Emerging Technologies for Developing Countries 5th EAI International Conference, AFRICATEK 2022, Bloemfontein, South Africa, December 5-7, 2022, Proceedings /
This book constitutes the refereed conference proceedings of the 5th International Conference on Emerging Technologies for Developing Countries, AFRICATEK 2022, held in Bloemfontein, South Africa, in December 5-7, 2022. The 14 full papers included in this book were carefully reviewed and selected fr...
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| 団体著者: | |
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| その他の著者: | , |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
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| 版: | 1st ed. 2023. |
| シリーズ: | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering,
503 |
| 主題: | |
| オンライン・アクセス: | https://doi.org/10.1007/978-3-031-35883-8 |
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目次:
- Education in the 4IR Era
- Reinforcement Learning in Education: A Multi-Armed Bandit Approach
- Assessing Institutional Readiness for the Fourth Industrial Revolution: Using Learning Analytics to Improve Student Experiences
- M-learning during COVID-19: A Systematic Literature Review
- Opportunities for driving Efficiencies and Effectiveness
- Archiving 4.0: Dataset Generation and Facial recognition of DRC political Figures Using Machine Learning
- On the Machine Learning Models To Predict Town-scale Energy Consumption In Burkina Faso
- Application of Latent Dirichlet Allocation topic model in identifying 4IR Research Trends
- A conceptual model for the digital inclusion of SMMEs in the Informal Sector in South Africa - The use of Blockchain Technology to access loans
- Key 4IR Baseline Architectures
- Multiple Robotic Formation Control Based on Differential Flatness
- AComparison of Publish-Subscribe and Client-Server Models for Streaming IoT Telemetry data
- Fourth industrial revolution research outputs in Africa: A bibliometric review
- Modelling DDoS Attacks in IoT Networks using Machine Learning
- Application of 4IR in Environment and Agriculture Monitoring
- Towards a microservice-based middleware for a multi-hazard early warning system
- Indigenous Knowledge mobile-based application that quantifies farmers’ season predictions with the help of scientific knowledge
- Weed Identification in Plant Seedlings Using Convolutional Neural Networks.