Bøger af Kishor Kumar Sadasivuni

Biofuel Cells and Energy Generation analyzes the current state-of-the-art and offers solutions to key challenges in developing carbohydrate-based biofuel cell technology. The book provides a critical review of biofuel cell technology, including principles, components, applications, obstacles, and prospects, and assesses the economic, safety, health, and environmental implications. Sections focus on the diversity of biomass resources, the fundamental characteristics of biomass, the major effects of biomass composition variations on biofuel cell technology, and a thorough review of the research literature on approaches for decreasing the detrimental impacts of biomass variability on fuel cells. In addition, a comprehensive examination of biofuel cell technology's current state and applications is presented that is supported by an explanation of the fundamentals, concepts, mechanisms, characteristics, optimal parameters, analytical characterization techniques, diverse types, all-category materials, catalysts, engineering designs, implantable biofuel cells, applications, and critical criteria. A variety of applications are addressed, including power implanted devices in biomedical applications, biosensors for smart communities, and nanomaterials for biofuel cells, among others. For each application, unresolved issues are identified, and solutions proposed.

This book covers the medical condition of diabetic patients, their early symptoms and methods conventionally used for diagnosing and monitoring diabetes. It describes various techniques and technologies used for diabetes detection. The content is built upon moving from regressive technology (invasive) and adapting new-age pain-free technologies (non-invasive), machine learning and artificial intelligence for diabetes monitoring and management. This book details all the popular technologies used in the health care and medical fields for diabetic patients. An entire chapter is dedicated to how the future of this field will be shaping up and the challenges remaining to be conquered. Finally, it shows artificial intelligence and predictions, which can be beneficial for the early detection, dose monitoring and surveillance for patients suffering from diabetes