with the question if there is such a thing as abstract general mathematical knowledge detached from concrete reality. Educational Neuroscience may give answers to the question why students develop their mathematical knowledge in isolated subjective domains of experience and if it is generally possible to think in abstract terms. To address these questions, we will provide examples from different fields of mathematics education e.g. students’ development and understanding of the general concept of variables or the mathematical notion of universal proofs. We want to discuss these aspects in the reflection of functional studies which elucidate the role of specific brain regions in mathematical learning processes. In doing this the paper addresses concept formation processes of students in the mathematics classroom and how to support them adequately considering the results of (educational) neuroscience.

Keywords: brain regions, concept formation processes in mathematics education, proofs, teaching-learning processes

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Authors: Yuriy A. Shevchenko, Konstantin V. Nefedev

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We consider the antiferromagnetic systems of Ising spins located at the sites of the hexagonal, triangular and pyrochlore lattices. Such systems can be diluted to a certain concentration level by randomly replacing the magnetic spins with nonmagnetic ones. Quite recently we studied density of states (DOS) was calculated by the Wang-Landau method. Based on the obtained data, we calculated the dependence of the residual entropy (entropy at a temperature tending to zero) on the dilution concentration for quite large systems (more than 2000 spins). In the current study, we obtained the same data for small systems (less than 20 spins) by a complete search of all possible magnetic configurations and compared the result with the result for large systems. The shape of the curve remains unchanged in both cases, but the specific values of the residual entropy are different because of the finite size effect.

Keywords: entropy, pyrochlore, spin ice, Wang-Landau algorithm

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Seyedali Seyedkavoosi, Mohammad Obadat, Seantorrion Boyle

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The purpose of this study is to assess the effectiveness of a nontraditional experiential learning strategy in improving the success and interest of mechanical engineering students, using the Kinematics/Dynamics of Machine course as a case study. This upper-division technical course covers a wide range of topics, including mechanism and machine system analysis and synthesis, yet the complexities of ideas like acceleration, motion, and machine component relationships are hard to explain using standard teaching techniques. To solve this problem, a thorough design project was created that gave students hands-on experience developing, manufacturing, and testing their inventions. The main goals of the project were to improve students' grasp of machine design and kinematics, to develop problem-solving and presenting abilities, and to familiarize them with professional software. A questionnaire survey was done to evaluate the effect of this technique on students' performance and interest in mechanical engineering. The outcomes of the study shed light on the usefulness of nontraditional experiential learning approaches in engineering education.

Keywords: experiential learning, nontraditional teaching, hands-on design project, engineering education

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Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

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Authors: Yuliana Wahyu, Ambros Leonangung Edu

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The learning praxis that is proposed by 2013 Curriculum (K-13) is no longer school-oriented as a supply-driven, but now a demand-driven provider. This vision is connected with Jokowi-Kalla Nawacita program to create a competitive nation in the global era. Competition is a social fact that must be faced. Therefore the curriculum will design a process to be the innovators and entrepreneurs.To get this goal, K-13 implements the character education. This aims at creating the innovators and entrepreneurs from an early age (primary school). One part of strengthening it is literacy formations (reading, numeracy, science, ICT, finance, and culture). Thus, science literacy is an integral part of character education. The above outputs are only formed through the innovative process through intra-curricular (blended learning), co-curriculer (hands-on learning) and extra-curricular (personalized learning). Unlike the curriculums before that child cram with the theories dominating the intellectual process, new breakthroughs make natural, social, and cultural phenomena as learning sources. For example, Science in primary schoolsplaceBiology as the platform. And Science places natural, social, and cultural phenomena as a learning field so that students can learn, discover, solve concrete problems, and the prospects of development and application in their everyday lives. Science education not only learns about facts collection or natural phenomena but also methods and scientific attitudes. In turn, Science will form the science literacy. Science literacy have critical, creative, logical, and initiative competences in responding to the issues of culture, science and technology. This is linked with science nature which includes hands-on and minds-on. To sustain the effectiveness of science learning, K-13 opens a new way of viewing a contextual learning model in which facts or natural phenomena are drawn closer to the child's learning environment to be studied and analyzed scientifically. Thus, the topic of elementary science discussion is the practical and contextual things that students encounter. This research is about to contextualize Science in primary schools at Manggarai, NTT, by placing local wisdom as a learning source and media to form the science literacy. Explicitly, this study discovers the concept of science and mathematics in Mbaru Niang. Mbaru Niang is a forgotten potentials of the centralistic-theoretical mainstream curriculum so far. In fact, the traditional Manggarai community stores and inherits much of the science-mathematical indigenous sciences. In the traditional house structures are full of science and mathematics knowledge. Every details have style, sound and mathematical symbols. Learning this, students are able to collaborate and synergize the content and learning resources in student learning activities. This is constructivist contextual learning that will be applied in meaningful learning. Meaningful learning allows students to learn by doing. Students then connect topics to the context, and science literacy is constructed from their factual experiences. The research location will be conducted in Manggarai through observation, interview, and literature study.

Keywords: indigenous science, Mbaru Niang, science literacy, science

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Authors: Kavitha Thamadharan, Nurazean Maarop

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The implementation of e-assessment as tool to support the process of teaching and learning in university has become a popular technological means in universities. E-Assessment provides many advantages to the users especially the flexibility in teaching and learning. The e-assessment system has the capability to improve its quality of delivering education. However, there still exists a drawback in terms of security which limits the user acceptance of the online learning system. Even though there are studies providing solutions for identified security threats in e-learning usage, there is no particular model which addresses the factors that influences the acceptance of e-assessment system by lecturers from security perspective. The aim of this study is to explore security aspects of e-assessment in regard to the acceptance of the technology. As a result a conceptual model of secure acceptance of e-assessment is proposed. Both human and security factors are considered in formulation of this conceptual model. In order to increase understanding of critical issues related to the subject of this study, interpretive approach involving convergent mixed method research method is proposed to be used to execute the research. This study will be useful in providing more insightful understanding regarding the factors that influence the user acceptance of e-assessment system from security perspective.

Keywords: secure technology acceptance, e-assessment security, e-assessment, education technology

Procedia PDF Downloads 459

Authors: Guessabi Fatiha

Abstract:

Nowadays, there is no sphere of human life that does not use Information and Communication Technologies (ICTs) in practice. This type of development grew widely in the last years of the 20th century and impacted many fields such as education, health, financing, job markets, communication, governments, industrial productivity, etc. Recently, in higher education, the use of ICTs has been essential and significant during the Covid19 pandemic. Thanks to technology, although the universities in Algeria were locked down during the period of covid19, learning was easily continued, and students were collaborating, communicating, socializing, and learning at a distance. Therefore, ICT tools are required in translation courses to enhance and improve translation teaching. This research explores the use of ICT in teaching and learning translation. The research comes along with a theoretical framework; the literature review is produced to highlight some essential ICT concepts and translation teaching. In order to achieve the study objective, a questionnaire is distributed to the third-year English LMD students at Tahri Mohamed University, and an interview is addressed to the translation teacher. The results and discussion obtained from this investigation confirmed the hypothesis and revealed that the use of ICT is essential in translation courses and it improves translation teaching. Hence, by using ICT in the classroom, the students become more active, and the teachers of translation become knowledge facilitators and leaders.

Keywords: COVID19, ICT, learning, students, teaching, TMU, translation

Procedia PDF Downloads 128

Authors: Azzeddine Atibi, Khadija El Kababi, Salim Ahmed, Mohamed Radid

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The principal objective of this study is to undertake a comprehensive comparative analysis of distance learning and blended learning modalities, with a particular emphasis on evaluating their effectiveness during the confinement period mandated by the COVID-19 pandemic. This investigation is rooted in the firsthand experiences of educators at the high school and secondary levels within both private and public educational institutions. To acquire the requisite data, we meticulously designed and distributed a survey to these educators, soliciting detailed narratives of their professional experiences throughout this challenging period. The survey aims to elucidate the specific difficulties encountered by teachers, as well as to highlight the innovative pedagogical strategies they devised in response to these challenges. By synthesizing the insights garnered from this survey, our goal is to foster an exchange of experiences among educators and to generate informed recommendations that will inform future educational reforms. Ultimately, this study aspires to contribute to the ongoing discourse on optimizing educational practices in the face of unprecedented disruptions.

Keywords: distance learning, blended learning, covid 19, secondary/ high school, teachingperformance, evaluation

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Authors: Jussi Horelli, Salla Niittymäki

Abstract:

In this acceleratingly developing world, it will be crucial for our students to not only to adapt to continuous change, but to be the driving force of it. This raises the question of how can the educational processes motivate and encourage the students to learn the perhaps most important skill there for their further work career: the ability to learn and absorb more by themselves. In engineering education, the learning contents and methods have traditionally been very substance oriented and teacher-centered. In Häme University of Applied Sciences (HAMK), the pedagogical model has been completely renewed during the past few years. Terms like phenomenon or skills-based learning and collaborative teaching are things which have not very often been related to engineering education, but are now the foundation of HAMK’s pedagogical model in all disciplines, even in engineering studies. In this paper, a new flexible way of executing engineering studies will be introduced. The paper will summarize three years’ experiences and observations of a process where traditional teacher-centric mechanical engineering teaching was converted into a model where teachers work collaboratively in teams supporting the students’ learning processes.

Keywords: team teaching, collaborative learning, engineering education, new pedagogy

Procedia PDF Downloads 221

Authors: Murzabekova Gulden

Abstract:

Directional implicit functions for underdetermined nonsmooth systems in terms of the new tool of the Nonsmooth analysis - exhausters are considered. A method for finding an implicit function for underdetermined nonsmooth systems is proposed.

Keywords: implicit function, exhauster, nonsmooth systems

Procedia PDF Downloads 245

Authors: Shannon Melideo

Abstract:

Post-secondary schools that provide specialized instruction for college students with special needs have been in existence for some time in the United States of America. Whether students experience learning disabilities, visual impairments, physical limitations, Autism Spectrum Disorders or any other issue that impacts their learning are able to attend universities that intentionally cater to their needs. While this selection of post-secondary education may be preferred by some students, other have sought a different experience. Over the last ten years, the number of students with Autism Spectrum Disorders (ASD) attending traditional universities in the United States of America has increased significantly. Students with ASD tend to select smaller, private institutions that appear to offer more personal attention and services. This paper will examine how traditional American universities are preparing for this relatively new group of students in their college classrooms. This paper will provide a brief historical timeline of access to university instruction for students with Autism Spectrum Disorders, and how and if students with ASD are received in colleges around the globe, and best research supported practices for success.

Keywords: autism spectrum disorders, access to learning, university instruction, accommodations

Procedia PDF Downloads 174