Special Issues

Smart digital education and scientific programming

Submission Deadline: 05 January 2023 (closed) View: 39

Guest Editors

Dr. Shah Nazir, University of Swabi, Pakistan.
Dr. Habib Ullah Khan, Qatar University, Qatar.
Dr. Iván García-Magariño, Complutense University of Madrid, Spain.

Summary

Software applications for smart surroundings, such as smart surveillance, smart healthcare, industrial automation, and so on, have risen to the forefront of computing in recent years. Technology is rapidly evolving and infiltrating our lives in the knowledge and information society. Digital education debates are currently a major topic of research. With the introduction of the coronavirus (Covid-19) and its tremendous influence on the education industry, concerns about digital education have reached a new high. People presently live in a world dominated by digital technologies and the Internet. The evolution and trends in social structure with regard to the use of technology have already altered not only how we live but also how we obtain knowledge. Traditional classroom activities have been placed on hold and suspended since the beginning of the COVID-19 epidemic. Institutions and organizations are shifting their teaching from the classroom to the internet in order to provide their students with a safe, flexible, and convenient education.

The international market requires information technology professionals that not only have good technical knowledge but also the ability to communicate that knowledge in a cross-cultural context. Students' ability to gain professional knowledge and solve professional challenges is cultivated through digital education in colleges and universities. Meanwhile, they work to improve students' ability to transmit professional information through language. In terms of the status and use of information technology in higher education, most colleges and universities continue to use the traditional "teacher-oriented" cramming teaching method, which results in a general lack of comprehensive professional ability, teamwork ability, and oral expression and communication ability among students. In this context, novel research on the teaching mode and method of information technology in the classroom is a new topic that needs to be explored urgently in order to boost the training of information technology talents.

The goal of this special issue is to bring together academic researchers and industry practitioners to exchange and discuss the most recent advances in programming aspects aimed at modelling and system design for higher education institutions to focus on the development of students' and teachers' digital education, create relevant learning strategies, and use appropriate tools to improve educational quality. The submission of original research and review articles is encouraged.


Keywords

Potential topics include but are not limited to the following:
• Scientific programming for smart digital education
• Information technology and digital education
• Scientific programming for digital education in Covid- 19
• Scientific programming for Teacher students communication
• Artificial Intelligence for digital education
• Software applications for digital education
• Advances for digital education in pandemic
• Machine learning and distance education

Published Papers


  • Open Access

    ARTICLE

    3D Model Construction and Ecological Environment Investigation on a Regional Scale Using UAV Remote Sensing

    Chao Chen, Yankun Chen, Haohai Jin, Li Chen, Zhisong Liu, Haozhe Sun, Junchi Hong, Haonan Wang, Shiyu Fang, Xin Zhang
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1655-1672, 2023, DOI:10.32604/iasc.2023.039057
    (This article belongs to the Special Issue: Smart digital education and scientific programming)
    Abstract The acquisition of digital regional-scale information and ecological environmental data has high requirements for structural texture, spatial resolution, and multiple parameter categories, which is challenging to achieve using satellite remote sensing. Considering the convenient, facilitative, and flexible characteristics of UAV (unmanned air vehicle) remote sensing technology, this study selects a campus as a typical research area and uses the Pegasus D2000 equipped with a D-MSPC2000 multi-spectral camera and a CAM3000 aerial camera to acquire oblique images and multi-spectral data. Using professional software, including Context Capture, ENVI, and ArcGIS, a 3D (three-dimensional) campus model, a digital More >

  • Open Access

    ARTICLE

    Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques

    Abdus Saboor, Arif Hussain, Bless Lord Y. Agbley, Amin ul Haq, Jian Ping Li, Rajesh Kumar
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1325-1344, 2023, DOI:10.32604/iasc.2023.038849
    (This article belongs to the Special Issue: Smart digital education and scientific programming)
    Abstract Stock market forecasting has drawn interest from both economists and computer scientists as a classic yet difficult topic. With the objective of constructing an effective prediction model, both linear and machine learning tools have been investigated for the past couple of decades. In recent years, recurrent neural networks (RNNs) have been observed to perform well on tasks involving sequence-based data in many research domains. With this motivation, we investigated the performance of long-short term memory (LSTM) and gated recurrent units (GRU) and their combination with the attention mechanism; LSTM + Attention, GRU + Attention, and More >

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