Special Issue "Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0"
Submission Deadline: 31 July 2021
Submission Deadline: 31 July 2021
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Guest Editors
Prof. Dr. Abdul Rahman, Universitas Negeri Makassar, Indonesia.
Dr. Rusli, Universitas Negeri Makassar, Indonesia.
Dr. Luca Di Nunzio, University of Rome “Tor Vergata”, Italy.
Dr. Rusli, Universitas Negeri Makassar, Indonesia.
Dr. Luca Di Nunzio, University of Rome “Tor Vergata”, Italy.
Summary
At present, the world has entered the era of the Industrial Revolution 4.0 (RI4), an era in which everything is associated with technology. This RI4 era prioritizes work automation using technology, such as the use of the Internet of Think (IoT). The COVID-19 pandemic has provided shock therapy for the world of education because face-to-face education cannot be carried out as usual. This certainly has an impact on the learning process. Using AI/ML/IoT/BigData techniques in education, providing optimal solution becomes important. It aims to find new challenges and overcome the difficulties of new models/techniques of learning and learning process using AI/ML/IoT/BigData to achieve learning goals. This calls for bringing new ideas in AI/ML/IoT/BigData based on COVID-19 and RI 4.0. which will provide value to researchers and scientists. The proposal aims to collect innovative and unpublished work that focuses on methods and technologies suitable for use in the learning process, or other online learning models for COVID-19 and RI 4.0. This special issue provides an opportunity for researchers around the world to share their new ideas in an interesting field.
Keywords
• Artificial Intelligence methods for Learning Process
• Learning methods for COVID-19 and Revolution Industries 4.0
• Technology learning assessment
• Learning Technology
• Novel methods with AI/ML/IoT for the learning process in COVID-19 and Revolution Industries 4.0
• Decision making
• Learning methods for COVID-19 and Revolution Industries 4.0
• Technology learning assessment
• Learning Technology
• Novel methods with AI/ML/IoT for the learning process in COVID-19 and Revolution Industries 4.0
• Decision making
Published Papers
- OPEN ACCESS ARTICLE
- A Model for Selecting a Biomass Furnace Supplier Based on Qualitative and Quantitative Factors
- CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2339-2353, 2021, DOI:10.32604/cmc.2021.016284
- （This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
- Abstract In developing countries, solar energy is the largest source of energy, accounting for 35%–45% of the total energy supply. This energy resource plays a vital role in meeting the energy needs of the world, especially in Vietnam. Vietnam has favorable natural conditions for this energy production. Because it is hot and humid, and it has much rainfall and fertile soil, biomass develops very quickly. Therefore, byproducts from agriculture and forestry are abundant and continuously increasing. However, byproducts that are considered natural waste have become the cause of environmental pollution; these include burning forests, straw, and sawdust in the North; and… More
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- OPEN ACCESS ARTICLE
- Implications COVID-19 on Performance and Energy Management in the Production Electricity
- CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 895-911, 2021, DOI:10.32604/cmc.2021.018012
- （This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
- Abstract The COVID-19 pandemic has directly impacted the electric power industry; the energy sector has experienced huge losses in electricity production. These losses have also affected the reliability of communication and employees’ performance, hence destabilizing the electric power system. This article aims at achieving two objectives. First, analyzing the impact of the COVID-19 pandemic on the communication of performance (human error and human factors) and energy management in electricity production. Second, to develop a conceptual framework model to alleviate effects of the pandemic on the power sector and then improve energy management and human performance. This paper involves investigating the influence… More
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Downloads:1547
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- OPEN ACCESS ARTICLE
- Minimizing Warpage for Macro-Size Fused Deposition Modeling Parts
- CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2913-2923, 2021, DOI:10.32604/cmc.2021.016064
- （This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
- Abstract In this study, we investigated warpage and corner lifting minimization for three-dimensional printed parts generated by macro-size fused deposition modeling (FDM). First, the reasons for warpage were theoretically elucidated. This approach revealed that the thermal deformation and differential volumetric shrinkage of the extruded molten plastic resulted in warpage of FDM parts. In addition, low adhesion between the deposited model and the heated or non-heated printing bed may intensify warpage further. As a next step, initial small-size and medium-size models were used to identify parameters to manage and minimize warpage in a way that would reduce material consumption and running time.… More
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Downloads:379
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- OPEN ACCESS ARTICLE
- Rasch Model Assessment for Bloom Digital Taxonomy Applications
- CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1235-1253, 2021, DOI:10.32604/cmc.2021.016143
- （This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
- Abstract Assessment using Bloom’s taxonomy levels has evolved in a variety of contexts and uses. In the era of the COVID-19 pandemic, which necessitates use of online assessment, the need for teachers to use digital-based taxonomy skills or Bloom’s Digital Taxonomy (BDT) has increased even more. However, the existing studies on validity and reliability of BDT items are limited. To overcome this limitation, this study aims to test whether BDT has good psychometric characteristics as a teacher’s self-assessment tool using the Rasch model analysis and to investigate the pattern of BDT usage in teaching and learning. By using a quantitative online… More
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Views:465
Downloads:498
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