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  • Open Access

    ARTICLE

    Hybrid Ensemble-Learning Approach for Renewable Energy Resources Evaluation in Algeria

    El-Sayed M. El-Kenawy1,2, Abdelhameed Ibrahim3, Nadjem Bailek4,*, Kada Bouchouicha5, Muhammed A. Hassan6, Basharat Jamil7, Nadhir Al-Ansari8

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5837-5854, 2022, DOI:10.32604/cmc.2022.023257 - 14 January 2022

    Abstract In order to achieve a highly accurate estimation of solar energy resource potential, a novel hybrid ensemble-learning approach, hybridizing Advanced Squirrel-Search Optimization Algorithm (ASSOA) and support vector regression, is utilized to estimate the hourly tilted solar irradiation for selected arid regions in Algeria. Long-term measured meteorological data, including mean-air temperature, relative humidity, wind speed, alongside global horizontal irradiation and extra-terrestrial horizontal irradiance, were obtained for the two cities of Tamanrasset-and-Adrar for two years. Five computational algorithms were considered and analyzed for the suitability of estimation. Further two new algorithms, namely Average Ensemble and Ensemble using… More >

  • Open Access

    ARTICLE

    A Machine-Learning Framework to Improve Wi-Fi Based Indoorpositioning

    Venkateswari Pichaimani1, K. R. Manjula2,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 383-397, 2022, DOI:10.32604/iasc.2022.023105 - 05 January 2022

    Abstract The indoor positioning system comprises portable wireless devices that aid in finding the location of people or objects within the buildings. Identification of the items is through the capacity level of the signal received from various access points (i.e., Wi-Fi routers). The positioning of the devices utilizing some algorithms has drawn more attention from the researchers. Yet, the designed algorithm still has problems for accurate floor planning. So, the accuracy of position estimation with minimum error is made possible by introducing Gaussian Distributive Feature Embedding based Deep Recurrent Perceptive Neural Learning (GDFE-DRPNL), a novel framework.… More >

  • Open Access

    ARTICLE

    Engagement Detection Based on Analyzing Micro Body Gestures Using 3D CNN

    Shoroog Khenkar1,*, Salma Kammoun Jarraya1,2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2655-2677, 2022, DOI:10.32604/cmc.2022.019152 - 27 September 2021

    Abstract This paper proposes a novel, efficient and affordable approach to detect the students’ engagement levels in an e-learning environment by using webcams. Our method analyzes spatiotemporal features of e-learners’ micro body gestures, which will be mapped to emotions and appropriate engagement states. The proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video frames. We follow a transfer learning approach by using the C3D model that was trained on the Sports-1M dataset. The adopted C3D model was used based on two different approaches; as a feature More >

  • Open Access

    ARTICLE

    Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

    K. Abhirami1,*, M. K. Kavitha Devi2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1127-1144, 2022, DOI:10.32604/csse.2022.020013 - 24 September 2021

    Abstract With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The… More >

  • Open Access

    ARTICLE

    I-Quiz: An Intelligent Assessment Tool for Non-Verbal Behaviour Detection

    B. T. Shobana1,*, G. A. Sathish Kumar2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1007-1021, 2022, DOI:10.32604/csse.2022.019523 - 24 September 2021

    Abstract Electronic learning (e-learning) has become one of the widely used modes of pedagogy in higher education today due to the convenience and flexibility offered in comparison to traditional learning activities. Advancements in Information and Communication Technology have eased learner connectivity online and enabled access to an extensive range of learning materials on the World Wide Web. Post covid-19 pandemic, online learning has become the most essential and inevitable medium of learning in primary, secondary and higher education. In recent times, Massive Open Online Courses (MOOCs) have transformed the current education strategy by offering a technology-rich… More >

  • Open Access

    ARTICLE

    Implementing Effective Learning with Ubiquitous Learning Technology During Coronavirus Pandemic

    Hosam F. El-Sofany1,2,*, Samir A. El-Seoud3

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 389-404, 2022, DOI:10.32604/csse.2022.018619 - 26 August 2021

    Abstract Ubiquitous computing supports U-learning to develop and implement a new educational environment that provides effective and interactive learning to students wherever they are. This study aims to present a qualitative evaluation for using U-learning instead of traditional education to avoid the spread of the Coronavirus pandemic. The authors introduce a UTAUT (Unified Theory of Acceptance and Use of Technology) model to assess the capability of the given factors that are expected to affect the learners’ intention and behavior for accepting the U-learning technology for full E-learning. The research study shows a promising impact on the… More >

  • Open Access

    ARTICLE

    Securing Fog Computing For E-Learning System Using Integration of Two Encryption Algorithms

    Hind A. Alshambri1,* Fawaz Alassery2

    Journal of Cyber Security, Vol.3, No.3, pp. 149-166, 2021, DOI:10.32604/jcs.2021.022112 - 17 November 2021

    Abstract Currently, the majority of institutions have made use of information technologies to improve and develop their diverse educational methods to attract more learners. Through information technologies, e-learning and learning-on-the go have been adopted by the institutions to provide affordability and flexibility of educational services. Most of the educational institutes are offering online teaching classes using the technologies like cloud computing, networking, etc. Educational institutes have developed their e-learning platforms for the online learning process, through this way they have paved the way for distance learning. But e-learning platform has to face a lot of… More >

  • Open Access

    ARTICLE

    Using DEMATEL for Contextual Learner Modeling in Personalized and Ubiquitous Learning

    Saurabh Pal1, Pijush Kanti Dutta Pramanik1, Musleh Alsulami2, Anand Nayyar3,*, Mohammad Zarour4, Prasenjit Choudhury1

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3981-4001, 2021, DOI:10.32604/cmc.2021.017966 - 24 August 2021

    Abstract With the popularity of e-learning, personalization and ubiquity have become important aspects of online learning. To make learning more personalized and ubiquitous, we propose a learner model for a query-based personalized learning recommendation system. Several contextual attributes characterize a learner, but considering all of them is costly for a ubiquitous learning system. In this paper, a set of optimal intrinsic and extrinsic contexts of a learner are identified for learner modeling. A total of 208 students are surveyed. DEMATEL (Decision Making Trial and Evaluation Laboratory) technique is used to establish the validity and importance of More >

  • Open Access

    ARTICLE

    Evaluating and Ranking Mobile Learning Factors Using a Multi-criterion Decision-making (MCDM) Approach

    Quadri Noorulhasan Naveed1, Ali M. Aseere1, AbdulHafeez Muhammad2, Saiful Islam3, Mohamed Rafik N. Qureshi3, Ansar Siddique4,*, Mohammad Rashid Hussain1, Samreen Shahwar5

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 111-129, 2021, DOI:10.32604/iasc.2021.015009 - 12 May 2021

    Abstract The escalating growth in digital technology is setting the stage for changes in university education, as E-learning brings students and faculties outside the contained classroom environment. While mobile learning is considered an emerging technology, there is comprehensive literature on mobile learning and its applications. However, there has been relatively little research on mobile learning recognition and readiness compared to mobile learning studies and implementations. The advent of mobile learning (M-learning) provides additional flexibility in terms of time and location. M-learning lacks an established place in university education. The influence of its critical success factors (CSFs)… More >

  • Open Access

    ARTICLE

    Developing a Recognition System for Classifying COVID-19 Using a Convolutional Neural Network Algorithm

    Fawaz Waselallah Alsaade1, Theyazn H. H. Aldhyani2,*, Mosleh Hmoud Al-Adhaileh3

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 805-819, 2021, DOI:10.32604/cmc.2021.016264 - 22 March 2021

    Abstract The COVID-19 pandemic poses an additional serious public health threat due to little or no pre-existing human immunity, and developing a system to identify COVID-19 in its early stages will save millions of lives. This study applied support vector machine (SVM), k-nearest neighbor (K-NN) and deep learning convolutional neural network (CNN) algorithms to classify and detect COVID-19 using chest X-ray radiographs. To test the proposed system, chest X-ray radiographs and CT images were collected from different standard databases, which contained 95 normal images, 140 COVID-19 images and 10 SARS images. Two scenarios were considered to… More >

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