Proceedings Of The Second International Conference On Advances In Computing Research Acr24

This book concentrates on advances in research in the areas of computational intelligence, cybersecurity engineering, data analytics, network and communications, cloud and mobile computing, and robotics and automation. The Second International Conference on Advances in Computing Research (ACR’24), June 3–5, 2024, in Madrid, brings together a diverse group of researchers from all over the world with the intent of fostering collaboration and dissemination of the advances in computing technologies. The conference is aptly segmented into six tracks to promote a birds-of-the-same-feather congregation and maximize participation. It introduces the concepts, techniques, methods, approaches, and trends needed by researchers, graduate students, specialists, and educators for keeping current and enhancing their research and knowledge in these areas.

The rise of Artificial Intelligence (AI) amidst the backdrop of a world that is changing at lightning speed presents a whole new set of challenges. One of our biggest hurdles is more transparency in AI solutions. It's a complex issue, but one that we need to address if we want to ensure that the benefits of AI are accessible to everyone. Across diverse sectors such as healthcare, surveillance, and human-computer interaction, the inability to understand and evaluate AI's decision-making processes hinders progress and raises concerns about accountability. Cross-Industry AI Applications is a groundbreaking solution to illuminate the mysteries of AI-driven human behavior analysis. This pioneering book addresses the necessity of transparency and explainability in AI systems, particularly in analyzing human behavior. Compiling insights from leading experts and academics offers a comprehensive exploration of state-of-the-art methodologies, benchmarks, and systems for understanding and predicting human behavior using AI. Each chapter delves into novel approaches and real-world applications, from facial expressions to gesture recognition, providing invaluable knowledge for scholars and professionals alike.

The real world is complicated, as a result of which most mathematical models arising from mechanics, physics, chemistry and biology are nonlinear. Based on the efforts of scientists in the 20th century, especially in the last three decades, topological, variational, geometrical and other methods have developed rapidly in nonlinear analysis, which made direct studies of nonlinear models possible in many cases, and provided global information on nonlinear problems which was not available by the traditional linearization method. This volume reflects that rapid development in many areas of nonlinear analysis.