Vol. 4 No. 1 (2024): Journal of AI-Assisted Scientific Discovery
Articles

Affective Computing and AI-Enhanced Emotion-Aware Systems: Leveraging Emotion Recognition for Change Management in User Interaction

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  • Dr. Olga Petrova
Dr. Olga Petrova
Professor of Applied Mathematics, National Research University Higher School of Economics (HSE), Russiar
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Published 19-06-2024

Keywords

  • emotion recognition,
  • data security
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Olga Petrova, “Affective Computing and AI-Enhanced Emotion-Aware Systems: Leveraging Emotion Recognition for Change Management in User Interaction”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, pp. 233–243, Jun. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/128

Abstract

Affective computing, a multidisciplinary field that merges psychology, AI, and cognitive science, focuses on creating systems capable of recognizing, interpreting, and responding to human emotions. Emotion-aware systems, when integrated into AI-driven Change Management frameworks, can significantly enhance user experience and interaction, especially in dynamic project environments. This paper explores the latest advancements in affective computing techniques and their applications, highlighting how emotion recognition technologies are transforming user engagement in change-centric systems. Additionally, the paper addresses the ethical considerations surrounding privacy and data security, offering insights into the challenges and future directions of emotion-aware systems within the context of change management and predictive analytics.

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References

  1. Vemoori, Vamsi. "Envisioning a Seamless Multi-Modal Transportation Network: A Framework for Connected Intelligence, Real-Time Data Exchange, and Adaptive Cybersecurity in Autonomous Vehicle Ecosystems." Australian Journal of Machine Learning Research & Applications 4.1 (2024): 98-131.
  2. Sadhu, Ashok Kumar Reddy, et al. "Enhancing Customer Service Automation and User Satisfaction: An Exploration of AI-powered Chatbot Implementation within Customer Relationship Management Systems." Journal of Computational Intelligence and Robotics 4.1 (2024): 103-123.
  3. Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.
  4. Perumalsamy, Jegatheeswari, Chandrashekar Althati, and Lavanya Shanmugam. "Advanced AI and Machine Learning Techniques for Predictive Analytics in Annuity Products: Enhancing Risk Assessment and Pricing Accuracy." Journal of Artificial Intelligence Research 2.2 (2022): 51-82.
  5. Venkatasubbu, Selvakumar, Jegatheeswari Perumalsamy, and Subhan Baba Mohammed. "Machine Learning Models for Life Insurance Risk Assessment: Techniques, Applications, and Case Studies." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 423-449.
  6. Mohammed, Subhan Baba, Bhavani Krothapalli, and Chandrashekar Althat. "Advanced Techniques for Storage Optimization in Resource-Constrained Systems Using AI and Machine Learning." Journal of Science & Technology 4.1 (2023): 89-125.
  7. Krothapalli, Bhavani, Lavanya Shanmugam, and Subhan Baba Mohammed. "Machine Learning Algorithms for Efficient Storage Management in Resource-Limited Systems: Techniques and Applications." Journal of Artificial Intelligence Research and Applications 3.1 (2023): 406-442.
  8. Devan, Munivel, Chandrashekar Althati, and Jegatheeswari Perumalsamy. "Real-Time Data Analytics for Fraud Detection in Investment Banking Using AI and Machine Learning: Techniques and Case Studies." Cybersecurity and Network Defense Research 3.1 (2023): 25-56.
  9. Althati, Chandrashekar, Jegatheeswari Perumalsamy, and Bhargav Kumar Konidena. "Enhancing Life Insurance Risk Models with AI: Predictive Analytics, Data Integration, and Real-World Applications." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 448-486.
  10. Selvaraj, Amsa, Bhavani Krothapalli, and Lavanya Shanmugam. "AI and Machine Learning Techniques for Automated Test Data Generation in FinTech: Enhancing Accuracy and Efficiency." Journal of Artificial Intelligence Research and Applications 4.1 (2024): 329-363.
  11. Konidena, Bhargav Kumar, Jesu Narkarunai Arasu Malaiyappan, and Anish Tadimarri. "Ethical Considerations in the Development and Deployment of AI Systems." European Journal of Technology 8.2 (2024): 41-53.
  12. Devan, Munivel, et al. "AI-driven Solutions for Cloud Compliance Challenges." AIJMR-Advanced International Journal of Multidisciplinary Research 2.2 (2024).
  13. Makka, Arpan Khoresh Amit. “Integrating SAP Basis and Security: Enhancing Data Privacy and Communications Network Security”. Asian Journal of Multidisciplinary Research & Review, vol. 1, no. 2, Nov. 2020, pp. 131-69, https://ajmrr.org/journal/article/view/187.
  14. Katari, Monish, Gowrisankar Krishnamoorthy, and Jawaharbabu Jeyaraman. "Novel Materials and Processes for Miniaturization in Semiconductor Packaging." Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023 2.1 (2024): 251-271.
  15. Tatineni, Sumanth, and Naga Vikas Chakilam. "Integrating Artificial Intelligence with DevOps for Intelligent Infrastructure Management: Optimizing Resource Allocation and Performance in Cloud-Native Applications." Journal of Bioinformatics and Artificial Intelligence 4.1 (2024): 109-142.
  16. Sistla, Sai Mani Krishna, and Bhargav Kumar Konidena. "IoT-Edge Healthcare Solutions Empowered by Machine Learning." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 126-135.
  17. Katari, Monish, Lavanya Shanmugam, and Jesu Narkarunai Arasu Malaiyappan. "Integration of AI and Machine Learning in Semiconductor Manufacturing for Defect Detection and Yield Improvement." Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023 3.1 (2024): 418-431.
  18. Tembhekar, Prachi, Munivel Devan, and Jawaharbabu Jeyaraman. "Role of GenAI in Automated Code Generation within DevOps Practices: Explore how Generative AI." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2.2 (2023): 500-512.
  19. Peddisetty, Namratha, and Amith Kumar Reddy. "Leveraging Artificial Intelligence for Predictive Change Management in Information Systems Projects." Distributed Learning and Broad Applications in Scientific Research 10 (2024): 88-94.
  20. Venkataramanan, Srinivasan, et al. "Leveraging Artificial Intelligence for Enhanced Sales Forecasting Accuracy: A Review of AI-Driven Techniques and Practical Applications in Customer Relationship Management Systems." Australian Journal of Machine Learning Research & Applications 4.1 (2024): 267-287.

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