2024 Ieee 6th International Conference On Cybernetics Cognition And Machine Learning Applications Icccmla
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2024 IEEE 6th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)
Intelligent Computing, Cybernetics, Machine Learning Artificial Intelligence, Communication Technologies
Applications of Mathematics in Science and Technology
The Conference dealt with one of the most important problems faced in International development in Pure Mathematics and Applied mathematics development in engineering such as Cryptography, Cyber Security, Network, Operations Research, Heat Equation and so forth. The aim of the conference was to provide a platform for researchers, engineers, academicians, as well as industrial professionals, to present their research results and development activities in Pure and Apply Mathematics, and its applied technology. It provided opportunities for the delegates to exchange new ideas and application experiences, to establish business or research relations and to find global partners for future collaboration.
Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.