In today's competitive market, a manager must be able to look at data, understand it, analyze it, and then interpret it to design a smart business strategy. Big data is also a valuable source of information on how customers interact with firms through various mediums such as social media platforms, online reviews, and many more. The applications and uses of business analytics are numerous and must be further studied to ensure they are utilized appropriately. Data-Driven Approaches for Effective Managerial Decision Making investigates management concepts and applications using data analytics and outlines future research directions. The book also addresses contemporary advancements and innovations in the field of management. Covering key topics such as big data, business intelligence, and artificial intelligence, this reference work is ideal for managers, business owners, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.

The book is about climate resilience and environmental sustainability approaches, discussing knowledge at global level and the local challenges, presented by authors from various countries. Environmental sustainability is at stake and implications of climate change are clearly visible in most parts of the world. In the times of the prevailing global environmental crisis, this book discusses key issues of climate change and sustainable energy alternatives, waste management and development. It discusses climate change scenario using simulation models in various Asian countries, signatures of climate change in Antarctica, implications in the Indian Ocean and the Indian scenario of REDD+. A special focus has been given on building climate resilience in our agricultural ecosystems and sustainable agriculture. It discusses the prospects and challenges of renewable energy options including biofuels and energy from wastewaters, explores the technical aspects of eco-friendly bioremediation of pollutants, sustainable solid waste management practices and challenges, carbon footprints of industry, and emphasizes on the significance of combining traditional knowledge with modern technology with novel approaches including involvement of social enterprises and corporate social responsibility to achieve the Sustainable Development Goals. This is an important document for researchers and policy makers working in multidisciplinary fields of sustainability sciences.

The book is about climate resilience and environmental sustainability approaches, discussing knowledge at global level and the local challenges, presented by authors from various countries. Environmental sustainability is at stake and implications of climate change are clearly visible in most parts of the world. In the times of the prevailing global environmental crisis, this book discusses key issues of climate change and sustainable energy alternatives, waste management and development. It discusses climate change scenario using simulation models in various Asian countries, signatures of climate change in Antarctica, implications in the Indian Ocean and the Indian scenario of REDD+. A special focus has been given on building climate resilience in our agricultural ecosystems and sustainable agriculture. It discusses the prospects and challenges of renewable energy options including biofuels and energy from wastewaters, explores the technical aspects of eco-friendly bioremediation of pollutants, sustainable solid waste management practices and challenges, carbon footprints of industry, and emphasizes on the significance of combining traditional knowledge with modern technology with novel approaches including involvement of social enterprises and corporate social responsibility to achieve the Sustainable Development Goals. This is an important document for researchers and policy makers working in multidisciplinary fields of sustainability sciences.

This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.

In today's competitive market, a manager must be able to look at data, understand it, analyze it, and then interpret it to design a smart business strategy. Big data is also a valuable source of information on how customers interact with firms through various mediums such as social media platforms, online reviews, and many more. The applications and uses of business analytics are numerous and must be further studied to ensure they are utilized appropriately. Data-Driven Approaches for Effective Managerial Decision Making investigates management concepts and applications using data analytics and outlines future research directions. The book also addresses contemporary advancements and innovations in the field of management. Covering key topics such as big data, business intelligence, and artificial intelligence, this reference work is ideal for managers, business owners, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.