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Research Anthology on Ecosystem Conservation and Preserving Biodiversity
In today’s rapidly evolving world, it has never been more critical to consider key environmental issues such as climate change, pollution, and endangered species. Society faces an unknown future where the fate of the environment is continuously in flux based on current preservation initiatives that governments develop. In order to ensure the world is protected moving forward, further study on the importance of securing environments, ecosystems, and species is necessary to successfully implement change. The Research Anthology on Ecosystem Conservation and Preserving Biodiversity considers the best practices and strategies for protecting our current ecosystems as well as the potential ramifications of failing to implement policies. Society is at a crossroads where if we continue to ignore the danger and warning signs brought about by environmental issues, we will be unable to maintain a healthy environment. Covering essential topics such as extinction, climate change, and pollution, this major reference work is ideal for scientists, industry professionals, researchers, academicians, policymakers, scholars, practitioners, instructors, and students.
Linguistics Anthology Insights From Students Research
Through this book, entitled Linguistics Anthology: Insights from Students Research, we want to provide our students with the opportunity of writing scientific essays that will be beneficial for them in the future. This book also facilitates their outstanding ideas in their initial research in the field of Linguistics. As part of the Linguistics practicum program, we selected their best research essays from the Linguistics classes; Introduction to Semantics and Pragmatics, Psycholinguistics, Second Language Acquisition, Sociolinguistics; at the Study Program of English Literature, Universitas Brawijaya.
Machine Learning and Generative AI in Smart Healthcare
The healthcare landscape is constantly evolving, and one of the most significant concerns that healthcare professionals deal with is understanding how to use biomedical intelligence to improve patient outcomes. With the increasing complexity of healthcare computing systems, including technologies like deep learning and the Internet of Things, it can be challenging to navigate these advancements. Machine Learning and Generative AI in Smart Healthcare is a practical tool for healthcare professionals, researchers, and policymakers who are seeking to implement biomedical intelligence solutions. It provides a clear roadmap for using prescriptive and predictive analytics in machine learning to enhance healthcare outcomes. Going beyond the basics, it delves into healthcare computing and networking complexities. By delving into topics such as data mining, disease prediction, and AI applications, deep learning approaches, decision support systems, and optimization techniques, this book equips readers with the practical knowledge they need to optimize healthcare delivery and management.
