Ulteriori informazioni
The book focuses on how information technology may assist in achieving goals and provide solutions to problems like the pandemic. It explores and describes the current state-of-the-art research conducted during the pandemic. Topics covered include the IT Viewpoint and the rules governing digital transformation throughout the epidemic.
Sommario
1. Automatic HTML Generator from Sketch Using Deep Learning to Speed Up Web Developing Post-COVID-19, 2. Dealing with COVID-19 Using Deep Learning for Computer Vision, 3. Real-Time Detection of COVID-19 Protocol Implementation Using Convolutional Neural Networks and Inverse Perspective Mapping, 4. Marketplace Product Image Grouping Using Transfer Learning of Deep Convolutional Neural Network in COVID-19 Post-Pandemic Situation, 5. The Chamber Monitoring Suspected COVID-19 Based on IoT Geographic Information Systems, 6. Comprehensive Analysis of Information Technology Solutions and the Impact of the COVID-19 Pandemic on Human Life, 7. The Microcontroller-Based Technology for Developing Countries in the COVID-19 Pandemic Era, 8. A Wireless Infrastructure Prototype Based on a Cloud Networking Solution to Optimize Service Provision in a Health Provider Entity, 9. Virtual Reality as Social Interaction Medium Between COVID-19 Pandemic and Endemic Situations, 10. The Integration of Ambient Intelligence with Serious Game for Recommendation System of Tourist Destinations Post-COVID-19 Pandemic, 11. Designing a Virtual Expo Area Amidst the Pandemic, 12. Continuance Intention in Massive Open Online Courses Using Extended Expectation-Confirmation Model, 13. Online Supervision for Internship Student During the COVID-19 Pandemic and Beyond, 14. The Lecturer Document Management System in the COVID-19 Pandemic: Benefits, Challenges, Potential, and Difficulties, 15. Fast-Track Program with Recognition of Prior Learning in Post-Pandemic COVID-19, 16. Student Satisfaction with Distance Learning during Pandemic Era Using Machine Learning Methods, 17. Food Security Clustering in Indonesia around the COVID-19 Pandemic, 18. Support Vector Machine for Sentiment Analysis of COVID-19 Vaccine, 19. Seasonal and Trend Forecasting of COVID-19 Cases Using Deep Learning, 20. Immunology and Microbiology Journals Quartile Classification Using Decision Tree (ID3) Ensemble Models, 21. Opinion Mining on Post-COVID-19 Hybrid Learning, 22. Sentiment Analysis Concerning Indonesian Community Acceptance of COVID-19 Vaccine in Social Media, 23. Graph Clustering for Social Media Listening during COVID-19
Info autore
Aji Prasetya Wibawa was awarded a doctoral degree in Electrical and Information Engineering from the University of South Australia (UniSA). He was formerly the head of the Electrical Engineering Department at Universitas Negeri Malang (UM) in Indonesia. He is currently head of the Academic Publication Center at UM. He is the leader of a research group that focuses on knowledge engineering and data science (KEDS). His research interests include artificial intelligence, data mining, machine translation, and social informatics. These research interests are reflected in the journals he edits, such
as Knowledge Engineering and Data Science (
KEDS) and
Bulletin of Social Informatics Theory and Application (
BUSINTA).
